Blood flow in intracranial aneurysms treated with Pipeline embolization devices: computational simulation and verification with Doppler ultrasonography on phantom models

PubMed Central

2015-01-01

Purpose: The aim of this study was to validate a computational fluid dynamics (CFD) simulation of flow-diverter treatment through Doppler ultrasonography measurements in patient-specific models of intracranial bifurcation and side-wall aneurysms. Methods: Computational and physical models of patient-specific bifurcation and sidewall aneurysms were constructed from computed tomography angiography with use of stereolithography, a three-dimensional printing technology. Flow dynamics parameters before and after flow-diverter treatment were measured with pulse-wave and color Doppler ultrasonography, and then compared with CFD simulations. Results: CFD simulations showed drastic flow reduction after flow-diverter treatment in both aneurysms. The mean volume flow rate decreased by 90% and 85% for the bifurcation aneurysm and the side-wall aneurysm, respectively. Velocity contour plots from computer simulations before and after flow diversion closely resembled the patterns obtained by color Doppler ultrasonography. Conclusion: The CFD estimation of flow reduction in aneurysms treated with a flow-diverting stent was verified by Doppler ultrasonography in patient-specific phantom models of bifurcation and side-wall aneurysms. The combination of CFD and ultrasonography may constitute a feasible and reliable technique in studying the treatment of intracranial aneurysms with flow-diverting stents. PMID:25754367

A Computational Model of Reasoning from the Clinical Literature

PubMed Central

Rennels, Glenn D.

1986-01-01

This paper explores the premise that a formalized representation of empirical studies can play a central role in computer-based decision support. The specific motivations underlying this research include the following propositions: 1. Reasoning from experimental evidence contained in the clinical literature is central to the decisions physicians make in patient care. 2. A computational model, based upon a declarative representation for published reports of clinical studies, can drive a computer program that selectively tailors knowledge of the clinical literature as it is applied to a particular case. 3. The development of such a computational model is an important first step toward filling a void in computer-based decision support systems. Furthermore, the model may help us better understand the general principles of reasoning from experimental evidence both in medicine and other domains. Roundsman is a developmental computer system which draws upon structured representations of the clinical literature in order to critique plans for the management of primary breast cancer. Roundsman is able to produce patient-specific analyses of breast cancer management options based on the 24 clinical studies currently encoded in its knowledge base. The Roundsman system is a first step in exploring how the computer can help to bring a critical analysis of the relevant literature to the physician, structured around a particular patient and treatment decision.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example.

PubMed

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C

2017-01-01

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.

A pull-back algorithm to determine the unloaded vascular geometry in anisotropic hyperelastic AAA passive mechanics.

PubMed

Riveros, Fabián; Chandra, Santanu; Finol, Ender A; Gasser, T Christian; Rodriguez, Jose F

2013-04-01

Biomechanical studies on abdominal aortic aneurysms (AAA) seek to provide for better decision criteria to undergo surgical intervention for AAA repair. More accurate results can be obtained by using appropriate material models for the tissues along with accurate geometric models and more realistic boundary conditions for the lesion. However, patient-specific AAA models are generated from gated medical images in which the artery is under pressure. Therefore, identification of the AAA zero pressure geometry would allow for a more realistic estimate of the aneurysmal wall mechanics. This study proposes a novel iterative algorithm to find the zero pressure geometry of patient-specific AAA models. The methodology allows considering the anisotropic hyperelastic behavior of the aortic wall, its thickness and accounts for the presence of the intraluminal thrombus. Results on 12 patient-specific AAA geometric models indicate that the procedure is computational tractable and efficient, and preserves the global volume of the model. In addition, a comparison of the peak wall stress computed with the zero pressure and CT-based geometries during systole indicates that computations using CT-based geometric models underestimate the peak wall stress by 59 ± 64 and 47 ± 64 kPa for the isotropic and anisotropic material models of the arterial wall, respectively.

Preoperative computer simulation for planning of vascular access surgery in hemodialysis patients.

PubMed

Zonnebeld, Niek; Huberts, Wouter; van Loon, Magda M; Delhaas, Tammo; Tordoir, Jan H M

2017-03-06

The arteriovenous fistula (AVF) is the preferred vascular access for hemodialysis patients. Unfortunately, 20-40% of all constructed AVFs fail to mature (FTM), and are therefore not usable for hemodialysis. AVF maturation importantly depends on postoperative blood volume flow. Predicting patient-specific immediate postoperative flow could therefore support surgical planning. A computational model predicting blood volume flow is available, but the effect of blood flow predictions on the clinical endpoint of maturation (at least 500 mL/min blood volume flow, diameter of the venous cannulation segment ≥4 mm) remains undetermined. A multicenter randomized clinical trial will be conducted in which 372 patients will be randomized (1:1 allocation ratio) between conventional healthcare and computational model-aided decision making. All patients are extensively examined using duplex ultrasonography (DUS) during preoperative assessment (12 venous and 11 arterial diameter measurements; 3 arterial volume flow measurements). The computational model will predict patient-specific immediate postoperative blood volume flows based on this DUS examination. Using these predictions, the preferred AVF configuration is recommended for the individual patient (radiocephalic, brachiocephalic, or brachiobasilic). The primary endpoint is FTM rate at six weeks in both groups, secondary endpoints include AVF functionality and patency rates at 6 and 12 months postoperatively. ClinicalTrials.gov (NCT02453412), and ToetsingOnline.nl (NL51610.068.14).

Patient-Specific Computational Modeling of Human Phonation

NASA Astrophysics Data System (ADS)

Xue, Qian; Zheng, Xudong; University of Maine Team

2013-11-01

Phonation is a common biological process resulted from the complex nonlinear coupling between glottal aerodynamics and vocal fold vibrations. In the past, the simplified symmetric straight geometric models were commonly employed for experimental and computational studies. The shape of larynx lumen and vocal folds are highly three-dimensional indeed and the complex realistic geometry produces profound impacts on both glottal flow and vocal fold vibrations. To elucidate the effect of geometric complexity on voice production and improve the fundamental understanding of human phonation, a full flow-structure interaction simulation is carried out on a patient-specific larynx model. To the best of our knowledge, this is the first patient-specific flow-structure interaction study of human phonation. The simulation results are well compared to the established human data. The effects of realistic geometry on glottal flow and vocal fold dynamics are investigated. It is found that both glottal flow and vocal fold dynamics present a high level of difference from the previous simplified model. This study also paved the important step toward the development of computer model for voice disease diagnosis and surgical planning. The project described was supported by Grant Number ROlDC007125 from the National Institute on Deafness and Other Communication Disorders (NIDCD).

A Novel Computer-Aided Approach for Parametric Investigation of Custom Design of Fracture Fixation Plates.

PubMed

Chen, Xiaozhong; He, Kunjin; Chen, Zhengming

2017-01-01

The present study proposes an integrated computer-aided approach combining femur surface modeling, fracture evidence recover plate creation, and plate modification in order to conduct a parametric investigation of the design of custom plate for a specific patient. The study allows for improving the design efficiency of specific plates on the patients' femur parameters and the fracture information. Furthermore, the present approach will lead to exploration of plate modification and optimization. The three-dimensional (3D) surface model of a detailed femur and the corresponding fixation plate were represented with high-level feature parameters, and the shape of the specific plate was recursively modified in order to obtain the optimal plate for a specific patient. The proposed approach was tested and verified on a case study, and it could be helpful for orthopedic surgeons to design and modify the plate in order to fit the specific femur anatomy and the fracture information.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example

PubMed Central

Gunalan, Kabilar; Chaturvedi, Ashutosh; Howell, Bryan; Duchin, Yuval; Lempka, Scott F.; Patriat, Remi; Sapiro, Guillermo; Harel, Noam; McIntyre, Cameron C.

2017-01-01

Background Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Objective Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Methods Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson’s disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Results Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Conclusion Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation. PMID:28441410

75 FR 18849 - Food and Drug Administration/National Heart Lung and Blood Institute/National Science Foundation...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-13

... cardiovascular diseases and therapies; Patient-specific modeling, including virtual surgical planning and... Workshop on Computer Methods for Cardiovascular Devices: The Integration of Nonclinical and Clinical Models... Workshop on Computer Methods for Cardiovascular Devices: The Integration of Nonclinical and Clinical Models...

Wall Shear Stress Distribution in a Patient-Specific Cerebral Aneurysm Model using Reduced Order Modeling

NASA Astrophysics Data System (ADS)

Han, Suyue; Chang, Gary Han; Schirmer, Clemens; Modarres-Sadeghi, Yahya

2016-11-01

We construct a reduced-order model (ROM) to study the Wall Shear Stress (WSS) distributions in image-based patient-specific aneurysms models. The magnitude of WSS has been shown to be a critical factor in growth and rupture of human aneurysms. We start the process by running a training case using Computational Fluid Dynamics (CFD) simulation with time-varying flow parameters, such that these parameters cover the range of parameters of interest. The method of snapshot Proper Orthogonal Decomposition (POD) is utilized to construct the reduced-order bases using the training CFD simulation. The resulting ROM enables us to study the flow patterns and the WSS distributions over a range of system parameters computationally very efficiently with a relatively small number of modes. This enables comprehensive analysis of the model system across a range of physiological conditions without the need to re-compute the simulation for small changes in the system parameters.

Validation of a computational knee joint model using an alignment method for the knee laxity test and computed tomography.

PubMed

Kang, Kyoung-Tak; Kim, Sung-Hwan; Son, Juhyun; Lee, Young Han; Koh, Yong-Gon

2017-01-01

Computational models have been identified as efficient techniques in the clinical decision-making process. However, computational model was validated using published data in most previous studies, and the kinematic validation of such models still remains a challenge. Recently, studies using medical imaging have provided a more accurate visualization of knee joint kinematics. The purpose of the present study was to perform kinematic validation for the subject-specific computational knee joint model by comparison with subject's medical imaging under identical laxity condition. The laxity test was applied to the anterior-posterior drawer under 90° flexion and the varus-valgus under 20° flexion with a series of stress radiographs, a Telos device, and computed tomography. The loading condition in the computational subject-specific knee joint model was identical to the laxity test condition in the medical image. Our computational model showed knee laxity kinematic trends that were consistent with the computed tomography images, except for negligible differences because of the indirect application of the subject's in vivo material properties. Medical imaging based on computed tomography with the laxity test allowed us to measure not only the precise translation but also the rotation of the knee joint. This methodology will be beneficial in the validation of laxity tests for subject- or patient-specific computational models.

Patient specific CFD models of nasal airflow: overview of methods and challenges.

PubMed

Kim, Sung Kyun; Na, Yang; Kim, Jee-In; Chung, Seung-Kyu

2013-01-18

Respiratory physiology and pathology are strongly dependent on the airflow inside the nasal cavity. However, the nasal anatomy, which is characterized by complex airway channels and significant individual differences, is difficult to analyze. Thus, commonly adopted diagnostic tools have yielded limited success. Nevertheless, with the rapid advances in computer resources, there have been more elaborate attempts to correlate airflow characteristics in human nasal airways with the symptoms and functions of the nose by computational fluid dynamics study. Furthermore, the computed nasal geometry can be virtually modified to reflect predicted results of the proposed surgical technique. In this article, several computational fluid mechanics (CFD) issues on patient-specific three dimensional (3D) modeling of nasal cavity and clinical applications were reviewed in relation to the cases of deviated nasal septum (decision for surgery), turbinectomy, and maxillary sinus ventilation (simulated- and post-surgery). Clinical relevance of fluid mechanical parameters, such as nasal resistance, flow allocation, wall shear stress, heat/humidity/NO gas distributions, to the symptoms and surgical outcome were discussed. Absolute values of such parameters reported by many research groups were different each other due to individual difference of nasal anatomy, the methodology for 3D modeling and numerical grid, laminar/turbulent flow model in CFD code. But, the correlation of these parameters to symptoms and surgery outcome seems to be obvious in each research group with subject-specific models and its variations (virtual- and post-surgery models). For the more reliable, patient-specific, and objective tools for diagnosis and outcomes of nasal surgery by using CFD, the future challenges will be the standardizations on the methodology for creating 3D airway models and the CFD procedures. Copyright © 2012 Elsevier Ltd. All rights reserved.

LBM-EP: Lattice-Boltzmann method for fast cardiac electrophysiology simulation from 3D images.

PubMed

Rapaka, S; Mansi, T; Georgescu, B; Pop, M; Wright, G A; Kamen, A; Comaniciu, Dorin

2012-01-01

Current treatments of heart rhythm troubles require careful planning and guidance for optimal outcomes. Computational models of cardiac electrophysiology are being proposed for therapy planning but current approaches are either too simplified or too computationally intensive for patient-specific simulations in clinical practice. This paper presents a novel approach, LBM-EP, to solve any type of mono-domain cardiac electrophysiology models at near real-time that is especially tailored for patient-specific simulations. The domain is discretized on a Cartesian grid with a level-set representation of patient's heart geometry, previously estimated from images automatically. The cell model is calculated node-wise, while the transmembrane potential is diffused using Lattice-Boltzmann method within the domain defined by the level-set. Experiments on synthetic cases, on a data set from CESC'10 and on one patient with myocardium scar showed that LBM-EP provides results comparable to an FEM implementation, while being 10 - 45 times faster. Fast, accurate, scalable and requiring no specific meshing, LBM-EP paves the way to efficient and detailed models of cardiac electrophysiology for therapy planning.

in silico Vascular Modeling for Personalized Nanoparticle Delivery

PubMed Central

Hossain, Shaolie S.; Zhang, Yongjie; Liang, Xinghua; Hussain, Fazle; Ferrari, Mauro; Hughes, Thomas J. R.; Decuzzi, Paolo

2013-01-01

Aims To predict the deposition of nanoparticles in a patient-specific arterial tree as a function of the vascular architecture, flow conditions, receptor surface density, and nanoparticle properties. Materials & methods The patient-specific vascular geometry is reconstructed from CT Angiography images. The Isogeometric Analysis framework integrated with a special boundary condition for the firm wall adhesion of nanoparticles is implemented. A parallel plate flow chamber system is used to validate the computational model in vitro. Results Particle adhesion is dramatically affected by changes in patient-specific attributes, such as branching angle and receptor density. The adhesion pattern correlates well with the spatial and temporal distribution of the wall shear rates. For the case considered, the larger (2.0 μm) particles adhere ≈ 2 times more in the lower branches of the arterial tree, whereas the smaller (0.5 μm) particles deposit more in the upper branches. Conclusion Our computational framework in conjunction with patient specific attributes can be used to rationally select nanoparticle properties to personalize, thus optimize, therapeutic interventions. PMID:23199308

Biomechanical Model for Computing Deformations for Whole-Body Image Registration: A Meshless Approach

PubMed Central

Li, Mao; Miller, Karol; Joldes, Grand Roman; Kikinis, Ron; Wittek, Adam

2016-01-01

Patient-specific biomechanical models have been advocated as a tool for predicting deformations of soft body organs/tissue for medical image registration (aligning two sets of images) when differences between the images are large. However, complex and irregular geometry of the body organs makes generation of patient-specific biomechanical models very time consuming. Meshless discretisation has been proposed to solve this challenge. However, applications so far have been limited to 2-D models and computing single organ deformations. In this study, 3-D comprehensive patient-specific non-linear biomechanical models implemented using Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms are applied to predict a 3-D deformation field for whole-body image registration. Unlike a conventional approach which requires dividing (segmenting) the image into non-overlapping constituents representing different organs/tissues, the mechanical properties are assigned using the Fuzzy C-Means (FCM) algorithm without the image segmentation. Verification indicates that the deformations predicted using the proposed meshless approach are for practical purposes the same as those obtained using the previously validated finite element models. To quantitatively evaluate the accuracy of the predicted deformations, we determined the spatial misalignment between the registered (i.e. source images warped using the predicted deformations) and target images by computing the edge-based Hausdorff distance. The Hausdorff distance-based evaluation determines that our meshless models led to successful registration of the vast majority of the image features. PMID:26791945

A framework for different levels of integration of computational models into web-based virtual patients.

PubMed

Kononowicz, Andrzej A; Narracott, Andrew J; Manini, Simone; Bayley, Martin J; Lawford, Patricia V; McCormack, Keith; Zary, Nabil

2014-01-23

Virtual patients are increasingly common tools used in health care education to foster learning of clinical reasoning skills. One potential way to expand their functionality is to augment virtual patients' interactivity by enriching them with computational models of physiological and pathological processes. The primary goal of this paper was to propose a conceptual framework for the integration of computational models within virtual patients, with particular focus on (1) characteristics to be addressed while preparing the integration, (2) the extent of the integration, (3) strategies to achieve integration, and (4) methods for evaluating the feasibility of integration. An additional goal was to pilot the first investigation of changing framework variables on altering perceptions of integration. The framework was constructed using an iterative process informed by Soft System Methodology. The Virtual Physiological Human (VPH) initiative has been used as a source of new computational models. The technical challenges associated with development of virtual patients enhanced by computational models are discussed from the perspectives of a number of different stakeholders. Concrete design and evaluation steps are discussed in the context of an exemplar virtual patient employing the results of the VPH ARCH project, as well as improvements for future iterations. The proposed framework consists of four main elements. The first element is a list of feasibility features characterizing the integration process from three perspectives: the computational modelling researcher, the health care educationalist, and the virtual patient system developer. The second element included three integration levels: basic, where a single set of simulation outcomes is generated for specific nodes in the activity graph; intermediate, involving pre-generation of simulation datasets over a range of input parameters; advanced, including dynamic solution of the model. The third element is the description of four integration strategies, and the last element consisted of evaluation profiles specifying the relevant feasibility features and acceptance thresholds for specific purposes. The group of experts who evaluated the virtual patient exemplar found higher integration more interesting, but at the same time they were more concerned with the validity of the result. The observed differences were not statistically significant. This paper outlines a framework for the integration of computational models into virtual patients. The opportunities and challenges of model exploitation are discussed from a number of user perspectives, considering different levels of model integration. The long-term aim for future research is to isolate the most crucial factors in the framework and to determine their influence on the integration outcome.

A comprehensive computational human lung model incorporating inter-acinar dependencies: Application to spontaneous breathing and mechanical ventilation.

PubMed

Roth, Christian J; Ismail, Mahmoud; Yoshihara, Lena; Wall, Wolfgang A

2017-01-01

In this article, we propose a comprehensive computational model of the entire respiratory system, which allows simulating patient-specific lungs under different ventilation scenarios and provides a deeper insight into local straining and stressing of pulmonary acini. We include novel 0D inter-acinar linker elements to respect the interplay between neighboring alveoli, an essential feature especially in heterogeneously distended lungs. The model is applicable to healthy and diseased patient-specific lung geometries. Presented computations in this work are based on a patient-specific lung geometry obtained from computed tomography data and composed of 60,143 conducting airways, 30,072 acini, and 140,135 inter-acinar linkers. The conducting airways start at the trachea and end before the respiratory bronchioles. The acini are connected to the conducting airways via terminal airways and to each other via inter-acinar linkers forming a fully coupled anatomically based respiratory model. Presented numerical examples include simulation of breathing during a spirometry-like test, measurement of a quasi-static pressure-volume curve using a supersyringe maneuver, and volume-controlled mechanical ventilation. The simulations show that our model incorporating inter-acinar dependencies successfully reproduces physiological results in healthy and diseased states. Moreover, within these scenarios, a deeper insight into local pressure, volume, and flow rate distribution in the human lung is investigated and discussed. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Computational modeling of neurostimulation in brain diseases.

PubMed

Wang, Yujiang; Hutchings, Frances; Kaiser, Marcus

2015-01-01

Neurostimulation as a therapeutic tool has been developed and used for a range of different diseases such as Parkinson's disease, epilepsy, and migraine. However, it is not known why the efficacy of the stimulation varies dramatically across patients or why some patients suffer from severe side effects. This is largely due to the lack of mechanistic understanding of neurostimulation. Hence, theoretical computational approaches to address this issue are in demand. This chapter provides a review of mechanistic computational modeling of brain stimulation. In particular, we will focus on brain diseases, where mechanistic models (e.g., neural population models or detailed neuronal models) have been used to bridge the gap between cellular-level processes of affected neural circuits and the symptomatic expression of disease dynamics. We show how such models have been, and can be, used to investigate the effects of neurostimulation in the diseased brain. We argue that these models are crucial for the mechanistic understanding of the effect of stimulation, allowing for a rational design of stimulation protocols. Based on mechanistic models, we argue that the development of closed-loop stimulation is essential in order to avoid inference with healthy ongoing brain activity. Furthermore, patient-specific data, such as neuroanatomic information and connectivity profiles obtainable from neuroimaging, can be readily incorporated to address the clinical issue of variability in efficacy between subjects. We conclude that mechanistic computational models can and should play a key role in the rational design of effective, fully integrated, patient-specific therapeutic brain stimulation. © 2015 Elsevier B.V. All rights reserved.

Percutaneous Transcatheter Mitral Valve Replacement: Patient-specific Three-dimensional Computer-based Heart Model and Prototyping.

PubMed

Vaquerizo, Beatriz; Theriault-Lauzier, Pascal; Piazza, Nicolo

2015-12-01

Mitral regurgitation is the most prevalent valvular heart disease worldwide. Despite the widespread availability of curative surgical intervention, a considerable proportion of patients with severe mitral regurgitation are not referred for treatment, largely due to the presence of left ventricular dysfunction, advanced age, and comorbid illnesses. Transcatheter mitral valve replacement is a promising therapeutic alternative to traditional surgical valve replacement. The complex anatomical and pathophysiological nature of the mitral valvular complex, however, presents significant challenges to the successful design and implementation of novel transcatheter mitral replacement devices. Patient-specific 3-dimensional computer-based models enable accurate assessment of the mitral valve anatomy and preprocedural simulations for transcatheter therapies. Such information may help refine the design features of novel transcatheter mitral devices and enhance procedural planning. Herein, we describe a novel medical image-based processing tool that facilitates accurate, noninvasive assessment of the mitral valvular complex, by creating precise three-dimensional heart models. The 3-dimensional computer reconstructions are then converted to a physical model using 3-dimensional printing technology, thereby enabling patient-specific assessment of the interaction between device and patient. It may provide new opportunities for a better understanding of the mitral anatomy-pathophysiology-device interaction, which is of critical importance for the advancement of transcatheter mitral valve replacement. Copyright © 2015 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Data mining to support simulation modeling of patient flow in hospitals.

PubMed

Isken, Mark W; Rajagopalan, Balaji

2002-04-01

Spiraling health care costs in the United States are driving institutions to continually address the challenge of optimizing the use of scarce resources. One of the first steps towards optimizing resources is to utilize capacity effectively. For hospital capacity planning problems such as allocation of inpatient beds, computer simulation is often the method of choice. One of the more difficult aspects of using simulation models for such studies is the creation of a manageable set of patient types to include in the model. The objective of this paper is to demonstrate the potential of using data mining techniques, specifically clustering techniques such as K-means, to help guide the development of patient type definitions for purposes of building computer simulation or analytical models of patient flow in hospitals. Using data from a hospital in the Midwest this study brings forth several important issues that researchers need to address when applying clustering techniques in general and specifically to hospital data.

A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

PubMed Central

Rockne, Russell C.; Trister, Andrew D.; Jacobs, Joshua; Hawkins-Daarud, Andrea J.; Neal, Maxwell L.; Hendrickson, Kristi; Mrugala, Maciej M.; Rockhill, Jason K.; Kinahan, Paul; Krohn, Kenneth A.; Swanson, Kristin R.

2015-01-01

Glioblastoma multiforme (GBM) is a highly invasive primary brain tumour that has poor prognosis despite aggressive treatment. A hallmark of these tumours is diffuse invasion into the surrounding brain, necessitating a multi-modal treatment approach, including surgery, radiation and chemotherapy. We have previously demonstrated the ability of our model to predict radiographic response immediately following radiation therapy in individual GBM patients using a simplified geometry of the brain and theoretical radiation dose. Using only two pre-treatment magnetic resonance imaging scans, we calculate net rates of proliferation and invasion as well as radiation sensitivity for a patient's disease. Here, we present the application of our clinically targeted modelling approach to a single glioblastoma patient as a demonstration of our method. We apply our model in the full three-dimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [18F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patient-specific three-dimensional radiation treatment plan. Incorporation of hypoxia into our model with FMISO-PET increases the model–data agreement by an order of magnitude. This improvement was robust to our definition of hypoxia or the degree of radiation resistance quantified with the FMISO-PET image and our computational model, respectively. This work demonstrates a useful application of patient-specific modelling in personalized medicine and how mathematical modelling has the potential to unify multi-modality imaging and radiation treatment planning. PMID:25540239

A Framework for Different Levels of Integration of Computational Models Into Web-Based Virtual Patients

PubMed Central

Narracott, Andrew J; Manini, Simone; Bayley, Martin J; Lawford, Patricia V; McCormack, Keith; Zary, Nabil

2014-01-01

Background Virtual patients are increasingly common tools used in health care education to foster learning of clinical reasoning skills. One potential way to expand their functionality is to augment virtual patients’ interactivity by enriching them with computational models of physiological and pathological processes. Objective The primary goal of this paper was to propose a conceptual framework for the integration of computational models within virtual patients, with particular focus on (1) characteristics to be addressed while preparing the integration, (2) the extent of the integration, (3) strategies to achieve integration, and (4) methods for evaluating the feasibility of integration. An additional goal was to pilot the first investigation of changing framework variables on altering perceptions of integration. Methods The framework was constructed using an iterative process informed by Soft System Methodology. The Virtual Physiological Human (VPH) initiative has been used as a source of new computational models. The technical challenges associated with development of virtual patients enhanced by computational models are discussed from the perspectives of a number of different stakeholders. Concrete design and evaluation steps are discussed in the context of an exemplar virtual patient employing the results of the VPH ARCH project, as well as improvements for future iterations. Results The proposed framework consists of four main elements. The first element is a list of feasibility features characterizing the integration process from three perspectives: the computational modelling researcher, the health care educationalist, and the virtual patient system developer. The second element included three integration levels: basic, where a single set of simulation outcomes is generated for specific nodes in the activity graph; intermediate, involving pre-generation of simulation datasets over a range of input parameters; advanced, including dynamic solution of the model. The third element is the description of four integration strategies, and the last element consisted of evaluation profiles specifying the relevant feasibility features and acceptance thresholds for specific purposes. The group of experts who evaluated the virtual patient exemplar found higher integration more interesting, but at the same time they were more concerned with the validity of the result. The observed differences were not statistically significant. Conclusions This paper outlines a framework for the integration of computational models into virtual patients. The opportunities and challenges of model exploitation are discussed from a number of user perspectives, considering different levels of model integration. The long-term aim for future research is to isolate the most crucial factors in the framework and to determine their influence on the integration outcome. PMID:24463466

Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration.

PubMed

Wittek, Adam; Joldes, Grand; Couton, Mathieu; Warfield, Simon K; Miller, Karol

2010-12-01

Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer. Copyright © 2010 Elsevier Ltd. All rights reserved.

Patient-specific polyetheretherketone facial implants in a computer-aided planning workflow.

PubMed

Guevara-Rojas, Godoberto; Figl, Michael; Schicho, Kurt; Seemann, Rudolf; Traxler, Hannes; Vacariu, Apostolos; Carbon, Claus-Christian; Ewers, Rolf; Watzinger, Franz

2014-09-01

In the present study, we report an innovative workflow using polyetheretherketone (PEEK) patient-specific implants for esthetic corrections in the facial region through onlay grafting. The planning includes implant design according to virtual osteotomy and generation of a subtraction volume. The implant design was refined by stepwise changing the implant geometry according to soft tissue simulations. One patient was scanned using computed tomography. PEEK implants were interactively designed and manufactured using rapid prototyping techniques. Positioning intraoperatively was assisted by computer-aided navigation. Two months after surgery, a 3-dimensional surface model of the patient's face was generated using photogrammetry. Finally, the Hausdorff distance calculation was used to quantify the overall error, encompassing the failures in soft tissue simulation and implantation. The implant positioning process during surgery was satisfactory. The simulated soft tissue surface and the photogrammetry scan of the patient showed a high correspondence, especially where the skin covered the implants. The mean total error (Hausdorff distance) was 0.81 ± 1.00 mm (median 0.48, interquartile range 1.11). The spatial deviation remained less than 0.7 mm for the vast majority of points. The proposed workflow provides a complete computer-aided design, computer-aided manufacturing, and computer-aided surgery chain for implant design, allowing for soft tissue simulation, fabrication of patient-specific implants, and image-guided surgery to position the implants. Much of the surgical complexity resulting from osteotomies of the zygoma, chin, or mandibular angle might be transferred into the planning phase of patient-specific implants. Copyright © 2014 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Patterned corneal collagen crosslinking for astigmatism: Computational modeling study

PubMed Central

Seven, Ibrahim; Roy, Abhijit Sinha; Dupps, William J.

2014-01-01

PURPOSE To test the hypothesis that spatially selective corneal stromal stiffening can alter corneal astigmatism and assess the effects of treatment orientation, pattern, and material model complexity in computational models using patient-specific geometries. SETTING Cornea and Refractive Surgery Service, Academic Eye Institute, Cleveland, Ohio, USA. DESIGN Computational modeling study. METHODS Three-dimensional corneal geometries from 10 patients with corneal astigmatism were exported from a clinical tomography system (Pentacam). Corneoscleral finite element models of each eye were generated. Four candidate treatment patterns were simulated, and the effects of treatment orientation and magnitude of stiffening on anterior curvature and aberrations were studied. The effect of material model complexity on simulated outcomes was also assessed. RESULTS Pretreatment anterior corneal astigmatism ranged from 1.22 to 3.92 diopters (D) in a series that included regular and irregular astigmatic patterns. All simulated treatment patterns oriented on the flat axis resulted in mean reductions in corneal astigmatism and depended on the pattern geometry. The linear bow-tie pattern produced a greater mean reduction in astigmatism (1.08 D ± 0.13 [SD]; range 0.74 to 1.23 D) than other patterns tested under an assumed 2-times increase in corneal stiffness, and it had a nonlinear relationship to the degree of stiffening. The mean astigmatic effect did not change significantly with a fiber- or depth-dependent model, but it did affect the coupling ratio. CONCLUSIONS In silico simulations based on patient-specific geometries suggest that clinically significant reductions in astigmatism are possible with patterned collagen crosslinking. Effect magnitude was dependent on patient-specific geometry, effective stiffening pattern, and treatment orientation. PMID:24767795

Finite element strategies to satisfy clinical and engineering requirements in the field of percutaneous valves.

PubMed

Capelli, Claudio; Biglino, Giovanni; Petrini, Lorenza; Migliavacca, Francesco; Cosentino, Daria; Bonhoeffer, Philipp; Taylor, Andrew M; Schievano, Silvia

2012-12-01

Finite element (FE) modelling can be a very resourceful tool in the field of cardiovascular devices. To ensure result reliability, FE models must be validated experimentally against physical data. Their clinical application (e.g., patients' suitability, morphological evaluation) also requires fast simulation process and access to results, while engineering applications need highly accurate results. This study shows how FE models with different mesh discretisations can suit clinical and engineering requirements for studying a novel device designed for percutaneous valve implantation. Following sensitivity analysis and experimental characterisation of the materials, the stent-graft was first studied in a simplified geometry (i.e., compliant cylinder) and validated against in vitro data, and then in a patient-specific implantation site (i.e., distensible right ventricular outflow tract). Different meshing strategies using solid, beam and shell elements were tested. Results showed excellent agreement between computational and experimental data in the simplified implantation site. Beam elements were found to be convenient for clinical applications, providing reliable results in less than one hour in a patient-specific anatomical model. Solid elements remain the FE choice for engineering applications, albeit more computationally expensive (>100 times). This work also showed how information on device mechanical behaviour differs when acquired in a simplified model as opposed to a patient-specific model.

WE-DE-201-12: Thermal and Dosimetric Properties of a Ferrite-Based Thermo-Brachytherapy Seed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warrell, G; Shvydka, D; Parsai, E I

Purpose: The novel thermo-brachytherapy (TB) seed provides a simple means of adding hyperthermia to LDR prostate permanent implant brachytherapy. The high blood perfusion rate (BPR) within the prostate motivates the use of the ferrite and conductive outer layer design for the seed cores. We describe the results of computational analyses of the thermal properties of this ferrite-based TB seed in modelled patient-specific anatomy, as well as studies of the interseed and scatter (ISA) effect. Methods: The anatomies (including the thermophysical properties of the main tissue types) and seed distributions of 6 prostate patients who had been treated with LDR brachytherapymore » seeds were modelled in the finite element analysis software COMSOL, using ferrite-based TB and additional hyperthermia-only (HT-only) seeds. The resulting temperature distributions were compared to those computed for patient-specific seed distributions, but in uniform anatomy with a constant blood perfusion rate. The ISA effect was quantified in the Monte Carlo software package MCNP5. Results: Compared with temperature distributions calculated in modelled uniform tissue, temperature distributions in the patient-specific anatomy were higher and more heterogeneous. Moreover, the maximum temperature to the rectal wall was typically ∼1 °C greater for patient-specific anatomy than for uniform anatomy. The ISA effect of the TB and HT-only seeds caused a reduction in D90 similar to that found for previously-investigated NiCu-based seeds, but of a slightly smaller magnitude. Conclusion: The differences between temperature distributions computed for uniform and patient-specific anatomy for ferrite-based seeds are significant enough that heterogeneous anatomy should be considered. Both types of modelling indicate that ferrite-based seeds provide sufficiently high and uniform hyperthermia to the prostate, without excessively heating surrounding tissues. The ISA effect of these seeds is slightly less than that for the previously-presented NiCu-based seeds.« less

Incremental Learning With Selective Memory (ILSM): Towards Fast Prostate Localization for Image Guided Radiotherapy

PubMed Central

Gao, Yaozong; Zhan, Yiqiang

2015-01-01

Image-guided radiotherapy (IGRT) requires fast and accurate localization of the prostate in 3-D treatment-guided radiotherapy, which is challenging due to low tissue contrast and large anatomical variation across patients. On the other hand, the IGRT workflow involves collecting a series of computed tomography (CT) images from the same patient under treatment. These images contain valuable patient-specific information yet are often neglected by previous works. In this paper, we propose a novel learning framework, namely incremental learning with selective memory (ILSM), to effectively learn the patient-specific appearance characteristics from these patient-specific images. Specifically, starting with a population-based discriminative appearance model, ILSM aims to “personalize” the model to fit patient-specific appearance characteristics. The model is personalized with two steps: backward pruning that discards obsolete population-based knowledge and forward learning that incorporates patient-specific characteristics. By effectively combining the patient-specific characteristics with the general population statistics, the incrementally learned appearance model can localize the prostate of a specific patient much more accurately. This work has three contributions: 1) the proposed incremental learning framework can capture patient-specific characteristics more effectively, compared to traditional learning schemes, such as pure patient-specific learning, population-based learning, and mixture learning with patient-specific and population data; 2) this learning framework does not have any parametric model assumption, hence, allowing the adoption of any discriminative classifier; and 3) using ILSM, we can localize the prostate in treatment CTs accurately (DSC ∼0.89) and fast (∼4 s), which satisfies the real-world clinical requirements of IGRT. PMID:24495983

Patient- and cohort-specific dose and risk estimation for abdominopelvic CT: a study based on 100 patients

NASA Astrophysics Data System (ADS)

Tian, Xiaoyu; Li, Xiang; Segars, W. Paul; Frush, Donald P.; Samei, Ehsan

2012-03-01

The purpose of this work was twofold: (a) to estimate patient- and cohort-specific radiation dose and cancer risk index for abdominopelvic computer tomography (CT) scans; (b) to evaluate the effects of patient anatomical characteristics (size, age, and gender) and CT scanner model on dose and risk conversion coefficients. The study included 100 patient models (42 pediatric models, 58 adult models) and multi-detector array CT scanners from two commercial manufacturers (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare). A previously-validated Monte Carlo program was used to simulate organ dose for each patient model and each scanner, from which DLP-normalized-effective dose (k factor) and DLP-normalized-risk index values (q factor) were derived. The k factor showed exponential decrease with increasing patient size. For a given gender, q factor showed exponential decrease with both increasing patient size and patient age. The discrepancies in k and q factors across scanners were on average 8% and 15%, respectively. This study demonstrates the feasibility of estimating patient-specific organ dose and cohort-specific effective dose and risk index in abdominopelvic CT requiring only the knowledge of patient size, gender, and age.

Biomechanical model for computing deformations for whole-body image registration: A meshless approach.

PubMed

Li, Mao; Miller, Karol; Joldes, Grand Roman; Kikinis, Ron; Wittek, Adam

2016-12-01

Patient-specific biomechanical models have been advocated as a tool for predicting deformations of soft body organs/tissue for medical image registration (aligning two sets of images) when differences between the images are large. However, complex and irregular geometry of the body organs makes generation of patient-specific biomechanical models very time-consuming. Meshless discretisation has been proposed to solve this challenge. However, applications so far have been limited to 2D models and computing single organ deformations. In this study, 3D comprehensive patient-specific nonlinear biomechanical models implemented using meshless Total Lagrangian explicit dynamics algorithms are applied to predict a 3D deformation field for whole-body image registration. Unlike a conventional approach that requires dividing (segmenting) the image into non-overlapping constituents representing different organs/tissues, the mechanical properties are assigned using the fuzzy c-means algorithm without the image segmentation. Verification indicates that the deformations predicted using the proposed meshless approach are for practical purposes the same as those obtained using the previously validated finite element models. To quantitatively evaluate the accuracy of the predicted deformations, we determined the spatial misalignment between the registered (i.e. source images warped using the predicted deformations) and target images by computing the edge-based Hausdorff distance. The Hausdorff distance-based evaluation determines that our meshless models led to successful registration of the vast majority of the image features. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

An efficient two-stage approach for image-based FSI analysis of atherosclerotic arteries

PubMed Central

Rayz, Vitaliy L.; Mofrad, Mohammad R. K.; Saloner, David

2010-01-01

Patient-specific biomechanical modeling of atherosclerotic arteries has the potential to aid clinicians in characterizing lesions and determining optimal treatment plans. To attain high levels of accuracy, recent models use medical imaging data to determine plaque component boundaries in three dimensions, and fluid–structure interaction is used to capture mechanical loading of the diseased vessel. As the plaque components and vessel wall are often highly complex in shape, constructing a suitable structured computational mesh is very challenging and can require a great deal of time. Models based on unstructured computational meshes require relatively less time to construct and are capable of accurately representing plaque components in three dimensions. These models unfortunately require additional computational resources and computing time for accurate and meaningful results. A two-stage modeling strategy based on unstructured computational meshes is proposed to achieve a reasonable balance between meshing difficulty and computational resource and time demand. In this method, a coarsegrained simulation of the full arterial domain is used to guide and constrain a fine-scale simulation of a smaller region of interest within the full domain. Results for a patient-specific carotid bifurcation model demonstrate that the two-stage approach can afford a large savings in both time for mesh generation and time and resources needed for computation. The effects of solid and fluid domain truncation were explored, and were shown to minimally affect accuracy of the stress fields predicted with the two-stage approach. PMID:19756798

Patient-specific surgical planning and hemodynamic computational fluid dynamics optimization through free-form haptic anatomy editing tool (SURGEM).

PubMed

Pekkan, Kerem; Whited, Brian; Kanter, Kirk; Sharma, Shiva; de Zelicourt, Diane; Sundareswaran, Kartik; Frakes, David; Rossignac, Jarek; Yoganathan, Ajit P

2008-11-01

The first version of an anatomy editing/surgical planning tool (SURGEM) targeting anatomical complexity and patient-specific computational fluid dynamics (CFD) analysis is presented. Novel three-dimensional (3D) shape editing concepts and human-shape interaction technologies have been integrated to facilitate interactive surgical morphology alterations, grid generation and CFD analysis. In order to implement "manual hemodynamic optimization" at the surgery planning phase for patients with congenital heart defects, these tools are applied to design and evaluate possible modifications of patient-specific anatomies. In this context, anatomies involve complex geometric topologies and tortuous 3D blood flow pathways with multiple inlets and outlets. These tools make it possible to freely deform the lumen surface and to bend and position baffles through real-time, direct manipulation of the 3D models with both hands, thus eliminating the tedious and time-consuming phase of entering the desired geometry using traditional computer-aided design (CAD) systems. The 3D models of the modified anatomies are seamlessly exported and meshed for patient-specific CFD analysis. Free-formed anatomical modifications are quantified using an in-house skeletization based cross-sectional geometry analysis tool. Hemodynamic performance of the systematically modified anatomies is compared with the original anatomy using CFD. CFD results showed the relative importance of the various surgically created features such as pouch size, vena cave to pulmonary artery (PA) flare and PA stenosis. An interactive surgical-patch size estimator is also introduced. The combined design/analysis cycle time is used for comparing and optimizing surgical plans and improvements are tabulated. The reduced cost of patient-specific shape design and analysis process, made it possible to envision large clinical studies to assess the validity of predictive patient-specific CFD simulations. In this paper, model anatomical design studies are performed on a total of eight different complex patient specific anatomies. Using SURGEM, more than 30 new anatomical designs (or candidate configurations) are created, and the corresponding user times presented. CFD performances for eight of these candidate configurations are also presented.

Success and Failure in Dynamic Decision Environments: Understanding Treatment Strategies for Patients with a Chronic Disease

ERIC Educational Resources Information Center

Ramsey, Gregory W.

2010-01-01

This dissertation proposes and tests a theory explaining how people make decisions to achieve a goal in a specific task environment. The theory is represented as a computational model and implemented as a computer program. The task studied was primary care physicians treating patients with type 2 diabetes. Some physicians succeed in achieving…

Multiscale modeling and simulation of blood flow in coronary artery bypass graft surgeries

NASA Astrophysics Data System (ADS)

Sankaran, Sethuraman; Esmaily Moghadam, Mahdi; Kahn, Andy; Marsden, Alison

2011-11-01

We present a computational framework for modeling and simulation of blood flow in patients who undergo coronary artery bypass graft (CABG) surgeries. We evaluate the influence of shape on the homeostatic state, cardiac output, and other quantities of interest. We present a case study on a patient with multiple CABG. We build a patient-specific model of the blood vessels comprised of the aorta, vessels branching from the top of the aorta (brachiocephalic artery and carotids) and the coronary arteries, in addition to bypass grafts. The rest of the circulatory system is modeled using lumped parameter 0D models comprised of resistances, compliances, inertances and elastance. An algorithm is presented that computes these parameters automatically given constraints on the flow. A Finite element framework is used to compute blood flow and pressure in the 3D model to which the 0D code is coupled at the model inlets and outlets. An adaptive closed loop BC is used to capture the coupling of the various outlets of the model with inlets, and is compared with a model with fixed inlet BC. We compare and contrast the pressure, flowrate, coronary perfusion, and PV curves obtained in the different cases. Further, we compare and contrast quantities of interest such as wall shear stress, wall shear stress gradients and oscillatory shear index for different surgical geometries and discuss implications of patient-specific optimization. I would like to acknowlege AHA for funding this work.

Computational Motion Phantoms and Statistical Models of Respiratory Motion

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Klinder, Tobias; Lorenz, Cristian

Breathing motion is not a robust and 100 % reproducible process, and inter- and intra-fractional motion variations form an important problem in radiotherapy of the thorax and upper abdomen. A widespread consensus nowadays exists that it would be useful to use prior knowledge about respiratory organ motion and its variability to improve radiotherapy planning and treatment delivery. This chapter discusses two different approaches to model the variability of respiratory motion. In the first part, we review computational motion phantoms, i.e. computerized anatomical and physiological models. Computational phantoms are excellent tools to simulate and investigate the effects of organ motion in radiation therapy and to gain insight into methods for motion management. The second part of this chapter discusses statistical modeling techniques to describe the breathing motion and its variability in a population of 4D images. Population-based models can be generated from repeatedly acquired 4D images of the same patient (intra-patient models) and from 4D images of different patients (inter-patient models). The generation of those models is explained and possible applications of those models for motion prediction in radiotherapy are exemplified. Computational models of respiratory motion and motion variability have numerous applications in radiation therapy, e.g. to understand motion effects in simulation studies, to develop and evaluate treatment strategies or to introduce prior knowledge into the patient-specific treatment planning.

Two-part models with stochastic processes for modelling longitudinal semicontinuous data: Computationally efficient inference and modelling the overall marginal mean.

PubMed

Yiu, Sean; Tom, Brian Dm

2017-01-01

Several researchers have described two-part models with patient-specific stochastic processes for analysing longitudinal semicontinuous data. In theory, such models can offer greater flexibility than the standard two-part model with patient-specific random effects. However, in practice, the high dimensional integrations involved in the marginal likelihood (i.e. integrated over the stochastic processes) significantly complicates model fitting. Thus, non-standard computationally intensive procedures based on simulating the marginal likelihood have so far only been proposed. In this paper, we describe an efficient method of implementation by demonstrating how the high dimensional integrations involved in the marginal likelihood can be computed efficiently. Specifically, by using a property of the multivariate normal distribution and the standard marginal cumulative distribution function identity, we transform the marginal likelihood so that the high dimensional integrations are contained in the cumulative distribution function of a multivariate normal distribution, which can then be efficiently evaluated. Hence, maximum likelihood estimation can be used to obtain parameter estimates and asymptotic standard errors (from the observed information matrix) of model parameters. We describe our proposed efficient implementation procedure for the standard two-part model parameterisation and when it is of interest to directly model the overall marginal mean. The methodology is applied on a psoriatic arthritis data set concerning functional disability.

Computer-assisted versus non-computer-assisted preoperative planning of corrective osteotomy for extra-articular distal radius malunions: a randomized controlled trial.

PubMed

Leong, Natalie L; Buijze, Geert A; Fu, Eric C; Stockmans, Filip; Jupiter, Jesse B

2010-12-14

Malunion is the most common complication of distal radius fracture. It has previously been demonstrated that there is a correlation between the quality of anatomical correction and overall wrist function. However, surgical correction can be difficult because of the often complex anatomy associated with this condition. Computer assisted surgical planning, combined with patient-specific surgical guides, has the potential to improve pre-operative understanding of patient anatomy as well as intra-operative accuracy. For patients with malunion of the distal radius fracture, this technology could significantly improve clinical outcomes that largely depend on the quality of restoration of normal anatomy. Therefore, the objective of this study is to compare patient outcomes after corrective osteotomy for distal radius malunion with and without preoperative computer-assisted planning and peri-operative patient-specific surgical guides. This study is a multi-center randomized controlled trial of conventional planning versus computer-assisted planning for surgical correction of distal radius malunion. Adult patients with extra-articular malunion of the distal radius will be invited to enroll in our study. After providing informed consent, subjects will be randomized to two groups: one group will receive corrective surgery with conventional preoperative planning, while the other will receive corrective surgery with computer-assisted pre-operative planning and peri-operative patient specific surgical guides. In the computer-assisted planning group, a CT scan of the affected forearm as well as the normal, contralateral forearm will be obtained. The images will be used to construct a 3D anatomical model of the defect and patient-specific surgical guides will be manufactured. Outcome will be measured by DASH and PRWE scores, grip strength, radiographic measurements, and patient satisfaction at 3, 6, and 12 months postoperatively. Computer-assisted surgical planning, combined with patient-specific surgical guides, is a powerful new technology that has the potential to improve the accuracy and consistency of orthopaedic surgery. To date, the role of this technology in upper extremity surgery has not been adequately investigated, and it is unclear whether its use provides any significant clinical benefit over traditional preoperative imaging protocols. Our study will represent the first randomized controlled trial investigating the use of computer assisted surgery in corrective osteotomy for distal radius malunions. NCT01193010.

A patient-specific aortic valve model based on moving resistive immersed implicit surfaces.

PubMed

Fedele, Marco; Faggiano, Elena; Dedè, Luca; Quarteroni, Alfio

2017-10-01

In this paper, we propose a full computational framework to simulate the hemodynamics in the aorta including the valve. Closed and open valve surfaces, as well as the lumen aorta, are reconstructed directly from medical images using new ad hoc algorithms, allowing a patient-specific simulation. The fluid dynamics problem that accounts from the movement of the valve is solved by a new 3D-0D fluid-structure interaction model in which the valve surface is implicitly represented through level set functions, yielding, in the Navier-Stokes equations, a resistive penalization term enforcing the blood to adhere to the valve leaflets. The dynamics of the valve between its closed and open position is modeled using a reduced geometric 0D model. At the discrete level, a finite element formulation is used and the SUPG stabilization is extended to include the resistive term in the Navier-Stokes equations. Then, after time discretization, the 3D fluid and 0D valve models are coupled through a staggered approach. This computational framework, applied to a patient-specific geometry and data, allows to simulate the movement of the valve, the sharp pressure jump occurring across the leaflets, and the blood flow pattern inside the aorta.

Applications of patient-specific 3D printing in medicine.

PubMed

Heller, Martin; Bauer, Heide-Katharina; Goetze, Elisabeth; Gielisch, Matthias; Roth, Klaus E; Drees, Philipp; Maier, Gerrit S; Dorweiler, Bernhard; Ghazy, Ahmed; Neufurth, Meik; Müller, Werner E G; Schröder, Heinz C; Wang, Xiaohong; Vahl, Christian-Friedrich; Al-Nawas, Bilal

Already three decades ago, the potential of medical 3D printing (3DP) or rapid prototyping for improved patient treatment began to be recognized. Since then, more and more medical indications in different surgical disciplines have been improved by using this new technique. Numerous examples have demonstrated the enormous benefit of 3DP in the medical care of patients by, for example, planning complex surgical interventions preoperatively, reducing implantation steps and anesthesia times, and helping with intraoperative orientation. At the beginning of every individual 3D model, patient-specific data on the basis of computed tomography (CT), magnetic resonance imaging (MRI), or ultrasound data is generated, which is then digitalized and processed using computer-aided design/computer-aided manufacturing (CAD/CAM) software. Finally, the resulting data sets are used to generate 3D-printed models or even implants. There are a variety of different application areas in the various medical fields, eg, drill or positioning templates, or surgical guides in maxillofacial surgery, or patient-specific implants in orthopedics. Furthermore, in vascular surgery it is possible to visualize pathologies such as aortic aneurysms so as to improve the planning of surgical treatment. Although rapid prototyping of individual models and implants is already applied very successfully in regenerative medicine, most of the materials used for 3DP are not yet suitable for implantation in the body. Therefore, it will be necessary in future to develop novel therapy approaches and design new materials in order to completely reconstruct natural tissue.

Modular, Semantics-Based Composition of Biosimulation Models

ERIC Educational Resources Information Center

Neal, Maxwell Lewis

2010-01-01

Biosimulation models are valuable, versatile tools used for hypothesis generation and testing, codification of biological theory, education, and patient-specific modeling. Driven by recent advances in computational power and the accumulation of systems-level experimental data, modelers today are creating models with an unprecedented level of…

Patient-specific radiation dose and cancer risk estimation in CT: Part II. Application to patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Xiang; Samei, Ehsan; Segars, W. Paul

2011-01-15

Purpose: Current methods for estimating and reporting radiation dose from CT examinations are largely patient-generic; the body size and hence dose variation from patient to patient is not reflected. Furthermore, the current protocol designs rely on dose as a surrogate for the risk of cancer incidence, neglecting the strong dependence of risk on age and gender. The purpose of this study was to develop a method for estimating patient-specific radiation dose and cancer risk from CT examinations. Methods: The study included two patients (a 5-week-old female patient and a 12-year-old male patient), who underwent 64-slice CT examinations (LightSpeed VCT, GEmore » Healthcare) of the chest, abdomen, and pelvis at our institution in 2006. For each patient, a nonuniform rational B-spine (NURBS) based full-body computer model was created based on the patient's clinical CT data. Large organs and structures inside the image volume were individually segmented and modeled. Other organs were created by transforming an existing adult male or female full-body computer model (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. A Monte Carlo program previously developed and validated for dose simulation on the LightSpeed VCT scanner was used to estimate patient-specific organ dose, from which effective dose and risks of cancer incidence were derived. Patient-specific organ dose and effective dose were compared with patient-generic CT dose quantities in current clinical use: the volume-weighted CT dose index (CTDI{sub vol}) and the effective dose derived from the dose-length product (DLP). Results: The effective dose for the CT examination of the newborn patient (5.7 mSv) was higher but comparable to that for the CT examination of the teenager patient (4.9 mSv) due to the size-based clinical CT protocols at our institution, which employ lower scan techniques for smaller patients. However, the overall risk of cancer incidence attributable to the CT examination was much higher for the newborn (2.4 in 1000) than for the teenager (0.7 in 1000). For the two pediatric-aged patients in our study, CTDI{sub vol} underestimated dose to large organs in the scan coverage by 30%-48%. The effective dose derived from DLP using published conversion coefficients differed from that calculated using patient-specific organ dose values by -57% to 13%, when the tissue weighting factors of ICRP 60 were used, and by -63% to 28%, when the tissue weighting factors of ICRP 103 were used. Conclusions: It is possible to estimate patient-specific radiation dose and cancer risk from CT examinations by combining a validated Monte Carlo program with patient-specific anatomical models that are derived from the patients' clinical CT data and supplemented by transformed models of reference adults. With the construction of a large library of patient-specific computer models encompassing patients of all ages and weight percentiles, dose and risk can be estimated for any patient prior to or after a CT examination. Such information may aid in decisions for image utilization and can further guide the design and optimization of CT technologies and scan protocols.« less

Perfusion kinetics in human brain tumor with DCE-MRI derived model and CFD analysis.

PubMed

Bhandari, A; Bansal, A; Singh, A; Sinha, N

2017-07-05

Cancer is one of the leading causes of death all over the world. Among the strategies that are used for cancer treatment, the effectiveness of chemotherapy is often hindered by factors such as irregular and non-uniform uptake of drugs inside tumor. Thus, accurate prediction of drug transport and deposition inside tumor is crucial for increasing the effectiveness of chemotherapeutic treatment. In this study, a computational model of human brain tumor is developed that incorporates dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data into a voxelized porous media model. The model takes into account realistic transport and perfusion kinetics parameters together with realistic heterogeneous tumor vasculature and accurate arterial input function (AIF), which makes it patient specific. The computational results for interstitial fluid pressure (IFP), interstitial fluid velocity (IFV) and tracer concentration show good agreement with the experimental results. The computational model can be extended further for predicting the deposition of chemotherapeutic drugs in tumor environment as well as selection of the best chemotherapeutic drug for a specific patient. Copyright © 2017 Elsevier Ltd. All rights reserved.

Models of neuromodulation for computational psychiatry.

PubMed

Iglesias, Sandra; Tomiello, Sara; Schneebeli, Maya; Stephan, Klaas E

2017-05-01

Psychiatry faces fundamental challenges: based on a syndrome-based nosology, it presently lacks clinical tests to infer on disease processes that cause symptoms of individual patients and must resort to trial-and-error treatment strategies. These challenges have fueled the recent emergence of a novel field-computational psychiatry-that strives for mathematical models of disease processes at physiological and computational (information processing) levels. This review is motivated by one particular goal of computational psychiatry: the development of 'computational assays' that can be applied to behavioral or neuroimaging data from individual patients and support differential diagnosis and guiding patient-specific treatment. Because the majority of available pharmacotherapeutic approaches in psychiatry target neuromodulatory transmitters, models that infer (patho)physiological and (patho)computational actions of different neuromodulatory transmitters are of central interest for computational psychiatry. This article reviews the (many) outstanding questions on the computational roles of neuromodulators (dopamine, acetylcholine, serotonin, and noradrenaline), outlines available evidence, and discusses promises and pitfalls in translating these findings to clinical applications. WIREs Cogn Sci 2017, 8:e1420. doi: 10.1002/wcs.1420 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Patient-specific radiation dose and cancer risk estimation in CT: Part II. Application to patients

PubMed Central

Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Toncheva, Greta; Yoshizumi, Terry T.; Frush, Donald P.

2011-01-01

Purpose: Current methods for estimating and reporting radiation dose from CT examinations are largely patient-generic; the body size and hence dose variation from patient to patient is not reflected. Furthermore, the current protocol designs rely on dose as a surrogate for the risk of cancer incidence, neglecting the strong dependence of risk on age and gender. The purpose of this study was to develop a method for estimating patient-specific radiation dose and cancer risk from CT examinations. Methods: The study included two patients (a 5-week-old female patient and a 12-year-old male patient), who underwent 64-slice CT examinations (LightSpeed VCT, GE Healthcare) of the chest, abdomen, and pelvis at our institution in 2006. For each patient, a nonuniform rational B-spine (NURBS) based full-body computer model was created based on the patient’s clinical CT data. Large organs and structures inside the image volume were individually segmented and modeled. Other organs were created by transforming an existing adult male or female full-body computer model (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. A Monte Carlo program previously developed and validated for dose simulation on the LightSpeed VCT scanner was used to estimate patient-specific organ dose, from which effective dose and risks of cancer incidence were derived. Patient-specific organ dose and effective dose were compared with patient-generic CT dose quantities in current clinical use: the volume-weighted CT dose index (CTDIvol) and the effective dose derived from the dose-length product (DLP). Results: The effective dose for the CT examination of the newborn patient (5.7 mSv) was higher but comparable to that for the CT examination of the teenager patient (4.9 mSv) due to the size-based clinical CT protocols at our institution, which employ lower scan techniques for smaller patients. However, the overall risk of cancer incidence attributable to the CT examination was much higher for the newborn (2.4 in 1000) than for the teenager (0.7 in 1000). For the two pediatric-aged patients in our study, CTDIvol underestimated dose to large organs in the scan coverage by 30%–48%. The effective dose derived from DLP using published conversion coefficients differed from that calculated using patient-specific organ dose values by −57% to 13%, when the tissue weighting factors of ICRP 60 were used, and by −63% to 28%, when the tissue weighting factors of ICRP 103 were used. Conclusions: It is possible to estimate patient-specific radiation dose and cancer risk from CT examinations by combining a validated Monte Carlo program with patient-specific anatomical models that are derived from the patients’ clinical CT data and supplemented by transformed models of reference adults. With the construction of a large library of patient-specific computer models encompassing patients of all ages and weight percentiles, dose and risk can be estimated for any patient prior to or after a CT examination. Such information may aid in decisions for image utilization and can further guide the design and optimization of CT technologies and scan protocols. PMID:21361209

Hemodynamic Assessment of Compliance of Pre-Stressed Pulmonary Valve-Vasculature in Patient Specific Geometry Using an Inverse Algorithm

NASA Astrophysics Data System (ADS)

Hebbar, Ullhas; Paul, Anup; Banerjee, Rupak

2016-11-01

Image based modeling is finding increasing relevance in assisting diagnosis of Pulmonary Valve-Vasculature Dysfunction (PVD) in congenital heart disease patients. This research presents compliant artery - blood interaction in a patient specific Pulmonary Artery (PA) model. This is an improvement over our previous numerical studies which assumed rigid walled arteries. The impedance of the arteries and the energy transfer from the Right Ventricle (RV) to PA is governed by compliance, which in turn is influenced by the level of pre-stress in the arteries. In order to evaluate the pre-stress, an inverse algorithm was developed using an in-house script written in MATLAB and Python, and implemented using the Finite Element Method (FEM). This analysis used a patient specific material model developed by our group, in conjunction with measured pressure (invasive) and velocity (non-invasive) values. The analysis was performed on an FEM solver, and preliminary results indicated that the Main PA (MPA) exhibited higher compliance as well as increased hysteresis over the cardiac cycle when compared with the Left PA (LPA). The computed compliance values for the MPA and LPA were 14% and 34% lesser than the corresponding measured values. Further, the computed pressure drop and flow waveforms were in close agreement with the measured values. In conclusion, compliant artery - blood interaction models of patient specific geometries can play an important role in hemodynamics based diagnosis of PVD.

Patient-Specific Simulation of Cardiac Blood Flow From High-Resolution Computed Tomography.

PubMed

Lantz, Jonas; Henriksson, Lilian; Persson, Anders; Karlsson, Matts; Ebbers, Tino

2016-12-01

Cardiac hemodynamics can be computed from medical imaging data, and results could potentially aid in cardiac diagnosis and treatment optimization. However, simulations are often based on simplified geometries, ignoring features such as papillary muscles and trabeculae due to their complex shape, limitations in image acquisitions, and challenges in computational modeling. This severely hampers the use of computational fluid dynamics in clinical practice. The overall aim of this study was to develop a novel numerical framework that incorporated these geometrical features. The model included the left atrium, ventricle, ascending aorta, and heart valves. The framework used image registration to obtain patient-specific wall motion, automatic remeshing to handle topological changes due to the complex trabeculae motion, and a fast interpolation routine to obtain intermediate meshes during the simulations. Velocity fields and residence time were evaluated, and they indicated that papillary muscles and trabeculae strongly interacted with the blood, which could not be observed in a simplified model. The framework resulted in a model with outstanding geometrical detail, demonstrating the feasibility as well as the importance of a framework that is capable of simulating blood flow in physiologically realistic hearts.

Complex Osteotomies of Tibial Plateau Malunions Using Computer-Assisted Planning and Patient-Specific Surgical Guides.

PubMed

Fürnstahl, Philipp; Vlachopoulos, Lazaros; Schweizer, Andreas; Fucentese, Sandro F; Koch, Peter P

2015-08-01

The accurate reduction of tibial plateau malunions can be challenging without guidance. In this work, we report on a novel technique that combines 3-dimensional computer-assisted planning with patient-specific surgical guides for improving reliability and accuracy of complex intraarticular corrective osteotomies. Preoperative planning based on 3-dimensional bone models was performed to simulate fragment mobilization and reduction in 3 cases. Surgical implementation of the preoperative plan using patient-specific cutting and reduction guides was evaluated; benefits and limitations of the approach were identified and discussed. The preliminary results are encouraging and show that complex, intraarticular corrective osteotomies can be accurately performed with this technique. For selective patients with complex malunions around the tibia plateau, this method might be an attractive option, with the potential to facilitate achieving the most accurate correction possible.

A modular inverse elastostatics approach to resolve the pressure-induced stress state for in vivo imaging based cardiovascular modeling.

PubMed

Peirlinck, Mathias; De Beule, Matthieu; Segers, Patrick; Rebelo, Nuno

2018-05-28

Patient-specific biomechanical modeling of the cardiovascular system is complicated by the presence of a physiological pressure load given that the imaged tissue is in a pre-stressed and -strained state. Neglect of this prestressed state into solid tissue mechanics models leads to erroneous metrics (e.g. wall deformation, peak stress, wall shear stress) which in their turn are used for device design choices, risk assessment (e.g. procedure, rupture) and surgery planning. It is thus of utmost importance to incorporate this deformed and loaded tissue state into the computational models, which implies solving an inverse problem (calculating an undeformed geometry given the load and the deformed geometry). Methodologies to solve this inverse problem can be categorized into iterative and direct methodologies, both having their inherent advantages and disadvantages. Direct methodologies are typically based on the inverse elastostatics (IE) approach and offer a computationally efficient single shot methodology to compute the in vivo stress state. However, cumbersome and problem-specific derivations of the formulations and non-trivial access to the finite element analysis (FEA) code, especially for commercial products, refrain a broad implementation of these methodologies. For that reason, we developed a novel, modular IE approach and implemented this methodology in a commercial FEA solver with minor user subroutine interventions. The accuracy of this methodology was demonstrated in an arterial tube and porcine biventricular myocardium model. The computational power and efficiency of the methodology was shown by computing the in vivo stress and strain state, and the corresponding unloaded geometry, for two models containing multiple interacting incompressible, anisotropic (fiber-embedded) and hyperelastic material behaviors: a patient-specific abdominal aortic aneurysm and a full 4-chamber heart model. Copyright © 2018 Elsevier Ltd. All rights reserved.

Computational Psychotherapy Research: Scaling up the evaluation of patient-provider interactions

PubMed Central

Imel, Zac E.; Steyvers, Mark; Atkins, David C.

2014-01-01

In psychotherapy, the patient-provider interaction contains the treatment’s active ingredients. However, the technology for analyzing the content of this interaction has not fundamentally changed in decades, limiting both the scale and specificity of psychotherapy research. New methods are required in order to “scale up” to larger evaluation tasks and “drill down” into the raw linguistic data of patient-therapist interactions. In the current paper we demonstrate the utility of statistical text analysis models called topic models for discovering the underlying linguistic structure in psychotherapy. Topic models identify semantic themes (or topics) in a collection of documents (here, transcripts). We used topic models to summarize and visualize 1,553 psychotherapy and drug therapy (i.e., medication management) transcripts. Results showed that topic models identified clinically relevant content, including affective, content, and intervention related topics. In addition, topic models learned to identify specific types of therapist statements associated with treatment related codes (e.g., different treatment approaches, patient-therapist discussions about the therapeutic relationship). Visualizations of semantic similarity across sessions indicate that topic models identify content that discriminates between broad classes of therapy (e.g., cognitive behavioral therapy vs. psychodynamic therapy). Finally, predictive modeling demonstrated that topic model derived features can classify therapy type with a high degree of accuracy. Computational psychotherapy research has the potential to scale up the study of psychotherapy to thousands of sessions at a time, and we conclude by discussing the implications of computational methods such as topic models for the future of psychotherapy research and practice. PMID:24866972

Computational psychotherapy research: scaling up the evaluation of patient-provider interactions.

PubMed

Imel, Zac E; Steyvers, Mark; Atkins, David C

2015-03-01

In psychotherapy, the patient-provider interaction contains the treatment's active ingredients. However, the technology for analyzing the content of this interaction has not fundamentally changed in decades, limiting both the scale and specificity of psychotherapy research. New methods are required to "scale up" to larger evaluation tasks and "drill down" into the raw linguistic data of patient-therapist interactions. In the current article, we demonstrate the utility of statistical text analysis models called topic models for discovering the underlying linguistic structure in psychotherapy. Topic models identify semantic themes (or topics) in a collection of documents (here, transcripts). We used topic models to summarize and visualize 1,553 psychotherapy and drug therapy (i.e., medication management) transcripts. Results showed that topic models identified clinically relevant content, including affective, relational, and intervention related topics. In addition, topic models learned to identify specific types of therapist statements associated with treatment-related codes (e.g., different treatment approaches, patient-therapist discussions about the therapeutic relationship). Visualizations of semantic similarity across sessions indicate that topic models identify content that discriminates between broad classes of therapy (e.g., cognitive-behavioral therapy vs. psychodynamic therapy). Finally, predictive modeling demonstrated that topic model-derived features can classify therapy type with a high degree of accuracy. Computational psychotherapy research has the potential to scale up the study of psychotherapy to thousands of sessions at a time. We conclude by discussing the implications of computational methods such as topic models for the future of psychotherapy research and practice. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Combining population and patient-specific characteristics for prostate segmentation on 3D CT images

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Tian, Zhiqiang; Venkataraman, Rajesh; Sarkar, Saradwata; Liu, Xiabi; Tade, Funmilayo; Schuster, David M.; Fei, Baowei

2016-03-01

Prostate segmentation on CT images is a challenging task. In this paper, we explore the population and patient-specific characteristics for the segmentation of the prostate on CT images. Because population learning does not consider the inter-patient variations and because patient-specific learning may not perform well for different patients, we are combining the population and patient-specific information to improve segmentation performance. Specifically, we train a population model based on the population data and train a patient-specific model based on the manual segmentation on three slice of the new patient. We compute the similarity between the two models to explore the influence of applicable population knowledge on the specific patient. By combining the patient-specific knowledge with the influence, we can capture the population and patient-specific characteristics to calculate the probability of a pixel belonging to the prostate. Finally, we smooth the prostate surface according to the prostate-density value of the pixels in the distance transform image. We conducted the leave-one-out validation experiments on a set of CT volumes from 15 patients. Manual segmentation results from a radiologist serve as the gold standard for the evaluation. Experimental results show that our method achieved an average DSC of 85.1% as compared to the manual segmentation gold standard. This method outperformed the population learning method and the patient-specific learning approach alone. The CT segmentation method can have various applications in prostate cancer diagnosis and therapy.

Preservation of kinematics with posterior cruciate-, bicruciate- and patient-specific bicruciate-retaining prostheses in total knee arthroplasty by using computational simulation with normal knee model

PubMed Central

Koh, Y-G.; Son, J.; Kwon, S-K.; Kim, H-J.; Kang, K-T.

2017-01-01

Objectives Preservation of both anterior and posterior cruciate ligaments in total knee arthroplasty (TKA) can lead to near-normal post-operative joint mechanics and improved knee function. We hypothesised that a patient-specific bicruciate-retaining prosthesis preserves near-normal kinematics better than standard off-the-shelf posterior cruciate-retaining and bicruciate-retaining prostheses in TKA. Methods We developed the validated models to evaluate the post-operative kinematics in patient-specific bicruciate-retaining, standard off-the-shelf bicruciate-retaining and posterior cruciate-retaining TKA under gait and deep knee bend loading conditions using numerical simulation. Results Tibial posterior translation and internal rotation in patient-specific bicruciate-retaining prostheses preserved near-normal kinematics better than other standard off-the-shelf prostheses under gait loading conditions. Differences from normal kinematics were minimised for femoral rollback and internal-external rotation in patient-specific bicruciate-retaining, followed by standard off-the-shelf bicruciate-retaining and posterior cruciate-retaining TKA under deep knee bend loading conditions. Moreover, the standard off-the-shelf posterior cruciate-retaining TKA in this study showed the most abnormal performance in kinematics under gait and deep knee bend loading conditions, whereas patient-specific bicruciate-retaining TKA led to near-normal kinematics. Conclusion This study showed that restoration of the normal geometry of the knee joint in patient-specific bicruciate-retaining TKA and preservation of the anterior cruciate ligament can lead to improvement in kinematics compared with the standard off-the-shelf posterior cruciate-retaining and bicruciate-retaining TKA. Cite this article: Y-G. Koh, J. Son, S-K. Kwon, H-J. Kim, O-R. Kwon, K-T. Kang. Preservation of kinematics with posterior cruciate-, bicruciate- and patient-specific bicruciate-retaining prostheses in total knee arthroplasty by using computational simulation with normal knee model. Bone Joint Res 2017;6:557–565. DOI: 10.1302/2046-3758.69.BJR-2016-0250.R1. PMID:28947604

Grid convergence errors in hemodynamic solution of patient-specific cerebral aneurysms.

PubMed

Hodis, Simona; Uthamaraj, Susheil; Smith, Andrea L; Dennis, Kendall D; Kallmes, David F; Dragomir-Daescu, Dan

2012-11-15

Computational fluid dynamics (CFD) has become a cutting-edge tool for investigating hemodynamic dysfunctions in the body. It has the potential to help physicians quantify in more detail the phenomena difficult to capture with in vivo imaging techniques. CFD simulations in anatomically realistic geometries pose challenges in generating accurate solutions due to the grid distortion that may occur when the grid is aligned with complex geometries. In addition, results obtained with computational methods should be trusted only after the solution has been verified on multiple high-quality grids. The objective of this study was to present a comprehensive solution verification of the intra-aneurysmal flow results obtained on different morphologies of patient-specific cerebral aneurysms. We chose five patient-specific brain aneurysm models with different dome morphologies and estimated the grid convergence errors for each model. The grid convergence errors were estimated with respect to an extrapolated solution based on the Richardson extrapolation method, which accounts for the degree of grid refinement. For four of the five models, calculated velocity, pressure, and wall shear stress values at six different spatial locations converged monotonically, with maximum uncertainty magnitudes ranging from 12% to 16% on the finest grids. Due to the geometric complexity of the fifth model, the grid convergence errors showed oscillatory behavior; therefore, each patient-specific model required its own grid convergence study to establish the accuracy of the analysis. Copyright © 2012 Elsevier Ltd. All rights reserved.

Creation of an idealized nasopharynx geometry for accurate computational fluid dynamics simulations of nasal airflow in patient-specific models lacking the nasopharynx anatomy

PubMed Central

Borojeni, Azadeh A.T.; Frank-Ito, Dennis O.; Kimbell, Julia S.; Rhee, John S.; Garcia, Guilherme J. M.

2016-01-01

Virtual surgery planning based on computational fluid dynamics (CFD) simulations has the potential to improve surgical outcomes for nasal airway obstruction (NAO) patients, but the benefits of virtual surgery planning must outweigh the risks of radiation exposure. Cone beam computed tomography (CBCT) scans represent an attractive imaging modality for virtual surgery planning due to lower costs and lower radiation exposures compared with conventional CT scans. However, to minimize the radiation exposure, the CBCT sinusitis protocol sometimes images only the nasal cavity, excluding the nasopharynx. The goal of this study was to develop an idealized nasopharynx geometry for accurate representation of outlet boundary conditions when the nasopharynx geometry is unavailable. Anatomically-accurate models of the nasopharynx created from thirty CT scans were intersected with planes rotated at different angles to obtain an average geometry. Cross sections of the idealized nasopharynx were approximated as ellipses with cross-sectional areas and aspect ratios equal to the average in the actual patient-specific models. CFD simulations were performed to investigate whether nasal airflow patterns were affected when the CT-based nasopharynx was replaced by the idealized nasopharynx in 10 NAO patients. Despite the simple form of the idealized geometry, all biophysical variables (nasal resistance, airflow rate, and heat fluxes) were very similar in the idealized vs. patient-specific models. The results confirmed the expectation that the nasopharynx geometry has a minimal effect in the nasal airflow patterns during inspiration. The idealized nasopharynx geometry will be useful in future CFD studies of nasal airflow based on medical images that exclude the nasopharynx. PMID:27525807

GPU-based RFA simulation for minimally invasive cancer treatment of liver tumours.

PubMed

Mariappan, Panchatcharam; Weir, Phil; Flanagan, Ronan; Voglreiter, Philip; Alhonnoro, Tuomas; Pollari, Mika; Moche, Michael; Busse, Harald; Futterer, Jurgen; Portugaller, Horst Rupert; Sequeiros, Roberto Blanco; Kolesnik, Marina

2017-01-01

Radiofrequency ablation (RFA) is one of the most popular and well-standardized minimally invasive cancer treatments (MICT) for liver tumours, employed where surgical resection has been contraindicated. Less-experienced interventional radiologists (IRs) require an appropriate planning tool for the treatment to help avoid incomplete treatment and so reduce the tumour recurrence risk. Although a few tools are available to predict the ablation lesion geometry, the process is computationally expensive. Also, in our implementation, a few patient-specific parameters are used to improve the accuracy of the lesion prediction. Advanced heterogeneous computing using personal computers, incorporating the graphics processing unit (GPU) and the central processing unit (CPU), is proposed to predict the ablation lesion geometry. The most recent GPU technology is used to accelerate the finite element approximation of Penne's bioheat equation and a three state cell model. Patient-specific input parameters are used in the bioheat model to improve accuracy of the predicted lesion. A fast GPU-based RFA solver is developed to predict the lesion by doing most of the computational tasks in the GPU, while reserving the CPU for concurrent tasks such as lesion extraction based on the heat deposition at each finite element node. The solver takes less than 3 min for a treatment duration of 26 min. When the model receives patient-specific input parameters, the deviation between real and predicted lesion is below 3 mm. A multi-centre retrospective study indicates that the fast RFA solver is capable of providing the IR with the predicted lesion in the short time period before the intervention begins when the patient has been clinically prepared for the treatment.

Development of the Patient-specific Cardiovascular Modeling System Using Immersed Boundary Technique

NASA Astrophysics Data System (ADS)

Tay, Wee-Beng; Lin, Liang-Yu; Tseng, Wen-Yih; Tseng, Yu-Heng

2010-05-01

A computational fluid dynamics (CFD) based, patient-specific cardiovascular modeling system is under-developed. The system can identify possible diseased conditions and facilitate physicians' diagnosis at early stage through the hybrid CFD simulation and time-resolved magnetic resonance imaging (MRI). The CFD simulation is initially based on the three-dimensional heart model developed by McQueen and Peskin, which can simultaneously compute fluid motions and elastic boundary motions using the immersed boundary method. We extend and improve the three-dimensional heart model for the clinical application by including the patient-specific hemodynamic information. The flow features in the ventricles and their responses are investigated under different inflow and outflow conditions during diastole and systole phases based on the quasi-realistic heart model, which takes advantage of the observed flow scenarios. Our results indicate distinct differences between the two groups of participants, including the vortex formation process in the left ventricle (LV), as well as the flow rate distributions at different identified sources such as the aorta, vena cava and pulmonary veins/artery. We further identify some key parameters which may affect the vortex formation in the LV. Thus it is hypothesized that disease-related dysfunctions in intervals before complete heart failure can be observed in the dynamics of transmitral blood flow during early LV diastole.

Creation of Anatomically Accurate Computer-Aided Design (CAD) Solid Models from Medical Images

NASA Technical Reports Server (NTRS)

Stewart, John E.; Graham, R. Scott; Samareh, Jamshid A.; Oberlander, Eric J.; Broaddus, William C.

1999-01-01

Most surgical instrumentation and implants used in the world today are designed with sophisticated Computer-Aided Design (CAD)/Computer-Aided Manufacturing (CAM) software. This software automates the mechanical development of a product from its conceptual design through manufacturing. CAD software also provides a means of manipulating solid models prior to Finite Element Modeling (FEM). Few surgical products are designed in conjunction with accurate CAD models of human anatomy because of the difficulty with which these models are created. We have developed a novel technique that creates anatomically accurate, patient specific CAD solids from medical images in a matter of minutes.

MRI-based patient-specific human carotid atherosclerotic vessel material property variations in patients, vessel location and long-term follow up

PubMed Central

Wang, Qingyu; Canton, Gador; Guo, Jian; Guo, Xiaoya; Hatsukami, Thomas S.; Billiar, Kristen L.; Yuan, Chun; Wu, Zheyang

2017-01-01

Background Image-based computational models are widely used to determine atherosclerotic plaque stress/strain conditions and investigate their association with plaque progression and rupture. However, patient-specific vessel material properties are in general lacking in those models, limiting the accuracy of their stress/strain measurements. A noninvasive approach of combining in vivo 3D multi-contrast and Cine magnetic resonance imaging (MRI) and computational modeling was introduced to quantify patient-specific carotid plaque material properties for potential plaque model improvements. Vessel material property variation in patients, along vessel segment, and between baseline and follow up were investigated. Methods In vivo 3D multi-contrast and Cine MRI carotid plaque data were acquired from 8 patients with follow-up (18 months) with written informed consent obtained. 3D thin-layer models and an established iterative procedure were used to determine parameter values of the Mooney-Rivlin models for the 81slices from 16 plaque samples. Effective Young’s Modulus (YM) values were calculated for comparison and analysis. Results Average Effective Young’s Modulus (YM) and circumferential shrinkage rate (C-Shrink) value of the 81 slices was 411kPa and 5.62%, respectively. Slice YM value varied from 70 kPa (softest) to 1284 kPa (stiffest), a 1734% difference. Average slice YM values by vessel varied from 109 kPa (softest) to 922 kPa (stiffest), a 746% difference. Location-wise, the maximum slice YM variation rate within a vessel was 311% (149 kPa vs. 613 kPa). The average slice YM variation rate for the 16 vessels was 134%. The average variation of YM values for all patients from baseline to follow up was 61.0%. The range of the variation of YM values was [-28.4%, 215%]. For plaque progression study, YM at follow-up showed negative correlation with plaque progression measured by wall thickness increase (WTI) (r = -0.7764, p = 0.0235). Wall thickness at baseline correlated with WTI negatively, with r = -0.5253 (p = 0.1813). Plaque burden at baseline correlated with YM change between baseline and follow-up, with r = 0.5939 (p = 0.1205). Conclusion In vivo carotid vessel material properties have large variations from patient to patient, along the diseased segment within a patient, and with time. The use of patient-specific, location specific and time-specific material properties in plaque models could potentially improve the accuracy of model stress/strain calculations. PMID:28715441

Three-dimensional-printed cardiac prototypes aid surgical decision-making and preoperative planning in selected cases of complex congenital heart diseases: Early experience and proof of concept in a resource-limited environment.

PubMed

Kappanayil, Mahesh; Koneti, Nageshwara Rao; Kannan, Rajesh R; Kottayil, Brijesh P; Kumar, Krishna

2017-01-01

Three-dimensional. (3D) printing is an innovative manufacturing process that allows computer-assisted conversion of 3D imaging data into physical "printouts" Healthcare applications are currently in evolution. The objective of this study was to explore the feasibility and impact of using patient-specific 3D-printed cardiac prototypes derived from high-resolution medical imaging data (cardiac magnetic resonance imaging/computed tomography [MRI/CT]) on surgical decision-making and preoperative planning in selected cases of complex congenital heart diseases (CHDs). Five patients with complex CHD with previously unresolved management decisions were chosen. These included two patients with complex double-outlet right ventricle, two patients with criss-cross atrioventricular connections, and one patient with congenitally corrected transposition of great arteries with pulmonary atresia. Cardiac MRI was done for all patients, cardiac CT for one; specific surgical challenges were identified. Volumetric data were used to generate patient-specific 3D models. All cases were reviewed along with their 3D models, and the impact on surgical decision-making and preoperative planning was assessed. Accurate life-sized 3D cardiac prototypes were successfully created for all patients. The models enabled radically improved 3D understanding of anatomy, identification of specific technical challenges, and precise surgical planning. Augmentation of existing clinical and imaging data by 3D prototypes allowed successful execution of complex surgeries for all five patients, in accordance with the preoperative planning. 3D-printed cardiac prototypes can radically assist decision-making, planning, and safe execution of complex congenital heart surgery by improving understanding of 3D anatomy and allowing anticipation of technical challenges.

Direct Visuo-Haptic 4D Volume Rendering Using Respiratory Motion Models.

PubMed

Fortmeier, Dirk; Wilms, Matthias; Mastmeyer, Andre; Handels, Heinz

2015-01-01

This article presents methods for direct visuo-haptic 4D volume rendering of virtual patient models under respiratory motion. Breathing models are computed based on patient-specific 4D CT image data sequences. Virtual patient models are visualized in real-time by ray casting based rendering of a reference CT image warped by a time-variant displacement field, which is computed using the motion models at run-time. Furthermore, haptic interaction with the animated virtual patient models is provided by using the displacements computed at high rendering rates to translate the position of the haptic device into the space of the reference CT image. This concept is applied to virtual palpation and the haptic simulation of insertion of a virtual bendable needle. To this aim, different motion models that are applicable in real-time are presented and the methods are integrated into a needle puncture training simulation framework, which can be used for simulated biopsy or vessel puncture in the liver. To confirm real-time applicability, a performance analysis of the resulting framework is given. It is shown that the presented methods achieve mean update rates around 2,000 Hz for haptic simulation and interactive frame rates for volume rendering and thus are well suited for visuo-haptic rendering of virtual patients under respiratory motion.

Cognitive training in Parkinson disease: cognition-specific vs nonspecific computer training.

PubMed

Zimmermann, Ronan; Gschwandtner, Ute; Benz, Nina; Hatz, Florian; Schindler, Christian; Taub, Ethan; Fuhr, Peter

2014-04-08

In this study, we compared a cognition-specific computer-based cognitive training program with a motion-controlled computer sports game that is not cognition-specific for their ability to enhance cognitive performance in various cognitive domains in patients with Parkinson disease (PD). Patients with PD were trained with either a computer program designed to enhance cognition (CogniPlus, 19 patients) or a computer sports game with motion-capturing controllers (Nintendo Wii, 20 patients). The effect of training in 5 cognitive domains was measured by neuropsychological testing at baseline and after training. Group differences over all variables were assessed with multivariate analysis of variance, and group differences in single variables were assessed with 95% confidence intervals of mean difference. The groups were similar regarding age, sex, and educational level. Patients with PD who were trained with Wii for 4 weeks performed better in attention (95% confidence interval: -1.49 to -0.11) than patients trained with CogniPlus. In our study, patients with PD derived at least the same degree of cognitive benefit from non-cognition-specific training involving movement as from cognition-specific computerized training. For patients with PD, game consoles may be a less expensive and more entertaining alternative to computer programs specifically designed for cognitive training. This study provides Class III evidence that, in patients with PD, cognition-specific computer-based training is not superior to a motion-controlled computer game in improving cognitive performance.

Flow stagnation volume and abdominal aortic aneurysm growth: Insights from patient-specific computational flow dynamics of Lagrangian-coherent structures.

PubMed

Joly, Florian; Soulez, Gilles; Garcia, Damien; Lessard, Simon; Kauffmann, Claude

2018-01-01

Abdominal aortic aneurysms (AAA) are localized, commonly-occurring dilations of the aorta. When equilibrium between blood pressure (loading) and wall mechanical resistance is lost, rupture ensues, and patient death follows, if not treated immediately. Experimental and numerical analyses of flow patterns in arteries show direct correlations between wall shear stress and wall mechano-adaptation with the development of zones prone to thrombus formation. For further insights into AAA flow topology/growth interaction, a workout of patient-specific computational flow dynamics (CFD) is proposed to compute finite-time Lyapunov exponents and extract Lagrangian-coherent structures (LCS). This computational model was first compared with 4-D phase-contrast magnetic resonance imaging (MRI) in 5 patients. To better understand the impact of flow topology and transport on AAA growth, hyperbolic, repelling LCS were computed in 1 patient during 8-year follow-up, including 9 volumetric morphologic AAA measures by computed tomography-angiography (CTA). LCS defined barriers to Lagrangian jet cores entering AAA. Domains enclosed between LCS and the aortic wall were considered to be stagnation zones. Their evolution was studied during AAA growth. Good correlation - 2-D cross-correlation coefficients of 0.65, 0.86 and 0.082 (min, max, SD) - was obtained between numerical simulations and 4-D MRI acquisitions in 6 specific cross-sections from 4 patients. In follow-up study, LCS divided AAA lumens into 3 dynamically-isolated zones: 2 stagnation volumes lying in dilated portions of the AAA, and circulating volume connecting the inlet to the outlet. The volume of each zone was tracked over time. Although circulating volume remained unchanged during 8-year follow-up, the AAA lumen and main stagnation zones grew significantly (8 cm 3 /year and 6 cm 3 /year, respectively). This study reveals that transient transport topology can be quantified in patient-specific AAA during disease progression by CTA, in parallel with lumen morphology. It is anticipated that analysis of the main AAA stagnation zones by patient-specific CFD on a yearly basis could help to predict AAA growth and rupture. Copyright © 2017 Elsevier Ltd. All rights reserved.

Patient-specific cardiac phantom for clinical training and preprocedure surgical planning.

PubMed

Laing, Justin; Moore, John; Vassallo, Reid; Bainbridge, Daniel; Drangova, Maria; Peters, Terry

2018-04-01

Minimally invasive mitral valve repair procedures including MitraClip ® are becoming increasingly common. For cases of complex or diseased anatomy, clinicians may benefit from using a patient-specific cardiac phantom for training, surgical planning, and the validation of devices or techniques. An imaging compatible cardiac phantom was developed to simulate a MitraClip ® procedure. The phantom contained a patient-specific cardiac model manufactured using tissue mimicking materials. To evaluate accuracy, the patient-specific model was imaged using computed tomography (CT), segmented, and the resulting point cloud dataset was compared using absolute distance to the original patient data. The result, when comparing the molded model point cloud to the original dataset, resulted in a maximum Euclidean distance error of 7.7 mm, an average error of 0.98 mm, and a standard deviation of 0.91 mm. The phantom was validated using a MitraClip ® device to ensure anatomical features and tools are identifiable under image guidance. Patient-specific cardiac phantoms may allow for surgical complications to be accounted for preoperative planning. The information gained by clinicians involved in planning and performing the procedure should lead to shorter procedural times and better outcomes for patients.

Design and manufacturing of patient-specific orthodontic appliances by computer-aided engineering techniques.

PubMed

Barone, Sandro; Neri, Paolo; Paoli, Alessandro; Razionale, Armando Viviano

2018-01-01

Orthodontic treatments are usually performed using fixed brackets or removable oral appliances, which are traditionally made from alginate impressions and wax registrations. Among removable devices, eruption guidance appliances are used for early orthodontic treatments in order to intercept and prevent malocclusion problems. Commercially available eruption guidance appliances, however, are symmetric devices produced using a few standard sizes. For this reason, they are not able to meet all the specific patient's needs since the actual dental anatomies present various geometries and asymmetric conditions. In this article, a computer-aided design-based methodology for the design and manufacturing of a patient-specific eruption guidance appliances is presented. The proposed approach is based on the digitalization of several steps of the overall process: from the digital reconstruction of patients' anatomies to the manufacturing of customized appliances. A finite element model has been developed to evaluate the temporomandibular joint disks stress level caused by using symmetric eruption guidance appliances with different teeth misalignment conditions. The developed model can then be used to guide the design of a patient-specific appliance with the aim at reducing the patient discomfort. At this purpose, two different customization levels are proposed in order to face both arches and single tooth misalignment issues. A low-cost manufacturing process, based on an additive manufacturing technique, is finally presented and discussed.

Assessment Of Coronary Artery Aneurysms Using Transluminal Attenuation Gradient And Computational Modeling In Kawasaki Disease Patients

NASA Astrophysics Data System (ADS)

Grande Gutierrez, Noelia; Kahn, Andrew; Shirinsky, Olga; Gagarina, Nina; Lyskina, Galina; Fukazawa, Ryuji; Owaga, Shunichi; Burns, Jane; Marsden, Alison

2015-11-01

Kawasaki Disease (KD) can result in coronary artery aneurysms (CAA) in up to 25% of patients, putting them at risk of thrombus formation, myocardial infarction and sudden death. Clinical guidelines recommend CAA diameter >8 mm as the arbitrary criterion for initiating systemic anticoagulation. KD patient specific modeling and flow simulations suggest that hemodynamic data can predict regions at increased risk of thrombosis. Transluminal Attenuation Gradient (TAG) is determined from the change in radiological attenuation per vessel length and has been proposed as a non-invasive method for characterizing coronary stenosis from CT Angiography. We hypothesized that CAA abnormal flow could be quantified using TAG. We computed hemodynamics for patient specific coronary models using a stabilized finite element method, coupled numerically to a lumped parameter network to model the heart and vascular boundary conditions. TAG was quantified in the major coronary arteries. We compared TAG for aneurysmal and normal arteries and we analyzed TAG correlation with hemodynamic and geometrical parameters. Our results suggest that TAG may provide hemodynamic data not available from anatomy alone. TAG represents a possible extension to standard CTA that could help to better evaluate the risk of thrombus formation in KD.

Computing volume potentials for noninvasive imaging of cardiac excitation.

PubMed

van der Graaf, A W Maurits; Bhagirath, Pranav; van Driel, Vincent J H M; Ramanna, Hemanth; de Hooge, Jacques; de Groot, Natasja M S; Götte, Marco J W

2015-03-01

In noninvasive imaging of cardiac excitation, the use of body surface potentials (BSP) rather than body volume potentials (BVP) has been favored due to enhanced computational efficiency and reduced modeling effort. Nowadays, increased computational power and the availability of open source software enable the calculation of BVP for clinical purposes. In order to illustrate the possible advantages of this approach, the explanatory power of BVP is investigated using a rectangular tank filled with an electrolytic conductor and a patient specific three dimensional model. MRI images of the tank and of a patient were obtained in three orthogonal directions using a turbo spin echo MRI sequence. MRI images were segmented in three dimensional using custom written software. Gmsh software was used for mesh generation. BVP were computed using a transfer matrix and FEniCS software. The solution for 240,000 nodes, corresponding to a resolution of 5 mm throughout the thorax volume, was computed in 3 minutes. The tank experiment revealed that an increased electrode surface renders the position of the 4 V equipotential plane insensitive to mesh cell size and reduces simulated deviations. In the patient-specific model, the impact of assigning a different conductivity to lung tissue on the distribution of volume potentials could be visualized. Generation of high quality volume meshes and computation of BVP with a resolution of 5 mm is feasible using generally available software and hardware. Estimation of BVP may lead to an improved understanding of the genesis of BSP and sources of local inaccuracies. © 2014 Wiley Periodicals, Inc.

Computational Medicine: Translating Models to Clinical Care

PubMed Central

Winslow, Raimond L.; Trayanova, Natalia; Geman, Donald; Miller, Michael I.

2013-01-01

Because of the inherent complexity of coupled nonlinear biological systems, the development of computational models is necessary for achieving a quantitative understanding of their structure and function in health and disease. Statistical learning is applied to high-dimensional biomolecular data to create models that describe relationships between molecules and networks. Multiscale modeling links networks to cells, organs, and organ systems. Computational approaches are used to characterize anatomic shape and its variations in health and disease. In each case, the purposes of modeling are to capture all that we know about disease and to develop improved therapies tailored to the needs of individuals. We discuss advances in computational medicine, with specific examples in the fields of cancer, diabetes, cardiology, and neurology. Advances in translating these computational methods to the clinic are described, as well as challenges in applying models for improving patient health. PMID:23115356

GPU-accelerated Lattice Boltzmann method for anatomical extraction in patient-specific computational hemodynamics

NASA Astrophysics Data System (ADS)

Yu, H.; Wang, Z.; Zhang, C.; Chen, N.; Zhao, Y.; Sawchuk, A. P.; Dalsing, M. C.; Teague, S. D.; Cheng, Y.

2014-11-01

Existing research of patient-specific computational hemodynamics (PSCH) heavily relies on software for anatomical extraction of blood arteries. Data reconstruction and mesh generation have to be done using existing commercial software due to the gap between medical image processing and CFD, which increases computation burden and introduces inaccuracy during data transformation thus limits the medical applications of PSCH. We use lattice Boltzmann method (LBM) to solve the level-set equation over an Eulerian distance field and implicitly and dynamically segment the artery surfaces from radiological CT/MRI imaging data. The segments seamlessly feed to the LBM based CFD computation of PSCH thus explicit mesh construction and extra data management are avoided. The LBM is ideally suited for GPU (graphic processing unit)-based parallel computing. The parallel acceleration over GPU achieves excellent performance in PSCH computation. An application study will be presented which segments an aortic artery from a chest CT dataset and models PSCH of the segmented artery.

3D printing based on cardiac CT assists anatomic visualization prior to transcatheter aortic valve replacement.

PubMed

Ripley, Beth; Kelil, Tatiana; Cheezum, Michael K; Goncalves, Alexandra; Di Carli, Marcelo F; Rybicki, Frank J; Steigner, Mike; Mitsouras, Dimitrios; Blankstein, Ron

2016-01-01

3D printing is a promising technique that may have applications in medicine, and there is expanding interest in the use of patient-specific 3D models to guide surgical interventions. To determine the feasibility of using cardiac CT to print individual models of the aortic root complex for transcatheter aortic valve replacement (TAVR) planning as well as to determine the ability to predict paravalvular aortic regurgitation (PAR). This retrospective study included 16 patients (9 with PAR identified on blinded interpretation of post-procedure trans-thoracic echocardiography and 7 age, sex, and valve size-matched controls with no PAR). 3D printed models of the aortic root were created from pre-TAVR cardiac computed tomography data. These models were fitted with printed valves and predictions regarding post-implant PAR were made using a light transmission test. Aortic root 3D models were highly accurate, with excellent agreement between annulus measurements made on 3D models and those made on corresponding 2D data (mean difference of -0.34 mm, 95% limits of agreement: ± 1.3 mm). The 3D printed valve models were within 0.1 mm of their designed dimensions. Examination of the fit of valves within patient-specific aortic root models correctly predicted PAR in 6 of 9 patients (6 true positive, 3 false negative) and absence of PAR in 5 of 7 patients (5 true negative, 2 false positive). Pre-TAVR 3D-printing based on cardiac CT provides a unique patient-specific method to assess the physical interplay of the aortic root and implanted valves. With additional optimization, 3D models may complement traditional techniques used for predicting which patients are more likely to develop PAR. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Full 3-D OCT-based pseudophakic custom computer eye model

PubMed Central

Sun, M.; Pérez-Merino, P.; Martinez-Enriquez, E.; Velasco-Ocana, M.; Marcos, S.

2016-01-01

We compared measured wave aberrations in pseudophakic eyes implanted with aspheric intraocular lenses (IOLs) with simulated aberrations from numerical ray tracing on customized computer eye models, built using quantitative 3-D OCT-based patient-specific ocular geometry. Experimental and simulated aberrations show high correlation (R = 0.93; p<0.0001) and similarity (RMS for high order aberrations discrepancies within 23.58%). This study shows that full OCT-based pseudophakic custom computer eye models allow understanding the relative contribution of optical geometrical and surgically-related factors to image quality, and are an excellent tool for characterizing and improving cataract surgery. PMID:27231608

SU-D-BRC-05: Effects of Motion and Variable RBE in a Lung Patient Treated with Passively Scattered Protons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mirkovic, D; Titt, U; Mohan, R

2016-06-15

Purpose: To evaluate effects of motion and variable relative biological effectiveness (RBE) in a lung cancer patient treated with passively scattered proton therapy using dose volume histograms associated with patient dose computed using three different methods. Methods: A proton treatment plan of a lung cancer patient optimized using clinical treatment planning system (TPS) was used to construct a detailed Monte Carlo (MC) model of the beam delivery system and the patient specific aperture and compensator. A phase space file containing all particles transported through the beam line was collected at the distal surface of the range compensator and subsequently transportedmore » through two different patient models. The first model was based on the average CT used by the TPS and the second model included all 10 phases of the corresponding 4DCT. The physical dose and proton linear energy transfer (LET) were computed in each voxel of two models and used to compute constant and variable RBE MC dose on average CT and 4D CT. The MC computed doses were compared to the TPS dose using dose volume histograms for relevant structures. Results: The results show significant differences in doses to the target and critical structures suggesting the need for more accurate proton dose computation methods. In particular, the 4D dose shows reduced coverage of the target and higher dose to the spinal cord, while variable RBE dose shows higher lung dose. Conclusion: The methodology developed in this pilot study is currently used for the analysis of a cohort of ∼90 lung patients from a clinical trial comparing proton and photon therapy for lung cancer. The results from this study will help us in determining the clinical significance of more accurate dose computation models in proton therapy.« less

Patient-specific reconstruction plates are the missing link in computer-assisted mandibular reconstruction: A showcase for technical description.

PubMed

Cornelius, Carl-Peter; Smolka, Wenko; Giessler, Goetz A; Wilde, Frank; Probst, Florian A

2015-06-01

Preoperative planning of mandibular reconstruction has moved from mechanical simulation by dental model casts or stereolithographic models into an almost completely virtual environment. CAD/CAM applications allow a high level of accuracy by providing a custom template-assisted contouring approach for bone flaps. However, the clinical accuracy of CAD reconstruction is limited by the use of prebent reconstruction plates, an analogue step in an otherwise digital workstream. In this paper the integration of computerized, numerically-controlled (CNC) milled, patient-specific mandibular plates (PSMP) within the virtual workflow of computer-assisted mandibular free fibula flap reconstruction is illustrated in a clinical case. Intraoperatively, the bone segments as well as the plate arms showed a very good fit. Postoperative CT imaging demonstrated close approximation of the PSMP and fibular segments, and good alignment of native mandible and fibular segments and intersegmentally. Over a follow-up period of 12 months, there was an uneventful course of healing with good bony consolidation. The virtual design and automated fabrication of patient-specific mandibular reconstruction plates provide the missing link in the virtual workflow of computer-assisted mandibular free fibula flap reconstruction. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

A Representation for Gaining Insight into Clinical Decision Models

PubMed Central

Jimison, Holly B.

1988-01-01

For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient- specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.

Representation and Use of Temporal Information in ONCOCIN

PubMed Central

Kahn, Michael G.; Ferguson, Jay C.; Shortliffe, Edward H.; Fagan, Lawrence M.

1985-01-01

The past medical history of a patient is a complex collection of events yet the understanding of these past events is critical for effective medical diagnostic and therapeutic decisions. Although computers can store vast quantities of patient data, diagnostic and therapeutic computer programs have had difficulty in accessing and analyzing collections of patient information that is clinically pertinent to a specific decision facing a particular patient at a given moment in his disease. Without some model of the patient's past, the computer cannot fully interpret the meaning of the available patient data. We present some of the difficulties that were encountered in ONCOCIN, a cancer chemotherapy planning program. This program must be able to reason about the patient's past treatment history in order to generate a therapy plan that is responsive to the problems he or she may have encountered in the past. A design is presented that supports a more intuitive approach to capture and analyze important temporal relationships in a patient's computer record. In order to represent the time course of a patient, we have implemented a structure called the temporal network and a temporal syntax for data storage and retrieval. Using this system, ONCOCIN is able to quickly obtain data that is patient-specific and context-sensitive. Adding the temporal network to the ONCOCIN system has markedly improved the program's handling of complex temporal issues.

Computer modeling of airway deposition distribution of Foster(®) NEXThaler(®) and Seretide(®) Diskus(®) dry powder combination drugs.

PubMed

Jókay, Ágnes; Farkas, Árpád; Füri, Péter; Horváth, Alpár; Tomisa, Gábor; Balásházy, Imre

2016-06-10

Asthma is a serious global health problem with rising prevalence and treatment costs. Due to the growing number of different types of inhalation devices and aerosol drugs, physicians often face difficulties in choosing the right medication for their patients. The main objectives of this study are (i) to elucidate the possibility and the advantages of the application of numerical modeling techniques in aerosol drug and device selection, and (ii) to demonstrate the possibility of the optimization of inhalation modes in asthma therapy with a numerical lung model by simulating patient-specific drug deposition distributions. In this study we measured inhalation parameter values of 25 healthy adult volunteers when using Foster(®) NEXThaler(®) and Seretide(®) Diskus(®). Relationships between emitted doses and patient-specific inhalation flow rates were established. Furthermore, individualized emitted particle size distributions were determined applying size distributions at measured flow rates. Based on the measured breathing parameter values, we calculated patient-specific drug deposition distributions for the active components (steroid and bronchodilator) of both drugs by the help of a validated aerosol lung deposition model adapted to therapeutic aerosols. Deposited dose fractions and deposition densities have been computed in the entire respiratory tract, in distinct anatomical regions of the airways and at the level of airway generations. We found that Foster(®) NEXThaler(®) deposits more efficiently in the lungs (average deposited steroid dose: 42.32±5.76% of the nominal emitted dose) than Seretide(®) Diskus(®) (average deposited steroid dose: 24.33±2.83% of the nominal emitted dose), but the variance of the deposition values of different individuals in the lung is significant. In addition, there are differences in the required minimal flow rates, therefore at certain patients Seretide(®) Diskus(®) or pMDIs could be a better choice. Our results show that validated computer deposition models could be useful tools in providing valuable deposition data and assisting health professionals in the personalized drug selection and delivery optimization. Patient-specific modeling could open a new horizon in the treatment of asthma towards a more effective personalized medicine in the future. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatic construction of patient-specific finite-element mesh of the spine from IVDs and vertebra segmentations

NASA Astrophysics Data System (ADS)

Castro-Mateos, Isaac; Pozo, Jose M.; Lazary, Aron; Frangi, Alejandro F.

2016-03-01

Computational medicine aims at developing patient-specific models to help physicians in the diagnosis and treatment selection for patients. The spine, and other skeletal structures, is an articulated object, composed of rigid bones (vertebrae) and non-rigid parts (intervertebral discs (IVD), ligaments and muscles). These components are usually extracted from different image modalities, involving patient repositioning. In the case of the spine, these models require the segmentation of IVDs from MR and vertebrae from CT. In the literature, there exists a vast selection of segmentations methods, but there is a lack of approaches to align the vertebrae and IVDs. This paper presents a method to create patient-specific finite element meshes for biomechanical simulations, integrating rigid and non-rigid parts of articulated objects. First, the different parts are aligned in a complete surface model. Vertebrae extracted from CT are rigidly repositioned in between the IVDs, initially using the IVDs location and then refining the alignment using the MR image with a rigid active shape model algorithm. Finally, a mesh morphing algorithm, based on B-splines, is employed to map a template finite-element (volumetric) mesh to the patient-specific surface mesh. This morphing reduces possible misalignments and guarantees the convexity of the model elements. Results show that the accuracy of the method to align vertebrae into MR, together with IVDs, is similar to that of the human observers. Thus, this method is a step forward towards the automation of patient-specific finite element models for biomechanical simulations.

Flow pattern analysis in a highly stenotic patient-specific carotid bifurcation model using a turbulence model.

PubMed

Li, Zhi-Yong; Tan, Felicia P P; Soloperto, Giulia; Wood, Nigel B; Xu, Xiao Y; Gillard, Jonathan H

2015-08-01

The aim of this study is to investigate the blood flow pattern in carotid bifurcation with a high degree of luminal stenosis, combining in vivo magnetic resonance imaging (MRI) and computational fluid dynamics (CFD). A newly developed two-equation transitional model was employed to evaluate wall shear stress (WSS) distribution and pressure drop across the stenosis, which are closely related to plaque vulnerability. A patient with an 80% left carotid stenosis was imaged using high resolution MRI, from which a patient-specific geometry was reconstructed and flow boundary conditions were acquired for CFD simulation. A transitional model was implemented to investigate the flow velocity and WSS distribution in the patient-specific model. The peak time-averaged WSS value of approximately 73 Pa was predicted by the transitional flow model, and the regions of high WSS occurred at the throat of the stenosis. High oscillatory shear index values up to 0.50 were present in a helical flow pattern from the outer wall of the internal carotid artery immediately after the throat. This study shows the potential suitability of a transitional turbulent flow model in capturing the flow phenomena in severely stenosed carotid arteries using patient-specific MRI data and provides the basis for further investigation of the links between haemodynamic variables and plaque vulnerability. It may be useful in the future for risk assessment of patients with carotid disease.

Effects of walking in deep venous thrombosis: a new integrated solid and fluid mechanics model.

PubMed

López, Josep M; Fortuny, Gerard; Puigjaner, Dolors; Herrero, Joan; Marimon, Francesc; Garcia-Bennett, Josep

2017-05-01

Deep venous thrombosis (DVT) is a common disease. Large thrombi in venous vessels cause bad blood circulation and pain; and when a blood clot detaches from a vein wall, it causes an embolism whose consequences range from mild to fatal. Walking is recommended to DVT patients as a therapeutical complement. In this study the mechanical effects of walking on a specific patient of DVT were simulated by means of an unprecedented integration of 3 elements: a real geometry, a biomechanical model of body tissues, and a computational fluid dynamics study. A set of computed tomography images of a patient's leg with a thrombus in the popliteal vein was employed to reconstruct a geometry model. Then a biomechanical model was used to compute the new deformed geometry of the vein as a function of the fiber stretch level of the semimembranosus muscle. Finally, a computational fluid dynamics study was performed to compute the blood flow and the wall shear stress (WSS) at the vein and thrombus walls. Calculations showed that either a lengthening or shortening of the semimembranosus muscle led to a decrease of WSS levels up to 10%. Notwithstanding, changes in blood viscosity properties or blood flow rate may easily have a greater impact in WSS. Copyright © 2016 John Wiley & Sons, Ltd.

A machine-learning approach for computation of fractional flow reserve from coronary computed tomography.

PubMed

Itu, Lucian; Rapaka, Saikiran; Passerini, Tiziano; Georgescu, Bogdan; Schwemmer, Chris; Schoebinger, Max; Flohr, Thomas; Sharma, Puneet; Comaniciu, Dorin

2016-07-01

Fractional flow reserve (FFR) is a functional index quantifying the severity of coronary artery lesions and is clinically obtained using an invasive, catheter-based measurement. Recently, physics-based models have shown great promise in being able to noninvasively estimate FFR from patient-specific anatomical information, e.g., obtained from computed tomography scans of the heart and the coronary arteries. However, these models have high computational demand, limiting their clinical adoption. In this paper, we present a machine-learning-based model for predicting FFR as an alternative to physics-based approaches. The model is trained on a large database of synthetically generated coronary anatomies, where the target values are computed using the physics-based model. The trained model predicts FFR at each point along the centerline of the coronary tree, and its performance was assessed by comparing the predictions against physics-based computations and against invasively measured FFR for 87 patients and 125 lesions in total. Correlation between machine-learning and physics-based predictions was excellent (0.9994, P < 0.001), and no systematic bias was found in Bland-Altman analysis: mean difference was -0.00081 ± 0.0039. Invasive FFR ≤ 0.80 was found in 38 lesions out of 125 and was predicted by the machine-learning algorithm with a sensitivity of 81.6%, a specificity of 83.9%, and an accuracy of 83.2%. The correlation was 0.729 (P < 0.001). Compared with the physics-based computation, average execution time was reduced by more than 80 times, leading to near real-time assessment of FFR. Average execution time went down from 196.3 ± 78.5 s for the CFD model to ∼2.4 ± 0.44 s for the machine-learning model on a workstation with 3.4-GHz Intel i7 8-core processor. Copyright © 2016 the American Physiological Society.

A Relation Between Near-Wall Particle-Hemodynamics and Onset of Thrombus Formation in Abdominal Aortic Aneurysms

PubMed Central

Basciano, C.; Kleinstreuer, C.; Hyun, S.; Finol, E. A.

2014-01-01

A novel computational particle-hemodynamics analysis of key criteria for the onset of an intraluminal thrombus (ILT) in a patient-specific abdominal aortic aneurysm (AAA) is presented. The focus is on enhanced platelet and white blood cell residence times as well as their elevated surface-shear loads in near-wall regions of the AAA sac. The generalized results support the hypothesis that a patient's AAA geometry and associated particle-hemodynamics have the potential to entrap activated blood particles, which will play a role in the onset of ILT. Although the ILT history of only a single patient was considered, the modeling and simulation methodology provided allow for the development of an efficient computational tool to predict the onset of ILT formation in complex patient-specific cases. PMID:21373952

Multiplex-PCR-Based Screening and Computational Modeling of Virulence Factors and T-Cell Mediated Immunity in Helicobacter pylori Infections for Accurate Clinical Diagnosis.

PubMed

Oktem-Okullu, Sinem; Tiftikci, Arzu; Saruc, Murat; Cicek, Bahattin; Vardareli, Eser; Tozun, Nurdan; Kocagoz, Tanil; Sezerman, Ugur; Yavuz, Ahmet Sinan; Sayi-Yazgan, Ayca

2015-01-01

The outcome of H. pylori infection is closely related with bacteria's virulence factors and host immune response. The association between T cells and H. pylori infection has been identified, but the effects of the nine major H. pylori specific virulence factors; cagA, vacA, oipA, babA, hpaA, napA, dupA, ureA, ureB on T cell response in H. pylori infected patients have not been fully elucidated. We developed a multiplex- PCR assay to detect nine H. pylori virulence genes with in a three PCR reactions. Also, the expression levels of Th1, Th17 and Treg cell specific cytokines and transcription factors were detected by using qRT-PCR assays. Furthermore, a novel expert derived model is developed to identify set of factors and rules that can distinguish the ulcer patients from gastritis patients. Within all virulence factors that we tested, we identified a correlation between the presence of napA virulence gene and ulcer disease as a first data. Additionally, a positive correlation between the H. pylori dupA virulence factor and IFN-γ, and H. pylori babA virulence factor and IL-17 was detected in gastritis and ulcer patients respectively. By using computer-based models, clinical outcomes of a patients infected with H. pylori can be predicted by screening the patient's H. pylori vacA m1/m2, ureA and cagA status and IFN-γ (Th1), IL-17 (Th17), and FOXP3 (Treg) expression levels. Herein, we report, for the first time, the relationship between H. pylori virulence factors and host immune responses for diagnostic prediction of gastric diseases using computer-based models.

A 12-week pilot study of acceptance of a computer-based chronic disease self-monitoring system among patients with type 2 diabetes mellitus and/or hypertension.

PubMed

Yan, Mian; Or, Calvin

2017-08-01

This study tested a structural model examining the effects of perceived usefulness, perceived ease of use, attitude, subjective norm, perceived behavioral control, health consciousness, and application-specific self-efficacy on the acceptance (i.e. behavioral intention and actual usage) of a computer-based chronic disease self-monitoring system among patients with type 2 diabetes mellitus and/or hypertension. The model was tested using partial least squares structural equation modeling, with 119 observations that were obtained by pooling data across three time points over a 12-week period. The results indicate that all of the seven constructs examined had a significant total effect on behavioral intention and explained 74 percent of the variance. Also, application-specific self-efficacy and behavioral intention had a significant total effect on actual usage and explained 17 percent of the variance. This study demonstrates that technology acceptance is determined by patient characteristics, technology attributes, and social influences. Applying the findings may increase the likelihood of acceptance.

Tissue-scale, personalized modeling and simulation of prostate cancer growth

NASA Astrophysics Data System (ADS)

Lorenzo, Guillermo; Scott, Michael A.; Tew, Kevin; Hughes, Thomas J. R.; Zhang, Yongjie Jessica; Liu, Lei; Vilanova, Guillermo; Gomez, Hector

2016-11-01

Recently, mathematical modeling and simulation of diseases and their treatments have enabled the prediction of clinical outcomes and the design of optimal therapies on a personalized (i.e., patient-specific) basis. This new trend in medical research has been termed “predictive medicine.” Prostate cancer (PCa) is a major health problem and an ideal candidate to explore tissue-scale, personalized modeling of cancer growth for two main reasons: First, it is a small organ, and, second, tumor growth can be estimated by measuring serum prostate-specific antigen (PSA, a PCa biomarker in blood), which may enable in vivo validation. In this paper, we present a simple continuous model that reproduces the growth patterns of PCa. We use the phase-field method to account for the transformation of healthy cells to cancer cells and use diffusion-reaction equations to compute nutrient consumption and PSA production. To accurately and efficiently compute tumor growth, our simulations leverage isogeometric analysis (IGA). Our model is shown to reproduce a known shape instability from a spheroidal pattern to fingered growth. Results of our computations indicate that such shift is a tumor response to escape starvation, hypoxia, and, eventually, necrosis. Thus, branching enables the tumor to minimize the distance from inner cells to external nutrients, contributing to cancer survival and further development. We have also used our model to perform tissue-scale, personalized simulation of a PCa patient, based on prostatic anatomy extracted from computed tomography images. This simulation shows tumor progression similar to that seen in clinical practice.

Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

PubMed

Obrzut, Bogdan; Kusy, Maciej; Semczuk, Andrzej; Obrzut, Marzanna; Kluska, Jacek

2017-12-12

Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for 5-year overall survival prediction in patients with cervical cancer treated by radical hysterectomy. The data set was collected from 102 patients with cervical cancer FIGO stage IA2-IIB, that underwent primary surgical treatment. Twenty-three demographic, tumor-related parameters and selected perioperative data of each patient were collected. The simulations involved six computational intelligence methods: the probabilistic neural network (PNN), multilayer perceptron network, gene expression programming classifier, support vector machines algorithm, radial basis function neural network and k-Means algorithm. The prediction ability of the models was determined based on the accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve. The results of the computational intelligence methods were compared with the results of linear regression analysis as a reference model. The best results were obtained by the PNN model. This neural network provided very high prediction ability with an accuracy of 0.892 and sensitivity of 0.975. The area under the receiver operating characteristics curve of PNN was also high, 0.818. The outcomes obtained by other classifiers were markedly worse. The PNN model is an effective tool for predicting 5-year overall survival in cervical cancer patients treated with radical hysterectomy.

3D Modelling and Printing Technology to Produce Patient-Specific 3D Models.

PubMed

Birbara, Nicolette S; Otton, James M; Pather, Nalini

2017-11-10

A comprehensive knowledge of mitral valve (MV) anatomy is crucial in the assessment of MV disease. While the use of three-dimensional (3D) modelling and printing in MV assessment has undergone early clinical evaluation, the precision and usefulness of this technology requires further investigation. This study aimed to assess and validate 3D modelling and printing technology to produce patient-specific 3D MV models. A prototype method for MV 3D modelling and printing was developed from computed tomography (CT) scans of a plastinated human heart. Mitral valve models were printed using four 3D printing methods and validated to assess precision. Cardiac CT and 3D echocardiography imaging data of four MV disease patients was used to produce patient-specific 3D printed models, and 40 cardiac health professionals (CHPs) were surveyed on the perceived value and potential uses of 3D models in a clinical setting. The prototype method demonstrated submillimetre precision for all four 3D printing methods used, and statistical analysis showed a significant difference (p<0.05) in precision between these methods. Patient-specific 3D printed models, particularly using multiple print materials, were considered useful by CHPs for preoperative planning, as well as other applications such as teaching and training. This study suggests that, with further advances in 3D modelling and printing technology, patient-specific 3D MV models could serve as a useful clinical tool. The findings also highlight the potential of this technology to be applied in a variety of medical areas within both clinical and educational settings. Copyright © 2017 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

The impact of personalized probabilistic wall thickness models on peak wall stress in abdominal aortic aneurysms.

PubMed

Biehler, J; Wall, W A

2018-02-01

If computational models are ever to be used in high-stakes decision making in clinical practice, the use of personalized models and predictive simulation techniques is a must. This entails rigorous quantification of uncertainties as well as harnessing available patient-specific data to the greatest extent possible. Although researchers are beginning to realize that taking uncertainty in model input parameters into account is a necessity, the predominantly used probabilistic description for these uncertain parameters is based on elementary random variable models. In this work, we set out for a comparison of different probabilistic models for uncertain input parameters using the example of an uncertain wall thickness in finite element models of abdominal aortic aneurysms. We provide the first comparison between a random variable and a random field model for the aortic wall and investigate the impact on the probability distribution of the computed peak wall stress. Moreover, we show that the uncertainty about the prevailing peak wall stress can be reduced if noninvasively available, patient-specific data are harnessed for the construction of the probabilistic wall thickness model. Copyright © 2017 John Wiley & Sons, Ltd.

Haemodynamic imaging of thoracic stent-grafts by computational fluid dynamics (CFD): presentation of a patient-specific method combining magnetic resonance imaging and numerical simulations.

PubMed

Midulla, Marco; Moreno, Ramiro; Baali, Adil; Chau, Ming; Negre-Salvayre, Anne; Nicoud, Franck; Pruvo, Jean-Pierre; Haulon, Stephan; Rousseau, Hervé

2012-10-01

In the last decade, there was been increasing interest in finding imaging techniques able to provide a functional vascular imaging of the thoracic aorta. The purpose of this paper is to present an imaging method combining magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) to obtain a patient-specific haemodynamic analysis of patients treated by thoracic endovascular aortic repair (TEVAR). MRI was used to obtain boundary conditions. MR angiography (MRA) was followed by cardiac-gated cine sequences which covered the whole thoracic aorta. Phase contrast imaging provided the inlet and outlet profiles. A CFD mesh generator was used to model the arterial morphology, and wall movements were imposed according to the cine imaging. CFD runs were processed using the finite volume (FV) method assuming blood as a homogeneous Newtonian fluid. Twenty patients (14 men; mean age 62.2 years) with different aortic lesions were evaluated. Four-dimensional mapping of velocity and wall shear stress were obtained, depicting different patterns of flow (laminar, turbulent, stenosis-like) and local alterations of parietal stress in-stent and along the native aorta. A computational method using a combined approach with MRI appears feasible and seems promising to provide detailed functional analysis of thoracic aorta after stent-graft implantation. • Functional vascular imaging of the thoracic aorta offers new diagnostic opportunities • CFD can model vascular haemodynamics for clinical aortic problems • Combining CFD with MRI offers patient specific method of aortic analysis • Haemodynamic analysis of stent-grafts could improve clinical management and follow-up.

Learning-based stochastic object models for characterizing anatomical variations

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

2018-03-01

It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

Patient-Specific Geometry Modeling and Mesh Generation for Simulating Obstructive Sleep Apnea Syndrome Cases by Maxillomandibular Advancement

PubMed Central

Ito, Yasushi; Cheng, Gary C.; Shih, Alan M.; Koomullil, Roy P.; Soni, Bharat K.; Sittitavornwong, Somsak; Waite, Peter D.

2011-01-01

The objective of this paper is the reconstruction of upper airway geometric models as hybrid meshes from clinically used Computed Tomography (CT) data sets in order to understand the dynamics and behaviors of the pre- and postoperative upper airway systems of Obstructive Sleep Apnea Syndrome (OSAS) patients by viscous Computational Fluid Dynamics (CFD) simulations. The selection criteria for OSAS cases studied are discussed because two reasonable pre- and postoperative upper airway models for CFD simulations may not be created for every case without a special protocol for CT scanning. The geometry extraction and manipulation methods are presented with technical barriers that must be overcome so that they can be used along with computational simulation software as a daily clinical evaluation tool. Eight cases are presented in this paper, and each case consists of pre- and postoperative configurations. The results of computational simulations of two cases are included in this paper as demonstration. PMID:21625395

Patient-specific system for prognosis of surgical treatment outcomes of human cardiovascular system

NASA Astrophysics Data System (ADS)

Golyadkina, Anastasiya A.; Kalinin, Aleksey A.; Kirillova, Irina V.; Kossovich, Elena L.; Kossovich, Leonid Y.; Menishova, Liyana R.; Polienko, Asel V.

2015-03-01

Object of study: Improvement of life quality of patients with high stroke risk ia the main goal for development of system for patient-specific modeling of cardiovascular system. This work is dedicated at increase of safety outcomes for surgical treatment of brain blood supply alterations. The objects of study are common carotid artery, internal and external carotid arteries and bulb. Methods: We estimated mechanical properties of carotid arteries tissues and patching materials utilized at angioplasty. We studied angioarchitecture features of arteries. We developed and clinically adapted computer biomechanical models, which are characterized by geometrical, physical and mechanical similarity with carotid artery in norm and with pathology (atherosclerosis, pathological tortuosity, and their combination). Results: Collaboration of practicing cardiovascular surgeons and specialists in the area of Mathematics and Mechanics allowed to successfully conduct finite-element modeling of surgical treatment taking into account various features of operation techniques and patching materials for a specific patient. Numerical experiment allowed to reveal factors leading to brain blood supply decrease and atherosclerosis development. Modeling of carotid artery reconstruction surgery for a specific patient on the basis of the constructed biomechanical model demonstrated the possibility of its application in clinical practice at approximation of numerical experiment to the real conditions.

Development of three-dimensional brain arteriovenous malformation model for patient communication and young neurosurgeon education.

PubMed

Dong, Mengqi; Chen, Guangzhong; Qin, Kun; Ding, Xiaowen; Zhou, Dong; Peng, Chao; Zeng, Shaojian; Deng, Xianming

2018-01-15

Rapid prototyping technology is used to fabricate three-dimensional (3D) brain arteriovenous malformation (AVM) models and facilitate presurgical patient communication and medical education for young surgeons. Two intracranial AVM cases were selected for this study. Using 3D CT angiography or 3D rotational angiography images, the brain AVM models were reconstructed on personal computer and the rapid prototyping process was completed using a 3D printer. The size and morphology of the models were compared to brain digital subtraction arteriography of the same patients. 3D brain AVM models were used for preoperative patient communication and young neurosurgeon education. Two brain AVM models were successfully produced. By neurosurgeons' evaluation, the printed models have high fidelity with the actual brain AVM structures of the patients. The patient responded positively toward the brain AVM model specific to himself. Twenty surgical residents from residency programs tested the brain AVM models and provided positive feedback on their usefulness as educational tool and resemblance to real brain AVM structures. Patient-specific 3D printed models of brain AVM can be constructed with high fidelity. 3D printed brain AVM models are proved to be helpful in preoperative patient consultation, surgical planning and resident training.

Statistical modeling of 4D respiratory lung motion using diffeomorphic image registration.

PubMed

Ehrhardt, Jan; Werner, René; Schmidt-Richberg, Alexander; Handels, Heinz

2011-02-01

Modeling of respiratory motion has become increasingly important in various applications of medical imaging (e.g., radiation therapy of lung cancer). Current modeling approaches are usually confined to intra-patient registration of 3D image data representing the individual patient's anatomy at different breathing phases. We propose an approach to generate a mean motion model of the lung based on thoracic 4D computed tomography (CT) data of different patients to extend the motion modeling capabilities. Our modeling process consists of three steps: an intra-subject registration to generate subject-specific motion models, the generation of an average shape and intensity atlas of the lung as anatomical reference frame, and the registration of the subject-specific motion models to the atlas in order to build a statistical 4D mean motion model (4D-MMM). Furthermore, we present methods to adapt the 4D mean motion model to a patient-specific lung geometry. In all steps, a symmetric diffeomorphic nonlinear intensity-based registration method was employed. The Log-Euclidean framework was used to compute statistics on the diffeomorphic transformations. The presented methods are then used to build a mean motion model of respiratory lung motion using thoracic 4D CT data sets of 17 patients. We evaluate the model by applying it for estimating respiratory motion of ten lung cancer patients. The prediction is evaluated with respect to landmark and tumor motion, and the quantitative analysis results in a mean target registration error (TRE) of 3.3 ±1.6 mm if lung dynamics are not impaired by large lung tumors or other lung disorders (e.g., emphysema). With regard to lung tumor motion, we show that prediction accuracy is independent of tumor size and tumor motion amplitude in the considered data set. However, tumors adhering to non-lung structures degrade local lung dynamics significantly and the model-based prediction accuracy is lower in these cases. The statistical respiratory motion model is capable of providing valuable prior knowledge in many fields of applications. We present two examples of possible applications in radiation therapy and image guided diagnosis.

Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective

PubMed Central

Kassab, Ghassan S.; An, Gary; Sander, Edward A.; Miga, Michael; Guccione, Julius M.; Ji, Songbai; Vodovotz, Yoram

2016-01-01

In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for 1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with 2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery. PMID:27015816

Computational replication of the patient-specific stenting procedure for coronary artery bifurcations: From OCT and CT imaging to structural and hemodynamics analyses.

PubMed

Chiastra, Claudio; Wu, Wei; Dickerhoff, Benjamin; Aleiou, Ali; Dubini, Gabriele; Otake, Hiromasa; Migliavacca, Francesco; LaDisa, John F

2016-07-26

The optimal stenting technique for coronary artery bifurcations is still debated. With additional advances computational simulations can soon be used to compare stent designs or strategies based on verified structural and hemodynamics results in order to identify the optimal solution for each individual's anatomy. In this study, patient-specific simulations of stent deployment were performed for 2 cases to replicate the complete procedure conducted by interventional cardiologists. Subsequent computational fluid dynamics (CFD) analyses were conducted to quantify hemodynamic quantities linked to restenosis. Patient-specific pre-operative models of coronary bifurcations were reconstructed from CT angiography and optical coherence tomography (OCT). Plaque location and composition were estimated from OCT and assigned to models, and structural simulations were performed in Abaqus. Artery geometries after virtual stent expansion of Xience Prime or Nobori stents created in SolidWorks were compared to post-operative geometry from OCT and CT before being extracted and used for CFD simulations in SimVascular. Inflow boundary conditions based on body surface area, and downstream vascular resistances and capacitances were applied at branches to mimic physiology. Artery geometries obtained after virtual expansion were in good agreement with those reconstructed from patient images. Quantitative comparison of the distance between reconstructed and post-stent geometries revealed a maximum difference in area of 20.4%. Adverse indices of wall shear stress were more pronounced for thicker Nobori stents in both patients. These findings verify structural analyses of stent expansion, introduce a workflow to combine software packages for solid and fluid mechanics analysis, and underscore important stent design features from prior idealized studies. The proposed approach may ultimately be useful in determining an optimal choice of stent and position for each patient. Copyright © 2015 Elsevier Ltd. All rights reserved.

Restoration of the Patient-Specific Anatomy of the Proximal and Distal Parts of the Humerus: Statistical Shape Modeling Versus Contralateral Registration Method.

PubMed

Vlachopoulos, Lazaros; Lüthi, Marcel; Carrillo, Fabio; Gerber, Christian; Székely, Gábor; Fürnstahl, Philipp

2018-04-18

In computer-assisted reconstructive surgeries, the contralateral anatomy is established as the best available reconstruction template. However, existing intra-individual bilateral differences or a pathological, contralateral humerus may limit the applicability of the method. The aim of the study was to evaluate whether a statistical shape model (SSM) has the potential to predict accurately the pretraumatic anatomy of the humerus from the posttraumatic condition. Three-dimensional (3D) triangular surface models were extracted from the computed tomographic data of 100 paired cadaveric humeri without a pathological condition. An SSM was constructed, encoding the characteristic shape variations among the individuals. To predict the patient-specific anatomy of the proximal (or distal) part of the humerus with the SSM, we generated segments of the humerus of predefined length excluding the part to predict. The proximal and distal humeral prediction (p-HP and d-HP) errors, defined as the deviation of the predicted (bone) model from the original (bone) model, were evaluated. For comparison with the state-of-the-art technique, i.e., the contralateral registration method, we used the same segments of the humerus to evaluate whether the SSM or the contralateral anatomy yields a more accurate reconstruction template. The p-HP error (mean and standard deviation, 3.8° ± 1.9°) using 85% of the distal end of the humerus to predict the proximal humeral anatomy was significantly smaller (p = 0.001) compared with the contralateral registration method. The difference between the d-HP error (mean, 5.5° ± 2.9°), using 85% of the proximal part of the humerus to predict the distal humeral anatomy, and the contralateral registration method was not significant (p = 0.61). The restoration of the humeral length was not significantly different between the SSM and the contralateral registration method. SSMs accurately predict the patient-specific anatomy of the proximal and distal aspects of the humerus. The prediction errors of the SSM depend on the size of the healthy part of the humerus. The prediction of the patient-specific anatomy of the humerus is of fundamental importance for computer-assisted reconstructive surgeries.

Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate

NASA Astrophysics Data System (ADS)

Deng, Dongdong; Murphy, Michael J.; Hakim, Joe B.; Franceschi, William H.; Zahid, Sohail; Pashakhanloo, Farhad; Trayanova, Natalia A.; Boyle, Patrick M.

2017-09-01

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, causing morbidity and mortality in millions worldwide. The atria of patients with persistent AF (PsAF) are characterized by the presence of extensive and distributed atrial fibrosis, which facilitates the formation of persistent reentrant drivers (RDs, i.e., spiral waves), which promote fibrillatory activity. Targeted catheter ablation of RD-harboring tissues has shown promise as a clinical treatment for PsAF, but the outcomes remain sub-par. Personalized computational modeling has been proposed as a means of non-invasively predicting optimal ablation targets in individual PsAF patients, but it remains unclear how RD localization dynamics are influenced by inter-patient variability in the spatial distribution of atrial fibrosis, action potential duration (APD), and conduction velocity (CV). Here, we conduct simulations in computational models of fibrotic atria derived from the clinical imaging of PsAF patients to characterize the sensitivity of RD locations to these three factors. We show that RDs consistently anchor to boundaries between fibrotic and non-fibrotic tissues, as delineated by late gadolinium-enhanced magnetic resonance imaging, but those changes in APD/CV can enhance or attenuate the likelihood that an RD will anchor to a specific site. These findings show that the level of uncertainty present in patient-specific atrial models reconstructed without any invasive measurements (i.e., incorporating each individual's unique distribution of fibrotic tissue from medical imaging alongside an average representation of AF-remodeled electrophysiology) is sufficiently high that a personalized ablation strategy based on targeting simulation-predicted RD trajectories alone may not produce the desired result.

Hemodynamics of a Patient-Specific Aneurysm Model with Proper Orthogonal Decomposition

NASA Astrophysics Data System (ADS)

Han, Suyue; Chang, Gary Han; Modarres-Sadeghi, Yahya

2017-11-01

Wall shear stress (WSS) and oscillatory shear index (OSI) are two of the most-widely studied hemodynamic quantities in cardiovascular systems that have been shown to have the ability to elicit biological responses of the arterial wall, which could be used to predict the aneurysm development and rupture. In this study, a reduced-order model (ROM) of the hemodynamics of a patient-specific cerebral aneurysm is studied. The snapshot Proper Orthogonal Decomposition (POD) is utilized to construct the reduced-order bases of the flow using a CFD training set with known inflow parameters. It was shown that the area of low WSS and high OSI is correlated to higher POD modes. The resulting ROM can reproduce both WSS and OSI computationally for future parametric studies with significantly less computational cost. Agreement was observed between the WSS and OSI values obtained using direct CFD results and ROM results.

Why not try harder? Computational approach to motivation deficits in neuro-psychiatric diseases.

PubMed

Pessiglione, Mathias; Vinckier, Fabien; Bouret, Sébastien; Daunizeau, Jean; Le Bouc, Raphaël

2017-11-29

Motivation deficits, such as apathy, are pervasive in both neurological and psychiatric diseases. Even when they are not the core symptom, they reduce quality of life, compromise functional outcome and increase the burden for caregivers. They are currently assessed with clinical scales that do not give any mechanistic insight susceptible to guide therapeutic intervention. Here, we present another approach that consists of phenotyping the behaviour of patients in motivation tests, using computational models. These formal models impose a precise and operational definition of motivation that is embedded in decision theory. Motivation can be defined as the function that orients and activates the behaviour according to two attributes: a content (the goal) and a quantity (the goal value). Decision theory offers a way to quantify motivation, as the cost that patients would accept to endure in order to get the benefit of achieving their goal. We then review basic and clinical studies that have investigated the trade-off between the expected cost entailed by potential actions and the expected benefit associated with potential rewards. These studies have shown that the trade-off between effort and reward involves specific cortical, subcortical and neuromodulatory systems, such that it may be shifted in particular clinical conditions, and reinstated by appropriate treatments. Finally, we emphasize the promises of computational phenotyping for clinical purposes. Ideally, there would be a one-to-one mapping between specific neural components and distinct computational variables and processes of the decision model. Thus, fitting computational models to patients' behaviour would allow inferring of the dysfunctional mechanism in both cognitive terms (e.g. hyposensitivity to reward) and neural terms (e.g. lack of dopamine). This computational approach may therefore not only give insight into the motivation deficit but also help personalize treatment. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Volume effects of late term normal tissue toxicity in prostate cancer radiotherapy

NASA Astrophysics Data System (ADS)

Bonta, Dacian Viorel

Modeling of volume effects for treatment toxicity is paramount for optimization of radiation therapy. This thesis proposes a new model for calculating volume effects in gastro-intestinal and genito-urinary normal tissue complication probability (NTCP) following radiation therapy for prostate carcinoma. The radiobiological and the pathological basis for this model and its relationship to other models are detailed. A review of the radiobiological experiments and published clinical data identified salient features and specific properties a biologically adequate model has to conform to. The new model was fit to a set of actual clinical data. In order to verify the goodness of fit, two established NTCP models and a non-NTCP measure for complication risk were fitted to the same clinical data. The method of fit for the model parameters was maximum likelihood estimation. Within the framework of the maximum likelihood approach I estimated the parameter uncertainties for each complication prediction model. The quality-of-fit was determined using the Aikaike Information Criterion. Based on the model that provided the best fit, I identified the volume effects for both types of toxicities. Computer-based bootstrap resampling of the original dataset was used to estimate the bias and variance for the fitted parameter values. Computer simulation was also used to estimate the population size that generates a specific uncertainty level (3%) in the value of predicted complication probability. The same method was used to estimate the size of the patient population needed for accurate choice of the model underlying the NTCP. The results indicate that, depending on the number of parameters of a specific NTCP model, 100 (for two parameter models) and 500 patients (for three parameter models) are needed for accurate parameter fit. Correlation of complication occurrence in patients was also investigated. The results suggest that complication outcomes are correlated in a patient, although the correlation coefficient is rather small.

Computer-assisted planning and patient-specific guides for the treatment of midshaft clavicle malunions.

PubMed

Vlachopoulos, Lazaros; Schweizer, Andreas; Meyer, Dominik C; Gerber, Christian; Fürnstahl, Philipp

2017-08-01

The surgical treatment of malunions after midshaft clavicle fractures is associated with a number of potential complications and the surgical procedure is challenging. However, with appropriate and meticulous preoperative surgical planning, the surgical correction yields satisfactory results. The purpose of this study was to provide a guideline and detailed overview for the computer-assisted planning and 3-dimensional (3D) correction of malunions of the clavicle. The 3D bone surface models of the pathologic and contralateral sides were created on the basis of computed tomography data. The computer-assisted assessment of the deformity, the preoperative plan, and the design of patient-specific guides enabling compression plating are described. We demonstrate the benefit and versatility of computer-assisted planning for corrective osteotomies of malunions of the midshaft clavicle. In combination with patient-specific guides and compression plating technique, the correction can be performed in a more standardized fashion. We describe the determination of the contact-optimized osteotomy plane. An osteotomy along this plane facilitates the correction and enlarges the contact between the fragments at once. We further developed a technique of a stepped osteotomy that is based on the calculation of the contact-optimized osteotomy plane. The stepped osteotomy enables the length to be restored without the need of structural bone graft. The application of the stepped osteotomy is presented for malunions of the clavicle with shortening and excessive callus formation. The 3D preoperative planning and patient-specific guides for corrective osteotomies of the clavicle may help reduce the number of potential complications and yield results that are more predictable. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Modeling Single Ventricle Physiology: Review of Engineering Tools to Study First Stage Palliation of Hypoplastic Left Heart Syndrome

PubMed Central

Biglino, Giovanni; Giardini, Alessandro; Hsia, Tain-Yen; Figliola, Richard; Taylor, Andrew M.; Schievano, Silvia

2013-01-01

First stage palliation of hypoplastic left heart syndrome, i.e., the Norwood operation, results in a complex physiological arrangement, involving different shunting options (modified Blalock-Taussig, RV-PA conduit, central shunt from the ascending aorta) and enlargement of the hypoplastic ascending aorta. Engineering techniques, both computational and experimental, can aid in the understanding of the Norwood physiology and their correct implementation can potentially lead to refinement of the decision-making process, by means of patient-specific simulations. This paper presents some of the available tools that can corroborate clinical evidence by providing detailed insight into the fluid dynamics of the Norwood circulation as well as alternative surgical scenarios (i.e., virtual surgery). Patient-specific anatomies can be manufactured by means of rapid prototyping and such models can be inserted in experimental set-ups (mock circulatory loops) that can provide a valuable source of validation data as well as hydrodynamic information. Such models can be tuned to respond to differing the patient physiologies. Experimental set-ups can also be compatible with visualization techniques, like particle image velocimetry and cardiovascular magnetic resonance, further adding to the knowledge of the local fluid dynamics. Multi-scale computational models include detailed three-dimensional (3D) anatomical information coupled to a lumped parameter network representing the remainder of the circulation. These models output both overall hemodynamic parameters while also enabling to investigate the local fluid dynamics of the aortic arch or the shunt. As an alternative, pure lumped parameter models can also be employed to model Stage 1 palliation, taking advantage of a much lower computational cost, albeit missing the 3D anatomical component. Finally, analytical techniques, such as wave intensity analysis, can be employed to study the Norwood physiology, providing a mechanistic perspective on the ventriculo-arterial coupling for this specific surgical scenario. PMID:24400277

Monte Carlo evaluation of glandular dose in cone-beam X-ray computed tomography dedicated to the breast: Homogeneous and heterogeneous breast models.

PubMed

Sarno, Antonio; Mettivier, Giovanni; Tucciariello, Raffaele M; Bliznakova, Kristina; Boone, John M; Sechopoulos, Ioannis; Di Lillo, Francesca; Russo, Paolo

2018-06-07

In cone-beam computed tomography dedicated to the breast (BCT), the mean glandular dose (MGD) is the dose metric of reference, evaluated from the measured air kerma by means of normalized glandular dose coefficients (DgN CT ). This work aimed at computing, for a simple breast model, a set of DgN CT values for monoenergetic and polyenergetic X-ray beams, and at validating the results vs. those for patient specific digital phantoms from BCT scans. We developed a Monte Carlo code for calculation of monoenergetic DgN CT coefficients (energy range 4.25-82.25 keV). The pendant breast was modelled as a cylinder of a homogeneous mixture of adipose and glandular tissue with glandular fractions by mass of 0.1%, 14.3%, 25%, 50% or 100%, enveloped by a 1.45 mm-thick skin layer. The breast diameter ranged between 8 cm and 18 cm. Then, polyenergetic DgN CT coefficients were analytically derived for 49-kVp W-anode spectra (half value layer 1.25-1.50 mm Al), as in a commercial BCT scanner. We compared the homogeneous models to 20 digital phantoms produced from classified 3D breast images. Polyenergetic DgN CT resulted 13% lower than most recent published data. The comparison vs. patient specific breast phantoms showed that the homogeneous cylindrical model leads to a DgN CT percentage difference between -15% and +27%, with an average overestimation of 8%. A dataset of monoenergetic and polyenergetic DgN CT coefficients for BCT was provided. Patient specific breast models showed a different volume distribution of glandular dose and determined a DgN CT 8% lower, on average, than homogeneous breast model. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives.

PubMed

Handels, H; Ehrhardt, J

2009-01-01

Medical image computing has become one of the most challenging fields in medical informatics. In image-based diagnostics of the future software assistance will become more and more important, and image analysis systems integrating advanced image computing methods are needed to extract quantitative image parameters to characterize the state and changes of image structures of interest (e.g. tumors, organs, vessels, bones etc.) in a reproducible and objective way. Furthermore, in the field of software-assisted and navigated surgery medical image computing methods play a key role and have opened up new perspectives for patient treatment. However, further developments are needed to increase the grade of automation, accuracy, reproducibility and robustness. Moreover, the systems developed have to be integrated into the clinical workflow. For the development of advanced image computing systems methods of different scientific fields have to be adapted and used in combination. The principal methodologies in medical image computing are the following: image segmentation, image registration, image analysis for quantification and computer assisted image interpretation, modeling and simulation as well as visualization and virtual reality. Especially, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients and will gain importance in diagnostic and therapy of the future. From a methodical point of view the authors identify the following future trends and perspectives in medical image computing: development of optimized application-specific systems and integration into the clinical workflow, enhanced computational models for image analysis and virtual reality training systems, integration of different image computing methods, further integration of multimodal image data and biosignals and advanced methods for 4D medical image computing. The development of image analysis systems for diagnostic support or operation planning is a complex interdisciplinary process. Image computing methods enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

Early Dose Response to Yttrium-90 Microsphere Treatment of Metastatic Liver Cancer by a Patient-Specific Method Using Single Photon Emission Computed Tomography and Positron Emission Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Campbell, Janice M.; Department of Radiation Oncology, Wayne State University, Detroit, MI; Wong, C. Oliver

2009-05-01

Purpose: To evaluate a patient-specific single photon emission computed tomography (SPECT)-based method of dose calculation for treatment planning of yttrium-90 ({sup 90}Y) microsphere selective internal radiotherapy (SIRT). Methods and Materials: Fourteen consecutive {sup 90}Y SIRTs for colorectal liver metastasis were retrospectively analyzed. Absorbed dose to tumor and normal liver tissue was calculated by partition methods with two different tumor/normal liver vascularity ratios: an average 3:1 and a patient-specific ratio derived from pretreatment technetium-99m macroaggregated albumin SPECT. Tumor response was quantitatively evaluated from fluorine-18 fluoro-2-deoxy-D-glucose positron emission tomography scans. Results: Positron emission tomography showed a significant decrease in total tumor standardizedmore » uptake value (average, 52%). There was a significant difference in the tumor absorbed dose between the average and specific methods (p = 0.009). Response vs. dose curves fit by linear and linear-quadratic modeling showed similar results. Linear fit r values increased for all tumor response parameters with the specific method (+0.20 for mean standardized uptake value). Conclusion: Tumor dose calculated with the patient-specific method was more predictive of response in liver-directed {sup 90}Y SIRT.« less

IVUS-Based Computational Modeling and Planar Biaxial Artery Material Properties for Human Coronary Plaque Vulnerability Assessment

PubMed Central

Liu, Haofei; Cai, Mingchao; Yang, Chun; Zheng, Jie; Bach, Richard; Kural, Mehmet H.; Billiar, Kristen L.; Muccigrosso, David; Lu, Dongsi; Tang, Dalin

2012-01-01

Image-based computational modeling has been introduced for vulnerable atherosclerotic plaques to identify critical mechanical conditions which may be used for better plaque assessment and rupture predictions. In vivo patient-specific coronary plaque models are lagging due to limitations on non-invasive image resolution, flow data, and vessel material properties. A framework is proposed to combine intravascular ultrasound (IVUS) imaging, biaxial mechanical testing and computational modeling with fluid-structure interactions and anisotropic material properties to acquire better and more complete plaque data and make more accurate plaque vulnerability assessment and predictions. Impact of pre-shrink-stretch process, vessel curvature and high blood pressure on stress, strain, flow velocity and flow maximum principal shear stress was investigated. PMID:22428362

Reconstruction of large cranial defects with poly-methyl-methacrylate (PMMA) using a rapid prototyping model and a new technique for intraoperative implant modeling.

PubMed

Unterhofer, Claudia; Wipplinger, Christoph; Verius, Michael; Recheis, Wolfgang; Thomé, Claudius; Ortler, Martin

Reconstruction of large cranial defects after craniectomy can be accomplished by free-hand poly-methyl-methacrylate (PMMA) or industrially manufactured implants. The free-hand technique often does not achieve satisfactory cosmetic results but is inexpensive. In an attempt to combine the accuracy of specifically manufactured implants with low cost of PMMA. Forty-six consecutive patients with large skull defects after trauma or infection were retrospectively analyzed. The defects were reconstructed using computer-aided design/computer-aided manufacturing (CAD/CAM) techniques. The computer file was imported into a rapid prototyping (RP) machine to produce an acrylonitrile-butadiene-styrene model (ABS) of the patient's bony head. The gas-sterilized model was used as a template for the intraoperative modeling of the PMMA cranioplasty. Thus, not the PMMA implant was generated by CAD/CAM technique but the model of the patients head to easily form a well-fitting implant. Cosmetic outcome was rated on a six-tiered scale by the patients after a minimum follow-up of three months. The mean size of the defect was 74.36cm 2 . The implants fitted well in all patients. Seven patients had a postoperative complication and underwent reoperation. Mean follow-up period was 41 months (range 2-91 months). Results were excellent in 42, good in three and not satisfactory in one patient. Costs per implant were approximately 550 Euros. PMMA implants fabricated in-house by direct molding using a bio-model of the patients bony head are easily produced, fit properly and are inexpensive compared to cranial implants fabricated with other RP or milling techniques. Copyright © 2017 Polish Neurological Society. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Analysis of flow patterns in a patient-specific aortic dissection model.

PubMed

Cheng, Z; Tan, F P P; Riga, C V; Bicknell, C D; Hamady, M S; Gibbs, R G J; Wood, N B; Xu, X Y

2010-05-01

Aortic dissection is the most common acute catastrophic event affecting the thoracic aorta. The majority of patients presenting with an uncomplicated type B dissection are treated medically, but 25% of these patients develop subsequent aneurysmal dilatation of the thoracic aorta. This study aimed at gaining more detailed knowledge of the flow phenomena associated with this condition. Morphological features and flow patterns in a dissected aortic segment of a presurgery type B dissection patient were analyzed based on computed tomography images acquired from the patient. Computational simulations of blood flow in the patient-specific model were performed by employing a correlation-based transitional version of Menter's hybrid k-epsilon/k-omega shear stress transport turbulence model implemented in ANSYS CFX 11. Our results show that the dissected aorta is dominated by locally highly disturbed, and possibly turbulent, flow with strong recirculation. A significant proportion (about 80%) of the aortic flow enters the false lumen, which may further increase the dilatation of the aorta. High values of wall shear stress have been found around the tear on the true lumen wall, perhaps increasing the likelihood of expanding the tear. Turbulence intensity in the tear region reaches a maximum of 70% at midsystolic deceleration phase. Incorporating the non-Newtonian behavior of blood into the same transitional flow model has yielded a slightly lower peak wall shear stress and higher maximum turbulence intensity without causing discernible changes to the distribution patterns. Comparisons between the laminar and turbulent flow simulations show a qualitatively similar distribution of wall shear stress but a significantly higher magnitude with the transitional turbulence model.

Cognitive and Neural Bases of Skilled Performance.

DTIC Science & Technology

1987-10-04

advantage is that this method is not computationally demanding, and model -specific analyses such as high -precision source localization with realistic...and a two- < " high -threshold model satisfy theoretical and pragmatic independence. Discrimination and bias measures from these two models comparing...recognition memory of patients with dementing diseases, amnesics, and normal controls. We found the two- high -threshold model to be more sensitive Lloyd

A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots.

PubMed

Ma, Ye; Xie, Shengquan; Zhang, Yanxin

2016-03-01

A patient-specific electromyography (EMG)-driven neuromuscular model (PENm) is developed for the potential use of human-inspired gait rehabilitation robots. The PENm is modified based on the current EMG-driven models by decreasing the calculation time and ensuring good prediction accuracy. To ensure the calculation efficiency, the PENm is simplified into two EMG channels around one joint with minimal physiological parameters. In addition, a dynamic computation model is developed to achieve real-time calculation. To ensure the calculation accuracy, patient-specific muscle kinematics information, such as the musculotendon lengths and the muscle moment arms during the entire gait cycle, are employed based on the patient-specific musculoskeletal model. Moreover, an improved force-length-velocity relationship is implemented to generate accurate muscle forces. Gait analysis data including kinematics, ground reaction forces, and raw EMG signals from six adolescents at three different speeds were used to evaluate the PENm. The simulation results show that the PENm has the potential to predict accurate joint moment in real-time. The design of advanced human-robot interaction control strategies and human-inspired gait rehabilitation robots can benefit from the application of the human internal state provided by the PENm. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational predictions of damage propagation preceding dissection of ascending thoracic aortic aneurysms.

PubMed

Mousavi, S Jamaleddin; Farzaneh, Solmaz; Avril, Stéphane

2018-04-01

Dissections of ascending thoracic aortic aneurysms (ATAAs) cause significant morbidity and mortality worldwide. They occur when a tear in the intima-media of the aorta permits the penetration of the blood and the subsequent delamination and separation of the wall in 2 layers, forming a false channel. To predict computationally the risk of tear formation, stress analyses should be performed layer-specifically and they should consider internal or residual stresses that exist in the tissue. In the present paper, we propose a novel layer-specific damage model based on the constrained mixture theory, which intrinsically takes into account these internal stresses and can predict appropriately the tear formation. The model is implemented in finite-element commercial software Abaqus coupled with user material subroutine. Its capability is tested by applying it to the simulation of different exemplary situations, going from in vitro bulge inflation experiments on aortic samples to in vivo overpressurizing of patient-specific ATAAs. The simulations reveal that damage correctly starts from the intimal layer (luminal side) and propagates across the media as a tear but never hits the adventitia. This scenario is typically the first stage of development of an acute dissection, which is predicted for pressures of about 2.5 times the diastolic pressure by the model after calibrating the parameters against experimental data performed on collected ATAA samples. Further validations on a larger cohort of patients should hopefully confirm the potential of the model in predicting patient-specific damage evolution and possible risk of dissection during aneurysm growth for clinical applications. Copyright © 2017 John Wiley & Sons, Ltd.

From Inverse Problems in Mathematical Physiology to Quantitative Differential Diagnoses

PubMed Central

Zenker, Sven; Rubin, Jonathan; Clermont, Gilles

2007-01-01

The improved capacity to acquire quantitative data in a clinical setting has generally failed to improve outcomes in acutely ill patients, suggesting a need for advances in computer-supported data interpretation and decision making. In particular, the application of mathematical models of experimentally elucidated physiological mechanisms could augment the interpretation of quantitative, patient-specific information and help to better target therapy. Yet, such models are typically complex and nonlinear, a reality that often precludes the identification of unique parameters and states of the model that best represent available data. Hypothesizing that this non-uniqueness can convey useful information, we implemented a simplified simulation of a common differential diagnostic process (hypotension in an acute care setting), using a combination of a mathematical model of the cardiovascular system, a stochastic measurement model, and Bayesian inference techniques to quantify parameter and state uncertainty. The output of this procedure is a probability density function on the space of model parameters and initial conditions for a particular patient, based on prior population information together with patient-specific clinical observations. We show that multimodal posterior probability density functions arise naturally, even when unimodal and uninformative priors are used. The peaks of these densities correspond to clinically relevant differential diagnoses and can, in the simplified simulation setting, be constrained to a single diagnosis by assimilating additional observations from dynamical interventions (e.g., fluid challenge). We conclude that the ill-posedness of the inverse problem in quantitative physiology is not merely a technical obstacle, but rather reflects clinical reality and, when addressed adequately in the solution process, provides a novel link between mathematically described physiological knowledge and the clinical concept of differential diagnoses. We outline possible steps toward translating this computational approach to the bedside, to supplement today's evidence-based medicine with a quantitatively founded model-based medicine that integrates mechanistic knowledge with patient-specific information. PMID:17997590

Design of a numerical model of lung by means of a special boundary condition in the truncated branches.

PubMed

Tena, Ana F; Fernández, Joaquín; Álvarez, Eduardo; Casan, Pere; Walters, D Keith

2017-06-01

The need for a better understanding of pulmonary diseases has led to increased interest in the development of realistic computational models of the human lung. To minimize computational cost, a reduced geometry model is used for a model lung airway geometry up to generation 16. Truncated airway branches require physiologically realistic boundary conditions to accurately represent the effect of the removed airway sections. A user-defined function has been developed, which applies velocities mapped from similar locations in fully resolved airway sections. The methodology can be applied in any general purpose computational fluid dynamics code, with the only limitation that the lung model must be symmetrical in each truncated branch. Unsteady simulations have been performed to verify the operation of the model. The test case simulates a spirometry because the lung is obliged to rapidly perform both inspiration and expiration. Once the simulation was completed, the obtained pressure in the lower level of the lung was used as a boundary condition. The output velocity, which is a numerical spirometry, was compared with the experimental spirometry for validation purposes. This model can be applied for a wide range of patient-specific resolution levels. If the upper airway generations have been constructed from a computed tomography scan, it would be possible to quickly obtain a complete reconstruction of the lung specific to a specific person, which would allow individualized therapies. Copyright © 2016 John Wiley & Sons, Ltd.

Computational modeling of radiofrequency ablation: evaluation on ex vivo data using ultrasound monitoring

NASA Astrophysics Data System (ADS)

Audigier, Chloé; Kim, Younsu; Dillow, Austin; Boctor, Emad M.

2017-03-01

Radiofrequency ablation (RFA) is the most widely used minimally invasive ablative therapy for liver cancer, but it is challenged by a lack of patient-specific monitoring. Inter-patient tissue variability and the presence of blood vessels make the prediction of the RFA difficult. A monitoring tool which can be personalized for a given patient during the intervention would be helpful to achieve a complete tumor ablation. However, the clinicians do not have access to such a tool, which results in incomplete treatment and a large number of recurrences. Computational models can simulate the phenomena and mechanisms governing this therapy. The temperature evolution as well as the resulted ablation can be modeled. When combined together with intraoperative measurements, computational modeling becomes an accurate and powerful tool to gain quantitative understanding and to enable improvements in the ongoing clinical settings. This paper shows how computational models of RFA can be evaluated using intra-operative measurements. First, simulations are used to demonstrate the feasibility of the method, which is then evaluated on two ex vivo datasets. RFA is simulated on a simplified geometry to generate realistic longitudinal temperature maps and the resulted necrosis. Computed temperatures are compared with the temperature evolution recorded using thermometers, and with temperatures monitored by ultrasound (US) in a 2D plane containing the ablation tip. Two ablations are performed on two cadaveric bovine livers, and we achieve error of 2.2 °C on average between the computed and the thermistors temperature and 1.4 °C and 2.7 °C on average between the temperature computed and monitored by US during the ablation at two different time points (t = 240 s and t = 900 s).

Patient flow within UK emergency departments: a systematic review of the use of computer simulation modelling methods

PubMed Central

Mohiuddin, Syed; Busby, John; Savović, Jelena; Richards, Alison; Northstone, Kate; Hollingworth, William; Donovan, Jenny L; Vasilakis, Christos

2017-01-01

Objectives Overcrowding in the emergency department (ED) is common in the UK as in other countries worldwide. Computer simulation is one approach used for understanding the causes of ED overcrowding and assessing the likely impact of changes to the delivery of emergency care. However, little is known about the usefulness of computer simulation for analysis of ED patient flow. We undertook a systematic review to investigate the different computer simulation methods and their contribution for analysis of patient flow within EDs in the UK. Methods We searched eight bibliographic databases (MEDLINE, EMBASE, COCHRANE, WEB OF SCIENCE, CINAHL, INSPEC, MATHSCINET and ACM DIGITAL LIBRARY) from date of inception until 31 March 2016. Studies were included if they used a computer simulation method to capture patient progression within the ED of an established UK National Health Service hospital. Studies were summarised in terms of simulation method, key assumptions, input and output data, conclusions drawn and implementation of results. Results Twenty-one studies met the inclusion criteria. Of these, 19 used discrete event simulation and 2 used system dynamics models. The purpose of many of these studies (n=16; 76%) centred on service redesign. Seven studies (33%) provided no details about the ED being investigated. Most studies (n=18; 86%) used specific hospital models of ED patient flow. Overall, the reporting of underlying modelling assumptions was poor. Nineteen studies (90%) considered patient waiting or throughput times as the key outcome measure. Twelve studies (57%) reported some involvement of stakeholders in the simulation study. However, only three studies (14%) reported on the implementation of changes supported by the simulation. Conclusions We found that computer simulation can provide a means to pretest changes to ED care delivery before implementation in a safe and efficient manner. However, the evidence base is small and poorly developed. There are some methodological, data, stakeholder, implementation and reporting issues, which must be addressed by future studies. PMID:28487459

Patient-specific musculoskeletal modeling of the hip joint for preoperative planning of total hip arthroplasty: A validation study based on in vivo measurements

PubMed Central

Schick, Fabian; Asseln, Malte; Damm, Philipp; Radermacher, Klaus

2018-01-01

Validation of musculoskeletal models for application in preoperative planning is still a challenging task. Ideally, the simulation results of a patient-specific musculoskeletal model are compared to corresponding in vivo measurements. Currently, the only possibility to measure in vivo joint forces is to implant an instrumented prosthesis in patients undergoing a total joint replacement. In this study, a musculoskeletal model of the AnyBody Modeling System was adapted patient-specifically and validated against the in vivo hip joint force measurements of ten subjects performing one-leg stance and level walking. The impact of four model parameters was evaluated; hip joint width, muscle strength, muscle recruitment, and type of muscle model. The smallest difference between simulated and in vivo hip joint force was achieved by using the hip joint width measured in computed tomography images, a muscle strength of 90 N/cm2, a third order polynomial muscle recruitment, and a simple muscle model. This parameter combination reached mean deviations between simulation and in vivo measurement during the peak force phase of 12% ± 14% in magnitude and 11° ± 5° in orientation for one-leg stance and 8% ± 6% in magnitude and 10° ± 5° in orientation for level walking. PMID:29649235

Computational biomechanics to simulate the femoropopliteal intersection during knee flexion: a preliminary study.

PubMed

Diehm, Nicolas; Sin, Sangmun; Hoppe, Hanno; Baumgartner, Iris; Büchler, Philippe

2011-06-01

To assess if finite element (FE) models can be used to predict deformation of the femoropopliteal segment during knee flexion. Magnetic resonance angiography (MRA) images were acquired on the lower limbs of 8 healthy volunteers (5 men; mean age 28 ± 4 years). Images were taken in 2 natural positions, with the lower limb fully extended and with the knee bent at ~ 40°. Patient-specific FE models were developed and used to simulate the experimental situation. The displacements of the artery during knee bending as predicted by the numerical model were compared to the corresponding positions measured on the MRA images. The numerical predictions showed a good overall agreement between the calculated displacements of the motion measures from MRA images. The average position error comparing the calculated vs. actual displacements of the femoropopliteal intersection measured on the MRA was 8 ± 4 mm. Two of the 8 subjects showed large prediction errors (average 13 ± 5 mm); these 2 volunteers were the tallest subjects involved in the study and had a low body mass index (20.5 kg/m²). The present computational model is able to capture the gross mechanical environment of the femoropopliteal intersection during knee bending and provide a better understanding of the complex biomechanical behavior. However, results suggest that patient-specific mechanical properties and detailed muscle modeling are required to provide accurate patient-specific numerical predictions of arterial displacement. Further adaptation of this model is expected to provide an improved ability to predict the multiaxial deformation of this arterial segment during leg movements and to optimize future stent designs.

Cluster-specific small airway modeling for imaging-based CFD analysis of pulmonary air flow and particle deposition in COPD smokers

NASA Astrophysics Data System (ADS)

Haghighi, Babak; Choi, Jiwoong; Choi, Sanghun; Hoffman, Eric A.; Lin, Ching-Long

2017-11-01

Accurate modeling of small airway diameters in patients with chronic obstructive pulmonary disease (COPD) is a crucial step toward patient-specific CFD simulations of regional airflow and particle transport. We proposed to use computed tomography (CT) imaging-based cluster membership to identify structural characteristics of airways in each cluster and use them to develop cluster-specific airway diameter models. We analyzed 284 COPD smokers with airflow limitation, and 69 healthy controls. We used multiscale imaging-based cluster analysis (MICA) to classify smokers into 4 clusters. With representative cluster patients and healthy controls, we performed multiple regressions to quantify variation of airway diameters by generation as well as by cluster. The cluster 2 and 4 showed more diameter decrease as generation increases than other clusters. The cluster 4 had more rapid decreases of airway diameters in the upper lobes, while cluster 2 in the lower lobes. We then used these regression models to estimate airway diameters in CT unresolved regions to obtain pressure-volume hysteresis curves using a 1D resistance model. These 1D flow solutions can be used to provide the patient-specific boundary conditions for 3D CFD simulations in COPD patients. Support for this study was provided, in part, by NIH Grants U01-HL114494, R01-HL112986 and S10-RR022421.

Patient-specific analysis of post-operative aortic hemodynamics: a focus on thoracic endovascular repair (TEVAR)

NASA Astrophysics Data System (ADS)

Auricchio, F.; Conti, M.; Lefieux, A.; Morganti, S.; Reali, A.; Sardanelli, F.; Secchi, F.; Trimarchi, S.; Veneziani, A.

2014-10-01

The purpose of this study is to quantitatively evaluate the impact of endovascular repair on aortic hemodynamics. The study addresses the assessment of post-operative hemodynamic conditions of a real clinical case through patient-specific analysis, combining accurate medical image analysis and advanced computational fluid-dynamics (CFD). Although the main clinical concern was firstly directed to the endoluminal protrusion of the prosthesis, the CFD simulations have demonstrated that there are two other important areas where the local hemodynamics is impaired and a disturbed blood flow is present: the first one is the ostium of the subclavian artery, which is partially closed by the graft; the second one is the stenosis of the distal thoracic aorta. Besides the clinical relevance of these specific findings, this study highlights how CFD analyses allow to observe important flow effects resulting from the specific features of patient vessel geometries. Consequently, our results demonstrate the potential impact of computational biomechanics not only on the basic knowledge of physiopathology, but also on the clinical practice, thanks to a quantitative extraction of knowledge made possible by merging medical data and mathematical models.

Identification of reduced-order thermal therapy models using thermal MR images: theory and validation.

PubMed

Niu, Ran; Skliar, Mikhail

2012-07-01

In this paper, we develop and validate a method to identify computationally efficient site- and patient-specific models of ultrasound thermal therapies from MR thermal images. The models of the specific absorption rate of the transduced energy and the temperature response of the therapy target are identified in the reduced basis of proper orthogonal decomposition of thermal images, acquired in response to a mild thermal test excitation. The method permits dynamic reidentification of the treatment models during the therapy by recursively utilizing newly acquired images. Such adaptation is particularly important during high-temperature therapies, which are known to substantially and rapidly change tissue properties and blood perfusion. The developed theory was validated for the case of focused ultrasound heating of a tissue phantom. The experimental and computational results indicate that the developed approach produces accurate low-dimensional treatment models despite temporal and spatial noises in MR images and slow image acquisition rate.

EON: a component-based approach to automation of protocol-directed therapy.

PubMed Central

Musen, M A; Tu, S W; Das, A K; Shahar, Y

1996-01-01

Provision of automated support for planning protocol-directed therapy requires a computer program to take as input clinical data stored in an electronic patient-record system and to generate as output recommendations for therapeutic interventions and laboratory testing that are defined by applicable protocols. This paper presents a synthesis of research carried out at Stanford University to model the therapy-planning task and to demonstrate a component-based architecture for building protocol-based decision-support systems. We have constructed general-purpose software components that (1) interpret abstract protocol specifications to construct appropriate patient-specific treatment plans; (2) infer from time-stamped patient data higher-level, interval-based, abstract concepts; (3) perform time-oriented queries on a time-oriented patient database; and (4) allow acquisition and maintenance of protocol knowledge in a manner that facilitates efficient processing both by humans and by computers. We have implemented these components in a computer system known as EON. Each of the components has been developed, evaluated, and reported independently. We have evaluated the integration of the components as a composite architecture by implementing T-HELPER, a computer-based patient-record system that uses EON to offer advice regarding the management of patients who are following clinical trial protocols for AIDS or HIV infection. A test of the reuse of the software components in a different clinical domain demonstrated rapid development of a prototype application to support protocol-based care of patients who have breast cancer. PMID:8930854

Patient-specific radiation dose and cancer risk estimation in CT: Part I. Development and validation of a Monte Carlo program

PubMed Central

Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Toncheva, Greta; Yoshizumi, Terry T.; Frush, Donald P.

2011-01-01

Purpose: Radiation-dose awareness and optimization in CT can greatly benefit from a dose-reporting system that provides dose and risk estimates specific to each patient and each CT examination. As the first step toward patient-specific dose and risk estimation, this article aimed to develop a method for accurately assessing radiation dose from CT examinations. Methods: A Monte Carlo program was developed to model a CT system (LightSpeed VCT, GE Healthcare). The geometry of the system, the energy spectra of the x-ray source, the three-dimensional geometry of the bowtie filters, and the trajectories of source motions during axial and helical scans were explicitly modeled. To validate the accuracy of the program, a cylindrical phantom was built to enable dose measurements at seven different radial distances from its central axis. Simulated radial dose distributions in the cylindrical phantom were validated against ion chamber measurements for single axial scans at all combinations of tube potential and bowtie filter settings. The accuracy of the program was further validated using two anthropomorphic phantoms (a pediatric one-year-old phantom and an adult female phantom). Computer models of the two phantoms were created based on their CT data and were voxelized for input into the Monte Carlo program. Simulated dose at various organ locations was compared against measurements made with thermoluminescent dosimetry chips for both single axial and helical scans. Results: For the cylindrical phantom, simulations differed from measurements by −4.8% to 2.2%. For the two anthropomorphic phantoms, the discrepancies between simulations and measurements ranged between (−8.1%, 8.1%) and (−17.2%, 13.0%) for the single axial scans and the helical scans, respectively. Conclusions: The authors developed an accurate Monte Carlo program for assessing radiation dose from CT examinations. When combined with computer models of actual patients, the program can provide accurate dose estimates for specific patients. PMID:21361208

Personalized design and virtual evaluation of physician-modified stent grafts for juxta-renal abdominal aortic aneurysms

NASA Astrophysics Data System (ADS)

Sanathkhani, Soroosh; Shroff, Sanjeev G.; Menon, Prahlad G.

2017-02-01

Endovascular aneurysm repair (EVAR) of juxtarenal aortic aneurysms (JAA) is particularly challenging owing to the requirement of suprarenal EVAR graft fixation, which has been associated with significant declines in long term renal function. Therefore, the ability to design fenestrated EVAR grafts on a personalized basis in order to ensure visceral and renal perfusion, is highly desirable. The objectives of this study are: a) To demonstrate novel 3D geometric methods to virtually design and deploy EVAR grafts into a virtually designed JAA, by applying a custom surface mesh deformation tool to a patient-specific descending aortic model reconstructed from computed tomographic (CT) images; and b) To virtually evaluate patient-specific renal flow and wall stresses in these patient-specific virtually EVAR geometries, using computational fluid dynamics (CFD). The presented framework may provide the modern cardiovascular surgeon the ability to leverage non-invasive, pre-operative imaging equipment to personalize and guide EVAR therapeutic strategy. Our CFD studies revealed that virtual EVAR grafting of a patient-specific JAA, with optimal fenestration sites and renal stenting, led to a 179.67±15.95% and 1051.43±18.34% improvement in right and left renal flow rates, respectively, when compared with the baseline patient-specific aortic geometry with renal stenoses, whereas a right and left renal flow improved by 36.44±2.24% and 885.93±12.41%, respectively, relative to the equivalently modeled JAA with renal stenoses, considering averages across the three simulated inflow rate cases. The proposed framework have utility to iteratively optimize suprarenal EVAR fixation length and achieve normal renal wall shear stresses and streamlined juxtarenal hemodynamics.

Systems oncology: towards patient-specific treatment regimes informed by multiscale mathematical modelling.

PubMed

Powathil, Gibin G; Swat, Maciej; Chaplain, Mark A J

2015-02-01

The multiscale complexity of cancer as a disease necessitates a corresponding multiscale modelling approach to produce truly predictive mathematical models capable of improving existing treatment protocols. To capture all the dynamics of solid tumour growth and its progression, mathematical modellers need to couple biological processes occurring at various spatial and temporal scales (from genes to tissues). Because effectiveness of cancer therapy is considerably affected by intracellular and extracellular heterogeneities as well as by the dynamical changes in the tissue microenvironment, any model attempt to optimise existing protocols must consider these factors ultimately leading to improved multimodal treatment regimes. By improving existing and building new mathematical models of cancer, modellers can play important role in preventing the use of potentially sub-optimal treatment combinations. In this paper, we analyse a multiscale computational mathematical model for cancer growth and spread, incorporating the multiple effects of radiation therapy and chemotherapy in the patient survival probability and implement the model using two different cell based modelling techniques. We show that the insights provided by such multiscale modelling approaches can ultimately help in designing optimal patient-specific multi-modality treatment protocols that may increase patients quality of life. Copyright © 2014 Elsevier Ltd. All rights reserved.

pyNS: an open-source framework for 0D haemodynamic modelling.

PubMed

Manini, Simone; Antiga, Luca; Botti, Lorenzo; Remuzzi, Andrea

2015-06-01

A number of computational approaches have been proposed for the simulation of haemodynamics and vascular wall dynamics in complex vascular networks. Among them, 0D pulse wave propagation methods allow to efficiently model flow and pressure distributions and wall displacements throughout vascular networks at low computational costs. Although several techniques are documented in literature, the availability of open-source computational tools is still limited. We here present python Network Solver, a modular solver framework for 0D problems released under a BSD license as part of the archToolkit ( http://archtk.github.com ). As an application, we describe patient-specific models of the systemic circulation and detailed upper extremity for use in the prediction of maturation after surgical creation of vascular access for haemodialysis.

A geometric scaling model for assessing the impact of aneurysm size ratio on hemodynamic characteristics

PubMed Central

2014-01-01

Background The intracranial aneurysm (IA) size has been proved to have impacts on the hemodynamics and can be applied for the prediction of IA rupture risk. Although the relationship between aspect ratio and hemodynamic parameters was investigated using real patients and virtual models, few studies focused on longitudinal experiments of IAs based on patient-specific aneurysm models. We attempted to do longitudinal simulation experiments of IAs by developing a series of scaled models. Methods In this work, a novel scaling approach was proposed to create IA models with different aneurysm size ratios (ASRs) defined as IA height divided by average neck diameter from a patient-specific aneurysm model and the relationship between the ASR and hemodynamics was explored based on a simulated longitudinal experiment. Wall shear stress, flow patterns and vessel wall displacement were computed from these models. Pearson correlation analysis was performed to elucidate the relationship between the ASR and wall shear stress. The correlation of the ASR and flow velocity was also computed and analyzed. Results The experiment results showed that there was a significant increase in IA area exposed to low WSS once the ASR > 0.7, and the flow became slower and the blood was more difficult to flow into the aneurysm as the ASR increased. Meanwhile, the results also indicated that average blood flow velocity and WSS had strongly negative correlations with the ASR (r = −0.938 and −0.925, respectively). A narrower impingement region and a more concentrated inflow jet appeared as the ASR increased, and the large local deformation at aneurysm apex could be found as the ASR >1.7 or 0.7 < the ASR <1.0. Conclusion Hemodynamic characteristics varied with the ASR. Besides, it is helpful to further explore the relationship between morphologies and hemodynamics based on a longitudinal simulation by building a series of patient-specific aneurysm scaled models applying our proposed IA scaling algorithm. PMID:24528952

Portable Brain-Computer Interface for the Intensive Care Unit Patient Communication Using Subject-Dependent SSVEP Identification.

PubMed

Dehzangi, Omid; Farooq, Muhamed

2018-01-01

A major predicament for Intensive Care Unit (ICU) patients is inconsistent and ineffective communication means. Patients rated most communication sessions as difficult and unsuccessful. This, in turn, can cause distress, unrecognized pain, anxiety, and fear. As such, we designed a portable BCI system for ICU communications (BCI4ICU) optimized to operate effectively in an ICU environment. The system utilizes a wearable EEG cap coupled with an Android app designed on a mobile device that serves as visual stimuli and data processing module. Furthermore, to overcome the challenges that BCI systems face today in real-world scenarios, we propose a novel subject-specific Gaussian Mixture Model- (GMM-) based training and adaptation algorithm. First, we incorporate subject-specific information in the training phase of the SSVEP identification model using GMM-based training and adaptation. We evaluate subject-specific models against other subjects. Subsequently, from the GMM discriminative scores, we generate the transformed vectors, which are passed to our predictive model. Finally, the adapted mixture mean scores of the subject-specific GMMs are utilized to generate the high-dimensional supervectors. Our experimental results demonstrate that the proposed system achieved 98.7% average identification accuracy, which is promising in order to provide effective and consistent communication for patients in the intensive care.

Computational Flow Modeling of Human Upper Airway Breathing

NASA Astrophysics Data System (ADS)

Mylavarapu, Goutham

Computational modeling of biological systems have gained a lot of interest in biomedical research, in the recent past. This thesis focuses on the application of computational simulations to study airflow dynamics in human upper respiratory tract. With advancements in medical imaging, patient specific geometries of anatomically accurate respiratory tracts can now be reconstructed from Magnetic Resonance Images (MRI) or Computed Tomography (CT) scans, with better and accurate details than traditional cadaver cast models. Computational studies using these individualized geometrical models have advantages of non-invasiveness, ease, minimum patient interaction, improved accuracy over experimental and clinical studies. Numerical simulations can provide detailed flow fields including velocities, flow rates, airway wall pressure, shear stresses, turbulence in an airway. Interpretation of these physical quantities will enable to develop efficient treatment procedures, medical devices, targeted drug delivery etc. The hypothesis for this research is that computational modeling can predict the outcomes of a surgical intervention or a treatment plan prior to its application and will guide the physician in providing better treatment to the patients. In the current work, three different computational approaches Computational Fluid Dynamics (CFD), Flow-Structure Interaction (FSI) and Particle Flow simulations were used to investigate flow in airway geometries. CFD approach assumes airway wall as rigid, and relatively easy to simulate, compared to the more challenging FSI approach, where interactions of airway wall deformations with flow are also accounted. The CFD methodology using different turbulence models is validated against experimental measurements in an airway phantom. Two case-studies using CFD, to quantify a pre and post-operative airway and another, to perform virtual surgery to determine the best possible surgery in a constricted airway is demonstrated. The unsteady Large Eddy simulations (LES) and a steady Reynolds Averaged Navier Stokes (RANS) approaches in CFD modeling are discussed. The more challenging FSI approach is modeled first in simple two-dimensional anatomical geometry and then extended to simplified three dimensional geometry and finally in three dimensionally accurate geometries. The concepts of virtual surgery and the differences to CFD are discussed. Finally, the influence of various drug delivery parameters on particle deposition efficiency in airway anatomy are investigated through particle-flow simulations in a nasal airway model.

Validation of a Cochlear Implant Patient-Specific Model of the Voltage Distribution in a Clinical Setting

PubMed Central

Nogueira, Waldo; Schurzig, Daniel; Büchner, Andreas; Penninger, Richard T.; Würfel, Waldemar

2016-01-01

Cochlear Implants (CIs) are medical implantable devices that can restore the sense of hearing in people with profound hearing loss. Clinical trials assessing speech intelligibility in CI users have found large intersubject variability. One possibility to explain the variability is the individual differences in the interface created between electrodes of the CI and the auditory nerve. In order to understand the variability, models of the voltage distribution of the electrically stimulated cochlea may be useful. With this purpose in mind, we developed a parametric model that can be adapted to each CI user based on landmarks from individual cone beam computed tomography (CBCT) scans of the cochlea before and after implantation. The conductivity values of each cochlea compartment as well as the weighting factors of different grounding modes have also been parameterized. Simulations were performed modeling the cochlea and electrode positions of 12 CI users. Three models were compared with different levels of detail: a homogeneous model (HM), a non-patient-specific model (NPSM), and a patient-specific model (PSM). The model simulations were compared with voltage distribution measurements obtained from the backward telemetry of the 12 CI users. Results show that the PSM produces the lowest error when predicting individual voltage distributions. Given a patient-specific geometry and electrode positions, we show an example on how to optimize the parameters of the model and how to couple it to an auditory nerve model. The model here presented may help to understand speech performance variability and support the development of new sound coding strategies for CIs. PMID:27933290

Patient-Specific Simulations of Reactivity in Models of the Pulmonary Vasculature: A 3-D Numerical Study with Fluid-Structure Interaction

NASA Astrophysics Data System (ADS)

Hunter, Kendall; Zhang, Yanhang; Lanning, Craig

2005-11-01

Insight into the progression of pulmonary hypertension may be obtained from thorough study of vascular flow during reactivity testing, an invasive diagnostic procedure which can dramatically alter vascular hemodynamics. Diagnostic imaging methods, however, are limited in their ability to provide extensive data. Here we present detailed flow and wall deformation results from simulations of pulmonary arteries undergoing this procedure. Patient-specific 3-D geometric reconstructions of the first four branches of the pulmonary vasculature were obtained clinically and meshed for use with computational software. Transient simulations in normal and reactive states were obtained from four such models were completed with patient-specific velocity inlet conditions and flow impedance exit conditions. A microstructurally based orthotropic hyperelastic model that simulates pulmonary artery mechanics under normotensive and hypoxic hypertensive conditions treated wall constitutive changes due to pressure reactivity and arterial remodeling. Pressure gradients, velocity fields, arterial deformation, and complete topography of shear stress were obtained. These models provide richer detail of hemodynamics than can be obtained from current imaging techniques, and should allow maximum characterization of vascular function in the clinical situation.

Assessing patient dose in interventional fluoroscopy using patient-dependent hybrid phantoms

NASA Astrophysics Data System (ADS)

Johnson, Perry Barnett

Interventional fluoroscopy uses ionizing radiation to guide small instruments through blood vessels or other body pathways to sites of clinical interest. The technique represents a tremendous advantage over invasive surgical procedures, as it requires only a small incision, thus reducing the risk of infection and providing for shorter recovery times. The growing use and increasing complexity of interventional procedures, however, has resulted in public health concerns regarding radiation exposures, particularly with respect to localized skin dose. Tracking and documenting patient-specific skin and internal organ dose has been specifically identified for interventional fluoroscopy where extended irradiation times, multiple projections, and repeat procedures can lead to some of the largest doses encountered in radiology. Furthermore, inprocedure knowledge of localized skin doses can be of significant clinical importance to managing patient risk and in training radiology residents. In this dissertation, a framework is presented for monitoring the radiation dose delivered to patients undergoing interventional procedures. The framework is built around two key points, developing better anthropomorphic models, and designing clinically relevant software systems for dose estimation. To begin, a library of 50 hybrid patient-dependent computational phantoms was developed based on the UF hybrid male and female reference phantoms. These phantoms represent a different type of anthropomorphic model whereby anthropometric parameters from an individual patient are used during phantom selection. The patient-dependent library was first validated and then used in two patient-phantom matching studies focused on cumulative organ and local skin dose. In terms of organ dose, patient-phantom matching was shown most beneficial for estimating the dose to large patients where error associated with soft tissue attenuation differences could be minimized. For small patients, inherent difference in organ size and location limited the effectiveness of matching. For skin dose, patient-phantom matching was found most beneficial for estimating the dose during lateral and anterior-posterior projections. Patient-sculpting of the patient.s outer body contour was also investigated for use during skin dose estimation and highlighted as a substantial step towards better patient-specificity. In order to utilize the models for actual patient dosimetry, two programs were developed based on the newly released Radiation Dose Structured Report (RDSR). The first program allows for the visualization of skin dose by translating the reference point air kerma to the location of the patient.s skin characterized by a computational model. The program represents an innovative tool that can be used by the interventional physician to modify behavior when clinically appropriate. The second program operates by automatically generating an input file from the RDSR which can then be run within a Monte Carlo based radiation transport code. The program has great potential for initiating and promoting the concept of 'cloud dosimetry', where patient-specific radiation transport is performed off-site and returned via the internet. Both programs are non-proprietary and transferable, and also incorporate the most advanced computational phantoms developed to date. Using the tools developed in this work, there exist a tangible opportunity to improve patient care with the end goal being a better understanding of the risk/benefit relationship that accompanies the medical use of ionizing radiation.

Modeling Patient-Specific Magnetic Drug Targeting Within the Intracranial Vasculature

PubMed Central

Patronis, Alexander; Richardson, Robin A.; Schmieschek, Sebastian; Wylie, Brian J. N.; Nash, Rupert W.; Coveney, Peter V.

2018-01-01

Drug targeting promises to substantially enhance future therapies, for example through the focussing of chemotherapeutic drugs at the site of a tumor, thus reducing the exposure of healthy tissue to unwanted damage. Promising work on the steering of medication in the human body employs magnetic fields acting on nanoparticles made of paramagnetic materials. We develop a computational tool to aid in the optimization of the physical parameters of these particles and the magnetic configuration, estimating the fraction of particles reaching a given target site in a large patient-specific vascular system for different physiological states (heart rate, cardiac output, etc.). We demonstrate the excellent computational performance of our model by its application to the simulation of paramagnetic-nanoparticle-laden flows in a circle of Willis geometry obtained from an MRI scan. The results suggest a strong dependence of the particle density at the target site on the strength of the magnetic forcing and the velocity of the background fluid flow. PMID:29725303

Modeling Patient-Specific Magnetic Drug Targeting Within the Intracranial Vasculature.

PubMed

Patronis, Alexander; Richardson, Robin A; Schmieschek, Sebastian; Wylie, Brian J N; Nash, Rupert W; Coveney, Peter V

2018-01-01

Drug targeting promises to substantially enhance future therapies, for example through the focussing of chemotherapeutic drugs at the site of a tumor, thus reducing the exposure of healthy tissue to unwanted damage. Promising work on the steering of medication in the human body employs magnetic fields acting on nanoparticles made of paramagnetic materials. We develop a computational tool to aid in the optimization of the physical parameters of these particles and the magnetic configuration, estimating the fraction of particles reaching a given target site in a large patient-specific vascular system for different physiological states (heart rate, cardiac output, etc.). We demonstrate the excellent computational performance of our model by its application to the simulation of paramagnetic-nanoparticle-laden flows in a circle of Willis geometry obtained from an MRI scan. The results suggest a strong dependence of the particle density at the target site on the strength of the magnetic forcing and the velocity of the background fluid flow.

A machine learning approach for real-time modelling of tissue deformation in image-guided neurosurgery.

PubMed

Tonutti, Michele; Gras, Gauthier; Yang, Guang-Zhong

2017-07-01

Accurate reconstruction and visualisation of soft tissue deformation in real time is crucial in image-guided surgery, particularly in augmented reality (AR) applications. Current deformation models are characterised by a trade-off between accuracy and computational speed. We propose an approach to derive a patient-specific deformation model for brain pathologies by combining the results of pre-computed finite element method (FEM) simulations with machine learning algorithms. The models can be computed instantaneously and offer an accuracy comparable to FEM models. A brain tumour is used as the subject of the deformation model. Load-driven FEM simulations are performed on a tetrahedral brain mesh afflicted by a tumour. Forces of varying magnitudes, positions, and inclination angles are applied onto the brain's surface. Two machine learning algorithms-artificial neural networks (ANNs) and support vector regression (SVR)-are employed to derive a model that can predict the resulting deformation for each node in the tumour's mesh. The tumour deformation can be predicted in real time given relevant information about the geometry of the anatomy and the load, all of which can be measured instantly during a surgical operation. The models can predict the position of the nodes with errors below 0.3mm, beyond the general threshold of surgical accuracy and suitable for high fidelity AR systems. The SVR models perform better than the ANN's, with positional errors for SVR models reaching under 0.2mm. The results represent an improvement over existing deformation models for real time applications, providing smaller errors and high patient-specificity. The proposed approach addresses the current needs of image-guided surgical systems and has the potential to be employed to model the deformation of any type of soft tissue. Copyright © 2017 Elsevier B.V. All rights reserved.

Patient-specific coronary artery blood flow simulation using myocardial volume partitioning

NASA Astrophysics Data System (ADS)

Kim, Kyung Hwan; Kang, Dongwoo; Kang, Nahyup; Kim, Ji-Yeon; Lee, Hyong-Euk; Kim, James D. K.

2013-03-01

Using computational simulation, we can analyze cardiovascular disease in non-invasive and quantitative manners. More specifically, computational modeling and simulation technology has enabled us to analyze functional aspect such as blood flow, as well as anatomical aspect such as stenosis, from medical images without invasive measurements. Note that the simplest ways to perform blood flow simulation is to apply patient-specific coronary anatomy with other average-valued properties; in this case, however, such conditions cannot fully reflect accurate physiological properties of patients. To resolve this limitation, we present a new patient-specific coronary blood flow simulation method by myocardial volume partitioning considering artery/myocardium structural correspondence. We focus on that blood supply is closely related to the mass of each myocardial segment corresponding to the artery. Therefore, we applied this concept for setting-up simulation conditions in the way to consider many patient-specific features as possible from medical image: First, we segmented coronary arteries and myocardium separately from cardiac CT; then the myocardium is partitioned into multiple regions based on coronary vasculature. The myocardial mass and required blood mass for each artery are estimated by converting myocardial volume fraction. Finally, the required blood mass is used as boundary conditions for each artery outlet, with given average aortic blood flow rate and pressure. To show effectiveness of the proposed method, fractional flow reserve (FFR) by simulation using CT image has been compared with invasive FFR measurement of real patient data, and as a result, 77% of accuracy has been obtained.

PROTO-PLASM: parallel language for adaptive and scalable modelling of biosystems.

PubMed

Bajaj, Chandrajit; DiCarlo, Antonio; Paoluzzi, Alberto

2008-09-13

This paper discusses the design goals and the first developments of PROTO-PLASM, a novel computational environment to produce libraries of executable, combinable and customizable computer models of natural and synthetic biosystems, aiming to provide a supporting framework for predictive understanding of structure and behaviour through multiscale geometric modelling and multiphysics simulations. Admittedly, the PROTO-PLASM platform is still in its infancy. Its computational framework--language, model library, integrated development environment and parallel engine--intends to provide patient-specific computational modelling and simulation of organs and biosystem, exploiting novel functionalities resulting from the symbolic combination of parametrized models of parts at various scales. PROTO-PLASM may define the model equations, but it is currently focused on the symbolic description of model geometry and on the parallel support of simulations. Conversely, CellML and SBML could be viewed as defining the behavioural functions (the model equations) to be used within a PROTO-PLASM program. Here we exemplify the basic functionalities of PROTO-PLASM, by constructing a schematic heart model. We also discuss multiscale issues with reference to the geometric and physical modelling of neuromuscular junctions.

Proto-Plasm: parallel language for adaptive and scalable modelling of biosystems

PubMed Central

Bajaj, Chandrajit; DiCarlo, Antonio; Paoluzzi, Alberto

2008-01-01

This paper discusses the design goals and the first developments of Proto-Plasm, a novel computational environment to produce libraries of executable, combinable and customizable computer models of natural and synthetic biosystems, aiming to provide a supporting framework for predictive understanding of structure and behaviour through multiscale geometric modelling and multiphysics simulations. Admittedly, the Proto-Plasm platform is still in its infancy. Its computational framework—language, model library, integrated development environment and parallel engine—intends to provide patient-specific computational modelling and simulation of organs and biosystem, exploiting novel functionalities resulting from the symbolic combination of parametrized models of parts at various scales. Proto-Plasm may define the model equations, but it is currently focused on the symbolic description of model geometry and on the parallel support of simulations. Conversely, CellML and SBML could be viewed as defining the behavioural functions (the model equations) to be used within a Proto-Plasm program. Here we exemplify the basic functionalities of Proto-Plasm, by constructing a schematic heart model. We also discuss multiscale issues with reference to the geometric and physical modelling of neuromuscular junctions. PMID:18559320

The virtual craniofacial patient: 3D jaw modeling and animation.

PubMed

Enciso, Reyes; Memon, Ahmed; Fidaleo, Douglas A; Neumann, Ulrich; Mah, James

2003-01-01

In this paper, we present new developments in the area of 3D human jaw modeling and animation. CT (Computed Tomography) scans have traditionally been used to evaluate patients with dental implants, assess tumors, cysts, fractures and surgical procedures. More recently this data has been utilized to generate models. Researchers have reported semi-automatic techniques to segment and model the human jaw from CT images and manually segment the jaw from MRI images. Recently opto-electronic and ultrasonic-based systems (JMA from Zebris) have been developed to record mandibular position and movement. In this research project we introduce: (1) automatic patient-specific three-dimensional jaw modeling from CT data and (2) three-dimensional jaw motion simulation using jaw tracking data from the JMA system (Zebris).

Exploring Temporal Frameworks for Constructing Longitudinal Instance-Specific Models from Clinical Data

ERIC Educational Resources Information Center

Watt, Emily

2012-01-01

The prevalence of the EMR in biomedical research is growing, the EMR being regarded as a source of contextually rich, longitudinal data for computation and statistical/trend analysis. However, models trained with data abstracted from the EMR often (1) do not capture all features needed to accurately predict the patient's future state and to…

Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation

PubMed Central

Sweet, Jennifer A.; Pace, Jonathan; Girgis, Fady; Miller, Jonathan P.

2016-01-01

Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS. PMID:27445709

Design and analysis of a tendon-based computed tomography-compatible robot with remote center of motion for lung biopsy.

PubMed

Yang, Yunpeng; Jiang, Shan; Yang, Zhiyong; Yuan, Wei; Dou, Huaisu; Wang, Wei; Zhang, Daguang; Bian, Yuan

2017-04-01

Nowadays, biopsy is a decisive method of lung cancer diagnosis, whereas lung biopsy is time-consuming, complex and inaccurate. So a computed tomography-compatible robot for rapid and precise lung biopsy is developed in this article. According to the actual operation process, the robot is divided into two modules: 4-degree-of-freedom position module for location of puncture point is appropriate for patient's almost all positions and 3-degree-of-freedom tendon-based orientation module with remote center of motion is compact and computed tomography-compatible to orientate and insert needle automatically inside computed tomography bore. The workspace of the robot surrounds patient's thorax, and the needle tip forms a cone under patient's skin. A new error model of the robot based on screw theory is proposed in view of structure error and actuation error, which are regarded as screw motions. Simulation is carried out to verify the precision of the error model contrasted with compensation via inverse kinematics. The results of insertion experiment on specific phantom prove the feasibility of the robot with mean error of 1.373 mm in laboratory environment, which is accurate enough to replace manual operation.

Evolution of design considerations in complex craniofacial reconstruction using patient-specific implants.

PubMed

Peel, Sean; Bhatia, Satyajeet; Eggbeer, Dominic; Morris, Daniel S; Hayhurst, Caroline

2017-06-01

Previously published evidence has established major clinical benefits from using computer-aided design, computer-aided manufacturing, and additive manufacturing to produce patient-specific devices. These include cutting guides, drilling guides, positioning guides, and implants. However, custom devices produced using these methods are still not in routine use, particularly by the UK National Health Service. Oft-cited reasons for this slow uptake include the following: a higher up-front cost than conventionally fabricated devices, material-choice uncertainty, and a lack of long-term follow-up due to their relatively recent introduction. This article identifies a further gap in current knowledge - that of design rules, or key specification considerations for complex computer-aided design/computer-aided manufacturing/additive manufacturing devices. This research begins to address the gap by combining a detailed review of the literature with first-hand experience of interdisciplinary collaboration on five craniofacial patient case studies. In each patient case, bony lesions in the orbito-temporal region were segmented, excised, and reconstructed in the virtual environment. Three cases translated these digital plans into theatre via polymer surgical guides. Four cases utilised additive manufacturing to fabricate titanium implants. One implant was machined from polyether ether ketone. From the literature, articles with relevant abstracts were analysed to extract design considerations. In all, 19 frequently recurring design considerations were extracted from previous publications. Nine new design considerations were extracted from the case studies - on the basis of subjective clinical evaluation. These were synthesised to produce a design considerations framework to assist clinicians with prescribing and design engineers with modelling. Promising avenues for further research are proposed.

A multi-GPU real-time dose simulation software framework for lung radiotherapy.

PubMed

Santhanam, A P; Min, Y; Neelakkantan, H; Papp, N; Meeks, S L; Kupelian, P A

2012-09-01

Medical simulation frameworks facilitate both the preoperative and postoperative analysis of the patient's pathophysical condition. Of particular importance is the simulation of radiation dose delivery for real-time radiotherapy monitoring and retrospective analyses of the patient's treatment. In this paper, a software framework tailored for the development of simulation-based real-time radiation dose monitoring medical applications is discussed. A multi-GPU-based computational framework coupled with inter-process communication methods is introduced for simulating the radiation dose delivery on a deformable 3D volumetric lung model and its real-time visualization. The model deformation and the corresponding dose calculation are allocated among the GPUs in a task-specific manner and is performed in a pipelined manner. Radiation dose calculations are computed on two different GPU hardware architectures. The integration of this computational framework with a front-end software layer and back-end patient database repository is also discussed. Real-time simulation of the dose delivered is achieved at once every 120 ms using the proposed framework. With a linear increase in the number of GPU cores, the computational time of the simulation was linearly decreased. The inter-process communication time also improved with an increase in the hardware memory. Variations in the delivered dose and computational speedup for variations in the data dimensions are investigated using D70 and D90 as well as gEUD as metrics for a set of 14 patients. Computational speed-up increased with an increase in the beam dimensions when compared with a CPU-based commercial software while the error in the dose calculation was <1%. Our analyses show that the framework applied to deformable lung model-based radiotherapy is an effective tool for performing both real-time and retrospective analyses.

Radiogenomics and radiotherapy response modeling

NASA Astrophysics Data System (ADS)

El Naqa, Issam; Kerns, Sarah L.; Coates, James; Luo, Yi; Speers, Corey; West, Catharine M. L.; Rosenstein, Barry S.; Ten Haken, Randall K.

2017-08-01

Advances in patient-specific information and biotechnology have contributed to a new era of computational medicine. Radiogenomics has emerged as a new field that investigates the role of genetics in treatment response to radiation therapy. Radiation oncology is currently attempting to embrace these recent advances and add to its rich history by maintaining its prominent role as a quantitative leader in oncologic response modeling. Here, we provide an overview of radiogenomics starting with genotyping, data aggregation, and application of different modeling approaches based on modifying traditional radiobiological methods or application of advanced machine learning techniques. We highlight the current status and potential for this new field to reshape the landscape of outcome modeling in radiotherapy and drive future advances in computational oncology.

Investigation of blood flow in the external carotid artery and its branches with a new 0D peripheral model.

PubMed

Ohhara, Yoshihito; Oshima, Marie; Iwai, Toshinori; Kitajima, Hiroaki; Yajima, Yasuharu; Mitsudo, Kenji; Krdy, Absy; Tohnai, Iwai

2016-02-04

Patient-specific modelling in clinical studies requires a realistic simulation to be performed within a reasonable computational time. The aim of this study was to develop simple but realistic outflow boundary conditions for patient-specific blood flow simulation which can be used to clarify the distribution of the anticancer agent in intra-arterial chemotherapy for oral cancer. In this study, the boundary conditions are expressed as a zero dimension (0D) resistance model of the peripheral vessel network based on the fractal characteristics of branching arteries combined with knowledge of the circulatory system and the energy minimization principle. This resistance model was applied to four patient-specific blood flow simulations at the region where the common carotid artery bifurcates into the internal and external carotid arteries. Results of these simulations with the proposed boundary conditions were compared with the results of ultrasound measurements for the same patients. The pressure was found to be within the physiological range. The difference in velocity in the superficial temporal artery results in an error of 5.21 ± 0.78 % between the numerical results and the measurement data. The proposed outflow boundary conditions, therefore, constitute a simple resistance-based model and can be used for performing accurate simulations with commercial fluid dynamics software.

Towards personalised management of atherosclerosis via computational models in vascular clinics: technology based on patient-specific simulation approach

PubMed Central

Di Tomaso, Giulia; Agu, Obiekezie; Pichardo-Almarza, Cesar

2014-01-01

The development of a new technology based on patient-specific modelling for personalised healthcare in the case of atherosclerosis is presented. Atherosclerosis is the main cause of death in the world and it has become a burden on clinical services as it manifests itself in many diverse forms, such as coronary artery disease, cerebrovascular disease/stroke and peripheral arterial disease. It is also a multifactorial, chronic and systemic process that lasts for a lifetime, putting enormous financial and clinical pressure on national health systems. In this Letter, the postulate is that the development of new technologies for healthcare using computer simulations can, in the future, be developed as in-silico management and support systems. These new technologies will be based on predictive models (including the integration of observations, theories and predictions across a range of temporal and spatial scales, scientific disciplines, key risk factors and anatomical sub-systems) combined with digital patient data and visualisation tools. Although the problem is extremely complex, a simulation workflow and an exemplar application of this type of technology for clinical use is presented, which is currently being developed by a multidisciplinary team following the requirements and constraints of the Vascular Service Unit at the University College Hospital, London. PMID:26609369

Validation of Computational Models in Biomechanics

PubMed Central

Henninger, Heath B.; Reese, Shawn P.; Anderson, Andrew E.; Weiss, Jeffrey A.

2010-01-01

The topics of verification and validation (V&V) have increasingly been discussed in the field of computational biomechanics, and many recent articles have applied these concepts in an attempt to build credibility for models of complex biological systems. V&V are evolving techniques that, if used improperly, can lead to false conclusions about a system under study. In basic science these erroneous conclusions may lead to failure of a subsequent hypothesis, but they can have more profound effects if the model is designed to predict patient outcomes. While several authors have reviewed V&V as they pertain to traditional solid and fluid mechanics, it is the intent of this manuscript to present them in the context of computational biomechanics. Specifically, the task of model validation will be discussed with a focus on current techniques. It is hoped that this review will encourage investigators to engage and adopt the V&V process in an effort to increase peer acceptance of computational biomechanics models. PMID:20839648

Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease.

PubMed

Randles, Amanda; Frakes, David H; Leopold, Jane A

2017-11-01

Noninvasive engineering models are now being used for diagnosing and planning the treatment of cardiovascular disease. Techniques in computational modeling and additive manufacturing have matured concurrently, and results from simulations can inform and enable the design and optimization of therapeutic devices and treatment strategies. The emerging synergy between large-scale simulations and 3D printing is having a two-fold benefit: first, 3D printing can be used to validate the complex simulations, and second, the flow models can be used to improve treatment planning for cardiovascular disease. In this review, we summarize and discuss recent methods and findings for leveraging advances in both additive manufacturing and patient-specific computational modeling, with an emphasis on new directions in these fields and remaining open questions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multiple organ definition in CT using a Bayesian approach for 3D model fitting

NASA Astrophysics Data System (ADS)

Boes, Jennifer L.; Weymouth, Terry E.; Meyer, Charles R.

1995-08-01

Organ definition in computed tomography (CT) is of interest for treatment planning and response monitoring. We present a method for organ definition using a priori information about shape encoded in a set of biometric organ models--specifically for the liver and kidney-- that accurately represents patient population shape information. Each model is generated by averaging surfaces from a learning set of organ shapes previously registered into a standard space defined by a small set of landmarks. The model is placed in a specific patient's data set by identifying these landmarks and using them as the basis for model deformation; this preliminary representation is then iteratively fit to the patient's data based on a Bayesian formulation of the model's priors and CT edge information, yielding a complete organ surface. We demonstrate this technique using a set of fifteen abdominal CT data sets for liver surface definition both before and after the addition of a kidney model to the fitting; we demonstrate the effectiveness of this tool for organ surface definition in this low-contrast domain.

Patient-specific in vitro models for hemodynamic analysis of congenital heart disease - Additive manufacturing approach.

PubMed

Medero, Rafael; García-Rodríguez, Sylvana; François, Christopher J; Roldán-Alzate, Alejandro

2017-03-21

Non-invasive hemodynamic assessment of total cavopulmonary connection (TCPC) is challenging due to the complex anatomy. Additive manufacturing (AM) is a suitable alternative for creating patient-specific in vitro models for flow measurements using four-dimensional (4D) Flow MRI. These in vitro systems have the potential to serve as validation for computational fluid dynamics (CFD), simulating different physiological conditions. This study investigated three different AM technologies, stereolithography (SLA), selective laser sintering (SLS) and fused deposition modeling (FDM), to determine differences in hemodynamics when measuring flow using 4D Flow MRI. The models were created using patient-specific MRI data from an extracardiac TCPC. These models were connected to a perfusion pump circulating water at three different flow rates. Data was processed for visualization and quantification of velocity, flow distribution, vorticity and kinetic energy. These results were compared between each model. In addition, the flow distribution obtained in vitro was compared to in vivo. The results showed significant difference in velocities measured at the outlets of the models that required internal support material when printing. Furthermore, an ultrasound flow sensor was used to validate flow measurements at the inlets and outlets of the in vitro models. These results were highly correlated to those measured with 4D Flow MRI. This study showed that commercially available AM technologies can be used to create patient-specific vascular models for in vitro hemodynamic studies at reasonable costs. However, technologies that do not require internal supports during manufacturing allow smoother internal surfaces, which makes them better suited for flow analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of a patient-specific anatomical foot model from structured light scan data.

PubMed

Lochner, Samuel J; Huissoon, Jan P; Bedi, Sanjeev S

2014-01-01

The use of anatomically accurate finite element (FE) models of the human foot in research studies has increased rapidly in recent years. Uses for FE foot models include advancing knowledge of orthotic design, shoe design, ankle-foot orthoses, pathomechanics, locomotion, plantar pressure, tissue mechanics, plantar fasciitis, joint stress and surgical interventions. Similar applications but for clinical use on a per-patient basis would also be on the rise if it were not for the high costs associated with developing patient-specific anatomical foot models. High costs arise primarily from the expense and challenges of acquiring anatomical data via magnetic resonance imaging (MRI) or computed tomography (CT) and reconstructing the three-dimensional models. The proposed solution morphs detailed anatomy from skin surface geometry and anatomical landmarks of a generic foot model (developed from CT or MRI) to surface geometry and anatomical landmarks acquired from an inexpensive structured light scan of a foot. The method yields a patient-specific anatomical foot model at a fraction of the cost of standard methods. Average error for bone surfaces was 2.53 mm for the six experiments completed. Highest accuracy occurred in the mid-foot and lowest in the forefoot due to the small, irregular bones of the toes. The method must be validated in the intended application to determine if the resulting errors are acceptable.

3D Printing Based on Cardiac CT Assists Anatomic Visualization Prior to Transcatheter Aortic Valve Replacement

PubMed Central

Ripley, Beth; Kelil, Tatiana; Cheezum, Michael K.; Goncalves, Alexandra; Di Carli, Marcelo F.; Rybicki, Frank J.; Steigner, Mike; Mitsouras, Dimitrios; Blankstein, Ron

2017-01-01

Background 3D printing is a promising technique that may have applications in medicine, and there is expanding interest in the use of patient-specific 3D models to guide surgical interventions. Objective To determine the feasibility of using cardiac CT to print individual models of the aortic root complex for transcatheter aortic valve replacement (TAVR) planning as well as to determine the ability to predict paravalvular aortic regurgitation (PAR). Methods This retrospective study included 16 patients (9 with PAR identified on blinded interpretation of post-procedure trans-thoracic echocardiography and 7 age, sex, and valve size-matched controls with no PAR). 3D printed models of the aortic root were created from pre-TAVR cardiac computed tomography data. These models were fitted with printed valves and predictions regarding post-implant PAR were made using a light transmission test. Results Aortic root 3D models were highly accurate, with excellent agreement between annulus measurements made on 3D models and those made on corresponding 2D data (mean difference of −0.34 mm, 95% limits of agreement: ± 1.3 mm). The 3D printed valve models were within 0.1 mm of their designed dimensions. Examination of the fit of valves within patient-specific aortic root models correctly predicted PAR in 6 of 9 patients (6 true positive, 3 false negative) and absence of PAR in 5 of 7 patients (5 true negative, 2 false positive). Conclusions Pre-TAVR 3D-printing based on cardiac CT provides a unique patient-specific method to assess the physical interplay of the aortic root and implanted valves. With additional optimization, 3D models may complement traditional techniques used for predicting which patients are more likely to develop PAR. PMID:26732862

PET-based compartmental modeling of (124)I-A33 antibody: quantitative characterization of patient-specific tumor targeting in colorectal cancer.

PubMed

Zanzonico, Pat; Carrasquillo, Jorge A; Pandit-Taskar, Neeta; O'Donoghue, Joseph A; Humm, John L; Smith-Jones, Peter; Ruan, Shutian; Divgi, Chaitanya; Scott, Andrew M; Kemeny, Nancy E; Fong, Yuman; Wong, Douglas; Scheinberg, David; Ritter, Gerd; Jungbluth, Achem; Old, Lloyd J; Larson, Steven M

2015-10-01

The molecular specificity of monoclonal antibodies (mAbs) directed against tumor antigens has proven effective for targeted therapy of human cancers, as shown by a growing list of successful antibody-based drug products. We describe a novel, nonlinear compartmental model using PET-derived data to determine the "best-fit" parameters and model-derived quantities for optimizing biodistribution of intravenously injected (124)I-labeled antitumor antibodies. As an example of this paradigm, quantitative image and kinetic analyses of anti-A33 humanized mAb (also known as "A33") were performed in 11 colorectal cancer patients. Serial whole-body PET scans of (124)I-labeled A33 and blood samples were acquired and the resulting tissue time-activity data for each patient were fit to a nonlinear compartmental model using the SAAM II computer code. Excellent agreement was observed between fitted and measured parameters of tumor uptake, "off-target" uptake in bowel mucosa, blood clearance, tumor antigen levels, and percent antigen occupancy. This approach should be generally applicable to antibody-antigen systems in human tumors for which the masses of antigen-expressing tumor and of normal tissues can be estimated and for which antibody kinetics can be measured with PET. Ultimately, based on each patient's resulting "best-fit" nonlinear model, a patient-specific optimum mAb dose (in micromoles, for example) may be derived.

Patient-specific reconstruction utilizing computer assisted 3D modelling for partial bone flap defect in hybrid cranioplasty

NASA Astrophysics Data System (ADS)

Hueh, Low Peh; Abdullah, Johari Yap; Abdullah, Abdul Manaf; Yahya, Suzana; Idris, Zamzuri; Mohamad, Dasmawati

2016-12-01

Autologous cranioplasty using a patient's original bone flap remain the commonest practice nowadays. However, partial bone flap defect is commonly encountered. Replacing the bone flap with pre-moulded synthetic bone flap is costly and not affordable to many patients. Hence most of the small to medium size defect was topped up with alloplastic material on a free hand basis intra-operatively which often resulted in inaccurate implant approximation with unsatisfactory cosmetic result. This study aims to evaluate implant accuracy and cosmetic outcome of cranioplasty candidates who underwent partial bone flap reconstruction utilising computer assisted 3D modelling. 3D images of the skull were obtained from post-craniectomy axial 1-mm spiral computed tomography (CT) scans and a virtual 3D model was generated using the Materialise Mimics software. The Materialise 3-Matic was then utilised to design a patient-specific implant. Prefabrication of the implant was performed by the 3D Objet printer, and a negative gypsum mold was created with the prefabricated cranial implant. Intraoperatively, a hybrid polymethyl methacrylate (PMMA)-autologous cranial implant was produced using the gypsum mold, and fit into the cranial defect. This study is still ongoing at the moment. To date, two men has underwent partial bone flap reconstruction utilising this technique and both revealed satisfactory implant alignment with favourable cosmesis. Mean implant size was 12cm2, and the mean duration of intraoperative reconstruction for the partial bone flap defect was 40 minutes. No significant complication was reported. As a conclusion, this new technique and approach resulted in satisfactory implant alignment and favourable cosmetic outcome. However, more study samples are needed to increase the validity of the study results.

Estimating patient-specific soft-tissue properties in a TKA knee.

PubMed

Ewing, Joseph A; Kaufman, Michelle K; Hutter, Erin E; Granger, Jeffrey F; Beal, Matthew D; Piazza, Stephen J; Siston, Robert A

2016-03-01

Surgical technique is one factor that has been identified as critical to success of total knee arthroplasty. Researchers have shown that computer simulations can aid in determining how decisions in the operating room generally affect post-operative outcomes. However, to use simulations to make clinically relevant predictions about knee forces and motions for a specific total knee patient, patient-specific models are needed. This study introduces a methodology for estimating knee soft-tissue properties of an individual total knee patient. A custom surgical navigation system and stability device were used to measure the force-displacement relationship of the knee. Soft-tissue properties were estimated using a parameter optimization that matched simulated tibiofemoral kinematics with experimental tibiofemoral kinematics. Simulations using optimized ligament properties had an average root mean square error of 3.5° across all tests while simulations using generic ligament properties taken from literature had an average root mean square error of 8.4°. Specimens showed large variability among ligament properties regardless of similarities in prosthetic component alignment and measured knee laxity. These results demonstrate the importance of soft-tissue properties in determining knee stability, and suggest that to make clinically relevant predictions of post-operative knee motions and forces using computer simulations, patient-specific soft-tissue properties are needed. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Patient-specific CFD simulation of intraventricular haemodynamics based on 3D ultrasound imaging.

PubMed

Bavo, A M; Pouch, A M; Degroote, J; Vierendeels, J; Gorman, J H; Gorman, R C; Segers, P

2016-09-09

The goal of this paper is to present a computational fluid dynamic (CFD) model with moving boundaries to study the intraventricular flows in a patient-specific framework. Starting from the segmentation of real-time transesophageal echocardiographic images, a CFD model including the complete left ventricle and the moving 3D mitral valve was realized. Their motion, known as a function of time from the segmented ultrasound images, was imposed as a boundary condition in an Arbitrary Lagrangian-Eulerian framework. The model allowed for a realistic description of the displacement of the structures of interest and for an effective analysis of the intraventricular flows throughout the cardiac cycle. The model provides detailed intraventricular flow features, and highlights the importance of the 3D valve apparatus for the vortex dynamics and apical flow. The proposed method could describe the haemodynamics of the left ventricle during the cardiac cycle. The methodology might therefore be of particular importance in patient treatment planning to assess the impact of mitral valve treatment on intraventricular flow dynamics.

Multiplex-PCR-Based Screening and Computational Modeling of Virulence Factors and T-Cell Mediated Immunity in Helicobacter pylori Infections for Accurate Clinical Diagnosis

PubMed Central

Oktem-Okullu, Sinem; Tiftikci, Arzu; Saruc, Murat; Cicek, Bahattin; Vardareli, Eser; Tozun, Nurdan; Kocagoz, Tanil; Sezerman, Ugur; Yavuz, Ahmet Sinan; Sayi-Yazgan, Ayca

2015-01-01

The outcome of H. pylori infection is closely related with bacteria's virulence factors and host immune response. The association between T cells and H. pylori infection has been identified, but the effects of the nine major H. pylori specific virulence factors; cagA, vacA, oipA, babA, hpaA, napA, dupA, ureA, ureB on T cell response in H. pylori infected patients have not been fully elucidated. We developed a multiplex- PCR assay to detect nine H. pylori virulence genes with in a three PCR reactions. Also, the expression levels of Th1, Th17 and Treg cell specific cytokines and transcription factors were detected by using qRT-PCR assays. Furthermore, a novel expert derived model is developed to identify set of factors and rules that can distinguish the ulcer patients from gastritis patients. Within all virulence factors that we tested, we identified a correlation between the presence of napA virulence gene and ulcer disease as a first data. Additionally, a positive correlation between the H. pylori dupA virulence factor and IFN-γ, and H. pylori babA virulence factor and IL-17 was detected in gastritis and ulcer patients respectively. By using computer-based models, clinical outcomes of a patients infected with H. pylori can be predicted by screening the patient's H. pylori vacA m1/m2, ureA and cagA status and IFN-γ (Th1), IL-17 (Th17), and FOXP3 (Treg) expression levels. Herein, we report, for the first time, the relationship between H. pylori virulence factors and host immune responses for diagnostic prediction of gastric diseases using computer—based models. PMID:26287606

A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests

PubMed Central

Chen, Yong; Liu, Yulun; Ning, Jing; Cormier, Janice; Chu, Haitao

2014-01-01

Systematic reviews of diagnostic tests often involve a mixture of case-control and cohort studies. The standard methods for evaluating diagnostic accuracy only focus on sensitivity and specificity and ignore the information on disease prevalence contained in cohort studies. Consequently, such methods cannot provide estimates of measures related to disease prevalence, such as population averaged or overall positive and negative predictive values, which reflect the clinical utility of a diagnostic test. In this paper, we propose a hybrid approach that jointly models the disease prevalence along with the diagnostic test sensitivity and specificity in cohort studies, and the sensitivity and specificity in case-control studies. In order to overcome the potential computational difficulties in the standard full likelihood inference of the proposed hybrid model, we propose an alternative inference procedure based on the composite likelihood. Such composite likelihood based inference does not suffer computational problems and maintains high relative efficiency. In addition, it is more robust to model mis-specifications compared to the standard full likelihood inference. We apply our approach to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma. PMID:25897179

Identification of Reduced-Order Thermal Therapy Models Using Thermal MR Images: Theory and Validation

PubMed Central

2013-01-01

In this paper, we develop and validate a method to identify computationally efficient site- and patient-specific models of ultrasound thermal therapies from MR thermal images. The models of the specific absorption rate of the transduced energy and the temperature response of the therapy target are identified in the reduced basis of proper orthogonal decomposition of thermal images, acquired in response to a mild thermal test excitation. The method permits dynamic reidentification of the treatment models during the therapy by recursively utilizing newly acquired images. Such adaptation is particularly important during high-temperature therapies, which are known to substantially and rapidly change tissue properties and blood perfusion. The developed theory was validated for the case of focused ultrasound heating of a tissue phantom. The experimental and computational results indicate that the developed approach produces accurate low-dimensional treatment models despite temporal and spatial noises in MR images and slow image acquisition rate. PMID:22531754

Integrating Flexible Sensor and Virtual Self-Organizing DC Grid Model With Cloud Computing for Blood Leakage Detection During Hemodialysis.

PubMed

Huang, Ping-Tzan; Jong, Tai-Lang; Li, Chien-Ming; Chen, Wei-Ling; Lin, Chia-Hung

2017-08-01

Blood leakage and blood loss are serious complications during hemodialysis. From the hemodialysis survey reports, these life-threatening events occur to attract nephrology nurses and patients themselves. When the venous needle and blood line are disconnected, it takes only a few minutes for an adult patient to lose over 40% of his / her blood, which is a sufficient amount of blood loss to cause the patient to die. Therefore, we propose integrating a flexible sensor and self-organizing algorithm to design a cloud computing-based warning device for blood leakage detection. The flexible sensor is fabricated via a screen-printing technique using metallic materials on a soft substrate in an array configuration. The self-organizing algorithm constructs a virtual direct current grid-based alarm unit in an embedded system. This warning device is employed to identify blood leakage levels via a wireless network and cloud computing. It has been validated experimentally, and the experimental results suggest specifications for its commercial designs. The proposed model can also be implemented in an embedded system.

Patient-Specific Modeling of Intraventricular Hemodynamics

NASA Astrophysics Data System (ADS)

Vedula, Vijay; Marsden, Alison

2017-11-01

Heart disease is the one of the leading causes of death in the world. Apart from malfunctions in electrophysiology and myocardial mechanics, abnormal hemodynamics is a major factor attributed to heart disease across all ages. Computer simulations offer an efficient means to accurately reproduce in vivo flow conditions and also make predictions of post-operative outcomes and disease progression. We present an experimentally validated computational framework for performing patient-specific modeling of intraventricular hemodynamics. Our modeling framework employs the SimVascular open source software to build an anatomic model and employs robust image registration methods to extract ventricular motion from the image data. We then employ a stabilized finite element solver to simulate blood flow in the ventricles, solving the Navier-Stokes equations in arbitrary Lagrangian-Eulerian (ALE) coordinates by prescribing the wall motion extracted during registration. We model the fluid-structure interaction effects of the cardiac valves using an immersed boundary method and discuss the potential application of this methodology in single ventricle physiology and trans-catheter aortic valve replacement (TAVR). This research is supported in part by the Stanford Child Health Research Institute and the Stanford NIH-NCATS-CTSA through Grant UL1 TR001085 and partly through NIH NHLBI R01 Grant 5R01HL129727-02.

The effect of inlet waveforms on computational hemodynamics of patient-specific intracranial aneurysms.

PubMed

Xiang, J; Siddiqui, A H; Meng, H

2014-12-18

Due to the lack of patient-specific inlet flow waveform measurements, most computational fluid dynamics (CFD) simulations of intracranial aneurysms usually employ waveforms that are not patient-specific as inlet boundary conditions for the computational model. The current study examined how this assumption affects the predicted hemodynamics in patient-specific aneurysm geometries. We examined wall shear stress (WSS) and oscillatory shear index (OSI), the two most widely studied hemodynamic quantities that have been shown to predict aneurysm rupture, as well as maximal WSS (MWSS), energy loss (EL) and pressure loss coefficient (PLc). Sixteen pulsatile CFD simulations were carried out on four typical saccular aneurysms using 4 different waveforms and an identical inflow rate as inlet boundary conditions. Our results demonstrated that under the same mean inflow rate, different waveforms produced almost identical WSS distributions and WSS magnitudes, similar OSI distributions but drastically different OSI magnitudes. The OSI magnitude is correlated with the pulsatility index of the waveform. Furthermore, there is a linear relationship between aneurysm-averaged OSI values calculated from one waveform and those calculated from another waveform. In addition, different waveforms produced similar MWSS, EL and PLc in each aneurysm. In conclusion, inlet waveform has minimal effects on WSS, OSI distribution, MWSS, EL and PLc and a strong effect on OSI magnitude, but aneurysm-averaged OSI from different waveforms has a strong linear correlation with each other across different aneurysms, indicating that for the same aneurysm cohort, different waveforms can consistently stratify (rank) OSI of aneurysms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Increased decision thresholds enhance information gathering performance in juvenile Obsessive-Compulsive Disorder (OCD)

PubMed Central

Iannaccone, Reto; Brem, Silvia; Walitza, Susanne

2017-01-01

Patients with obsessive-compulsive disorder (OCD) can be described as cautious and hesitant, manifesting an excessive indecisiveness that hinders efficient decision making. However, excess caution in decision making may also lead to better performance in specific situations where the cost of extended deliberation is small. We compared 16 juvenile OCD patients with 16 matched healthy controls whilst they performed a sequential information gathering task under different external cost conditions. We found that patients with OCD outperformed healthy controls, winning significantly more points. The groups also differed in the number of draws required prior to committing to a decision, but not in decision accuracy. A novel Bayesian computational model revealed that subjective sampling costs arose as a non-linear function of sampling, closely resembling an escalating urgency signal. Group difference in performance was best explained by a later emergence of these subjective costs in the OCD group, also evident in an increased decision threshold. Our findings present a novel computational model and suggest that enhanced information gathering in OCD can be accounted for by a higher decision threshold arising out of an altered perception of costs that, in some specific contexts, may be advantageous. PMID:28403139

A comprehensive pipeline for multi-resolution modeling of the mitral valve: Validation, computational efficiency, and predictive capability.

PubMed

Drach, Andrew; Khalighi, Amir H; Sacks, Michael S

2018-02-01

Multiple studies have demonstrated that the pathological geometries unique to each patient can affect the durability of mitral valve (MV) repairs. While computational modeling of the MV is a promising approach to improve the surgical outcomes, the complex MV geometry precludes use of simplified models. Moreover, the lack of complete in vivo geometric information presents significant challenges in the development of patient-specific computational models. There is thus a need to determine the level of detail necessary for predictive MV models. To address this issue, we have developed a novel pipeline for building attribute-rich computational models of MV with varying fidelity directly from the in vitro imaging data. The approach combines high-resolution geometric information from loaded and unloaded states to achieve a high level of anatomic detail, followed by mapping and parametric embedding of tissue attributes to build a high-resolution, attribute-rich computational models. Subsequent lower resolution models were then developed and evaluated by comparing the displacements and surface strains to those extracted from the imaging data. We then identified the critical levels of fidelity for building predictive MV models in the dilated and repaired states. We demonstrated that a model with a feature size of about 5 mm and mesh size of about 1 mm was sufficient to predict the overall MV shape, stress, and strain distributions with high accuracy. However, we also noted that more detailed models were found to be needed to simulate microstructural events. We conclude that the developed pipeline enables sufficiently complex models for biomechanical simulations of MV in normal, dilated, repaired states. Copyright © 2017 John Wiley & Sons, Ltd.

Morphometry-based impedance boundary conditions for patient-specific modeling of blood flow in pulmonary arteries.

PubMed

Spilker, Ryan L; Feinstein, Jeffrey A; Parker, David W; Reddy, V Mohan; Taylor, Charles A

2007-04-01

Patient-specific computational models could aid in planning interventions to relieve pulmonary arterial stenoses common in many forms of congenital heart disease. We describe a new approach to simulate blood flow in subject-specific models of the pulmonary arteries that consists of a numerical model of the proximal pulmonary arteries created from three-dimensional medical imaging data with terminal impedance boundary conditions derived from linear wave propagation theory applied to morphometric models of distal vessels. A tuning method, employing numerical solution methods for nonlinear systems of equations, was developed to modify the distal vasculature to match measured pressure and flow distribution data. One-dimensional blood flow equations were solved with a finite element method in image-based pulmonary arterial models using prescribed inlet flow and morphometry-based impedance at the outlets. Application of these methods in a pilot study of the effect of removal of unilateral pulmonary arterial stenosis induced in a pig showed good agreement with experimental measurements for flow redistribution and main pulmonary arterial pressure. Next, these methods were applied to a patient with repaired tetralogy of Fallot and predicted insignificant hemodynamic improvement with relief of the stenosis. This method of coupling image-based and morphometry-based models could enable increased fidelity in pulmonary hemodynamic simulation.

A Numerical Multiscale Framework for Modeling Patient-Specific Coronary Artery Bypass Surgeries

NASA Astrophysics Data System (ADS)

Ramachandra, Abhay B.; Kahn, Andrew; Marsden, Alison

2014-11-01

Coronary artery bypass graft (CABG) surgery is performed to revascularize diseased coronary arteries, using arterial, venous or synthetic grafts. Vein grafts, used in more than 70% of procedures, have failure rates as high as 50% in less than 10 years. Hemodynamics is known to play a key role in the mechano-biological response of vein grafts, but current non-invasive imaging techniques cannot fully characterize the hemodynamic and biomechanical environment. We numerically compute hemodynamics and wall mechanics in patient-specific 3D CABG geometries using stabilized finite element methods. The 3D patient-specific domain is coupled to a 0D lumped parameter circulatory model and parameters are tuned to match patient-specific blood pressures, stroke volumes, heart rates and heuristic flow-split values. We quantify differences in hemodynamics between arterial and venous grafts and discuss possible correlations to graft failure. Extension to a deformable wall approximation will also be discussed. The quantification of wall mechanics and hemodynamics is a necessary step towards coupling continuum models in solid and fluid mechanics with the cellular and sub-cellular responses of grafts, which in turn, should lead to a more accurate prediction of the long term outcome of CABG surgeries, including predictions of growth and remodeling.

BODY SIZE-SPECIFIC EFFECTIVE DOSE CONVERSION COEFFICIENTS FOR CT SCANS.

PubMed

Romanyukha, Anna; Folio, Les; Lamart, Stephanie; Simon, Steven L; Lee, Choonsik

2016-12-01

Effective dose from computed tomography (CT) examinations is usually estimated using the scanner-provided dose-length product and using conversion factors, also known as k-factors, which correspond to scan regions and differ by age according to five categories: 0, 1, 5, 10 y and adult. However, patients often deviate from the standard body size on which the conversion factor is based. In this study, a method for deriving body size-specific k-factors is presented, which can be determined from a simple regression curve based on patient diameter at the centre of the scan range. Using the International Commission on Radiological Protection reference paediatric and adult computational phantoms paired with Monte Carlo simulation of CT X-ray beams, the authors derived a regression-based k-factor model for the following CT scan types: head-neck, head, neck, chest, abdomen, pelvis, abdomen-pelvis (AP) and chest-abdomen-pelvis (CAP). The resulting regression functions were applied to a total of 105 paediatric and 279 adult CT scans randomly sampled from patients who underwent chest, AP and CAP scans at the National Institutes of Health Clinical Center. The authors have calculated and compared the effective doses derived from the conventional age-specific k-factors with the values computed using their body size-specific k-factor. They found that by using the age-specific k-factor, paediatric patients tend to have underestimates (up to 3-fold) of effective dose, while underweight and overweight adult patients tend to have underestimates (up to 2.6-fold) and overestimates (up to 4.6-fold) of effective dose, respectively, compared with the effective dose determined from their body size-dependent factors. The authors present these size-specific k-factors as an alternative to the existing age-specific factors. The body size-specific k-factor will assess effective dose more precisely and on a more individual level than the conventional age-specific k-factors and, hence, improve awareness of the true exposure, which is important for the clinical community to understand. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

PRIMsrc is a novel implementation of a non-parametric bump hunting procedure, based on the Patient Rule Induction Method (PRIM), offering a unified treatment of outcome variables, including censored time-to-event (Survival), continuous (Regression) and discrete (Classification) responses. To fit the model, it uses a recursive peeling procedure with specific peeling criteria and stopping rules depending on the response. To validate the model, it provides an objective function based on prediction-error or other specific statistic, as well as two alternative cross-validation techniques, adapted to the task of decision-rule making and estimation in the three types of settings. PRIMsrc comes as an open source R package, including at this point: (i) a main function for fitting a Survival Bump Hunting model with various options allowing cross-validated model selection to control model size (#covariates) and model complexity (#peeling steps) and generation of cross-validated end-point estimates; (ii) parallel computing; (iii) various S3-generic and specific plotting functions for data visualization, diagnostic, prediction, summary and display of results. It is available on CRAN and GitHub. PMID:26798326

Patient-specific atrium models for training and pre-procedure surgical planning

NASA Astrophysics Data System (ADS)

Laing, Justin; Moore, John; Bainbridge, Daniel; Drangova, Maria; Peters, Terry

2017-03-01

Minimally invasive cardiac procedures requiring a trans-septal puncture such as atrial ablation and MitraClip® mitral valve repair are becoming increasingly common. These procedures are performed on the beating heart, and require clinicians to rely on image-guided techniques. For cases of complex or diseased anatomy, in which fluoroscopic and echocardiography images can be difficult to interpret, clinicians may benefit from patient-specific atrial models that can be used for training, surgical planning, and the validation of new devices and guidance techniques. Computed tomography (CT) images of a patient's heart were segmented and used to generate geometric models to create a patient-specific atrial phantom. Using rapid prototyping, the geometric models were converted into physical representations and used to build a mold. The atria were then molded using tissue-mimicking materials and imaged using CT. The resulting images were segmented and used to generate a point cloud data set that could be registered to the original patient data. The absolute distance of the two point clouds was compared and evaluated to determine the model's accuracy. The result when comparing the molded model point cloud to the original data set, resulted in a maximum Euclidean distance error of 4.5 mm, an average error of 0.5 mm and a standard deviation of 0.6 mm. Using our workflow for creating atrial models, potential complications, particularly for complex repairs, may be accounted for in pre-operative planning. The information gained by clinicians involved in planning and performing the procedure should lead to shorter procedural times and better outcomes for patients.

Investigating the Role of Interventricular Interdependence in Development of Right Heart Dysfunction During LVAD Support: A Patient-Specific Methods-Based Approach.

PubMed

Sack, Kevin L; Dabiri, Yaghoub; Franz, Thomas; Solomon, Scott D; Burkhoff, Daniel; Guccione, Julius M

2018-01-01

Predictive computation models offer the potential to uncover the mechanisms of treatments whose actions cannot be easily determined by experimental or imaging techniques. This is particularly relevant for investigating left ventricular mechanical assistance, a therapy for end-stage heart failure, which is increasingly used as more than just a bridge-to-transplant therapy. The high incidence of right ventricular failure following left ventricular assistance reflects an undesired consequence of treatment, which has been hypothesized to be related to the mechanical interdependence between the two ventricles. To investigate the implication of this interdependence specifically in the setting of left ventricular assistance device (LVAD) support, we introduce a patient-specific finite-element model of dilated chronic heart failure. The model geometry and material parameters were calibrated using patient-specific clinical data, producing a mechanical surrogate of the failing in vivo heart that models its dynamic strain and stress throughout the cardiac cycle. The model of the heart was coupled to lumped-parameter circulatory systems to simulate realistic ventricular loading conditions. Finally, the impact of ventricular assistance was investigated by incorporating a pump with pressure-flow characteristics of an LVAD (HeartMate II™ operating between 8 and 12 k RPM) in parallel to the left ventricle. This allowed us to investigate the mechanical impact of acute left ventricular assistance at multiple operating-speeds on right ventricular mechanics and septal wall motion. Our findings show that left ventricular assistance reduces myofiber stress in the left ventricle and, to a lesser extent, right ventricle free wall, while increasing leftward septal-shift with increased operating-speeds. These effects were achieved with secondary, potentially negative effects on the interventricular septum which showed that support from LVADs, introduces unnatural bending of the septum and with it, increased localized stress regions. Left ventricular assistance unloads the left ventricle significantly and shifts the right ventricular pressure-volume-loop toward larger volumes and higher pressures; a consequence of left-to-right ventricular interactions and a leftward septal shift. The methods and results described in the present study are a meaningful advancement of computational efforts to investigate heart-failure therapies in silico and illustrate the potential of computational models to aid understanding of complex mechanical and hemodynamic effects of new therapies.

Antecedent characteristics of online cancer information seeking among rural breast cancer patients: an application of the Cognitive-Social Health Information Processing (C-SHIP) model.

PubMed

Shaw, Bret R; Dubenske, Lori L; Han, Jeong Yeob; Cofta-Woerpel, Ludmila; Bush, Nigel; Gustafson, David H; McTavish, Fiona

2008-06-01

Little research has examined the antecedent characteristics of patients most likely to seek online cancer information. This study employs the Cognitive-Social Health Information Processing (C-SHIP) model as a framework to understand what psychosocial characteristics precede online cancer-related information seeking among rural breast cancer patients who often have fewer health care providers and limited local support services. Examining 144 patients who were provided free computer hardware, Internet access, and training for how to use an interactive cancer communication system, pretest survey scores indicating patients' psychosocial status were correlated with specific online cancer information seeking behaviors. Each of the factors specified by the C-SHIP model had significant relationships with online cancer information seeking behaviors, with the strongest findings emerging for cancer-relevant encodings and self-construals, cancer-relevant beliefs and expectancies, and cancer-relevant self-regulatory competencies and skills. Specifically, patients with more negative appraisals in these domains were more likely to seek out online cancer information. Additionally, antecedent variables associated with the C-SHIP model had more frequent relationships with experiential information as compared with to didactic information. This study supports the applicability of the model to discern why people afflicted with cancer may seek online information to cope with their disease.

Modeling the Dynamics of Disease States in Depression

PubMed Central

Demic, Selver; Cheng, Sen

2014-01-01

Major depressive disorder (MDD) is a common and costly disorder associated with considerable morbidity, disability, and risk for suicide. The disorder is clinically and etiologically heterogeneous. Despite intense research efforts, the response rates of antidepressant treatments are relatively low and the etiology and progression of MDD remain poorly understood. Here we use computational modeling to advance our understanding of MDD. First, we propose a systematic and comprehensive definition of disease states, which is based on a type of mathematical model called a finite-state machine. Second, we propose a dynamical systems model for the progression, or dynamics, of MDD. The model is abstract and combines several major factors (mechanisms) that influence the dynamics of MDD. We study under what conditions the model can account for the occurrence and recurrence of depressive episodes and how we can model the effects of antidepressant treatments and cognitive behavioral therapy within the same dynamical systems model through changing a small subset of parameters. Our computational modeling suggests several predictions about MDD. Patients who suffer from depression can be divided into two sub-populations: a high-risk sub-population that has a high risk of developing chronic depression and a low-risk sub-population, in which patients develop depression stochastically with low probability. The success of antidepressant treatment is stochastic, leading to widely different times-to-remission in otherwise identical patients. While the specific details of our model might be subjected to criticism and revisions, our approach shows the potential power of computationally modeling depression and the need for different type of quantitative data for understanding depression. PMID:25330102

Epicardial potentials computed from the body surface potential map using inverse electrocardiography and an individualised torso model improve sensitivity for acute myocardial infarction diagnosis.

PubMed

Daly, Michael J; Finlay, Dewar D; Guldenring, Daniel; Bond, Raymond R; McCann, Aaron J; Scott, Peter J; Adgey, Jennifer A; Harbinson, Mark T

2017-12-01

Epicardial potentials (EPs) derived from the body surface potential map (BSPM) improve acute myocardial infarction (AMI) diagnosis. In this study, we compared EPs derived from the 80-lead BSPM using a standard thoracic volume conductor model (TVCM) with those derived using a patient-specific torso model (PSTM) based on body mass index (BMI). Consecutive patients presenting to both the emergency department and pre-hospital coronary care unit between August 2009 and August 2011 with acute ischaemic-type chest pain at rest were enrolled. At first medical contact, 12-lead electrocardiograms and BSPMs were recorded. The BMI for each patient was calculated. Cardiac troponin T (cTnT) was sampled 12 hours after symptom onset. Patients were excluded from analysis if they had any ECG confounders to interpretation of the ST-segment. A cardiologist assessed the 12-lead ECG for ST-segment elevation myocardial infarction by Minnesota criteria and the BSPM. BSPM ST-elevation (STE) was ⩾0.2 mV in anterior, ⩾0.1 mV in lateral, inferior, right ventricular or high right anterior and ⩾0.05 mV in posterior territories. To derive EPs, the BSPM data were interpolated to yield values at 352 nodes of a Dalhousie torso. Using an inverse solution based on the boundary element method, EPs at 98 cardiac nodes positioned within a standard TVCM were derived. The TVCM was then scaled to produce a PSTM using a model developed from computed tomography in 48 patients of varying BMIs, and EPs were recalculated. EPs >0.3 mV defined STE. A cardiologist blinded to both the 12-lead ECG and BSPM interpreted the EP map. AMI was defined as cTnT ⩾0.1 µg/L. Enrolled were 400 patients (age 62 ± 13 years; 57% male); 80 patients had exclusion criteria. Of the remaining 320 patients, the BMI was an average of 27.8 ± 5.6 kg/m 2 . Of these, 180 (56%) had AMI. Overall, 132 had Minnesota STE on ECG (sensitivity 65%, specificity 89%) and 160 had BSPM STE (sensitivity 81%, specificity 90%). EP STE occurred in 165 patients using TVCM (sensitivity 88%, specificity 95%; p < 0.001) and in 206 patients using PSTM (sensitivity 98%, specificity 79%; p < 0.001). Of those with AMI by cTnT and EPs ⩽0.3 mV using TVCM ( n = 22), 18 (82%) patients had EPs >0.3 mV when an individualised PSTM was used. Among patients presenting with ischaemic-type chest pain at rest, EPs derived from BSPM using a novel PSTM significantly improve sensitivity for AMI diagnosis.

[New simulation technologies in neurosurgery].

PubMed

Byvaltsev, V A; Belykh, E G; Konovalov, N A

2016-01-01

The article presents a literature review on the current state of simulation technologies in neurosurgery, a brief description of the basic technology and the classification of simulation models, and examples of simulation models and skills simulators used in neurosurgery. Basic models for the development of physical skills, the spectrum of available computer virtual simulators, and their main characteristics are described. It would be instructive to include microneurosurgical training and a cadaver course of neurosurgical approaches in neurosurgery training programs and to extend the use of three-dimensional imaging. Technologies for producing three-dimensional anatomical models and patient-specific computer simulators as well as improvement of tactile feedback systems and display quality of virtual models are promising areas. Continued professional education necessitates further research for assessing the validity and practical use of simulators and physical models.

Computer-Assisted Virtual Planning for Surgical Guide Manufacturing and Internal Distractor Adaptation in the Management of Midface Hypoplasia in Cleft Patients.

PubMed

Scolozzi, Paolo; Herzog, Georges

2017-07-01

We are reporting the treatment of severe maxillary hypoplasia in two patients with unilateral cleft lip and palate by using a specific approach combining the Le Fort I distraction osteogenesis technique coupled with computer-aided design/computer-aided manufacturing customized surgical guides and internal distractors based on virtual computational planning. This technology allows for the transfer of the virtual planned reconstruction to the operating room by using custom patient-specific implants, surgical splints, surgical cutting guides, and surgical guides to plate or distractor adaptation.

Effect of exercise on patient specific abdominal aortic aneurysm flow topology and mixing

PubMed Central

Arzani, Amirhossein; Les, Andrea S.; Dalman, Ronald L.; Shadden, Shawn C.

2014-01-01

SUMMARY Computational fluid dynamics modeling was used to investigate changes in blood transport topology between rest and exercise conditions in five patient-specific abdominal aortic aneurysm models. Magnetic resonance imaging was used to provide the vascular anatomy and necessary boundary conditions for simulating blood velocity and pressure fields inside each model. Finite-time Lyapunov exponent fields, and associated Lagrangian coherent structures, were computed from blood velocity data, and used to compare features of the transport topology between rest and exercise both mechanistically and qualitatively. A mix-norm and mix-variance measure based on fresh blood distribution throughout the aneurysm over time were implemented to quantitatively compare mixing between rest and exercise. Exercise conditions resulted in higher and more uniform mixing, and reduced the overall residence time in all aneurysms. Separated regions of recirculating flow were commonly observed in rest, and these regions were either reduced or removed by attached and unidirectional flow during exercise, or replaced with regional chaotic and transiently turbulent mixing, or persisted and even extended during exercise. The main factor that dictated the change in flow topology from rest to exercise was the behavior of the jet of blood penetrating into the aneurysm during systole. PMID:24493404

Coherent concepts are computed in the anterior temporal lobes.

PubMed

Lambon Ralph, Matthew A; Sage, Karen; Jones, Roy W; Mayberry, Emily J

2010-02-09

In his Philosophical Investigations, Wittgenstein famously noted that the formation of semantic representations requires more than a simple combination of verbal and nonverbal features to generate conceptually based similarities and differences. Classical and contemporary neuroscience has tended to focus upon how different neocortical regions contribute to conceptualization through the summation of modality-specific information. The additional yet critical step of computing coherent concepts has received little attention. Some computational models of semantic memory are able to generate such concepts by the addition of modality-invariant information coded in a multidimensional semantic space. By studying patients with semantic dementia, we demonstrate that this aspect of semantic memory becomes compromised following atrophy of the anterior temporal lobes and, as a result, the patients become increasingly influenced by superficial rather than conceptual similarities.

NOTE: Development and preliminary evaluation of a prototype audiovisual biofeedback device incorporating a patient-specific guiding waveform

NASA Astrophysics Data System (ADS)

Venkat, Raghu B.; Sawant, Amit; Suh, Yelin; George, Rohini; Keall, Paul J.

2008-06-01

The aim of this research was to investigate the effectiveness of a novel audio-visual biofeedback respiratory training tool to reduce respiratory irregularity. The audiovisual biofeedback system acquires sample respiratory waveforms of a particular patient and computes a patient-specific waveform to guide the patient's subsequent breathing. Two visual feedback models with different displays and cognitive loads were investigated: a bar model and a wave model. The audio instructions were ascending/descending musical tones played at inhale and exhale respectively to assist in maintaining the breathing period. Free-breathing, bar model and wave model training was performed on ten volunteers for 5 min for three repeat sessions. A total of 90 respiratory waveforms were acquired. It was found that the bar model was superior to free breathing with overall rms displacement variations of 0.10 and 0.16 cm, respectively, and rms period variations of 0.77 and 0.33 s, respectively. The wave model was superior to the bar model and free breathing for all volunteers, with an overall rms displacement of 0.08 cm and rms periods of 0.2 s. The reduction in the displacement and period variations for the bar model compared with free breathing was statistically significant (p = 0.005 and 0.002, respectively); the wave model was significantly better than the bar model (p = 0.006 and 0.005, respectively). Audiovisual biofeedback with a patient-specific guiding waveform significantly reduces variations in breathing. The wave model approach reduces cycle-to-cycle variations in displacement by greater than 50% and variations in period by over 70% compared with free breathing. The planned application of this device is anatomic and functional imaging procedures and radiation therapy delivery.

Estimating Radiation Dose Metrics for Patients Undergoing Tube Current Modulation CT Scans

NASA Astrophysics Data System (ADS)

McMillan, Kyle Lorin

Computed tomography (CT) has long been a powerful tool in the diagnosis of disease, identification of tumors and guidance of interventional procedures. With CT examinations comes the concern of radiation exposure and the associated risks. In order to properly understand those risks on a patient-specific level, organ dose must be quantified for each CT scan. Some of the most widely used organ dose estimates are derived from fixed tube current (FTC) scans of a standard sized idealized patient model. However, in current clinical practice, patient size varies from neonates weighing just a few kg to morbidly obese patients weighing over 200 kg, and nearly all CT exams are performed with tube current modulation (TCM), a scanning technique that adjusts scanner output according to changes in patient attenuation. Methods to account for TCM in CT organ dose estimates have been previously demonstrated, but these methods are limited in scope and/or restricted to idealized TCM profiles that are not based on physical observations and not scanner specific (e.g. don't account for tube limits, scanner-specific effects, etc.). The goal of this work was to develop methods to estimate organ doses to patients undergoing CT scans that take into account both the patient size as well as the effects of TCM. This work started with the development and validation of methods to estimate scanner-specific TCM schemes for any voxelized patient model. An approach was developed to generate estimated TCM schemes that match actual TCM schemes that would have been acquired on the scanner for any patient model. Using this approach, TCM schemes were then generated for a variety of body CT protocols for a set of reference voxelized phantoms for which TCM information does not currently exist. These are whole body patient models representing a variety of sizes, ages and genders that have all radiosensitive organs identified. TCM schemes for these models facilitated Monte Carlo-based estimates of fully-, partially- and indirectly-irradiated organ dose from TCM CT exams. By accounting for the effects of patient size in the organ dose estimates, a comprehensive set of patient-specific dose estimates from TCM CT exams was developed. These patient-specific organ dose estimates from TCM CT exams will provide a more complete understanding of the dose impact and risks associated with modern body CT scanning protocols.

Biomechanics of the soft-palate in sleep apnea patients with polycystic ovarian syndrome.

PubMed

Subramaniam, Dhananjay Radhakrishnan; Arens, Raanan; Wagshul, Mark E; Sin, Sanghun; Wootton, David M; Gutmark, Ephraim J

2018-05-17

Highly compliant tissue supporting the pharynx and low muscle tone enhance the possibility of upper airway occlusion in children with obstructive sleep apnea (OSA). The present study describes subject-specific computational modeling of flow-induced velopharyngeal narrowing in a female child with polycystic ovarian syndrome (PCOS) with OSA and a non-OSA control. Anatomically accurate three-dimensional geometries of the upper airway and soft-palate were reconstructed for both subjects using magnetic resonance (MR) images. A fluid-structure interaction (FSI) shape registration analysis was performed using subject-specific values of flow rate to iteratively compute the biomechanical properties of the soft-palate. The optimized shear modulus for the control was 38 percent higher than the corresponding value for the OSA patient. The proposed computational FSI model was then employed for planning surgical treatment for the apneic subject. A virtual surgery comprising of a combined adenoidectomy, palatoplasty and genioglossus advancement was performed to estimate the resulting post-operative patterns of airflow and tissue displacement. Maximum flow velocity and velopharyngeal resistance decreased by 80 percent and 66 percent respectively following surgery. Post-operative flow-induced forces on the anterior and posterior faces of the soft-palate were equilibrated and the resulting magnitude of tissue displacement was 63 percent lower compared to the pre-operative case. Results from this pilot study indicate that FSI computational modeling can be employed to characterize the mechanical properties of pharyngeal tissue and evaluate the effectiveness of various upper airway surgeries prior to their application. Copyright © 2018. Published by Elsevier Ltd.

Automated Surgical Approach Planning for Complex Skull Base Targets: Development and Validation of a Cost Function and Semantic At-las.

PubMed

Aghdasi, Nava; Whipple, Mark; Humphreys, Ian M; Moe, Kris S; Hannaford, Blake; Bly, Randall A

2018-06-01

Successful multidisciplinary treatment of skull base pathology requires precise preoperative planning. Current surgical approach (pathway) selection for these complex procedures depends on an individual surgeon's experiences and background training. Because of anatomical variation in both normal tissue and pathology (eg, tumor), a successful surgical pathway used on one patient is not necessarily the best approach on another patient. The question is how to define and obtain optimized patient-specific surgical approach pathways? In this article, we demonstrate that the surgeon's knowledge and decision making in preoperative planning can be modeled by a multiobjective cost function in a retrospective analysis of actual complex skull base cases. Two different approaches- weighted-sum approach and Pareto optimality-were used with a defined cost function to derive optimized surgical pathways based on preoperative computed tomography (CT) scans and manually designated pathology. With the first method, surgeon's preferences were input as a set of weights for each objective before the search. In the second approach, the surgeon's preferences were used to select a surgical pathway from the computed Pareto optimal set. Using preoperative CT and magnetic resonance imaging, the patient-specific surgical pathways derived by these methods were similar (85% agreement) to the actual approaches performed on patients. In one case where the actual surgical approach was different, revision surgery was required and was performed utilizing the computationally derived approach pathway.

Use of declarative statements in creating and maintaining computer-interpretable knowledge bases for guideline-based care.

PubMed

Tu, Samson W; Hrabak, Karen M; Campbell, James R; Glasgow, Julie; Nyman, Mark A; McClure, Robert; McClay, James; Abarbanel, Robert; Mansfield, James G; Martins, Susana M; Goldstein, Mary K; Musen, Mark A

2006-01-01

Developing computer-interpretable clinical practice guidelines (CPGs) to provide decision support for guideline-based care is an extremely labor-intensive task. In the EON/ATHENA and SAGE projects, we formulated substantial portions of CPGs as computable statements that express declarative relationships between patient conditions and possible interventions. We developed query and expression languages that allow a decision-support system (DSS) to evaluate these statements in specific patient situations. A DSS can use these guideline statements in multiple ways, including: (1) as inputs for determining preferred alternatives in decision-making, and (2) as a way to provide targeted commentaries in the clinical information system. The use of these declarative statements significantly reduces the modeling expertise and effort required to create and maintain computer-interpretable knowledge bases for decision-support purpose. We discuss possible implications for sharing of such knowledge bases.

Patient-based estimation of organ dose for a population of 58 adult patients across 13 protocol categories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sahbaee, Pooyan, E-mail: psahbae@ncsu.edu; Segars, W. Paul; Samei, Ehsan

2014-07-15

Purpose: This study aimed to provide a comprehensive patient-specific organ dose estimation across a multiplicity of computed tomography (CT) examination protocols. Methods: A validated Monte Carlo program was employed to model a common CT system (LightSpeed VCT, GE Healthcare). The organ and effective doses were estimated from 13 commonly used body and neurological CT examination. The dose estimation was performed on 58 adult computational extended cardiac-torso phantoms (35 male, 23 female, mean age 51.5 years, mean weight 80.2 kg). The organ dose normalized by CTDI{sub vol} (h factor) and effective dose normalized by the dose length product (DLP) (k factor)more » were calculated from the results. A mathematical model was derived for the correlation between the h and k factors with the patient size across the protocols. Based on this mathematical model, a dose estimation iPhone operating system application was designed and developed to be used as a tool to estimate dose to the patients for a variety of routinely used CT examinations. Results: The organ dose results across all the protocols showed an exponential decrease with patient body size. The correlation was generally strong for the organs which were fully or partially located inside the scan coverage (Pearson sample correlation coefficient (r) of 0.49). The correlation was weaker for organs outside the scan coverage for which distance between the organ and the irradiation area was a stronger predictor of dose to the organ. For body protocols, the effective dose before and after normalization by DLP decreased exponentially with increasing patient's body diameter (r > 0.85). The exponential relationship between effective dose and patient's body diameter was significantly weaker for neurological protocols (r < 0.41), where the trunk length was a slightly stronger predictor of effective dose (0.15 < r < 0.46). Conclusions: While the most accurate estimation of a patient dose requires specific modeling of the patient anatomy, a first order approximation of organ and effective doses from routine CT scan protocols can be reasonably estimated using size specific factors. Estimation accuracy is generally poor for organ outside the scan range and for neurological protocols. The dose calculator designed in this study can be used to conveniently estimate and report the dose values for a patient across a multiplicity of CT scan protocols.« less

Application of 3-Dimensional Printing in a Case of Osteogenesis Imperfecta for Patient Education, Anatomic Understanding, Preoperative Planning, and Intraoperative Evaluation.

PubMed

Eisenmenger, Laura B; Wiggins, Richard H; Fults, Daniel W; Huo, Eugene J

2017-11-01

The techniques and applications of 3-dimensional (3D) printing have progressed at a fast pace. In the last 10 years, there has been significant progress in applying this technology to medical applications. We present a case of osteogenesis imperfecta in which treatment was aided by prospectively using patient-specific, anatomically accurate 3D prints of the calvaria. The patient-specific, anatomically accurate 3D prints were used in the clinic and in the operating room to augment patient education, improve surgical decision making, and enhance preoperative planning. A 41-year-old woman with osteogenesis imperfecta and an extensive neurosurgical history presented for cranioplasty revision. Computed tomography (CT) data obtained as part of routine preoperative imaging were processed into a 3D model. The 3D patient-specific models were used in the clinic for patient education and in the operating room for preoperative visualization, planning, and intraoperative evaluation of anatomy. The patient reported the 3D models improved her understanding and comfort with the planned surgery when compared with discussing the procedure with the neurosurgeon or viewing the CT images with a neuroradiologist. The neurosurgeon reported an improved understanding of the patient's anatomy and potential cause of patient symptoms as well as improved preoperative planning compared with viewing the CT imaging alone. The neurosurgeon also reported an improvement in the planned surgical approach with a better intraoperative visualization and confirmation of the regions of planned calvarial resection. The use of patient-specific, anatomically accurate 3D prints may improve patient education, surgeon understanding and visualization, preoperative decision making, and intraoperative management. Copyright © 2017 Elsevier Inc. All rights reserved.

The impact of anthropometric patient-phantom matching on organ dose: A hybrid phantom study for fluoroscopy guided interventions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Perry B.; Geyer, Amy; Borrego, David

Purpose: To investigate the benefits and limitations of patient-phantom matching for determining organ dose during fluoroscopy guided interventions. Methods: In this study, 27 CT datasets representing patients of different sizes and genders were contoured and converted into patient-specific computational models. Each model was matched, based on height and weight, to computational phantoms selected from the UF hybrid patient-dependent series. In order to investigate the influence of phantom type on patient organ dose, Monte Carlo methods were used to simulate two cardiac projections (PA/left lateral) and two abdominal projections (RAO/LPO). Organ dose conversion coefficients were then calculated for each patient-specific andmore » patient-dependent phantom and also for a reference stylized and reference hybrid phantom. The coefficients were subsequently analyzed for any correlation between patient-specificity and the accuracy of the dose estimate. Accuracy was quantified by calculating an absolute percent difference using the patient-specific dose conversion coefficients as the reference. Results: Patient-phantom matching was shown most beneficial for estimating the dose to heavy patients. In these cases, the improvement over using a reference stylized phantom ranged from approximately 50% to 120% for abdominal projections and for a reference hybrid phantom from 20% to 60% for all projections. For lighter individuals, patient-phantom matching was clearly superior to using a reference stylized phantom, but not significantly better than using a reference hybrid phantom for certain fields and projections. Conclusions: The results indicate two sources of error when patients are matched with phantoms: Anatomical error, which is inherent due to differences in organ size and location, and error attributed to differences in the total soft tissue attenuation. For small patients, differences in soft tissue attenuation are minimal and are exceeded by inherent anatomical differences. For large patients, difference in soft tissue attenuation can be large. In these cases, patient-phantom matching proves most effective as differences in soft tissue attenuation are mitigated. With increasing obesity rates, overweight patients will continue to make up a growing fraction of all patients undergoing medical imaging. Thus, having phantoms that better represent this population represents a considerable improvement over previous methods. In response to this study, additional phantoms representing heavier weight percentiles will be added to the UFHADM and UFHADF patient-dependent series.« less

Virtual surgical planning, flow simulation, and 3-dimensional electrospinning of patient-specific grafts to optimize Fontan hemodynamics.

PubMed

Siallagan, Dominik; Loke, Yue-Hin; Olivieri, Laura; Opfermann, Justin; Ong, Chin Siang; de Zélicourt, Diane; Petrou, Anastasios; Daners, Marianne Schmid; Kurtcuoglu, Vartan; Meboldt, Mirko; Nelson, Kevin; Vricella, Luca; Johnson, Jed; Hibino, Narutoshi; Krieger, Axel

2018-04-01

Despite advances in the Fontan procedure, there is an unmet clinical need for patient-specific graft designs that are optimized for variations in patient anatomy. The objective of this study is to design and produce patient-specific Fontan geometries, with the goal of improving hepatic flow distribution (HFD) and reducing power loss (P loss ), and manufacturing these designs by electrospinning. Cardiac magnetic resonance imaging data from patients who previously underwent a Fontan procedure (n = 2) was used to create 3-dimensional models of their native Fontan geometry using standard image segmentation and geometry reconstruction software. For each patient, alternative designs were explored in silico, including tube-shaped and bifurcated conduits, and their performance in terms of P loss and HFD probed by computational fluid dynamic (CFD) simulations. The best-performing options were then fabricated using electrospinning. CFD simulations showed that the bifurcated conduit improved HFD between the left and right pulmonary arteries, whereas both types of conduits reduced P loss . In vitro testing with a flow-loop chamber supported the CFD results. The proposed designs were then successfully electrospun into tissue-engineered vascular grafts. Our unique virtual cardiac surgery approach has the potential to improve the quality of surgery by manufacturing patient-specific designs before surgery, that are also optimized with balanced HFD and minimal P loss , based on refinement of commercially available options for image segmentation, computer-aided design, and flow simulations. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Computational fluid dynamics comparisons of wall shear stress in patient-specific coronary artery bifurcation using coronary angiography and optical coherence tomography

NASA Astrophysics Data System (ADS)

Poon, Eric; Thondapu, Vikas; Chin, Cheng; Scheerlinck, Cedric; Zahtila, Tony; Mamon, Chris; Nguyen, Wilson; Ooi, Andrew; Barlis, Peter

2016-11-01

Blood flow dynamics directly influence biology of the arterial wall, and are closely linked with the development of coronary artery disease. Computational fluid dynamics (CFD) solvers may be employed to analyze the hemodynamic environment in patient-specific reconstructions of coronary arteries. Although coronary X-ray angiography (CA) is the most common medical imaging modality for 3D arterial reconstruction, models reconstructed from CA assume a circular or elliptical cross-sectional area. This limitation can be overcome with a reconstruction technique fusing CA with intravascular optical coherence tomography (OCT). OCT scans the interior of an artery using near-infrared light, achieving a 10-micron resolution and providing unprecedented detail of vessel geometry. We compared 3D coronary artery bifurcation models generated using CA alone versus OCT-angiography fusion. The model reconstructed from CA alone is unable to identify the detailed geometrical variations of diseased arteries, and also under-estimates the cross-sectional vessel area compared to OCT-angiography fusion. CFD was performed in both models under pulsatile flow in order to identify and compare regions of low wall shear stress, a hemodynamic parameter directly linked with progression of atherosclerosis. Supported by ARC LP150100233 and VLSCI VR0210.

Development of an Experimental and Digital Cardiovascular Arterial Model for Transient Hemodynamic and Postural Change Studies: "A Preliminary Framework Analysis".

PubMed

Hewlin, Rodward L; Kizito, John P

2018-03-01

The ultimate goal of the present work is to aid in the development of tools to assist in the treatment of cardiovascular disease. Gaining an understanding of hemodynamic parameters for medical implants allow clinicians to have some patient-specific proposals for intervention planning. In the present work an experimental and digital computational fluid dynamics (CFD) arterial model consisting of a number of major arteries (aorta, carotid bifurcation, cranial, femoral, jejunal, and subclavian arteries) were fabricated to study: (1) the effects of local hemodynamics (flow parameters) on global hemodynamics (2) the effects of transition from bedrest to upright position (postural change) on hemodynamics, and (3) diffusion of dye (medical drug diffusion simulation) in the arterial system via experimental and numerical techniques. The experimental and digital arterial models used in the present study are the first 3-D systems reported in literature to incorporate the major arterial vessels that deliver blood from the heart to the cranial and femoral arteries. These models are also the first reported in literature to be used for flow parameter assessment via medical drug delivery and orthostatic postural change studies. The present work addresses the design of the experimental and digital arterial model in addition to the design of measuring tools used to measure hemodynamic parameters. The experimental and digital arterial model analyzed in the present study was developed from patient specific computed tomography angiography (CTA) scans and simplified geometric data. Segments such as the aorta (ascending and descending) and carotid bifurcation arteries of the experimental and digital arterial model was created from online available patient-specific CTA scan data provided by Charite' Clinical and Research Hospital. The cranial and coronary arteries were simplified arterial geometries developed from dimensional specification data used in previous work. For the patient specific geometries, a MATLAB code was written to upload the CTA scans of each artery, calculate the centroids, and produce surface splines at each discrete cross section along the lumen centerline to create the patient specific arterial geometries. The MATLAB code worked in conjunction with computer aided software (CAD) Solidworks to produce solid models of the patient specific geometries and united them with the simplified geometries to produce the full arterial model (CAD model). The CAD model was also used as a blueprint to fabricate the experimental model which was used for flow visualization via particle imaging velocimetry (PIV) and postural change studies. A custom pulse duplicator (pulsatile pump) was also designed and developed for the present work. The pulse duplicator is capable of producing patient-specific volumetric waveforms for inlet flow to the experimental arterial model. A simple fluid structure interaction (FSI) study was also conducted via optical techniques to establish the magnitude of vessel diameter change due to the pulsatile flow. A medical drug delivery (dye dispersion and tracing) case was simulated via a dye being dispersed into the pulsatile flow stream to measure the transit time of the dye front. Pressure waveforms for diseased cases (hypertension & stenotic cases) were also obtained from the experimental arterial model during postural changes from bedrest (0°) to upright position (90°). The postural changes were simulated via attaching the experimental model to a tile table the can transition from 0° to 90°. The PIV results obtained from the experimental model provided parametric data such as velocity and wall shear stress data. The medical drug delivery simulations (experimental and numerical) studies produce time dependent data which is useful for predicting flow trajectory and transit time of medical drug dispersion. In the case of postural change studies, pressure waveforms were obtained from the common carotid artery and the femoral sections to yield pressure difference data useful for orthostatic hypotension analysis. Flow parametric data such as vorticity (flow reversal), wall shear stress, normal stress, and medical drug transit data was also obtained from the digital arterial model CFD simulations. Although the present work is preliminary work, the experimental and digital models proves to be useful in providing flow parametric data of interest such as: (1) normal stress which is useful for predicting the magnitude of forces which could promote arterial rupture or dislodging of medical implants, (2) wall shear stress which is useful for analyzing the magnitude of drug transport at the arterial wall, (3) vorticity which is useful for predicting the magnitude of flow reversal, and (4) arterial compliance in the case of the experimental model which could be useful in the efforts of developing FSI numerical simulations that incorporates compliance which realistically models the flow in the arterial system.

Quantitative comparison of hemodynamics in simulated and 3D angiography models of cerebral aneurysms by use of computational fluid dynamics.

PubMed

Saho, Tatsunori; Onishi, Hideo

2015-07-01

In this study, we evaluated hemodynamics using simulated models and determined how cerebral aneurysms develop in simulated and patient-specific models based on medical images. Computational fluid dynamics (CFD) was analyzed by use of OpenFOAM software. Flow velocity, stream line, and wall shear stress (WSS) were evaluated in a simulated model aneurysm with known geometry and in a three-dimensional angiographic model. The ratio of WSS at the aneurysm compared with that at the basilar artery was 1:10 in simulated model aneurysms with a diameter of 10 mm and 1:18 in the angiographic model, indicating similar tendencies. Vortex flow occurred in both model aneurysms, and the WSS decreased in larger model aneurysms. The angiographic model provided accurate CFD information, and the tendencies of simulated and angiographic models were similar. These findings indicate that hemodynamic effects are involved in the development of aneurysms.

Flow Residence Time and Regions of Intraluminal Thrombus Deposition in Intracranial Aneurysms

PubMed Central

Boussel, L.; Ge, L.; Leach, J. R.; Martin, A. J.; Lawton, M. T.; McCulloch, C.; Saloner, D.

2010-01-01

Thrombus formation in intracranial aneurysms, while sometimes stabilizing lesion growth, can present additional risk of thrombo-embolism. The role of hemodynamics in the progression of aneurysmal disease can be elucidated by patient-specific computational modeling. In our previous work, patient-specific computational fluid dynamics (CFD) models were constructed from MRI data for three patients who had fusiform basilar aneurysms that were thrombus-free and then proceeded to develop intraluminal thrombus. In this study, we investigated the effect of increased flow residence time (RT) by modeling passive scalar advection in the same aneurysmal geometries. Non-Newtonian pulsatile flow simulations were carried out in base-line geometries and a new postprocessing technique, referred to as “virtual ink” and based on the passive scalar distribution maps, was used to visualize the flow and estimate the flow RT. The virtual ink technique clearly depicted regions of flow separation. The flow RT at different locations adjacent to aneurysmal walls was calculated as the time the virtual ink scalar remained above a threshold value. The RT values obtained in different areas were then correlated with the location of intra-aneurysmal thrombus observed at a follow-up MR study. For each patient, the wall shear stress (WSS) distribution was also obtained from CFD simulations and correlated with thrombus location. The correlation analysis determined a significant relationship between regions where CFD predicted either an increased RT or low WSS and the regions where thrombus deposition was observed to occur in vivo. A model including both low WSS and increased RT predicted thrombus-prone regions significantly better than the models with RT or WSS alone. PMID:20499185

Prospective estimation of organ dose in CT under tube current modulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tian, Xiaoyu, E-mail: xt3@duke.edu; Li, Xiang; Segars, W. Paul

Purpose: Computed tomography (CT) has been widely used worldwide as a tool for medical diagnosis and imaging. However, despite its significant clinical benefits, CT radiation dose at the population level has become a subject of public attention and concern. In this light, optimizing radiation dose has become a core responsibility for the CT community. As a fundamental step to manage and optimize dose, it may be beneficial to have accurate and prospective knowledge about the radiation dose for an individual patient. In this study, the authors developed a framework to prospectively estimate organ dose for chest and abdominopelvic CT examsmore » under tube current modulation (TCM). Methods: The organ dose is mainly dependent on two key factors: patient anatomy and irradiation field. A prediction process was developed to accurately model both factors. To model the anatomical diversity and complexity in the patient population, the authors used a previously developed library of computational phantoms with broad distributions of sizes, ages, and genders. A selected clinical patient, represented by a computational phantom in the study, was optimally matched with another computational phantom in the library to obtain a representation of the patient’s anatomy. To model the irradiation field, a previously validated Monte Carlo program was used to model CT scanner systems. The tube current profiles were modeled using a ray-tracing program as previously reported that theoretically emulated the variability of modulation profiles from major CT machine manufacturers Li et al., [Phys. Med. Biol. 59, 4525–4548 (2014)]. The prediction of organ dose was achieved using the following process: (1) CTDI{sub vol}-normalized-organ dose coefficients (h{sub organ}) for fixed tube current were first estimated as the prediction basis for the computational phantoms; (2) each computation phantom, regarded as a clinical patient, was optimally matched with one computational phantom in the library; (3) to account for the effect of the TCM scheme, a weighted organ-specific CTDI{sub vol} [denoted as (CTDI{sub vol}){sub organ,weighted}] was computed for each organ based on the TCM profile and the anatomy of the “matched” phantom; (4) the organ dose was predicted by multiplying the weighted organ-specific CTDI{sub vol} with the organ dose coefficients (h{sub organ}). To quantify the prediction accuracy, each predicted organ dose was compared with the corresponding organ dose simulated from the Monte Carlo program with the TCM profile explicitly modeled. Results: The predicted organ dose showed good agreements with the simulated organ dose across all organs and modulation profiles. The average percentage error in organ dose estimation was generally within 20% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. For an average CTDI{sub vol} of a CT exam of 10 mGy, the average error at full modulation strength (α = 1) across all organs was 0.91 mGy for chest exams, and 0.82 mGy for abdominopelvic exams. Conclusions: This study developed a quantitative model to predict organ dose for clinical chest and abdominopelvic scans. Such information may aid in the design of optimized CT protocols in relation to a targeted level of image quality.« less

SU-E-T-13: A Feasibility Study of the Use of Hybrid Computational Phantoms for Improved Historical Dose Reconstruction in the Study of Late Radiation Effects for Hodgkin's Lymphoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petroccia, H; O'Reilly, S; Bolch, W

Purpose: Radiation-induced cancer effects are well-documented following radiotherapy. Further investigation is needed to more accurately determine a dose-response relationship for late radiation effects. Recent dosimetry studies tend to use representative patients (Taylor 2009) or anthropomorphic phantoms (Wirth 2008) for estimating organ mean doses. In this study, we compare hybrid computational phantoms to patient-specific voxel phantoms to test the accuracy of University of Florida Hybrid Phantom Library (UFHP Library) for historical dose reconstructions. Methods: A cohort of 10 patients with CT images was used to reproduce the data that was collected historically for Hodgkin's lymphoma patients (i.e. caliper measurements and photographs).more » Four types of phantoms were generated to show a range of refinement from reference hybrid-computational phantom to patient-specific phantoms. Each patient is matched to a reference phantom from the UFHP Library based on height and weight. The reference phantom is refined in the anterior/posterior direction to create a ‘caliper-scaled phantom’. A photograph is simulated using a surface rendering from segmented CT images. Further refinement in the lateral direction is performed using ratios from a simulated-photograph to create a ‘photograph and caliper-scaled phantom’; breast size and position is visually adjusted. Patient-specific hybrid phantoms, with matched organ volumes, are generated and show the capabilities of the UF Hybrid Phantom Library. Reference, caliper-scaled, photograph and caliper-scaled, and patient-specific hybrid phantoms are compared with patient-specific voxel phantoms to determine the accuracy of the study. Results: Progression from reference phantom to patient specific hybrid shows good agreement with the patient specific voxel phantoms. Each stage of refinement shows an overall trend of improvement in dose accuracy within the study, which suggests that computational phantoms can show improved accuracy in historical dose estimates. Conclusion: Computational hybrid phantoms show promise for improved accuracy within retrospective studies when CTs and other x-ray images are not available.« less

Clinical value of whole body fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography in the detection of metastatic bladder cancer.

PubMed

Yang, Zhongyi; Pan, Lingling; Cheng, Jingyi; Hu, Silong; Xu, Junyan; Ye, Dingwei; Zhang, Yingjian

2012-07-01

To investigate the value of whole-body fluorine-18 2-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography for the detection of metastatic bladder cancer. From December 2006 to August 2010, 60 bladder cancer patients (median age 60.5 years old, range 32-96) underwent whole body positron emission tomography/computed tomography positron emission tomography/computed tomography. The diagnostic accuracy was assessed by performing both organ-based and patient-based analyses. Identified lesions were further studied by biopsy or clinically followed for at least 6 months. One hundred and thirty-four suspicious lesions were identified. Among them, 4 primary cancers (2 pancreatic cancers, 1 colonic and 1 nasopharyngeal cancer) were incidentally detected, and the patients could be treated on time. For the remaining 130 lesions, positron emission tomography/computed tomography detected 118 true positive lesions (sensitivity = 95.9%). On the patient-based analysis, the overall sensitivity and specificity resulted to be 87.1% and 89.7%, respectively. There was no difference of sensitivity and specificity in patients with or without adjuvant treatment in terms of detection of metastatic sites by positron emission tomography/computed tomography. Compared with conventional imaging modality, positron emission tomography/computed tomography correctly changed the management in 15 patients (25.0%). Positron emission tomography/computed tomography has excellent sensitivity and specificity in the detection of metastatic bladder cancer and it provides additional diagnostic information compared to standard imaging techniques. © 2012 The Japanese Urological Association.

Antecedent Characteristics of Online Cancer Information Seeking Among Rural Breast Cancer Patients: An Application of the Cognitive-Social Health Information Processing (C-SHIP) Model

PubMed Central

Shaw, Bret R.; DuBenske, Lori L.; Han, Jeong Yeob; Cofta-Woerpel, Ludmila; Bush, Nigel; Gustafson, David H.; McTavish, Fiona

2013-01-01

Little research has examined the antecedent characteristics of patients most likely to seek online cancer information. This study employs the Cognitive-Social Health Information Processing (C-SHIP) model as a framework to understand what psychosocial characteristics precede online cancer-related information seeking among rural breast cancer patients who often have fewer healthcare providers and limited local support services. Examining 144 patients who were provided free computer hardware, Internet access and training for how to use an Interactive Cancer Communication System, pre-test survey scores indicating patients’ psychosocial status were correlated with specific online cancer information seeking behaviors. Each of the factors specified by the C-SHIP model had significant relationships with online cancer information seeking behaviors with the strongest findings emerging for cancer-relevant encodings and self-construals, cancer-relevant beliefs and expectancies and cancer-relevant self-regulatory competencies and skills. Specifically, patients with more negative appraisals in these domains were more likely to seek out online cancer information. Additionally, antecedent variables associated with the C-SHIP model had more frequent relationships with experiential information as compared to didactic information. This study supports the applicability of the model to discern why people afflicted with cancer may seek online information to cope with their disease. PMID:18569368

Estimating radiation dose to organs of patients undergoing conventional and novel multidetector CT exams using Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Angel, Erin

Advances in Computed Tomography (CT) technology have led to an increase in the modality's diagnostic capabilities and therefore its utilization, which has in turn led to an increase in radiation exposure to the patient population. As a result, CT imaging currently constitutes approximately half of the collective exposure to ionizing radiation from medical procedures. In order to understand the radiation risk, it is necessary to estimate the radiation doses absorbed by patients undergoing CT imaging. The most widely accepted risk models are based on radiosensitive organ dose as opposed to whole body dose. In this research, radiosensitive organ dose was estimated using Monte Carlo based simulations incorporating detailed multidetector CT (MDCT) scanner models, specific scan protocols, and using patient models based on accurate patient anatomy and representing a range of patient sizes. Organ dose estimates were estimated for clinical MDCT exam protocols which pose a specific concern for radiosensitive organs or regions. These dose estimates include estimation of fetal dose for pregnant patients undergoing abdomen pelvis CT exams or undergoing exams to diagnose pulmonary embolism and venous thromboembolism. Breast and lung dose were estimated for patients undergoing coronary CTA imaging, conventional fixed tube current chest CT, and conventional tube current modulated (TCM) chest CT exams. The correlation of organ dose with patient size was quantified for pregnant patients undergoing abdomen/pelvis exams and for all breast and lung dose estimates presented. Novel dose reduction techniques were developed that incorporate organ location and are specifically designed to reduce close to radiosensitive organs during CT acquisition. A generalizable model was created for simulating conventional and novel attenuation-based TCM algorithms which can be used in simulations estimating organ dose for any patient model. The generalizable model is a significant contribution of this work as it lays the foundation for the future of simulating TCM using Monte Carlo methods. As a result of this research organ dose can be estimated for individual patients undergoing specific conventional MDCT exams. This research also brings understanding to conventional and novel close reduction techniques in CT and their effect on organ dose.

Virtual medicine: Utilization of the advanced cardiac imaging patient avatar for procedural planning and facilitation.

PubMed

Shinbane, Jerold S; Saxon, Leslie A

Advances in imaging technology have led to a paradigm shift from planning of cardiovascular procedures and surgeries requiring the actual patient in a "brick and mortar" hospital to utilization of the digitalized patient in the virtual hospital. Cardiovascular computed tomographic angiography (CCTA) and cardiovascular magnetic resonance (CMR) digitalized 3-D patient representation of individual patient anatomy and physiology serves as an avatar allowing for virtual delineation of the most optimal approaches to cardiovascular procedures and surgeries prior to actual hospitalization. Pre-hospitalization reconstruction and analysis of anatomy and pathophysiology previously only accessible during the actual procedure could potentially limit the intrinsic risks related to time in the operating room, cardiac procedural laboratory and overall hospital environment. Although applications are specific to areas of cardiovascular specialty focus, there are unifying themes related to the utilization of technologies. The virtual patient avatar computer can also be used for procedural planning, computational modeling of anatomy, simulation of predicted therapeutic result, printing of 3-D models, and augmentation of real time procedural performance. Examples of the above techniques are at various stages of development for application to the spectrum of cardiovascular disease processes, including percutaneous, surgical and hybrid minimally invasive interventions. A multidisciplinary approach within medicine and engineering is necessary for creation of robust algorithms for maximal utilization of the virtual patient avatar in the digital medical center. Utilization of the virtual advanced cardiac imaging patient avatar will play an important role in the virtual health care system. Although there has been a rapid proliferation of early data, advanced imaging applications require further assessment and validation of accuracy, reproducibility, standardization, safety, efficacy, quality, cost effectiveness, and overall value to medical care. Copyright © 2018 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Pediatric chest and abdominopelvic CT: organ dose estimation based on 42 patient models.

PubMed

Tian, Xiaoyu; Li, Xiang; Segars, W Paul; Paulson, Erik K; Frush, Donald P; Samei, Ehsan

2014-02-01

To estimate organ dose from pediatric chest and abdominopelvic computed tomography (CT) examinations and evaluate the dependency of organ dose coefficients on patient size and CT scanner models. The institutional review board approved this HIPAA-compliant study and did not require informed patient consent. A validated Monte Carlo program was used to perform simulations in 42 pediatric patient models (age range, 0-16 years; weight range, 2-80 kg; 24 boys, 18 girls). Multidetector CT scanners were modeled on those from two commercial manufacturers (LightSpeed VCT, GE Healthcare, Waukesha, Wis; SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). Organ doses were estimated for each patient model for routine chest and abdominopelvic examinations and were normalized by volume CT dose index (CTDI(vol)). The relationships between CTDI(vol)-normalized organ dose coefficients and average patient diameters were evaluated across scanner models. For organs within the image coverage, CTDI(vol)-normalized organ dose coefficients largely showed a strong exponential relationship with the average patient diameter (R(2) > 0.9). The average percentage differences between the two scanner models were generally within 10%. For distributed organs and organs on the periphery of or outside the image coverage, the differences were generally larger (average, 3%-32%) mainly because of the effect of overranging. It is feasible to estimate patient-specific organ dose for a given examination with the knowledge of patient size and the CTDI(vol). These CTDI(vol)-normalized organ dose coefficients enable one to readily estimate patient-specific organ dose for pediatric patients in clinical settings. This dose information, and, as appropriate, attendant risk estimations, can provide more substantive information for the individual patient for both clinical and research applications and can yield more expansive information on dose profiles across patient populations within a practice. © RSNA, 2013.

Three-dimensional planning and use of patient-specific guides improve glenoid component position: an in vitro study.

PubMed

Walch, Gilles; Vezeridis, Peter S; Boileau, Pascal; Deransart, Pierric; Chaoui, Jean

2015-02-01

Glenoid component positioning is a key factor for success in total shoulder arthroplasty. Three-dimensional (3D) measurements of glenoid retroversion, inclination, and humeral head subluxation are helpful tools for preoperative planning. The purpose of this study was to assess the reliability and precision of a novel surgical method for placing the glenoid component with use of patient-specific templates created by preoperative surgical planning and 3D modeling. A preoperative computed tomography examination of cadaveric scapulae (N = 18) was performed. The glenoid implants were virtually placed, and patient-specific guides were created to direct the guide pin into the desired orientation and position in the glenoid. The 3D orientation and position of the guide pin were evaluated by performing a postoperative computed tomography scan for each scapula. The differences between the preoperative planning and the achieved result were analyzed. The mean error in 3D orientation of the guide pin was 2.39°, the mean entry point position error was 1.05 mm, and the mean inclination angle error was 1.42°. The average error in the version angle was 1.64°. There were no technical difficulties or complications related to use of patient-specific guides for guide pin placement. Quantitative analysis of guide pin positioning demonstrated a good correlation between preoperative planning and the achieved position of the guide pin. This study demonstrates the reliability and precision of preoperative planning software and patient-specific guides for glenoid component placement in total shoulder arthroplasty. Copyright © 2015. Published by Elsevier Inc.

Automated segmentation and reconstruction of patient-specific cardiac anatomy and pathology from in vivo MRI*

NASA Astrophysics Data System (ADS)

Ringenberg, Jordan; Deo, Makarand; Devabhaktuni, Vijay; Filgueiras-Rama, David; Pizarro, Gonzalo; Ibañez, Borja; Berenfeld, Omer; Boyers, Pamela; Gold, Jeffrey

2012-12-01

This paper presents an automated method to segment left ventricle (LV) tissues from functional and delayed-enhancement (DE) cardiac magnetic resonance imaging (MRI) scans using a sequential multi-step approach. First, a region of interest (ROI) is computed to create a subvolume around the LV using morphological operations and image arithmetic. From the subvolume, the myocardial contours are automatically delineated using difference of Gaussians (DoG) filters and GSV snakes. These contours are used as a mask to identify pathological tissues, such as fibrosis or scar, within the DE-MRI. The presented automated technique is able to accurately delineate the myocardium and identify the pathological tissue in patient sets. The results were validated by two expert cardiologists, and in one set the automated results are quantitatively and qualitatively compared with expert manual delineation. Furthermore, the method is patient-specific, performed on an entire patient MRI series. Thus, in addition to providing a quick analysis of individual MRI scans, the fully automated segmentation method is used for effectively tagging regions in order to reconstruct computerized patient-specific 3D cardiac models. These models can then be used in electrophysiological studies and surgical strategy planning.

Bimanual Force Coordination in Parkinson’s Disease Patients with Bilateral Subthalamic Deep Brain Stimulation

PubMed Central

Gorniak, Stacey L.; McIntyre, Cameron C.; Alberts, Jay L.

2013-01-01

Objective Studies of bimanual actions similar to activities of daily living (ADLs) are currently lacking in evaluating fine motor control in Parkinson’s disease patients implanted with bilateral subthalamic deep brain stimulators. We investigated basic time and force characteristics of a bimanual task that resembles performance of ADLs in a group of bilateral subthalamic deep brain stimulation (DBS) patients. Methods Patients were evaluated in three different DBS parameter conditions off stimulation, on clinically derived stimulation parameters, and on settings derived from a patient-specific computational model. Model-based parameters were computed as a means to minimize spread of current to non-motor regions of the subthalamic nucleus via Cicerone Deep Brain Stimulation software. Patients were evaluated off parkinsonian medications in each stimulation condition. Results The data indicate that DBS parameter state does not affect most aspects of fine motor control in ADL-like tasks; however, features such as increased grip force and grip symmetry varied with the stimulation state. In the absence of DBS parameters, patients exhibited significant grip force asymmetry. Overall UPDRS-III and UPDRS-III scores associated with hand function were lower while patients were experiencing clinically-derived or model-based parameters, as compared to the off-stimulation condition. Conclusion While bilateral subthalamic DBS has been shown to alleviate gross motor dysfunction, our results indicate that DBS may not provide the same magnitude of benefit to fine motor coordination. PMID:24244388

Hemodynamic simulations in coronary aneurysms of children with Kawasaki disease

NASA Astrophysics Data System (ADS)

Sengupta, Dibyendu; Burns, Jane; Marsden, Alison

2009-11-01

Kawasaki disease (KD) is a serious pediatric illness affecting the cardiovascular system. One of the most serious complications of KD, occurring in about 25% of untreated cases, is the formation of large aneurysms in the coronary arteries, which put patients at risk for myocardial infarction. In this project we performed patient specific computational simulations of blood flow in aneurysmal left and right coronary arteries of a KD patient to gain an understanding about their hemodynamics. Models were constructed from CT data using custom software. Typical pulsatile flow waveforms were applied at the model inlets, while resistance and RCR lumped models were applied and compared at the outlets. Simulated pressure waveforms compared well with typical physiologic data. High wall shear stress values are found in the narrow region at the base of the aneurysm and low shear values occur in regions of recirculation. A Lagrangian approach has been adopted to perform particle tracking and compute particle residence time in the recirculation. Our long-term goal will be to develop links between hemodynamics and the risk for thrombus formation in order to assist in clinical decision-making.

Model-based position correlation between breast images

NASA Astrophysics Data System (ADS)

Georgii, J.; Zöhrer, F.; Hahn, H. K.

2013-02-01

Nowadays, breast diagnosis is based on images of different projections and modalities, such that sensitivity and specificity of the diagnosis can be improved. However, this emburdens radiologists to find corresponding locations in these data sets, which is a time consuming task, especially since the resolution of the images increases and thus more and more data have to be considered in the diagnosis. Therefore, we aim at support radiologist by automatically synchronizing cursor positions between different views of the breast. Specifically, we present an automatic approach to compute the spatial correlation between MLO and CC mammogram or tomosynthesis projections of the breast. It is based on pre-computed finite element simulations of generic breast models, which are adapted to the patient-specific breast using a contour mapping approach. Our approach is designed to be fully automatic and efficient, such that it can be implemented directly into existing multimodal breast workstations. Additionally, it is extendable to support other breast modalities in future, too.

Wall shear stress in portal vein of cirrhotic patients with portal hypertension.

PubMed

Wei, Wei; Pu, Yan-Song; Wang, Xin-Kai; Jiang, An; Zhou, Rui; Li, Yu; Zhang, Qiu-Juan; Wei, Ya-Juan; Chen, Bin; Li, Zong-Fang

2017-05-14

To investigate wall shear stress (WSS) magnitude and distribution in cirrhotic patients with portal hypertension using computational fluid dynamics. Idealized portal vein (PV) system models were reconstructed with different angles of the PV-splenic vein (SV) and superior mesenteric vein (SMV)-SV. Patient-specific models were created according to enhanced computed tomography images. WSS was simulated by using a finite-element analyzer, regarding the blood as a Newtonian fluid and the vessel as a rigid wall. Analysis was carried out to compare the WSS in the portal hypertension group with that in healthy controls. For the idealized models, WSS in the portal hypertension group (0-10 dyn/cm 2 ) was significantly lower than that in the healthy controls (10-20 dyn/cm 2 ), and low WSS area (0-1 dyn/cm 2 ) only occurred in the left wall of the PV in the portal hypertension group. Different angles of PV-SV and SMV-SV had different effects on the magnitude and distribution of WSS, and low WSS area often occurred in smaller PV-SV angle and larger SMV-SV angle. In the patient-specific models, WSS in the cirrhotic patients with portal hypertension (10.13 ± 1.34 dyn/cm 2 ) was also significantly lower than that in the healthy controls ( P < 0.05). Low WSS area often occurred in the junction area of SV and SMV into the PV, in the area of the division of PV into left and right PV, and in the outer wall of the curving SV in the control group. In the cirrhotic patients with portal hypertension, the low WSS area extended to wider levels and the magnitude of WSS reached lower levels, thereby being more prone to disturbed flow occurrence. Cirrhotic patients with portal hypertension show dramatic hemodynamic changes with lower WSS and greater potential for disturbed flow, representing a possible causative factor of PV thrombosis.

Wall shear stress in portal vein of cirrhotic patients with portal hypertension

PubMed Central

Wei, Wei; Pu, Yan-Song; Wang, Xin-Kai; Jiang, An; Zhou, Rui; Li, Yu; Zhang, Qiu-Juan; Wei, Ya-Juan; Chen, Bin; Li, Zong-Fang

2017-01-01

AIM To investigate wall shear stress (WSS) magnitude and distribution in cirrhotic patients with portal hypertension using computational fluid dynamics. METHODS Idealized portal vein (PV) system models were reconstructed with different angles of the PV-splenic vein (SV) and superior mesenteric vein (SMV)-SV. Patient-specific models were created according to enhanced computed tomography images. WSS was simulated by using a finite-element analyzer, regarding the blood as a Newtonian fluid and the vessel as a rigid wall. Analysis was carried out to compare the WSS in the portal hypertension group with that in healthy controls. RESULTS For the idealized models, WSS in the portal hypertension group (0-10 dyn/cm2) was significantly lower than that in the healthy controls (10-20 dyn/cm2), and low WSS area (0-1 dyn/cm2) only occurred in the left wall of the PV in the portal hypertension group. Different angles of PV-SV and SMV-SV had different effects on the magnitude and distribution of WSS, and low WSS area often occurred in smaller PV-SV angle and larger SMV-SV angle. In the patient-specific models, WSS in the cirrhotic patients with portal hypertension (10.13 ± 1.34 dyn/cm2) was also significantly lower than that in the healthy controls (P < 0.05). Low WSS area often occurred in the junction area of SV and SMV into the PV, in the area of the division of PV into left and right PV, and in the outer wall of the curving SV in the control group. In the cirrhotic patients with portal hypertension, the low WSS area extended to wider levels and the magnitude of WSS reached lower levels, thereby being more prone to disturbed flow occurrence. CONCLUSION Cirrhotic patients with portal hypertension show dramatic hemodynamic changes with lower WSS and greater potential for disturbed flow, representing a possible causative factor of PV thrombosis. PMID:28566887

Computational fluid dynamics modelling in cardiovascular medicine.

PubMed

Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

2016-01-01

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

3D printing of the aortic annulus based on cardiovascular computed tomography: Preliminary experience in pre-procedural planning for aortic valve sizing.

PubMed

Faletti, Riccardo; Gatti, Marco; Cosentino, Aurelio; Bergamasco, Laura; Cura Stura, Erik; Garabello, Domenica; Pennisi, Giovanni; Salizzoni, Stefano; Veglia, Simona; Ottavio, Davini; Rinaldi, Mauro; Fonio, Paolo

2018-05-26

to determine reliability and reproducibility of measurements of aortic annulus in 3D models printed from cardiovascular computed tomography (CCT) images. Retrospective study on the records of 20 patients who underwent aortic valve replacement (AVR) with pre-surgery annulus assessment by CCT and intra-operative sizing by Hegar dilators (IOS). 3D models were fabricated by fused deposition modelling of thermoplastic polyurethane filaments. For each patient, two 3D models were independently segmented, modelled and printed by two blinded "manufacturers": a radiologist and a radiology technician. Two blinded cardiac surgeons performed the annulus diameter measurements by Hegar dilators on the two sets of models. Matched data from different measurements were analyzed with Wilcoxon test, Bland-Altmann plot and within-subject ANOVA. No significant differences were found among the measurements made by each cardiac surgeon on the same 3D model (p = 0.48) or on the 3D models printed by different manufacturers (p = 0.25); also, no intraobserver variability (p = 0.46). The annulus diameter measured on 3D models showed good agreement with the reference CCT measurement (p = 0.68) and IOH sizing (p = 0.11). Time and cost per model were: model creation ∼10-15 min; printing time ∼60 min; post-processing ∼5min; material cost ∼1€.
 CONCLUSION: 3D printing of aortic annulus can offer reliable, not expensive patient-specific information to be used in the pre-operative planning of AVR or transcatheter aortic valve implantation (TAVI). Copyright © 2018 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Three-dimensional visualization of the craniofacial patient: volume segmentation, data integration and animation.

PubMed

Enciso, R; Memon, A; Mah, J

2003-01-01

The research goal at the Craniofacial Virtual Reality Laboratory of the School of Dentistry in conjunction with the Integrated Media Systems Center, School of Engineering, University of Southern California, is to develop computer methods to accurately visualize patients in three dimensions using advanced imaging and data acquisition devices such as cone-beam computerized tomography (CT) and mandibular motion capture. Data from these devices were integrated for three-dimensional (3D) patient-specific visualization, modeling and animation. Generic methods are in development that can be used with common CT image format (DICOM), mesh format (STL) and motion data (3D position over time). This paper presents preliminary descriptive studies on: 1) segmentation of the lower and upper jaws with two types of CT data--(a) traditional whole head CT data and (b) the new dental Newtom CT; 2) manual integration of accurate 3D tooth crowns with the segmented lower jaw 3D model; 3) realistic patient-specific 3D animation of the lower jaw.

Working Memory Contributions to Reinforcement Learning Impairments in Schizophrenia

PubMed Central

Brown, Jaime K.; Gold, James M.; Waltz, James A.; Frank, Michael J.

2014-01-01

Previous research has shown that patients with schizophrenia are impaired in reinforcement learning tasks. However, behavioral learning curves in such tasks originate from the interaction of multiple neural processes, including the basal ganglia- and dopamine-dependent reinforcement learning (RL) system, but also prefrontal cortex-dependent cognitive strategies involving working memory (WM). Thus, it is unclear which specific system induces impairments in schizophrenia. We recently developed a task and computational model allowing us to separately assess the roles of RL (slow, cumulative learning) mechanisms versus WM (fast but capacity-limited) mechanisms in healthy adult human subjects. Here, we used this task to assess patients' specific sources of impairments in learning. In 15 separate blocks, subjects learned to pick one of three actions for stimuli. The number of stimuli to learn in each block varied from two to six, allowing us to separate influences of capacity-limited WM from the incremental RL system. As expected, both patients (n = 49) and healthy controls (n = 36) showed effects of set size and delay between stimulus repetitions, confirming the presence of working memory effects. Patients performed significantly worse than controls overall, but computational model fits and behavioral analyses indicate that these deficits could be entirely accounted for by changes in WM parameters (capacity and reliability), whereas RL processes were spared. These results suggest that the working memory system contributes strongly to learning impairments in schizophrenia. PMID:25297101

Modeling mechanical cardiopulmonary interactions for virtual environments.

PubMed

Kaye, J M

1997-01-01

We have developed a computer system for modeling mechanical cardiopulmonary behavior in an interactive, 3D virtual environment. The system consists of a compact, scalar description of cardiopulmonary mechanics, with an emphasis on respiratory mechanics, that drives deformable 3D anatomy to simulate mechanical behaviors of and interactions between physiological systems. Such an environment can be used to facilitate exploration of cardiopulmonary physiology, particularly in situations that are difficult to reproduce clinically. We integrate 3D deformable body dynamics with new, formal models of (scalar) cardiorespiratory physiology, associating the scalar physiological variables and parameters with corresponding 3D anatomy. Our approach is amenable to modeling patient-specific circumstances in two ways. First, using CT scan data, we apply semi-automatic methods for extracting and reconstructing the anatomy to use in our simulations. Second, our scalar models are defined in terms of clinically-measurable, patient-specific parameters. This paper describes our approach and presents a sample of results showing normal breathing and acute effects of pneumothoraces.

Simulations of Congenital Septal Defect Closure and Reactivity Testing in Patient-Specific Models of the Pediatric Pulmonary Vasculature: A 3D Numerical Study With Fluid-Structure Interaction

PubMed Central

Hunter, Kendall S.; Lanning, Craig J.; Chen, Shiuh-Yung J.; Zhang, Yanhang; Garg, Ruchira; Ivy, D. Dunbar; Shandas, Robin

2014-01-01

Clinical imaging methods are highly effective in the diagnosis of vascular pathologies, but they do not currently provide enough detail to shed light on the cause or progression of such diseases, and would be hard pressed to foresee the outcome of surgical interventions. Greater detail of and prediction capabilities for vascular hemodynamics and arterial mechanics are obtained here through the coupling of clinical imaging methods with computational techniques. Three-dimensional, patient-specific geometric reconstructions of the pediatric proximal pulmonary vasculature were obtained from x-ray angiogram images and meshed for use with commercial computational software. Two such models from hypertensive patients, one with multiple septal defects, the other who underwent vascular reactivity testing, were each completed with two sets of suitable fluid and structural initial and boundary conditions and used to obtain detailed transient simulations of artery wall motion and hemodynamics in both clinically measured and predicted configurations. The simulation of septal defect closure, in which input flow and proximal vascular stiffness were decreased, exhibited substantial decreases in proximal velocity, wall shear stress (WSS), and pressure in the post-op state. The simulation of vascular reactivity, in which distal vascular resistance and proximal vascular stiffness were decreased, displayed negligible changes in velocity and WSS but a significant drop in proximal pressure in the reactive state. This new patient-specific technique provides much greater detail regarding the function of the pulmonary circuit than can be obtained with current medical imaging methods alone, and holds promise for enabling surgical planning. PMID:16813447

Proof of Concept Study for the Design, Manufacturing, and Testing of a Patient-Specific Shape Memory Device for Treatment of Unicoronal Craniosynostosis.

PubMed

Borghi, Alessandro; Rodgers, Will; Schievano, Silvia; Ponniah, Allan; Jeelani, Owase; Dunaway, David

2018-01-01

Treatment of unicoronal craniosynostosis is a surgically challenging problem, due to the involvement of coronal suture and cranial base, with complex asymmetries of the calvarium and orbit. Several techniques for correction have been described, including surgical bony remodeling, early strip craniotomy with orthotic helmet remodeling and distraction. Current distraction devices provide unidirectional forces and have had very limited success. Nitinol is a shape memory alloy that can be programmed to the shape of a patient-specific anatomy by means of thermal treatment.In this work, a methodology to produce a nitinol patient-specific distractor is presented: computer tomography images of a 16-month-old patient with unicoronal craniosynostosis were processed to create a 3-dimensional model of his skull and define the ideal shape postsurgery. A mesh was produced from a nitinol sheet, formed to the ideal skull shape and heat treated to be malleable at room temperature. The mesh was afterward deformed to be attached to a rapid prototyped plastic skull, replica of the patient initial anatomy. The mesh/skull construct was placed in hot water to activate the mesh shape memory property: the deformed plastic skull was computed tomography scanned for comparison of its shape with the initial anatomy and with the desired shape, showing that the nitinol mesh had been able to distract the plastic skull to a shape close to the desired one.The shape-memory properties of nitinol allow for the design and production of patient-specific devices able to deliver complex, preprogrammable shape changes.

Computational Fluid Dynamics modeling of contrast transport in basilar aneurysms following flow-altering surgeries.

PubMed

Vali, Alireza; Abla, Adib A; Lawton, Michael T; Saloner, David; Rayz, Vitaliy L

2017-01-04

In vivo measurement of blood velocity fields and flow descriptors remains challenging due to image artifacts and limited resolution of current imaging methods; however, in vivo imaging data can be used to inform and validate patient-specific computational fluid dynamics (CFD) models. Image-based CFD can be particularly useful for planning surgical interventions in complicated cases such as fusiform aneurysms of the basilar artery, where it is crucial to alter pathological hemodynamics while preserving flow to the distal vasculature. In this study, patient-specific CFD modeling was conducted for two basilar aneurysm patients considered for surgical treatment. In addition to velocity fields, transport of contrast agent was simulated for the preoperative and postoperative conditions using two approaches. The transport of a virtual contrast passively following the flow streamlines was simulated to predict post-surgical flow regions prone to thrombus deposition. In addition, the transport of a mixture of blood with an iodine-based contrast agent was modeled to compare and verify the CFD results with X-ray angiograms. The CFD-predicted patterns of contrast flow were qualitatively compared to in vivo X-ray angiograms acquired before and after the intervention. The results suggest that the mixture modeling approach, accounting for the flow rates and properties of the contrast injection, is in better agreement with the X-ray angiography data. The virtual contrast modeling assessed the residence time based on flow patterns unaffected by the injection procedure, which makes the virtual contrast modeling approach better suited for prediction of thrombus deposition, which is not limited to the peri-procedural state. Copyright © 2016 Elsevier Ltd. All rights reserved.

Finite Element Analysis of Patient-Specific Mitral Valve with Mitral Regurgitation.

PubMed

Pham, Thuy; Kong, Fanwei; Martin, Caitlin; Wang, Qian; Primiano, Charles; McKay, Raymond; Elefteriades, John; Sun, Wei

2017-03-01

Functional mitral regurgitation (FMR) is a significant complication of left ventricular dysfunction and strongly associated with a poor prognosis. In this study, we developed a patient-specific finite element (FE) model of the mitral apparatus in a FMR patient which included: both leaflets with thickness, annulus, chordae tendineae, and chordae insertions on the leaflets and origins on the papillary muscles. The FE model incorporated human age- and gender-matched anisotropic hyperelastic material properties, and MV closure at systole was simulated. The model was validated by comparing the FE results from valve closure simulation with the in vivo geometry of the MV at systole. It was found that the FE model could not replicate the in vivo MV geometry without the application of tethering pre-tension force in the chordae at diastole. Upon applying the pre-tension force and performing model optimization by adjusting the chordal length, position, and leaflet length, a good agreement between the FE model and the in vivo model was established. Not only were the chordal forces high at both diastole and systole, but the tethering force on the anterior papillary muscle was higher than that of the posterior papillary muscle, which resulted in an asymmetrical gap with a larger orifice area at the anterolateral commissure resulting in MR. The analyses further show that high peak stress and strain were found at the chordal insertions where large chordal tethering forces were found. This study shows that the pre-tension tethering force plays an important role in accurately simulating the MV dynamics in this FMR patient, particularly in quantifying the degree of leaflet coaptation and stress distribution. Due to the complexity of the disease, the patient-specific computational modeling procedure of FMR patients presented should be further evaluated using a large patient cohort. However, this study provides useful insights into the MV biomechanics of a FMR patient, and could serve as a tool to assist in pre-operative planning for MV repair or replacement surgical or interventional procedures.

SU-E-I-88: Realistic Pathological Simulations of the NCAT and Zubal Anthropomorphic Models, Based on Clinical PET/CT Data.

PubMed

Papadimitroulas, P; Loudos, G; Le Maitre, A; Efthimiou, N; Visvikis, D; Nikiforidis, G; Kagadis, G C

2012-06-01

In the present study a patient-specific dataset of realistic PET simulations was created, taking into account the variability of clinical oncology data. Tumor variability was tested in the simulated results. A comparison of the produced simulated data was performed to clinical PET/CT data, for the validation and the evaluation of the procedure. Clinical PET/CT data of oncology patients were used as the basis of the simulated variability inserting patient-specific characteristics in the NCAT and the Zubal anthropomorphic phantoms. GATE Monte Carlo toolkit was used for simulating a commercial PET scanner. The standard computational anthropomorphic phantoms were adapted to the CT data (organ shapes), using a fitting algorithm. The activity map was derived from PET images. Patient tumors were segmented and inserted in the phantom, using different activity distributions. The produced simulated data were reconstructed using the STIR opensource software and compared to the original clinical ones. The accuracy of the procedure was tested in four different oncology cases. Each pathological situation was illustrated simulating a) a healthy body, b) insertion of the clinical tumor with homogenous activity, and c) insertion of the clinical tumor with variable activity (voxel-by-voxel) based on the clinical PET data. The accuracy of the presented dataset was compared to the original PET/CT data. Partial Volume Correction (PVC) was also applied in the simulated data. In this study patient-specific characteristics were used in computational anthropomorphic models for simulating realistic pathological patients. Voxel-by-voxel activity distribution with PVC within the tumor gives the most accurate results. Radiotherapy applications can utilize the benefits of the accurate realistic imaging simulations, using the anatomicaland biological information of each patient. Further work will incorporate the development of analytical anthropomorphic models with motion and cardiac correction, combined with pathological patients to achieve high accuracy in tumor imaging. This research was supported by the Joint Research and Technology Program between Greece and France; 2009-2011 (protocol ID: 09FR103). © 2012 American Association of Physicists in Medicine.

A self-taught artificial agent for multi-physics computational model personalization.

PubMed

Neumann, Dominik; Mansi, Tommaso; Itu, Lucian; Georgescu, Bogdan; Kayvanpour, Elham; Sedaghat-Hamedani, Farbod; Amr, Ali; Haas, Jan; Katus, Hugo; Meder, Benjamin; Steidl, Stefan; Hornegger, Joachim; Comaniciu, Dorin

2016-12-01

Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious, time-consuming, model- and data-specific process. We propose to use artificial intelligence concepts to learn this task, inspired by how human experts manually perform it. The problem is reformulated in terms of reinforcement learning. In an off-line phase, Vito, our self-taught artificial agent, learns a representative decision process model through exploration of the computational model: it learns how the model behaves under change of parameters. The agent then automatically learns an optimal strategy for on-line personalization. The algorithm is model-independent; applying it to a new model requires only adjusting few hyper-parameters of the agent and defining the observations to match. The full knowledge of the model itself is not required. Vito was tested in a synthetic scenario, showing that it could learn how to optimize cost functions generically. Then Vito was applied to the inverse problem of cardiac electrophysiology and the personalization of a whole-body circulation model. The obtained results suggested that Vito could achieve equivalent, if not better goodness of fit than standard methods, while being more robust (up to 11% higher success rates) and with faster (up to seven times) convergence rate. Our artificial intelligence approach could thus make personalization algorithms generalizable and self-adaptable to any patient and any model. Copyright © 2016. Published by Elsevier B.V.

Dental application of novel finite element analysis software for three-dimensional finite element modeling of a dentulous mandible from its computed tomography images.

PubMed

Nakamura, Keiko; Tajima, Kiyoshi; Chen, Ker-Kong; Nagamatsu, Yuki; Kakigawa, Hiroshi; Masumi, Shin-ich

2013-12-01

This study focused on the application of novel finite-element analysis software for constructing a finite-element model from the computed tomography data of a human dentulous mandible. The finite-element model is necessary for evaluating the mechanical response of the alveolar part of the mandible, resulting from occlusal force applied to the teeth during biting. Commercially available patient-specific general computed tomography-based finite-element analysis software was solely applied to the finite-element analysis for the extraction of computed tomography data. The mandibular bone with teeth was extracted from the original images. Both the enamel and the dentin were extracted after image processing, and the periodontal ligament was created from the segmented dentin. The constructed finite-element model was reasonably accurate using a total of 234,644 nodes and 1,268,784 tetrahedral and 40,665 shell elements. The elastic moduli of the heterogeneous mandibular bone were determined from the bone density data of the computed tomography images. The results suggested that the software applied in this study is both useful and powerful for creating a more accurate three-dimensional finite-element model of a dentulous mandible from the computed tomography data without the need for any other software.

Negative symptoms in schizophrenia result from a failure to represent the expected value of rewards: Behavioral and computational modeling evidence

PubMed Central

Gold, James M.; Waltz, James A.; Matveeva, Tatyana M.; Kasanova, Zuzana; Strauss, Gregory P.; Herbener, Ellen S.; Collins, Anne G.E.; Frank, Michael J.

2015-01-01

Context Negative symptoms are a core feature of schizophrenia, but their pathophysiology remains unclear. Objective Negative symptoms are defined by the absence of normal function. However, there must be a productive mechanism that leads to this absence. Here, we test a reinforcement learning account suggesting that negative symptoms result from a failure to represent the expected value of rewards coupled with preserved loss avoidance learning. Design Subjects performed a probabilistic reinforcement learning paradigm involving stimulus pairs in which choices resulted in either reward or avoidance of loss. Following training, subjects indicated their valuation of the stimuli in a transfer task. Computational modeling was used to distinguish between alternative accounts of the data. Setting A tertiary care research outpatient clinic. Patients A total of 47 clinically stable patients with a diagnosis of schizophrenia or schizoaffective disorder and 28 healthy volunteers participated. Patients were divided into high and low negative symptom groups. Main Outcome measures 1) The number of choices leading to reward or loss avoidance and 2) performance in the transfer phase. Quantitative fits from three different models were examined. Results High negative symptom patients demonstrated impaired learning from rewards but intact loss avoidance learning, and failed to distinguish rewarding stimuli from loss-avoiding stimuli in the transfer phase. Model fits revealed that high negative symptom patients were better characterized by an “actor-critic” model, learning stimulus-response associations, whereas controls and low negative symptom patients incorporated expected value of their actions (“Q-learning”) into the selection process. Conclusions Negative symptoms are associated with a specific reinforcement learning abnormality: High negative symptoms patients do not represent the expected value of rewards when making decisions but learn to avoid punishments through the use of prediction errors. This computational framework offers the potential to understand negative symptoms at a mechanistic level. PMID:22310503

On the Relative Relevance of Subject-Specific Geometries and Degeneration-Specific Mechanical Properties for the Study of Cell Death in Human Intervertebral Disk Models

PubMed Central

Malandrino, Andrea; Pozo, José M.; Castro-Mateos, Isaac; Frangi, Alejandro F.; van Rijsbergen, Marc M.; Ito, Keita; Wilke, Hans-Joachim; Dao, Tien Tuan; Ho Ba Tho, Marie-Christine; Noailly, Jérôme

2015-01-01

Capturing patient- or condition-specific intervertebral disk (IVD) properties in finite element models is outmost important in order to explore how biomechanical and biophysical processes may interact in spine diseases. However, disk degenerative changes are often modeled through equations similar to those employed for healthy organs, which might not be valid. As for the simulated effects of degenerative changes, they likely depend on specific disk geometries. Accordingly, we explored the ability of continuum tissue models to simulate disk degenerative changes. We further used the results in order to assess the interplay between these simulated changes and particular IVD morphologies, in relation to disk cell nutrition, a potentially important factor in disk tissue regulation. A protocol to derive patient-specific computational models from clinical images was applied to different spine specimens. In vitro, IVD creep tests were used to optimize poro-hyperelastic input material parameters in these models, in function of the IVD degeneration grade. The use of condition-specific tissue model parameters in the specimen-specific geometrical models was validated against independent kinematic measurements in vitro. Then, models were coupled to a transport-cell viability model in order to assess the respective effects of tissue degeneration and disk geometry on cell viability. While classic disk poro-mechanical models failed in representing known degenerative changes, additional simulation of tissue damage allowed model validation and gave degeneration-dependent material properties related to osmotic pressure and water loss, and to increased fibrosis. Surprisingly, nutrition-induced cell death was independent of the grade-dependent material properties, but was favored by increased diffusion distances in large IVDs. Our results suggest that in situ geometrical screening of IVD morphology might help to anticipate particular mechanisms of disk degeneration. PMID:25717471

Finite element analysis of TAVI: Impact of native aortic root computational modeling strategies on simulation outcomes.

PubMed

Finotello, Alice; Morganti, Simone; Auricchio, Ferdinando

2017-09-01

In the last few years, several studies, each with different aim and modeling detail, have been proposed to investigate transcatheter aortic valve implantation (TAVI) with finite elements. The present work focuses on the patient-specific finite element modeling of the aortic valve complex. In particular, we aim at investigating how different modeling strategies in terms of material models/properties and discretization procedures can impact analysis results. Four different choices both for the mesh size (from  20 k elements to  200 k elements) and for the material model (from rigid to hyperelastic anisotropic) are considered. Different approaches for modeling calcifications are also taken into account. Post-operative CT data of the real implant are used as reference solution with the aim of outlining a trade-off between computational model complexity and reliability of the results. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Computational Modeling and Real-Time Control of Patient-Specific Laser Treatment of Cancer

PubMed Central

Fuentes, D.; Oden, J. T.; Diller, K. R.; Hazle, J. D.; Elliott, A.; Shetty, A.; Stafford, R. J.

2014-01-01

An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging (MRTI). The system is built on what can be referred to as cyberinfrastructure - a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in-vivo, canine prostate. Over the course of an 18 minute laser induced thermal therapy (LITT) performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5°C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post operative histology of the canine prostate reveal that the damage region was within the targeted 1.2cm diameter treatment objective. PMID:19148754

Computational modeling and real-time control of patient-specific laser treatment of cancer.

PubMed

Fuentes, D; Oden, J T; Diller, K R; Hazle, J D; Elliott, A; Shetty, A; Stafford, R J

2009-04-01

An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.

Computed tomography landmark-based semi-automated mesh morphing and mapping techniques: generation of patient specific models of the human pelvis without segmentation.

PubMed

Salo, Zoryana; Beek, Maarten; Wright, David; Whyne, Cari Marisa

2015-04-13

Current methods for the development of pelvic finite element (FE) models generally are based upon specimen specific computed tomography (CT) data. This approach has traditionally required segmentation of CT data sets, which is time consuming and necessitates high levels of user intervention due to the complex pelvic anatomy. The purpose of this research was to develop and assess CT landmark-based semi-automated mesh morphing and mapping techniques to aid the generation and mechanical analysis of specimen-specific FE models of the pelvis without the need for segmentation. A specimen-specific pelvic FE model (source) was created using traditional segmentation methods and morphed onto a CT scan of a different (target) pelvis using a landmark-based method. The morphed model was then refined through mesh mapping by moving the nodes to the bone boundary. A second target model was created using traditional segmentation techniques. CT intensity based material properties were assigned to the morphed/mapped model and to the traditionally segmented target models. Models were analyzed to evaluate their geometric concurrency and strain patterns. Strains generated in a double-leg stance configuration were compared to experimental strain gauge data generated from the same target cadaver pelvis. CT landmark-based morphing and mapping techniques were efficiently applied to create a geometrically multifaceted specimen-specific pelvic FE model, which was similar to the traditionally segmented target model and better replicated the experimental strain results (R(2)=0.873). This study has shown that mesh morphing and mapping represents an efficient validated approach for pelvic FE model generation without the need for segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating Patient Dose from X-ray Tube Output Metrics: Automated Measurement of Patient Size from CT Images Enables Large-scale Size-specific Dose Estimates

PubMed Central

Ikuta, Ichiro; Warden, Graham I.; Andriole, Katherine P.; Khorasani, Ramin

2014-01-01

Purpose To test the hypothesis that patient size can be accurately calculated from axial computed tomographic (CT) images, including correction for the effects of anatomy truncation that occur in routine clinical CT image reconstruction. Materials and Methods Institutional review board approval was obtained for this HIPAA-compliant study, with waiver of informed consent. Water-equivalent diameter (DW) was computed from the attenuation-area product of each image within 50 adult CT scans of the thorax and of the abdomen and pelvis and was also measured for maximal field of view (FOV) reconstructions. Linear regression models were created to compare DW with the effective diameter (Deff) used to select size-specific volume CT dose index (CTDIvol) conversion factors as defined in report 204 of the American Association of Physicists in Medicine. Linear regression models relating reductions in measured DW to a metric of anatomy truncation were used to compensate for the effects of clinical image truncation. Results In the thorax, DW versus Deff had an R2 of 0.51 (n = 200, 50 patients at four anatomic locations); in the abdomen and pelvis, R2 was 0.90 (n = 150, 50 patients at three anatomic locations). By correcting for image truncation, the proportion of clinically reconstructed images with an extracted DW within ±5% of the maximal FOV DW increased from 54% to 90% in the thorax (n = 3602 images) and from 95% to 100% in the abdomen and pelvis (6181 images). Conclusion The DW extracted from axial CT images is a reliable measure of patient size, and varying degrees of clinical image truncation can be readily corrected. Automated measurement of patient size combined with CT radiation exposure metrics may enable patient-specific dose estimation on a large scale. © RSNA, 2013 PMID:24086075

Spatial enhancement of ECG using diagnostic similarity score based lead selective multi-scale linear model.

PubMed

Nallikuzhy, Jiss J; Dandapat, S

2017-06-01

In this work, a new patient-specific approach to enhance the spatial resolution of ECG is proposed and evaluated. The proposed model transforms a three-lead ECG into a standard twelve-lead ECG thereby enhancing its spatial resolution. The three leads used for prediction are obtained from the standard twelve-lead ECG. The proposed model takes advantage of the improved inter-lead correlation in wavelet domain. Since the model is patient-specific, it also selects the optimal predictor leads for a given patient using a lead selection algorithm. The lead selection algorithm is based on a new diagnostic similarity score which computes the diagnostic closeness between the original and the spatially enhanced leads. Standard closeness measures are used to assess the performance of the model. The similarity in diagnostic information between the original and the spatially enhanced leads are evaluated using various diagnostic measures. Repeatability and diagnosability are performed to quantify the applicability of the model. A comparison of the proposed model is performed with existing models that transform a subset of standard twelve-lead ECG into the standard twelve-lead ECG. From the analysis of the results, it is evident that the proposed model preserves diagnostic information better compared to other models. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-resolution Modeling Assisted Design of Customized and Individualized Transcranial Direct Current Stimulation Protocols

PubMed Central

Bikson, Marom; Rahman, Asif; Datta, Abhishek; Fregni, Felipe; Merabet, Lotfi

2012-01-01

Objectives Transcranial direct current stimulation (tDCS) is a neuromodulatory technique that delivers low-intensity currents facilitating or inhibiting spontaneous neuronal activity. tDCS is attractive since dose is readily adjustable by simply changing electrode number, position, size, shape, and current. In the recent past, computational models have been developed with increased precision with the goal to help customize tDCS dose. The aim of this review is to discuss the incorporation of high-resolution patient-specific computer modeling to guide and optimize tDCS. Methods In this review, we discuss the following topics: (i) The clinical motivation and rationale for models of transcranial stimulation is considered pivotal in order to leverage the flexibility of neuromodulation; (ii) The protocols and the workflow for developing high-resolution models; (iii) The technical challenges and limitations of interpreting modeling predictions, and (iv) Real cases merging modeling and clinical data illustrating the impact of computational models on the rational design of rehabilitative electrotherapy. Conclusions Though modeling for non-invasive brain stimulation is still in its development phase, it is predicted that with increased validation, dissemination, simplification and democratization of modeling tools, computational forward models of neuromodulation will become useful tools to guide the optimization of clinical electrotherapy. PMID:22780230

Estimation of Local Bone Loads for the Volume of Interest.

PubMed

Kim, Jung Jin; Kim, Youkyung; Jang, In Gwun

2016-07-01

Computational bone remodeling simulations have recently received significant attention with the aid of state-of-the-art high-resolution imaging modalities. They have been performed using localized finite element (FE) models rather than full FE models due to the excessive computational costs of full FE models. However, these localized bone remodeling simulations remain to be investigated in more depth. In particular, applying simplified loading conditions (e.g., uniform and unidirectional loads) to localized FE models have a severe limitation in a reliable subject-specific assessment. In order to effectively determine the physiological local bone loads for the volume of interest (VOI), this paper proposes a novel method of estimating the local loads when the global musculoskeletal loads are given. The proposed method is verified for the three VOI in a proximal femur in terms of force equilibrium, displacement field, and strain energy density (SED) distribution. The effect of the global load deviation on the local load estimation is also investigated by perturbing a hip joint contact force (HCF) in the femoral head. Deviation in force magnitude exhibits the greatest absolute changes in a SED distribution due to its own greatest deviation, whereas angular deviation perpendicular to a HCF provides the greatest relative change. With further in vivo force measurements and high-resolution clinical imaging modalities, the proposed method will contribute to the development of reliable patient-specific localized FE models, which can provide enhanced computational efficiency for iterative computing processes such as bone remodeling simulations.

The Potential of Computational Fluid Dynamics Simulation on Serial Monitoring of Hemodynamic Change in Type B Aortic Dissection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Simon C. H., E-mail: simonyu@cuhk.edu.hk; Liu, Wen; Wong, Randolph H. L.

PurposeWe aimed to assess the potential of computational fluid dynamics simulation (CFD) in detecting changes in pressure and flow velocity in response to morphological changes in type B aortic dissection.Materials and MethodsPressure and velocity in four morphological models of type B aortic dissection before and after closure of the entry tear were calculated with CFD and analyzed for changes among the different scenarios. The control model (Model 1) was patient specific and built from the DICOM data of CTA, which bore one entry tear and three re-entry tears. Models 2–4 were modifications of Model 1, with two re-entry tears lessmore » in Model 2, one re-entry tear more in Model 3, and a larger entry tear in Model 4.ResultsThe pressure and velocity pertaining to each of the morphological models were unique. Changes in pressure and velocity findings were accountable by the changes in morphological features of the different models. There was no blood flow in the false lumen across the entry tear after its closure, the blood flow direction across the re-entry tears was reversed after closure of the entry tear.ConclusionCFD simulation is probably useful to detect hemodynamic changes in the true and false lumens of type B aortic dissection in response to morphological changes, it may potentially be developed into a non-invasive and patient-specific tool for serial monitoring of hemodynamic changes of type B aortic dissection before and after treatment.« less

Fractional modeling of viscoelasticity in 3D cerebral arteries and aneurysms

NASA Astrophysics Data System (ADS)

Yu, Yue; Perdikaris, Paris; Karniadakis, George Em

2016-10-01

We develop efficient numerical methods for fractional order PDEs, and employ them to investigate viscoelastic constitutive laws for arterial wall mechanics. Recent simulations using one-dimensional models [1] have indicated that fractional order models may offer a more powerful alternative for modeling the arterial wall response, exhibiting reduced sensitivity to parametric uncertainties compared with the integer-calculus-based models. Here, we study three-dimensional (3D) fractional PDEs that naturally model the continuous relaxation properties of soft tissue, and for the first time employ them to simulate flow structure interactions for patient-specific brain aneurysms. To deal with the high memory requirements and in order to accelerate the numerical evaluation of hereditary integrals, we employ a fast convolution method [2] that reduces the memory cost to O (log ⁡ (N)) and the computational complexity to O (Nlog ⁡ (N)). Furthermore, we combine the fast convolution with high-order backward differentiation to achieve third-order time integration accuracy. We confirm that in 3D viscoelastic simulations, the integer order models strongly depends on the relaxation parameters, while the fractional order models are less sensitive. As an application to long-time simulations in complex geometries, we also apply the method to modeling fluid-structure interaction of a 3D patient-specific compliant cerebral artery with an aneurysm. Taken together, our findings demonstrate that fractional calculus can be employed effectively in modeling complex behavior of materials in realistic 3D time-dependent problems if properly designed efficient algorithms are employed to overcome the extra memory requirements and computational complexity associated with the non-local character of fractional derivatives.

Fractional modeling of viscoelasticity in 3D cerebral arteries and aneurysms

PubMed Central

Perdikaris, Paris; Karniadakis, George Em

2017-01-01

We develop efficient numerical methods for fractional order PDEs, and employ them to investigate viscoelastic constitutive laws for arterial wall mechanics. Recent simulations using one-dimensional models [1] have indicated that fractional order models may offer a more powerful alternative for modeling the arterial wall response, exhibiting reduced sensitivity to parametric uncertainties compared with the integer-calculus-based models. Here, we study three-dimensional (3D) fractional PDEs that naturally model the continuous relaxation properties of soft tissue, and for the first time employ them to simulate flow structure interactions for patient-specific brain aneurysms. To deal with the high memory requirements and in order to accelerate the numerical evaluation of hereditary integrals, we employ a fast convolution method [2] that reduces the memory cost to O(log(N)) and the computational complexity to O(N log(N)). Furthermore, we combine the fast convolution with high-order backward differentiation to achieve third-order time integration accuracy. We confirm that in 3D viscoelastic simulations, the integer order models strongly depends on the relaxation parameters, while the fractional order models are less sensitive. As an application to long-time simulations in complex geometries, we also apply the method to modeling fluid–structure interaction of a 3D patient-specific compliant cerebral artery with an aneurysm. Taken together, our findings demonstrate that fractional calculus can be employed effectively in modeling complex behavior of materials in realistic 3D time-dependent problems if properly designed efficient algorithms are employed to overcome the extra memory requirements and computational complexity associated with the non-local character of fractional derivatives. PMID:29104310

Mechanics, Mechanobiology, and Modeling of Human Abdominal Aorta and Aneurysms

PubMed Central

Humphrey, J.D.; Holzapfel, G.A.

2011-01-01

Biomechanical factors play fundamental roles in the natural history of abdominal aortic aneurysms (AAAs) and their responses to treatment. Advances during the past two decades have increased our understanding of the mechanics and biology of the human abdominal aorta and AAAs, yet there remains a pressing need for considerable new data and resulting patient-specific computational models that can better describe the current status of a lesion and better predict the evolution of lesion geometry, composition, and material properties and thereby improve interventional planning. In this paper, we briefly review data on the structure and function of the human abdominal aorta and aneurysmal wall, past models of the mechanics, and recent growth and remodeling models. We conclude by identifying open problems that we hope will motivate studies to improve our computational modeling and thus general understanding of AAAs. PMID:22189249

Acute imaging does not improve ASTRAL score's accuracy despite having a prognostic value.

PubMed

Ntaios, George; Papavasileiou, Vasileios; Faouzi, Mohamed; Vanacker, Peter; Wintermark, Max; Michel, Patrik

2014-10-01

The ASTRAL score was recently shown to reliably predict three-month functional outcome in patients with acute ischemic stroke. The study aims to investigate whether information from multimodal imaging increases ASTRAL score's accuracy. All patients registered in the ASTRAL registry until March 2011 were included. In multivariate logistic-regression analyses, we added covariates derived from parenchymal, vascular, and perfusion imaging to the 6-parameter model of the ASTRAL score. If a specific imaging covariate remained an independent predictor of three-month modified Rankin score>2, the area-under-the-curve (AUC) of this new model was calculated and compared with ASTRAL score's AUC. We also performed similar logistic regression analyses in arbitrarily chosen patient subgroups. When added to the ASTRAL score, the following covariates on admission computed tomography/magnetic resonance imaging-based multimodal imaging were not significant predictors of outcome: any stroke-related acute lesion, any nonstroke-related lesions, chronic/subacute stroke, leukoaraiosis, significant arterial pathology in ischemic territory on computed tomography angiography/magnetic resonance angiography/Doppler, significant intracranial arterial pathology in ischemic territory, and focal hypoperfusion on perfusion-computed tomography. The Alberta Stroke Program Early CT score on plain imaging and any significant extracranial arterial pathology on computed tomography angiography/magnetic resonance angiography/Doppler were independent predictors of outcome (odds ratio: 0·93, 95% CI: 0·87-0·99 and odds ratio: 1·49, 95% CI: 1·08-2·05, respectively) but did not increase ASTRAL score's AUC (0·849 vs. 0·850, and 0·8563 vs. 0·8564, respectively). In exploratory analyses in subgroups of different prognosis, age or stroke severity, no covariate was found to increase ASTRAL score's AUC, either. The addition of information derived from multimodal imaging does not increase ASTRAL score's accuracy to predict functional outcome despite having an independent prognostic value. More selected radiological parameters applied in specific subgroups of stroke patients may add prognostic value of multimodal imaging. © 2014 World Stroke Organization.

Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Depeursinge, Adrien, E-mail: adrien.depeursinge@hevs.ch; Yanagawa, Masahiro; Leung, Ann N.

Purpose: To investigate the importance of presurgical computed tomography (CT) intensity and texture information from ground-glass opacities (GGO) and solid nodule components for the prediction of adenocarcinoma recurrence. Methods: For this study, 101 patients with surgically resected stage I adenocarcinoma were selected. During the follow-up period, 17 patients had disease recurrence with six associated cancer-related deaths. GGO and solid tumor components were delineated on presurgical CT scans by a radiologist. Computational texture models of GGO and solid regions were built using linear combinations of steerable Riesz wavelets learned with linear support vector machines (SVMs). Unlike other traditional texture attributes, themore » proposed texture models are designed to encode local image scales and directions that are specific to GGO and solid tissue. The responses of the locally steered models were used as texture attributes and compared to the responses of unaligned Riesz wavelets. The texture attributes were combined with CT intensities to predict tumor recurrence and patient hazard according to disease-free survival (DFS) time. Two families of predictive models were compared: LASSO and SVMs, and their survival counterparts: Cox-LASSO and survival SVMs. Results: The best-performing predictive model of patient hazard was associated with a concordance index (C-index) of 0.81 ± 0.02 and was based on the combination of the steered models and CT intensities with survival SVMs. The same feature group and the LASSO model yielded the highest area under the receiver operating characteristic curve (AUC) of 0.8 ± 0.01 for predicting tumor recurrence, although no statistically significant difference was found when compared to using intensity features solely. For all models, the performance was found to be significantly higher when image attributes were based on the solid components solely versus using the entire tumors (p < 3.08 × 10{sup −5}). Conclusions: This study constitutes a novel perspective on how to interpret imaging information from CT examinations by suggesting that most of the information related to adenocarcinoma aggressiveness is related to the intensity and morphological properties of solid components of the tumor. The prediction of adenocarcinoma relapse was found to have low specificity but very high sensitivity. Our results could be useful in clinical practice to identify patients for which no recurrence is expected with a very high confidence using a presurgical CT scan only. It also provided an accurate estimation of the risk of recurrence after a given duration t from surgical resection (i.e., C-index = 0.81 ± 0.02)« less

A Competing Risk Model of First Failure Site after Definitive Chemoradiation Therapy for Locally Advanced Non-Small Cell Lung Cancer.

PubMed

Nygård, Lotte; Vogelius, Ivan R; Fischer, Barbara M; Kjær, Andreas; Langer, Seppo W; Aznar, Marianne C; Persson, Gitte F; Bentzen, Søren M

2018-04-01

The aim of the study was to build a model of first failure site- and lesion-specific failure probability after definitive chemoradiotherapy for inoperable NSCLC. We retrospectively analyzed 251 patients receiving definitive chemoradiotherapy for NSCLC at a single institution between 2009 and 2015. All patients were scanned by fludeoxyglucose positron emission tomography/computed tomography for radiotherapy planning. Clinical patient data and fludeoxyglucose positron emission tomography standardized uptake values from primary tumor and nodal lesions were analyzed by using multivariate cause-specific Cox regression. In patients experiencing locoregional failure, multivariable logistic regression was applied to assess risk of each lesion being the first site of failure. The two models were used in combination to predict probability of lesion failure accounting for competing events. Adenocarcinoma had a lower hazard ratio (HR) of locoregional failure than squamous cell carcinoma (HR = 0.45, 95% confidence interval [CI]: 0.26-0.76, p = 0.003). Distant failures were more common in the adenocarcinoma group (HR = 2.21, 95% CI: 1.41-3.48, p < 0.001). Multivariable logistic regression of individual lesions at the time of first failure showed that primary tumors were more likely to fail than lymph nodes (OR = 12.8, 95% CI: 5.10-32.17, p < 0.001). Increasing peak standardized uptake value was significantly associated with lesion failure (OR = 1.26 per unit increase, 95% CI: 1.12-1.40, p < 0.001). The electronic model is available at http://bit.ly/LungModelFDG. We developed a failure site-specific competing risk model based on patient- and lesion-level characteristics. Failure patterns differed between adenocarcinoma and squamous cell carcinoma, illustrating the limitation of aggregating them into NSCLC. Failure site-specific models add complementary information to conventional prognostic models. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Estimation of aortic valve leaflets from 3D CT images using local shape dictionaries and linear coding

NASA Astrophysics Data System (ADS)

Liang, Liang; Martin, Caitlin; Wang, Qian; Sun, Wei; Duncan, James

2016-03-01

Aortic valve (AV) disease is a significant cause of morbidity and mortality. The preferred treatment modality for severe AV disease is surgical resection and replacement of the native valve with either a mechanical or tissue prosthetic. In order to develop effective and long-lasting treatment methods, computational analyses, e.g., structural finite element (FE) and computational fluid dynamic simulations, are very effective for studying valve biomechanics. These computational analyses are based on mesh models of the aortic valve, which are usually constructed from 3D CT images though many hours of manual annotation, and therefore an automatic valve shape reconstruction method is desired. In this paper, we present a method for estimating the aortic valve shape from 3D cardiac CT images, which is represented by triangle meshes. We propose a pipeline for aortic valve shape estimation which includes novel algorithms for building local shape dictionaries and for building landmark detectors and curve detectors using local shape dictionaries. The method is evaluated on real patient image dataset using a leave-one-out approach and achieves an average accuracy of 0.69 mm. The work will facilitate automatic patient-specific computational modeling of the aortic valve.

A novel method for the evaluation of uncertainty in dose-volume histogram computation.

PubMed

Henríquez, Francisco Cutanda; Castrillón, Silvia Vargas

2008-03-15

Dose-volume histograms (DVHs) are a useful tool in state-of-the-art radiotherapy treatment planning, and it is essential to recognize their limitations. Even after a specific dose-calculation model is optimized, dose distributions computed by using treatment-planning systems are affected by several sources of uncertainty, such as algorithm limitations, measurement uncertainty in the data used to model the beam, and residual differences between measured and computed dose. This report presents a novel method to take them into account. To take into account the effect of associated uncertainties, a probabilistic approach using a new kind of histogram, a dose-expected volume histogram, is introduced. The expected value of the volume in the region of interest receiving an absorbed dose equal to or greater than a certain value is found by using the probability distribution of the dose at each point. A rectangular probability distribution is assumed for this point dose, and a formulation that accounts for uncertainties associated with point dose is presented for practical computations. This method is applied to a set of DVHs for different regions of interest, including 6 brain patients, 8 lung patients, 8 pelvis patients, and 6 prostate patients planned for intensity-modulated radiation therapy. Results show a greater effect on planning target volume coverage than in organs at risk. In cases of steep DVH gradients, such as planning target volumes, this new method shows the largest differences with the corresponding DVH; thus, the effect of the uncertainty is larger.

Patient-specific CFD models for intraventricular flow analysis from 3D ultrasound imaging: Comparison of three clinical cases.

PubMed

Bavo, A M; Pouch, A M; Degroote, J; Vierendeels, J; Gorman, J H; Gorman, R C; Segers, P

2017-01-04

As the intracardiac flow field is affected by changes in shape and motility of the heart, intraventricular flow features can provide diagnostic indications. Ventricular flow patterns differ depending on the cardiac condition and the exploration of different clinical cases can provide insights into how flow fields alter in different pathologies. In this study, we applied a patient-specific computational fluid dynamics model of the left ventricle and mitral valve, with prescribed moving boundaries based on transesophageal ultrasound images for three cardiac pathologies, to verify the abnormal flow patterns in impaired hearts. One case (P1) had normal ejection fraction but low stroke volume and cardiac output, P2 showed low stroke volume and reduced ejection fraction, P3 had a dilated ventricle and reduced ejection fraction. The shape of the ventricle and mitral valve, together with the pathology influence the flow field in the left ventricle, leading to distinct flow features. Of particular interest is the pattern of the vortex formation and evolution, influenced by the valvular orifice and the ventricular shape. The base-to-apex pressure difference of maximum 2mmHg is consistent with reported data. We used a CFD model with prescribed boundary motion to describe the intraventricular flow field in three patients with impaired diastolic function. The calculated intraventricular flow dynamics are consistent with the diagnostic patient records and highlight the differences between the different cases. The integration of clinical images and computational techniques, therefore, allows for a deeper investigation intraventricular hemodynamics in patho-physiology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of exercise on patient specific abdominal aortic aneurysm flow topology and mixing.

PubMed

Arzani, Amirhossein; Les, Andrea S; Dalman, Ronald L; Shadden, Shawn C

2014-02-01

Computational fluid dynamics modeling was used to investigate changes in blood transport topology between rest and exercise conditions in five patient-specific abdominal aortic aneurysm models. MRI was used to provide the vascular anatomy and necessary boundary conditions for simulating blood velocity and pressure fields inside each model. Finite-time Lyapunov exponent fields and associated Lagrangian coherent structures were computed from blood velocity data and were used to compare features of the transport topology between rest and exercise both mechanistically and qualitatively. A mix-norm and mix-variance measure based on fresh blood distribution throughout the aneurysm over time were implemented to quantitatively compare mixing between rest and exercise. Exercise conditions resulted in higher and more uniform mixing and reduced the overall residence time in all aneurysms. Separated regions of recirculating flow were commonly observed in rest, and these regions were either reduced or removed by attached and unidirectional flow during exercise, or replaced with regional chaotic and transiently turbulent mixing, or persisted and even extended during exercise. The main factor that dictated the change in flow topology from rest to exercise was the behavior of the jet of blood penetrating into the aneurysm during systole. Copyright © 2013 John Wiley & Sons, Ltd.

Mild anastomotic stenosis in patient-specific CABG model may enhance graft patency: a new hypothesis.

PubMed

Huo, Yunlong; Luo, Tong; Guccione, Julius M; Teague, Shawn D; Tan, Wenchang; Navia, José A; Kassab, Ghassan S

2013-01-01

It is well known that flow patterns at the anastomosis of coronary artery bypass graft (CABG) are complex and may affect the long-term patency. Various attempts at optimal designs of anastomosis have not improved long-term patency. Here, we hypothesize that mild anastomotic stenosis (area stenosis of about 40-60%) may be adaptive to enhance the hemodynamic conditions, which may contribute to slower progression of atherosclerosis. We further hypothesize that proximal/distal sites to the stenosis have converse changes that may be a risk factor for the diffuse expansion of atherosclerosis from the site of stenosis. Twelve (12) patient-specific models with various stenotic degrees were extracted from computed tomography images using a validated segmentation software package. A 3-D finite element model was used to compute flow patterns including wall shear stress (WSS) and its spatial and temporal gradients (WSS gradient, WSSG, and oscillatory shear index, OSI). The flow simulations showed that mild anastomotic stenosis significantly increased WSS (>15 dynes · cm(-2)) and decreased OSI (<0.02) to result in a more uniform distribution of hemodynamic parameters inside anastomosis albeit proximal/distal sites to the stenosis have a decrease of WSS (<4 dynes · cm(-2)). These findings have significant implications for graft adaptation and long-term patency.

Towards reducing thrombogenicity of LVAD therapy: optimizing surgical and patient management strategies

NASA Astrophysics Data System (ADS)

Chivukula, Venkat Keshav; Lafzi, Ali; Mokadam, Nahush; Beckman, Jennifer; Mahr, Claudius; Aliseda, Alberto

2017-11-01

Unfavourable hemodynamics in heart failure patients implanted with left ventricular assist devices (LVAD), due to non-optimal surgical configurations and patient management, strongly influence thrombogenicity. This is consistent with the increase in devastating thromboembolic complications (specifically thrombosis and stroke) in patients, even as the risk of thrombosis inside the device decreases with modern designs. Inflow cannula and outflow graft surgical configurations have been optimized via patient-specific modeling that computes the thrombogenic potential with a combination of Eulerian (endothelial) wall shear stress and Lagrangian (platelet shear history) tracking. Using this view of hemodynamics, the benefits of intermittent aortic valve opening (promoting washout and reducing stagnant flow in the aortic valve region) have been assessed in managing the patient's residual native cardiac output. The use of this methodology to understand the contribution of the hemodynamics in the flow surrounding the LVAD itself to thrombogenesis show promise in developing holistic patient-specific management strategies to minimize stroke risk and enhance efficacy of LVAD therapy. Funded in part by an AHA postdoctoral fellowship 16POST30520004.

Role of 0D peripheral vasculature model in fluid-structure interaction modeling of aneurysms

NASA Astrophysics Data System (ADS)

Torii, Ryo; Oshima, Marie; Kobayashi, Toshio; Takagi, Kiyoshi; Tezduyar, Tayfun E.

2010-06-01

Patient-specific simulations based on medical images such as CT and MRI offer information on the hemodynamic and wall tissue stress in patient-specific aneurysm configurations. These are considered important in predicting the rupture risk for individual aneurysms but are not possible to measure directly. In this paper, fluid-structure interaction (FSI) analyses of a cerebral aneurysm at the middle cerebral artery (MCA) bifurcation are presented. A 0D structural recursive tree model of the peripheral vasculature is incorporated and its impedance is coupled with the 3D FSI model to compute the outflow through the two branches accurately. The results are compared with FSI simulation with prescribed pressure variation at the outlets. The comparison shows that the pressure at the two outlets are nearly identical even with the peripheral vasculature model and the flow division to the two branches is nearly the same as what we see in the simulation without the peripheral vasculature model. This suggests that the role of the peripheral vasculature in FSI modeling of the MCA aneurysm is not significant.

A three-dimensional virtual environment for modeling mechanical cardiopulmonary interactions.

PubMed

Kaye, J M; Primiano, F P; Metaxas, D N

1998-06-01

We have developed a real-time computer system for modeling mechanical physiological behavior in an interactive, 3-D virtual environment. Such an environment can be used to facilitate exploration of cardiopulmonary physiology, particularly in situations that are difficult to reproduce clinically. We integrate 3-D deformable body dynamics with new, formal models of (scalar) cardiorespiratory physiology, associating the scalar physiological variables and parameters with the corresponding 3-D anatomy. Our framework enables us to drive a high-dimensional system (the 3-D anatomical models) from one with fewer parameters (the scalar physiological models) because of the nature of the domain and our intended application. Our approach is amenable to modeling patient-specific circumstances in two ways. First, using CT scan data, we apply semi-automatic methods for extracting and reconstructing the anatomy to use in our simulations. Second, our scalar physiological models are defined in terms of clinically measurable, patient-specific parameters. This paper describes our approach, problems we have encountered and a sample of results showing normal breathing and acute effects of pneumothoraces.

Fluid Structure Interaction simulation of heart prosthesis in patient-specific left-ventricle/aorta anatomies

NASA Astrophysics Data System (ADS)

Le, Trung; Borazjani, Iman; Sotiropoulos, Fotis

2009-11-01

In order to test and optimize heart valve prosthesis and enable virtual implantation of other biomedical devices it is essential to develop and validate high-resolution FSI-CFD codes for carrying out simulations in patient-specific geometries. We have developed a powerful numerical methodology for carrying out FSI simulations of cardiovascular flows based on the CURVIB approach (Borazjani, L. Ge, and F. Sotiropoulos, Journal of Computational physics, vol. 227, pp. 7587-7620 2008). We have extended our FSI method to overset grids to handle efficiently more complicated geometries e.g. simulating an MHV implanted in an anatomically realistic aorta and left-ventricle. A compliant, anatomic left-ventricle is modeled using prescribed motion in one domain. The mechanical heart valve is placed inside the second domain i.e. the body-fitted curvilinear mesh of the anatomic aorta. The simulations of an MHV with a left-ventricle model underscore the importance of inflow conditions and ventricular compliance for such simulations and demonstrate the potential of our method as a powerful tool for patient-specific simulations.

Development of three-dimensional patient face model that enables real-time collision detection and cutting operation for a dental simulator.

PubMed

Yamaguchi, Satoshi; Yamada, Yuya; Yoshida, Yoshinori; Noborio, Hiroshi; Imazato, Satoshi

2012-01-01

The virtual reality (VR) simulator is a useful tool to develop dental hand skill. However, VR simulations with reactions of patients have limited computational time to reproduce a face model. Our aim was to develop a patient face model that enables real-time collision detection and cutting operation by using stereolithography (STL) and deterministic finite automaton (DFA) data files. We evaluated dependence of computational cost and constructed the patient face model using the optimum condition for combining STL and DFA data files, and assessed the computational costs for operation in do-nothing, collision, cutting, and combination of collision and cutting. The face model was successfully constructed with low computational costs of 11.3, 18.3, 30.3, and 33.5 ms for do-nothing, collision, cutting, and collision and cutting, respectively. The patient face model could be useful for developing dental hand skill with VR.

[Application of 3D soft print models of the kidney for treatment of patients with localized cancer of the kidney (a pilot study)].

PubMed

Alyaev, Yu G; Sirota, E S; Bezrukov, E A; Fiev, D N; Bukatov, M D; Letunovskii, A V; Byadretdinov, I Sh

2017-12-01

To evaluate the possibility of using 3D-printing in the management of patients with localized kidney cancer. The study comprised five patients with localized kidney cancer who were treated at the Urology Clinic of the I.M. Sechenov First Moscow State Medical University from January 2016 to April 2017. Along with the standard examination, the patients underwent multispiral computed tomography (MSCT) to produce patient-specific 3D-printed models of the kidney tumors using 3D modeling and 3D printing. To evaluate the effectiveness of using 3D-printed models, two-stage preoperative planning was conducted, and five surgeons were surveyed using a four-question multiple choice questionnaire. At the first stage, the planning of operations was carried out based on MSCT findings. At the second stage, the surgeons were given patient-specific soft 3D models of the kidney with a tumor for preoperative training. After preoperative training, patients underwent laparoscopic resection of the kidney with a tumor. According to the survey results, each of the participating surgeons at least once changed surgical plan based on data obtained with 3D printed models of the kidney with the tumor. The implementation of preoperative training using 3D printed models of the kidney turned out to be effective. All patients underwent laparoscopic surgery performed by a single surgeon with extensive experience in this type of surgery. The mean operative time was 187 minutes. All operations were performed with main renal artery occlusion. The men warm ischemia time was 19.5 minutes and the mean blood loss was 170 ml. There were no conversions to open surgery and organ-removing operations. There were no postoperative complications or deaths. All surgical margins were negative. Morphological examination showed that four patients had renal cell carcinoma one patient had the oncocytoma. The study demonstrated the promise of using 3D printing for preoperative planning and surgical performance due to a high-precision three-dimensional soft patient-specific model of the localized kidney.

Performance of uncertainty quantification methodologies and linear solvers in cardiovascular simulations

NASA Astrophysics Data System (ADS)

Seo, Jongmin; Schiavazzi, Daniele; Marsden, Alison

2017-11-01

Cardiovascular simulations are increasingly used in clinical decision making, surgical planning, and disease diagnostics. Patient-specific modeling and simulation typically proceeds through a pipeline from anatomic model construction using medical image data to blood flow simulation and analysis. To provide confidence intervals on simulation predictions, we use an uncertainty quantification (UQ) framework to analyze the effects of numerous uncertainties that stem from clinical data acquisition, modeling, material properties, and boundary condition selection. However, UQ poses a computational challenge requiring multiple evaluations of the Navier-Stokes equations in complex 3-D models. To achieve efficiency in UQ problems with many function evaluations, we implement and compare a range of iterative linear solver and preconditioning techniques in our flow solver. We then discuss applications to patient-specific cardiovascular simulation and how the problem/boundary condition formulation in the solver affects the selection of the most efficient linear solver. Finally, we discuss performance improvements in the context of uncertainty propagation. Support from National Institute of Health (R01 EB018302) is greatly appreciated.

Variability of hemodynamic parameters using the common viscosity assumption in a computational fluid dynamics analysis of intracranial aneurysms.

PubMed

Suzuki, Takashi; Takao, Hiroyuki; Suzuki, Takamasa; Suzuki, Tomoaki; Masuda, Shunsuke; Dahmani, Chihebeddine; Watanabe, Mitsuyoshi; Mamori, Hiroya; Ishibashi, Toshihiro; Yamamoto, Hideki; Yamamoto, Makoto; Murayama, Yuichi

2017-01-01

In most simulations of intracranial aneurysm hemodynamics, blood is assumed to be a Newtonian fluid. However, it is a non-Newtonian fluid, and its viscosity profile differs among individuals. Therefore, the common viscosity assumption may not be valid for all patients. This study aims to test the suitability of the common viscosity assumption. Blood viscosity datasets were obtained from two healthy volunteers. Three simulations were performed for three different-sized aneurysms, two using measured value-based non-Newtonian models and one using a Newtonian model. The parameters proposed to predict an aneurysmal rupture obtained using the non-Newtonian models were compared with those obtained using the Newtonian model. The largest difference (25%) in the normalized wall shear stress (NWSS) was observed in the smallest aneurysm. Comparing the difference ratio to the NWSS with the Newtonian model between the two Non-Newtonian models, the difference of the ratio was 17.3%. Irrespective of the aneurysmal size, computational fluid dynamics simulations with either the common Newtonian or non-Newtonian viscosity assumption could lead to values different from those of the patient-specific viscosity model for hemodynamic parameters such as NWSS.

3D MR flow analysis in realistic rapid-prototyping model systems of the thoracic aorta: comparison with in vivo data and computational fluid dynamics in identical vessel geometries.

PubMed

Canstein, C; Cachot, P; Faust, A; Stalder, A F; Bock, J; Frydrychowicz, A; Küffer, J; Hennig, J; Markl, M

2008-03-01

The knowledge of local vascular anatomy and function in the human body is of high interest for the diagnosis and treatment of cardiovascular disease. A comprehensive analysis of the hemodynamics in the thoracic aorta is presented based on the integration of flow-sensitive 4D MRI with state-of-the-art rapid prototyping technology and computational fluid dynamics (CFD). Rapid prototyping was used to transform aortic geometries as measured by contrast-enhanced MR angiography into realistic vascular models with large anatomical coverage. Integration into a flow circuit with patient-specific pulsatile in-flow conditions and application of flow-sensitive 4D MRI permitted detailed analysis of local and global 3D flow dynamics in a realistic vascular geometry. Visualization of characteristic 3D flow patterns and quantitative comparisons of the in vitro experiments with in vivo data and CFD simulations in identical vascular geometries were performed to evaluate the accuracy of vascular model systems. The results indicate the potential of such patient-specific model systems for detailed experimental simulation of realistic vascular hemodynamics. Further studies are warranted to examine the influence of refined boundary conditions of the human circulatory system such as fluid-wall interaction and their effect on normal and pathological blood flow characteristics associated with vascular geometry. (c) 2008 Wiley-Liss, Inc.

Medicine clerkships and portable computing: a national survey of internal medicine clerkship directors.

PubMed

Ferenchick, Gary; Solomon, David; Durning, Steven J

2010-01-01

Portable computers are widely used by medical trainees, but there is a lack of data on how these devices are used in clinical education programs. The objective is to define the current use of portable computing in internal medicine clerkships and to determine medicine clerkship directors' perceptions of the current value and future importance of portable computing. A 2006 national survey of institutional members of the Clerkship Directors in Internal Medicine. Eighty-three of 110 (75%) of institutional members responded. An institutional requirement for portable computing was reported by 32 schools (39%), whereas only 13 (16%) provided students with a portable computer. Between 10 and 31 institutions (12-37%) reported student use for patient care activities (i.e. order entry, writing patient notes) and only 2 to 4 institutions (2-5%) required such use. The majority of respondents (59-95%) reported portable computer use for educational activities (i.e., tracking patient problems, knowledge resource), however, only in 5 to 19 (6-23%) were such educational uses required. Fifty-six respondents (68%) reported that portable computer's "added value" for teaching and 61 (73%) reported that portable computers would be important in meeting clerkship objectives in the next 3 years. Of interest, even among the institutions requiring portable computers, only 50% recommended or required specific software. Portable computing is required at 39% of allopathic medical schools in the United States. However required portable computing for specific patient care or educational tasks is uncommon. In addition, guidance on specific software exists in only one half of school requiring portable computers, suggesting informal or unstructured uses of required portable computer's in the remaining half. The educational impact of formal institutional requirements for software versus informal "user-defined" applications is unknown.

Shared and Disorder-Specific Neurocomputational Mechanisms of Decision-Making in Autism Spectrum Disorder and Obsessive-Compulsive Disorder.

PubMed

Carlisi, Christina O; Norman, Luke; Murphy, Clodagh M; Christakou, Anastasia; Chantiluke, Kaylita; Giampietro, Vincent; Simmons, Andrew; Brammer, Michael; Murphy, Declan G; Mataix-Cols, David; Rubia, Katya

2017-12-01

Autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD) often share phenotypes of repetitive behaviors, possibly underpinned by abnormal decision-making. To compare neural correlates underlying decision-making between these disorders, brain activation of boys with ASD (N = 24), OCD (N = 20) and typically developing controls (N = 20) during gambling was compared, and computational modeling compared performance. Patients were unimpaired on number of risky decisions, but modeling showed that both patient groups had lower choice consistency and relied less on reinforcement learning compared to controls. ASD individuals had disorder-specific choice perseverance abnormalities compared to OCD individuals. Neurofunctionally, ASD and OCD boys shared dorsolateral/inferior frontal underactivation compared to controls during decision-making. During outcome anticipation, patients shared underactivation compared to controls in lateral inferior/orbitofrontal cortex and ventral striatum. During reward receipt, ASD boys had disorder-specific enhanced activation in inferior frontal/insular regions relative to OCD boys and controls. Results showed that ASD and OCD individuals shared decision-making strategies that differed from controls to achieve comparable performance to controls. Patients showed shared abnormalities in lateral-(orbito)fronto-striatal reward circuitry, but ASD boys had disorder-specific lateral inferior frontal/insular overactivation, suggesting that shared and disorder-specific mechanisms underpin decision-making in these disorders. Findings provide evidence for shared neurobiological substrates that could serve as possible future biomarkers. © The Author 2017. Published by Oxford University Press.

In vivo serial MRI-based models and statistical methods to quantify sensitivity and specificity of mechanical predictors for carotid plaque rupture: location and beyond.

PubMed

Wu, Zheyang; Yang, Chun; Tang, Dalin

2011-06-01

It has been hypothesized that mechanical risk factors may be used to predict future atherosclerotic plaque rupture. Truly predictive methods for plaque rupture and methods to identify the best predictor(s) from all the candidates are lacking in the literature. A novel combination of computational and statistical models based on serial magnetic resonance imaging (MRI) was introduced to quantify sensitivity and specificity of mechanical predictors to identify the best candidate for plaque rupture site prediction. Serial in vivo MRI data of carotid plaque from one patient was acquired with follow-up scan showing ulceration. 3D computational fluid-structure interaction (FSI) models using both baseline and follow-up data were constructed and plaque wall stress (PWS) and strain (PWSn) and flow maximum shear stress (FSS) were extracted from all 600 matched nodal points (100 points per matched slice, baseline matching follow-up) on the lumen surface for analysis. Each of the 600 points was marked "ulcer" or "nonulcer" using follow-up scan. Predictive statistical models for each of the seven combinations of PWS, PWSn, and FSS were trained using the follow-up data and applied to the baseline data to assess their sensitivity and specificity using the 600 data points for ulcer predictions. Sensitivity of prediction is defined as the proportion of the true positive outcomes that are predicted to be positive. Specificity of prediction is defined as the proportion of the true negative outcomes that are correctly predicted to be negative. Using probability 0.3 as a threshold to infer ulcer occurrence at the prediction stage, the combination of PWS and PWSn provided the best predictive accuracy with (sensitivity, specificity) = (0.97, 0.958). Sensitivity and specificity given by PWS, PWSn, and FSS individually were (0.788, 0.968), (0.515, 0.968), and (0.758, 0.928), respectively. The proposed computational-statistical process provides a novel method and a framework to assess the sensitivity and specificity of various risk indicators and offers the potential to identify the optimized predictor for plaque rupture using serial MRI with follow-up scan showing ulceration as the gold standard for method validation. While serial MRI data with actual rupture are hard to acquire, this single-case study suggests that combination of multiple predictors may provide potential improvement to existing plaque assessment schemes. With large-scale patient studies, this predictive modeling process may provide more solid ground for rupture predictor selection strategies and methods for image-based plaque vulnerability assessment.

A patient workflow management system built on guidelines.

PubMed Central

Dazzi, L.; Fassino, C.; Saracco, R.; Quaglini, S.; Stefanelli, M.

1997-01-01

To provide high quality, shared, and distributed medical care, clinical and organizational issues need to be integrated. This work describes a methodology for developing a Patient Workflow Management System, based on a detailed model of both the medical work process and the organizational structure. We assume that the medical work process is represented through clinical practice guidelines, and that an ontological description of the organization is available. Thus, we developed tools 1) for acquiring the medical knowledge contained into a guideline, 2) to translate the derived formalized guideline into a computational formalism, precisely a Petri Net, 3) to maintain different representation levels. The high level representation guarantees that the Patient Workflow follows the guideline prescriptions, while the low level takes into account the specific organization characteristics and allow allocating resources for managing a specific patient in daily practice. PMID:9357606

Computerization of guidelines: towards a "guideline markup language".

PubMed

Dart, T; Xu, Y; Chatellier, G; Degoulet, P

2001-01-01

Medical decision making is one of the most difficult daily tasks for physicians. Guidelines have been designed to reduce variance between physicians in daily practice, to improve patient outcomes and to control costs. In fact, few physicians use guidelines in daily practice. A way to ease the use of guidelines is to implement computerised guidelines (computer reminders). We present in this paper a method of computerising guidelines. Our objectives were: 1) to propose a generic model that can be instantiated for any specific guidelines; 2) to use eXtensible Markup Language (XML) as a guideline representation language to instantiate the generic model for a specific guideline. Our model is an object representation of a clinical algorithm, it has been validated by running two different guidelines issued by a French official Agency. In spite of some limitations, we found that this model is expressive enough to represent complex guidelines devoted to diabetes and hypertension management. We conclude that XML can be used as a description format to structure guidelines and as an interface between paper-based guidelines and computer applications.

Planning acetabular fracture reduction using patient-specific multibody simulation of the hip

NASA Astrophysics Data System (ADS)

Oliveri, Hadrien; Boudissa, Mehdi; Tonetti, Jerome; Chabanas, Matthieu

2017-03-01

Acetabular fractures are a challenge in orthopedic surgery. Computer-aided solutions were proposed to segment bone fragments, simulate the fracture reduction or design the osteosynthesis fixation plates. This paper addresses the simulation part, which is usually carried out by freely moving bone fragments with six degrees of freedom to reproduce the pre-fracture state. Instead we propose a different paradigm, closer to actual surgeon's requirements: to simulate the surgical procedure itself rather than the desired result. A simple, patient-specific, biomechanical multibody model is proposed, integrating the main ligaments and muscles of the hip joint while accounting for contacts between bone fragments. Main surgical tools and actions can be simulated, such as clamps, Schanz screws or traction of the femur. Simulations are computed interactively, which enables clinicians to evaluate different strategies for an optimal surgical planning. Six retrospective cases were studied, with simple and complex fracture patterns. After interactively building the models from preoperative CT, gestures from the surgical reports were reproduced. Results of the simulations could then be compared with postoperative CT data. A qualitative study shows the model behavior is excellent and the simulated reductions fit the observed data. A more quantitative analysis is currently being completed. Two cases are particularly significant, for which the surgical reduction actually failed. Simulations show it was indeed not possible to reduce these fractures with the chosen approach. Had our simulator being used, a better planning may have avoided a second surgery to these patients.

Methodology for Image-Based Reconstruction of Ventricular Geometry for Patient-Specific Modeling of Cardiac Electrophysiology

PubMed Central

Prakosa, A.; Malamas, P.; Zhang, S.; Pashakhanloo, F.; Arevalo, H.; Herzka, D. A.; Lardo, A.; Halperin, H.; McVeigh, E.; Trayanova, N.; Vadakkumpadan, F.

2014-01-01

Patient-specific modeling of ventricular electrophysiology requires an interpolated reconstruction of the 3-dimensional (3D) geometry of the patient ventricles from the low-resolution (Lo-res) clinical images. The goal of this study was to implement a processing pipeline for obtaining the interpolated reconstruction, and thoroughly evaluate the efficacy of this pipeline in comparison with alternative methods. The pipeline implemented here involves contouring the epi- and endocardial boundaries in Lo-res images, interpolating the contours using the variational implicit functions method, and merging the interpolation results to obtain the ventricular reconstruction. Five alternative interpolation methods, namely linear, cubic spline, spherical harmonics, cylindrical harmonics, and shape-based interpolation were implemented for comparison. In the thorough evaluation of the processing pipeline, Hi-res magnetic resonance (MR), computed tomography (CT), and diffusion tensor (DT) MR images from numerous hearts were used. Reconstructions obtained from the Hi-res images were compared with the reconstructions computed by each of the interpolation methods from a sparse sample of the Hi-res contours, which mimicked Lo-res clinical images. Qualitative and quantitative comparison of these ventricular geometry reconstructions showed that the variational implicit functions approach performed better than others. Additionally, the outcomes of electrophysiological simulations (sinus rhythm activation maps and pseudo-ECGs) conducted using models based on the various reconstructions were compared. These electrophysiological simulations demonstrated that our implementation of the variational implicit functions-based method had the best accuracy. PMID:25148771

Diagnostic Machine Learning Models for Acute Abdominal Pain: Towards an e-Learning Tool for Medical Students.

PubMed

Khumrin, Piyapong; Ryan, Anna; Judd, Terry; Verspoor, Karin

2017-01-01

Computer-aided learning systems (e-learning systems) can help medical students gain more experience with diagnostic reasoning and decision making. Within this context, providing feedback that matches students' needs (i.e. personalised feedback) is both critical and challenging. In this paper, we describe the development of a machine learning model to support medical students' diagnostic decisions. Machine learning models were trained on 208 clinical cases presenting with abdominal pain, to predict five diagnoses. We assessed which of these models are likely to be most effective for use in an e-learning tool that allows students to interact with a virtual patient. The broader goal is to utilise these models to generate personalised feedback based on the specific patient information requested by students and their active diagnostic hypotheses.

Clinical use of computational modeling for surgical planning of arteriovenous fistula for hemodialysis.

PubMed

Bozzetto, Michela; Rota, Stefano; Vigo, Valentina; Casucci, Francesco; Lomonte, Carlo; Morale, Walter; Senatore, Massimo; Tazza, Luigi; Lodi, Massimo; Remuzzi, Giuseppe; Remuzzi, Andrea

2017-03-14

Autogenous arteriovenous fistula (AVF) is the best vascular access (VA) for hemodialysis, but its creation is still a critical procedure. Physical examination, vascular mapping and doppler ultrasound (DUS) evaluation are recommended for AVF planning, but they can not provide direct indication on AVF outcome. We recently developed and validated in a clinical trial a patient-specific computational model to predict pre-operatively the blood flow volume (BFV) in AVF for different surgical configuration on the basis of demographic, clinical and DUS data. In the present investigation we tested power of prediction and usability of the computational model in routine clinical setting. We developed a web-based system (AVF.SIM) that integrates the computational model in a single procedure, including data collection and transfer, simulation management and data storage. A usability test on observational data was designed to compare predicted vs. measured BFV and evaluate the acceptance of the system in the clinical setting. Six Italian nephrology units were involved in the evaluation for a 6-month period that included all incident dialysis patients with indication for AVF surgery. Out of the 74 patients, complete data from 60 patients were included in the final dataset. Predicted brachial BFV at 40 days after surgery showed a good correlation with measured values (in average 787 ± 306 vs. 751 ± 267 mL/min, R = 0.81, p < 0.001). For distal AVFs the mean difference (±SD) between predicted vs. measured BFV was -2.0 ± 20.9%, with 50% of predicted values in the range of 86-121% of measured BFV. Feedbacks provided by clinicians indicate that AVF.SIM is easy to use and well accepted in clinical routine, with limited additional workload. Clinical use of computational modeling for AVF surgical planning can help the surgeon to select the best surgical strategy, reducing AVF early failures and complications. This approach allows individualization of VA care, with the aim to reduce the costs associated with VA dysfunction, and to improve AVF clinical outcome.

A Method for Assessing Ground-Truth Accuracy of the 5DCT Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dou, Tai H., E-mail: tdou@mednet.ucla.edu; Thomas, David H.; O'Connell, Dylan P.

2015-11-15

Purpose: To develop a technique that assesses the accuracy of the breathing phase-specific volume image generation process by patient-specific breathing motion model using the original free-breathing computed tomographic (CT) scans as ground truths. Methods: Sixteen lung cancer patients underwent a previously published protocol in which 25 free-breathing fast helical CT scans were acquired with a simultaneous breathing surrogate. A patient-specific motion model was constructed based on the tissue displacements determined by a state-of-the-art deformable image registration. The first image was arbitrarily selected as the reference image. The motion model was used, along with the free-breathing phase information of the originalmore » 25 image datasets, to generate a set of deformation vector fields that mapped the reference image to the 24 nonreference images. The high-pitch helically acquired original scans served as ground truths because they captured the instantaneous tissue positions during free breathing. Image similarity between the simulated and the original scans was assessed using deformable registration that evaluated the pointwise discordance throughout the lungs. Results: Qualitative comparisons using image overlays showed excellent agreement between the simulated images and the original images. Even large 2-cm diaphragm displacements were very well modeled, as was sliding motion across the lung–chest wall boundary. The mean error across the patient cohort was 1.15 ± 0.37 mm, and the mean 95th percentile error was 2.47 ± 0.78 mm. Conclusion: The proposed ground truth–based technique provided voxel-by-voxel accuracy analysis that could identify organ-specific or tumor-specific motion modeling errors for treatment planning. Despite a large variety of breathing patterns and lung deformations during the free-breathing scanning session, the 5-dimensionl CT technique was able to accurately reproduce the original helical CT scans, suggesting its applicability to a wide range of patients.« less

Quantitative assessment of paravalvular leakage after transcatheter aortic valve replacement using a patient-specific pulsatile flow model.

PubMed

Tanaka, Yutaka; Saito, Shigeru; Sasuga, Saeko; Takahashi, Azuma; Aoyama, Yusuke; Obama, Kazuto; Umezu, Mitsuo; Iwasaki, Kiyotaka

2018-05-01

Quantitative assessment of post-transcatheter aortic valve replacement (TAVR) aortic regurgitation (AR) remains challenging. We developed patient-specific anatomical models with pulsatile flow circuit and investigated factors associated with AR after TAVR. Based on pre-procedural computed tomography (CT) data of the six patients who underwent transfemoral TAVR using a 23-mm SAPIEN XT, anatomically and mechanically equivalent aortic valve models were developed. Forward flow and heart rate of each patient in two days after TAVR were duplicated under mean aortic pressure of 80mmHg. Paravalvular leakage (PVL) volume in basal and additional conditions was measured for each model using an electromagnetic flow sensor. Incompletely apposed tract between the transcatheter and aortic valves was examined using a micro-CT. PVL volume in each patient-specific model was consistent with each patient's PVL grade, and was affected by hemodynamic conditions. PVL and total regurgitation volume increased with the mean aortic pressure, whereas closing volume did not change. In contrast, closing volume increased proportionately with heart rate, but PVL did not change. The minimal cross-sectional gap had a positive correlation with the PVL volumes (r=0.89, P=0.02). The gap areas typically occurred in the vicinity of the bulky calcified nodules under the native commissure. PVL volume, which could be affected by hemodynamic conditions, was significantly associated with the minimal cross-sectional gap area between the aortic annulus and the stent frame. These data may improve our understanding of the mechanism of the occurrence of post-TAVR PVL. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

The acceptance of virtual reality devices for cognitive rehabilitation: a report of positive results with schizophrenia.

PubMed

da Costa, Rosa Maria Esteves Moreira; de Carvalho, Luís Alfredo Vidal

2004-03-01

This study presents a process of virtual environment development supported by a cognitive model that is specific to cognitive deficits of diverse disorders or traumatic brain injury, and evaluates the acceptance of computer devices by a group of schizophrenic patients. The subjects that participated in this experiment accepted to work with computers and immersive glasses and demonstrated a high level of interest in the proposed tasks. No problems of illness have been observed. This experiment indicated that further research projects must be carried out to verify the value of virtual reality technology for cognitive rehabilitation of psychiatric patients. The results of the current study represent a small but necessary step in the realization of that potential.

3D patient-specific models for left atrium characterization to support ablation in atrial fibrillation patients.

PubMed

Valinoti, Maddalena; Fabbri, Claudio; Turco, Dario; Mantovan, Roberto; Pasini, Antonio; Corsi, Cristiana

2018-01-01

Radiofrequency ablation (RFA) is an important and promising therapy for atrial fibrillation (AF) patients. Optimization of patient selection and the availability of an accurate anatomical guide could improve RFA success rate. In this study we propose a unified, fully automated approach to build a 3D patient-specific left atrium (LA) model including pulmonary veins (PVs) in order to provide an accurate anatomical guide during RFA and without PVs in order to characterize LA volumetry and support patient selection for AF ablation. Magnetic resonance data from twenty-six patients referred for AF RFA were processed applying an edge-based level set approach guided by a phase-based edge detector to obtain the 3D LA model with PVs. An automated technique based on the shape diameter function was designed and applied to remove PVs and compute LA volume. 3D LA models were qualitatively compared with 3D LA surfaces acquired during the ablation procedure. An expert radiologist manually traced the LA on MR images twice. LA surfaces from the automatic approach and manual tracing were compared by mean surface-to-surface distance. In addition, LA volumes were compared with volumes from manual segmentation by linear and Bland-Altman analyses. Qualitative comparison of 3D LA models showed several inaccuracies, in particular PVs reconstruction was not accurate and left atrial appendage was missing in the model obtained during RFA procedure. LA surfaces were very similar (mean surface-to-surface distance: 2.3±0.7mm). LA volumes were in excellent agreement (y=1.03x-1.4, r=0.99, bias=-1.37ml (-1.43%) SD=2.16ml (2.3%), mean percentage difference=1.3%±2.1%). Results showed the proposed 3D patient-specific LA model with PVs is able to better describe LA anatomy compared to models derived from the navigation system, thus potentially improving electrograms and voltage information location and reducing fluoroscopic time during RFA. Quantitative assessment of LA volume derived from our 3D LA model without PVs is also accurate and may provide important information for patient selection for RFA. Copyright © 2017 Elsevier Inc. All rights reserved.

Management of queues in out-patient departments: the use of computer simulation.

PubMed

Aharonson-Daniel, L; Paul, R J; Hedley, A J

1996-01-01

Notes that patients attending public outpatient departments in Hong Kong spend a long time waiting for a short consultation, that clinics are congested and that both staff and patients are dissatisfied. Points out that experimentation of management changes in a busy clinical environment can be both expensive and difficult. Demonstrates computerized simulation modelling as a potential tool for clarifying processes occurring within such systems, improving clinic operation by suggesting possible answers to problems identified and evaluating the solutions, without interfering with the clinic routine. Adds that solutions can be implemented after they had proved to be successful on the model. Demonstrates some ways in which managers in health care facilities can benefit from the use of computerized simulation modelling. Specifically, shows the effect of changing the duration of consultation and the effect of the application of an appointment system on patients' waiting time.

Anatomy-based transmission factors for technique optimization in portable chest x-ray

NASA Astrophysics Data System (ADS)

Liptak, Christopher L.; Tovey, Deborah; Segars, William P.; Dong, Frank D.; Li, Xiang

2015-03-01

Portable x-ray examinations often account for a large percentage of all radiographic examinations. Currently, portable examinations do not employ automatic exposure control (AEC). To aid in the design of a size-specific technique chart, acrylic slabs of various thicknesses are often used to estimate x-ray transmission for patients of various body thicknesses. This approach, while simple, does not account for patient anatomy, tissue heterogeneity, and the attenuation properties of the human body. To better account for these factors, in this work, we determined x-ray transmission factors using computational patient models that are anatomically realistic. A Monte Carlo program was developed to model a portable x-ray system. Detailed modeling was done of the x-ray spectrum, detector positioning, collimation, and source-to-detector distance. Simulations were performed using 18 computational patient models from the extended cardiac-torso (XCAT) family (9 males, 9 females; age range: 2-58 years; weight range: 12-117 kg). The ratio of air kerma at the detector with and without a patient model was calculated as the transmission factor. Our study showed that the transmission factor decreased exponentially with increasing patient thickness. For the range of patient thicknesses examined (12-28 cm), the transmission factor ranged from approximately 21% to 1.9% when the air kerma used in the calculation represented an average over the entire imaging field of view. The transmission factor ranged from approximately 21% to 3.6% when the air kerma used in the calculation represented the average signals from two discrete AEC cells behind the lung fields. These exponential relationships may be used to optimize imaging techniques for patients of various body thicknesses to aid in the design of clinical technique charts.

Neural network modeling for surgical decisions on traumatic brain injury patients.

PubMed

Li, Y C; Liu, L; Chiu, W T; Jian, W S

2000-01-01

Computerized medical decision support systems have been a major research topic in recent years. Intelligent computer programs were implemented to aid physicians and other medical professionals in making difficult medical decisions. This report compares three different mathematical models for building a traumatic brain injury (TBI) medical decision support system (MDSS). These models were developed based on a large TBI patient database. This MDSS accepts a set of patient data such as the types of skull fracture, Glasgow Coma Scale (GCS), episode of convulsion and return the chance that a neurosurgeon would recommend an open-skull surgery for this patient. The three mathematical models described in this report including a logistic regression model, a multi-layer perceptron (MLP) neural network and a radial-basis-function (RBF) neural network. From the 12,640 patients selected from the database. A randomly drawn 9480 cases were used as the training group to develop/train our models. The other 3160 cases were in the validation group which we used to evaluate the performance of these models. We used sensitivity, specificity, areas under receiver-operating characteristics (ROC) curve and calibration curves as the indicator of how accurate these models are in predicting a neurosurgeon's decision on open-skull surgery. The results showed that, assuming equal importance of sensitivity and specificity, the logistic regression model had a (sensitivity, specificity) of (73%, 68%), compared to (80%, 80%) from the RBF model and (88%, 80%) from the MLP model. The resultant areas under ROC curve for logistic regression, RBF and MLP neural networks are 0.761, 0.880 and 0.897, respectively (P < 0.05). Among these models, the logistic regression has noticeably poorer calibration. This study demonstrated the feasibility of applying neural networks as the mechanism for TBI decision support systems based on clinical databases. The results also suggest that neural networks may be a better solution for complex, non-linear medical decision support systems than conventional statistical techniques such as logistic regression.

Bridging the gap between computation and clinical biology: validation of cable theory in humans

PubMed Central

Finlay, Malcolm C.; Xu, Lei; Taggart, Peter; Hanson, Ben; Lambiase, Pier D.

2013-01-01

Introduction: Computerized simulations of cardiac activity have significantly contributed to our understanding of cardiac electrophysiology, but techniques of simulations based on patient-acquired data remain in their infancy. We sought to integrate data acquired from human electrophysiological studies into patient-specific models, and validated this approach by testing whether electrophysiological responses to sequential premature stimuli could be predicted in a quantitatively accurate manner. Methods: Eleven patients with structurally normal hearts underwent electrophysiological studies. Semi-automated analysis was used to reconstruct activation and repolarization dynamics for each electrode. This S2 extrastimuli data was used to inform individualized models of cardiac conduction, including a novel derivation of conduction velocity restitution. Activation dynamics of multiple premature extrastimuli were then predicted from this model and compared against measured patient data as well as data derived from the ten-Tusscher cell-ionic model. Results: Activation dynamics following a premature S3 were significantly different from those after an S2. Patient specific models demonstrated accurate prediction of the S3 activation wave, (Pearson's R2 = 0.90, median error 4%). Examination of the modeled conduction dynamics allowed inferences into the spatial dispersion of activation delay. Further validation was performed against data from the ten-Tusscher cell-ionic model, with our model accurately recapitulating predictions of repolarization times (R2 = 0.99). Conclusions: Simulations based on clinically acquired data can be used to successfully predict complex activation patterns following sequential extrastimuli. Such modeling techniques may be useful as a method of incorporation of clinical data into predictive models. PMID:24027527

PARAMO: A Parallel Predictive Modeling Platform for Healthcare Analytic Research using Electronic Health Records

PubMed Central

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R.; Stewart, Walter F.; Malin, Bradley; Sun, Jimeng

2014-01-01

Objective Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: 1) cohort construction, 2) feature construction, 3) cross-validation, 4) feature selection, and 5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. Methods To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which 1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, 2) schedules the tasks in a topological ordering of the graph, and 3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. Results We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3 hours in parallel compared to 9 days if running sequentially. Conclusion This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. PMID:24370496

PARAMO: a PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records.

PubMed

Ng, Kenney; Ghoting, Amol; Steinhubl, Steven R; Stewart, Walter F; Malin, Bradley; Sun, Jimeng

2014-04-01

Healthcare analytics research increasingly involves the construction of predictive models for disease targets across varying patient cohorts using electronic health records (EHRs). To facilitate this process, it is critical to support a pipeline of tasks: (1) cohort construction, (2) feature construction, (3) cross-validation, (4) feature selection, and (5) classification. To develop an appropriate model, it is necessary to compare and refine models derived from a diversity of cohorts, patient-specific features, and statistical frameworks. The goal of this work is to develop and evaluate a predictive modeling platform that can be used to simplify and expedite this process for health data. To support this goal, we developed a PARAllel predictive MOdeling (PARAMO) platform which (1) constructs a dependency graph of tasks from specifications of predictive modeling pipelines, (2) schedules the tasks in a topological ordering of the graph, and (3) executes those tasks in parallel. We implemented this platform using Map-Reduce to enable independent tasks to run in parallel in a cluster computing environment. Different task scheduling preferences are also supported. We assess the performance of PARAMO on various workloads using three datasets derived from the EHR systems in place at Geisinger Health System and Vanderbilt University Medical Center and an anonymous longitudinal claims database. We demonstrate significant gains in computational efficiency against a standard approach. In particular, PARAMO can build 800 different models on a 300,000 patient data set in 3h in parallel compared to 9days if running sequentially. This work demonstrates that an efficient parallel predictive modeling platform can be developed for EHR data. This platform can facilitate large-scale modeling endeavors and speed-up the research workflow and reuse of health information. This platform is only a first step and provides the foundation for our ultimate goal of building analytic pipelines that are specialized for health data researchers. Copyright © 2013 Elsevier Inc. All rights reserved.

Numerical investigation of pulmonary drug delivery under mechanical ventilation conditions

NASA Astrophysics Data System (ADS)

Banerjee, Arindam; van Rhein, Timothy

2012-11-01

The effects of mechanical ventilation waveform on fluid flow and particle deposition were studied in a computer model of the human airways. The frequency with which aerosolized drugs are delivered to mechanically ventilated patients demonstrates the importance of understanding the effects of ventilation parameters. This study focuses specifically on the effects of mechanical ventilation waveforms using a computer model of the airways of patient undergoing mechanical ventilation treatment from the endotracheal tube to generation G7. Waveforms were modeled as those commonly used by commercial mechanical ventilators. Turbulence was modeled with LES. User defined particle force models were used to model the drag force with the Cunningham correction factor, the Saffman lift force, and Brownian motion force. The endotracheal tube (ETT) was found to be an important geometric feature, causing a fluid jet towards the right main bronchus, increased turbulence, and a recirculation zone in the right main bronchus. In addition to the enhanced deposition seen at the carinas of the airway bifurcations, enhanced deposition was also seen in the right main bronchus due to impaction and turbulent dispersion resulting from the fluid structures created by the ETT. Authors acknowledge financial support through University of Missouri Research Board Award.

The role of technology and engineering models in transforming healthcare.

PubMed

Pavel, Misha; Jimison, Holly Brugge; Wactlar, Howard D; Hayes, Tamara L; Barkis, Will; Skapik, Julia; Kaye, Jeffrey

2013-01-01

The healthcare system is in crisis due to challenges including escalating costs, the inconsistent provision of care, an aging population, and high burden of chronic disease related to health behaviors. Mitigating this crisis will require a major transformation of healthcare to be proactive, preventive, patient-centered, and evidence-based with a focus on improving quality-of-life. Information technology, networking, and biomedical engineering are likely to be essential in making this transformation possible with the help of advances, such as sensor technology, mobile computing, machine learning, etc. This paper has three themes: 1) motivation for a transformation of healthcare; 2) description of how information technology and engineering can support this transformation with the help of computational models; and 3) a technical overview of several research areas that illustrate the need for mathematical modeling approaches, ranging from sparse sampling to behavioral phenotyping and early detection. A key tenet of this paper concerns complementing prior work on patient-specific modeling and simulation by modeling neuropsychological, behavioral, and social phenomena. The resulting models, in combination with frequent or continuous measurements, are likely to be key components of health interventions to enhance health and wellbeing and the provision of healthcare.

In Vivo Knee Contact Force Prediction Using Patient-Specific Musculoskeletal Geometry in a Segment-Based Computational Model.

PubMed

Ding, Ziyun; Nolte, Daniel; Kit Tsang, Chui; Cleather, Daniel J; Kedgley, Angela E; Bull, Anthony M J

2016-02-01

Segment-based musculoskeletal models allow the prediction of muscle, ligament, and joint forces without making assumptions regarding joint degrees-of-freedom (DOF). The dataset published for the "Grand Challenge Competition to Predict in vivo Knee Loads" provides directly measured tibiofemoral contact forces for activities of daily living (ADL). For the Sixth Grand Challenge Competition to Predict in vivo Knee Loads, blinded results for "smooth" and "bouncy" gait trials were predicted using a customized patient-specific musculoskeletal model. For an unblinded comparison, the following modifications were made to improve the predictions: further customizations, including modifications to the knee center of rotation; reductions to the maximum allowable muscle forces to represent known loss of strength in knee arthroplasty patients; and a kinematic constraint to the hip joint to address the sensitivity of the segment-based approach to motion tracking artifact. For validation, the improved model was applied to normal gait, squat, and sit-to-stand for three subjects. Comparisons of the predictions with measured contact forces showed that segment-based musculoskeletal models using patient-specific input data can estimate tibiofemoral contact forces with root mean square errors (RMSEs) of 0.48-0.65 times body weight (BW) for normal gait trials. Comparisons between measured and predicted tibiofemoral contact forces yielded an average coefficient of determination of 0.81 and RMSEs of 0.46-1.01 times BW for squatting and 0.70-0.99 times BW for sit-to-stand tasks. This is comparable to the best validations in the literature using alternative models.

Shaping the future through innovations: From medical imaging to precision medicine.

PubMed

Comaniciu, Dorin; Engel, Klaus; Georgescu, Bogdan; Mansi, Tommaso

2016-10-01

Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information represents a critical component required for advancing precision medicine into clinical practice. This manuscript describes recently developed technologies for better handling of image information: photorealistic visualization of medical images with Cinematic Rendering, artificial agents for in-depth image understanding, support for minimally invasive procedures, and patient-specific computational models with enhanced predictive power. Throughout the manuscript we will analyze the capabilities of such technologies and extrapolate on their potential impact to advance the quality of medical care, while reducing its cost. Copyright © 2016 Elsevier B.V. All rights reserved.

Blood Flow in Idealized Vascular Access for Hemodialysis: A Review of Computational Studies.

PubMed

Ene-Iordache, Bogdan; Remuzzi, Andrea

2017-09-01

Although our understanding of the failure mechanism of vascular access for hemodialysis has increased substantially, this knowledge has not translated into successful therapies. Despite advances in technology, it is recognized that vascular access is difficult to maintain, due to complications such as intimal hyperplasia. Computational studies have been used to estimate hemodynamic changes induced by vascular access creation. Due to the heterogeneity of patient-specific geometries, and difficulties with obtaining reliable models of access vessels, idealized models were often employed. In this review we analyze the knowledge gained with the use of computational such simplified models. A review of the literature was conducted, considering studies employing a computational fluid dynamics approach to gain insights into the flow field phenotype that develops in idealized models of vascular access. Several important discoveries have originated from idealized model studies, including the detrimental role of disturbed flow and turbulent flow, and the beneficial role of spiral flow in intimal hyperplasia. The general flow phenotype was consistent among studies, but findings were not treated homogeneously since they paralleled achievements in cardiovascular biomechanics which spanned over the last two decades. Computational studies in idealized models are important for studying local blood flow features and evaluating new concepts that may improve the patency of vascular access for hemodialysis. For future studies we strongly recommend numerical modelling targeted at accurately characterizing turbulent flows and multidirectional wall shear disturbances.

Lung deformations and radiation-induced regional lung collapse in patients treated with stereotactic body radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diot, Quentin, E-mail: quentin.diot@ucdenver.edu; Kavanagh, Brian; Vinogradskiy, Yevgeniy

2015-11-15

Purpose: To differentiate radiation-induced fibrosis from regional lung collapse outside of the high dose region in patients treated with stereotactic body radiation therapy (SBRT) for lung tumors. Methods: Lung deformation maps were computed from pre-treatment and post-treatment computed tomography (CT) scans using a point-to-point translation method. Fifty anatomical landmarks inside the lung (vessel or airway branches) were matched on planning and follow-up scans for the computation process. Two methods using the deformation maps were developed to differentiate regional lung collapse from fibrosis: vector field and Jacobian methods. A total of 40 planning and follow-ups CT scans were analyzed for 20more » lung SBRT patients. Results: Regional lung collapse was detected in 15 patients (75%) using the vector field method, in ten patients (50%) using the Jacobian method, and in 12 patients (60%) by radiologists. In terms of sensitivity and specificity the Jacobian method performed better. Only weak correlations were observed between the dose to the proximal airways and the occurrence of regional lung collapse. Conclusions: The authors presented and evaluated two novel methods using anatomical lung deformations to investigate lung collapse and fibrosis caused by SBRT treatment. Differentiation of these distinct physiological mechanisms beyond what is usually labeled “fibrosis” is necessary for accurate modeling of lung SBRT-induced injuries. With the help of better models, it becomes possible to expand the therapeutic benefits of SBRT to a larger population of lung patients with large or centrally located tumors that were previously considered ineligible.« less

Using patient-specific phantoms to evaluate deformable image registration algorithms for adaptive radiation therapy

PubMed Central

Stanley, Nick; Glide-Hurst, Carri; Kim, Jinkoo; Adams, Jeffrey; Li, Shunshan; Wen, Ning; Chetty, Indrin J.; Zhong, Hualiang

2014-01-01

The quality of adaptive treatment planning depends on the accuracy of its underlying deformable image registration (DIR). The purpose of this study is to evaluate the performance of two DIR algorithms, B-spline–based deformable multipass (DMP) and deformable demons (Demons), implemented in a commercial software package. Evaluations were conducted using both computational and physical deformable phantoms. Based on a finite element method (FEM), a total of 11 computational models were developed from a set of CT images acquired from four lung and one prostate cancer patients. FEM generated displacement vector fields (DVF) were used to construct the lung and prostate image phantoms. Based on a fast-Fourier transform technique, image noise power spectrum was incorporated into the prostate image phantoms to create simulated CBCT images. The FEM-DVF served as a gold standard for verification of the two registration algorithms performed on these phantoms. The registration algorithms were also evaluated at the homologous points quantified in the CT images of a physical lung phantom. The results indicated that the mean errors of the DMP algorithm were in the range of 1.0 ~ 3.1 mm for the computational phantoms and 1.9 mm for the physical lung phantom. For the computational prostate phantoms, the corresponding mean error was 1.0–1.9 mm in the prostate, 1.9–2.4 mm in the rectum, and 1.8–2.1 mm over the entire patient body. Sinusoidal errors induced by B-spline interpolations were observed in all the displacement profiles of the DMP registrations. Regions of large displacements were observed to have more registration errors. Patient-specific FEM models have been developed to evaluate the DIR algorithms implemented in the commercial software package. It has been found that the accuracy of these algorithms is patient-dependent and related to various factors including tissue deformation magnitudes and image intensity gradients across the regions of interest. This may suggest that DIR algorithms need to be verified for each registration instance when implementing adaptive radiation therapy. PMID:24257278

Efficiency of timing delays and electrode positions in optimization of biventricular pacing: a simulation study.

PubMed

Miri, Raz; Graf, Iulia M; Dössel, Olaf

2009-11-01

Electrode positions and timing delays influence the efficacy of biventricular pacing (BVP). Accordingly, this study focuses on BVP optimization, using a detailed 3-D electrophysiological model of the human heart, which is adapted to patient-specific anatomy and pathophysiology. The research is effectuated on ten heart models with left bundle branch block and myocardial infarction derived from magnetic resonance and computed tomography data. Cardiac electrical activity is simulated with the ten Tusscher cell model and adaptive cellular automaton at physiological and pathological conduction levels. The optimization methods are based on a comparison between the electrical response of the healthy and diseased heart models, measured in terms of root mean square error (E(RMS)) of the excitation front and the QRS duration error (E(QRS)). Intra- and intermethod associations of the pacing electrodes and timing delays variables were analyzed with statistical methods, i.e., t -test for dependent data, one-way analysis of variance for electrode pairs, and Pearson model for equivalent parameters from the two optimization methods. The results indicate that lateral the left ventricle and the upper or middle septal area are frequently (60% of cases) the optimal positions of the left and right electrodes, respectively. Statistical analysis proves that the two optimization methods are in good agreement. In conclusion, a noninvasive preoperative BVP optimization strategy based on computer simulations can be used to identify the most beneficial patient-specific electrode configuration and timing delays.

Working memory contributions to reinforcement learning impairments in schizophrenia.

PubMed

Collins, Anne G E; Brown, Jaime K; Gold, James M; Waltz, James A; Frank, Michael J

2014-10-08

Previous research has shown that patients with schizophrenia are impaired in reinforcement learning tasks. However, behavioral learning curves in such tasks originate from the interaction of multiple neural processes, including the basal ganglia- and dopamine-dependent reinforcement learning (RL) system, but also prefrontal cortex-dependent cognitive strategies involving working memory (WM). Thus, it is unclear which specific system induces impairments in schizophrenia. We recently developed a task and computational model allowing us to separately assess the roles of RL (slow, cumulative learning) mechanisms versus WM (fast but capacity-limited) mechanisms in healthy adult human subjects. Here, we used this task to assess patients' specific sources of impairments in learning. In 15 separate blocks, subjects learned to pick one of three actions for stimuli. The number of stimuli to learn in each block varied from two to six, allowing us to separate influences of capacity-limited WM from the incremental RL system. As expected, both patients (n = 49) and healthy controls (n = 36) showed effects of set size and delay between stimulus repetitions, confirming the presence of working memory effects. Patients performed significantly worse than controls overall, but computational model fits and behavioral analyses indicate that these deficits could be entirely accounted for by changes in WM parameters (capacity and reliability), whereas RL processes were spared. These results suggest that the working memory system contributes strongly to learning impairments in schizophrenia. Copyright © 2014 the authors 0270-6474/14/3413747-10$15.00/0.

Regional Lung Ventilation Analysis Using Temporally Resolved Magnetic Resonance Imaging.

PubMed

Kolb, Christoph; Wetscherek, Andreas; Buzan, Maria Teodora; Werner, René; Rank, Christopher M; Kachelrie, Marc; Kreuter, Michael; Dinkel, Julien; Heuel, Claus Peter; Maier-Hein, Klaus

We propose a computer-aided method for regional ventilation analysis and observation of lung diseases in temporally resolved magnetic resonance imaging (4D MRI). A shape model-based segmentation and registration workflow was used to create an atlas-derived reference system in which regional tissue motion can be quantified and multimodal image data can be compared regionally. Model-based temporal registration of the lung surfaces in 4D MRI data was compared with the registration of 4D computed tomography (CT) images. A ventilation analysis was performed on 4D MR images of patients with lung fibrosis; 4D MR ventilation maps were compared with corresponding diagnostic 3D CT images of the patients and 4D CT maps of subjects without impaired lung function (serving as reference). Comparison between the computed patient-specific 4D MR regional ventilation maps and diagnostic CT images shows good correlation in conspicuous regions. Comparison to 4D CT-derived ventilation maps supports the plausibility of the 4D MR maps. Dynamic MRI-based flow-volume loops and spirograms further visualize the free-breathing behavior. The proposed methods allow for 4D MR-based regional analysis of tissue dynamics and ventilation in spontaneous breathing and comparison of patient data. The proposed atlas-based reference coordinate system provides an automated manner of annotating and comparing multimodal lung image data.

Estimating the hemodynamic impact of interventional treatments of aneurysms: numerical simulation with experimental validation: technical case report.

PubMed

Acevedo-Bolton, Gabriel; Jou, Liang-Der; Dispensa, Bradley P; Lawton, Michael T; Higashida, Randall T; Martin, Alastair J; Young, William L; Saloner, David

2006-08-01

The goal of this study was to use phase-contrast magnetic resonance imaging and computational fluid dynamics to estimate the hemodynamic outcome that might result from different interventional options for treating a patient with a giant fusiform aneurysm. We followed a group of patients with giant intracranial aneurysms who have no clear surgical options. One patient demonstrated dramatic aneurysm growth and was selected for further analysis. The aneurysm geometry and input and output flow conditions were measured with contrast-enhanced magnetic resonance angiography and phase-contrast magnetic resonance imaging. The data was imported into a computational fluid dynamics program and the velocity fields and wall shear stress distributions were calculated for the presenting physiological condition and for cases in which the opposing vertebral arteries were either occluded or opened. These models were validated with in vitro flow experiments using a geometrically exact silicone flow phantom. Simulation indicated that altering the flow ratio in the two vertebrals would deflect the main blood jet into the aneurysm belly, and that this would likely reduce the extent of the region of low wall shear stress in the growth zone. Computational fluid dynamics flow simulations in a complex patient-specific aneurysm geometry were validated by in vivo and in vitro phase-contrast magnetic resonance imaging, and were shown to be useful in modeling the likely hemodynamic impact of interventional treatment of the aneurysm.

Brain shift computation using a fully nonlinear biomechanical model.

PubMed

Wittek, Adam; Kikinis, Ron; Warfield, Simon K; Miller, Karol

2005-01-01

In the present study, fully nonlinear (i.e. accounting for both geometric and material nonlinearities) patient specific finite element brain model was applied to predict deformation field within the brain during the craniotomy-induced brain shift. Deformation of brain surface was used as displacement boundary conditions. Application of the computed deformation field to align (i.e. register) the preoperative images with the intraoperative ones indicated that the model very accurately predicts the displacements of gravity centers of the lateral ventricles and tumor even for very limited information about the brain surface deformation. These results are sufficient to suggest that nonlinear biomechanical models can be regarded as one possible way of complementing medical image processing techniques when conducting nonrigid registration. Important advantage of such models over the linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain tissue stress-strain relationship is linear.

A multiscale modelling approach to understand atherosclerosis formation: A patient-specific case study in the aortic bifurcation

PubMed Central

Alimohammadi, Mona; Pichardo-Almarza, Cesar; Agu, Obiekezie; Díaz-Zuccarini, Vanessa

2017-01-01

Atherogenesis, the formation of plaques in the wall of blood vessels, starts as a result of lipid accumulation (low-density lipoprotein cholesterol) in the vessel wall. Such accumulation is related to the site of endothelial mechanotransduction, the endothelial response to mechanical stimuli and haemodynamics, which determines biochemical processes regulating the vessel wall permeability. This interaction between biomechanical and biochemical phenomena is complex, spanning different biological scales and is patient-specific, requiring tools able to capture such mathematical and biological complexity in a unified framework. Mathematical models offer an elegant and efficient way of doing this, by taking into account multifactorial and multiscale processes and mechanisms, in order to capture the fundamentals of plaque formation in individual patients. In this study, a mathematical model to understand plaque and calcification locations is presented: this model provides a strong interpretability and physical meaning through a multiscale, complex index or metric (the penetration site of low-density lipoprotein cholesterol, expressed as volumetric flux). Computed tomography scans of the aortic bifurcation and iliac arteries are analysed and compared with the results of the multifactorial model. The results indicate that the model shows potential to predict the majority of the plaque locations, also not predicting regions where plaques are absent. The promising results from this case study provide a proof of concept that can be applied to a larger patient population. PMID:28427316

Patient-specific dose estimation for pediatric chest CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Xiang; Samei, Ehsan; Segars, W. Paul

2008-12-15

Current methods for organ and effective dose estimations in pediatric CT are largely patient generic. Physical phantoms and computer models have only been developed for standard/limited patient sizes at discrete ages (e.g., 0, 1, 5, 10, 15 years old) and do not reflect the variability of patient anatomy and body habitus within the same size/age group. In this investigation, full-body computer models of seven pediatric patients in the same size/protocol group (weight: 11.9-18.2 kg) were created based on the patients' actual multi-detector array CT (MDCT) data. Organs and structures in the scan coverage were individually segmented. Other organs and structuresmore » were created by morphing existing adult models (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. Organ and effective dose of these patients from a chest MDCT scan protocol (64 slice LightSpeed VCT scanner, 120 kVp, 70 or 75 mA, 0.4 s gantry rotation period, pitch of 1.375, 20 mm beam collimation, and small body scan field-of-view) was calculated using a Monte Carlo program previously developed and validated to simulate radiation transport in the same CT system. The seven patients had normalized effective dose of 3.7-5.3 mSv/100 mAs (coefficient of variation: 10.8%). Normalized lung dose and heart dose were 10.4-12.6 mGy/100 mAs and 11.2-13.3 mGy/100 mAs, respectively. Organ dose variations across the patients were generally small for large organs in the scan coverage (<7%), but large for small organs in the scan coverage (9%-18%) and for partially or indirectly exposed organs (11%-77%). Normalized effective dose correlated weakly with body weight (correlation coefficient: r=-0.80). Normalized lung dose and heart dose correlated strongly with mid-chest equivalent diameter (lung: r=-0.99, heart: r=-0.93); these strong correlation relationships can be used to estimate patient-specific organ dose for any other patient in the same size/protocol group who undergoes the chest scan. In summary, this work reported the first assessment of dose variations across pediatric CT patients in the same size/protocol group due to the variability of patient anatomy and body habitus and provided a previously unavailable method for patient-specific organ dose estimation, which will help in assessing patient risk and optimizing dose reduction strategies, including the development of scan protocols.« less

TU-FG-209-12: Treatment Site and View Recognition in X-Ray Images with Hierarchical Multiclass Recognition Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, X; Mazur, T; Yang, D

Purpose: To investigate an approach of automatically recognizing anatomical sites and imaging views (the orientation of the image acquisition) in 2D X-ray images. Methods: A hierarchical (binary tree) multiclass recognition model was developed to recognize the treatment sites and views in x-ray images. From top to bottom of the tree, the treatment sites are grouped hierarchically from more general to more specific. Each node in the hierarchical model was designed to assign images to one of two categories of anatomical sites. The binary image classification function of each node in the hierarchical model is implemented by using a PCA transformationmore » and a support vector machine (SVM) model. The optimal PCA transformation matrices and SVM models are obtained by learning from a set of sample images. Alternatives of the hierarchical model were developed to support three scenarios of site recognition that may happen in radiotherapy clinics, including two or one X-ray images with or without view information. The performance of the approach was tested with images of 120 patients from six treatment sites – brain, head-neck, breast, lung, abdomen and pelvis – with 20 patients per site and two views (AP and RT) per patient. Results: Given two images in known orthogonal views (AP and RT), the hierarchical model achieved a 99% average F1 score to recognize the six sites. Site specific view recognition models have 100 percent accuracy. The computation time to process a new patient case (preprocessing, site and view recognition) is 0.02 seconds. Conclusion: The proposed hierarchical model of site and view recognition is effective and computationally efficient. It could be useful to automatically and independently confirm the treatment sites and views in daily setup x-ray 2D images. It could also be applied to guide subsequent image processing tasks, e.g. site and view dependent contrast enhancement and image registration. The senior author received research grants from ViewRay Inc. and Varian Medical System.« less

Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

PubMed Central

Schiavazzi, Daniele E.; Baretta, Alessia; Pennati, Giancarlo; Hsia, Tain-Yen; Marsden, Alison L.

2017-01-01

Summary Computational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. PMID:27155892

RFA Guardian: Comprehensive Simulation of Radiofrequency Ablation Treatment of Liver Tumors.

PubMed

Voglreiter, Philip; Mariappan, Panchatcharam; Pollari, Mika; Flanagan, Ronan; Blanco Sequeiros, Roberto; Portugaller, Rupert Horst; Fütterer, Jurgen; Schmalstieg, Dieter; Kolesnik, Marina; Moche, Michael

2018-01-15

The RFA Guardian is a comprehensive application for high-performance patient-specific simulation of radiofrequency ablation of liver tumors. We address a wide range of usage scenarios. These include pre-interventional planning, sampling of the parameter space for uncertainty estimation, treatment evaluation and, in the worst case, failure analysis. The RFA Guardian is the first of its kind that exhibits sufficient performance for simulating treatment outcomes during the intervention. We achieve this by combining a large number of high-performance image processing, biomechanical simulation and visualization techniques into a generalized technical workflow. Further, we wrap the feature set into a single, integrated application, which exploits all available resources of standard consumer hardware, including massively parallel computing on graphics processing units. This allows us to predict or reproduce treatment outcomes on a single personal computer with high computational performance and high accuracy. The resulting low demand for infrastructure enables easy and cost-efficient integration into the clinical routine. We present a number of evaluation cases from the clinical practice where users performed the whole technical workflow from patient-specific modeling to final validation and highlight the opportunities arising from our fast, accurate prediction techniques.

Computational fluid dynamics modelling in cardiovascular medicine

PubMed Central

Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P

2016-01-01

This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards ‘digital patient’ or ‘virtual physiological human’ representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. PMID:26512019

Computer use in primary care and patient-physician communication.

PubMed

Sobral, Dilermando; Rosenbaum, Marcy; Figueiredo-Braga, Margarida

2015-07-08

This study evaluated how physicians and patients perceive the impact of computer use on clinical communication, and how a patient-centered orientation can influence this impact. The study followed a descriptive cross-sectional design and included 106 family physicians and 392 patients. An original questionnaire assessed computer use, participants' perspective of its impact, and patient centered strategies. Physicians reported spending 42% of consultation time in contact with the computer. A negative impact of computer in patient-physician communication regarding the consultation length, confidentiality, maintaining eye contact, active listening to the patient, and ability to understand the patient was reported by physicians, while patients reported a positive effect for all the items. Physicians considered that the usual computer placement in their consultation room was significantly unfavorable to patient-physician communication. Physicians perceive the impact of computer use on patient-physician communication as negative, while patients have a positive perception of computer use on patient-physician communication. Consultation support can represent a challenge to physicians who recognize its negative impact in patient centered orientation. Medical education programs aiming to enhance specific communication skills and to better integrate computer use in primary care settings are needed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Determination of stimulation focality in heterogeneous head models during transcranial magnetic stimulation (TMS)

NASA Astrophysics Data System (ADS)

Lee, Erik; Hadimani, Ravi; Jiles, David

2015-03-01

Transcranial Magnetic Stimulation (TMS) is an increasingly popular tool used by both the scientific and medical community to understand and treat the brain. TMS has the potential to help people with a wide range of diseases such as Parkinson's, Alzheimer's, and PTSD, while currently being used to treat people with chronic, drug-resistant depression. Through computer simulations, we are able to see the electric field that TMS induces in anatomical human models, but there is no measure to quantify this electric field in a way that relates to a specific patient undergoing TMS therapy. We propose a way to quantify the focality of the induced electric field in a heterogeneous head model during TMS by relating the surface area of the brain being stimulated to the total volume of the brain being stimulated. This figure would be obtained by conducting finite element analysis (FEA) simulations of TMS therapy on a patient specific head model. Using this figure to assist in TMS therapy will allow clinicians and researchers to more accurately stimulate the desired region of a patient's brain and be more equipped to do comparative studies on the effects of TMS across different patients. This work was funded by the Carver Charitable Trust.

Computational studies of transthoracic and transvenous defibrillation in a detailed 3-D human thorax model.

PubMed

Jorgenson, D B; Haynor, D R; Bardy, G H; Kim, Y

1995-02-01

A method for constructing and solving detailed patient-specific 3-D finite element models of the human thorax is presented for use in defibrillation studies. The method utilizes the patient's own X-ray CT scan and a simplified meshing scheme to quickly and efficiently generate a model typically composed of approximately 400,000 elements. A parameter sensitivity study on one human thorax model to examine the effects of variation in assigned tissue resistivity values, level of anatomical detail included in the model, and number of CT slices used to produce the model is presented. Of the seven tissue types examined, the average left ventricular (LV) myocardial voltage gradient was most sensitive to the values of myocardial and blood resistivity. Incorrectly simplifying the model, for example modeling the heart as a homogeneous structure by ignoring the blood in the chambers, caused the average LV myocardial voltage gradient to increase by 12%. The sensitivity of the model to variations in electrode size and position was also examined. Small changes (< 2.0 cm) in electrode position caused average LV myocardial voltage gradient values to increase by up to 12%. We conclude that patient-specific 3-D finite element modeling of human thoracic electric fields is feasible and may reduce the empiric approach to insertion of implantable defibrillators and improve transthoracic defibrillation techniques.

Effects of lung disease on the three-dimensional structure and air flow pattern in the human airway tree

NASA Astrophysics Data System (ADS)

van de Moortele, Tristan; Nemes, Andras; Wendt, Christine; Coletti, Filippo

2016-11-01

The morphological features of the airway tree directly affect the air flow features during breathing, which determines the gas exchange and inhaled particle transport. Lung disease, Chronic Obstructive Pulmonary Disease (COPD) in this study, affects the structural features of the lungs, which in turn negatively affects the air flow through the airways. Here bronchial tree air volume geometries are segmented from Computed Tomography (CT) scans of healthy and diseased subjects. Geometrical analysis of the airway centerlines and corresponding cross-sectional areas provide insight into the specific effects of COPD on the airway structure. These geometries are also used to 3D print anatomically accurate, patient specific flow models. Three-component, three-dimensional velocity fields within these models are acquired using Magnetic Resonance Imaging (MRI). The three-dimensional flow fields provide insight into the change in flow patterns and features. Additionally, particle trajectories are determined using the velocity fields, to identify the fate of therapeutic and harmful inhaled aerosols. Correlation between disease-specific and patient-specific anatomical features with dysfunctional airflow patterns can be achieved by combining geometrical and flow analysis.

Texture Analysis and Machine Learning for Detecting Myocardial Infarction in Noncontrast Low-Dose Computed Tomography: Unveiling the Invisible.

PubMed

Mannil, Manoj; von Spiczak, Jochen; Manka, Robert; Alkadhi, Hatem

2018-06-01

The aim of this study was to test whether texture analysis and machine learning enable the detection of myocardial infarction (MI) on non-contrast-enhanced low radiation dose cardiac computed tomography (CCT) images. In this institutional review board-approved retrospective study, we included non-contrast-enhanced electrocardiography-gated low radiation dose CCT image data (effective dose, 0.5 mSv) acquired for the purpose of calcium scoring of 27 patients with acute MI (9 female patients; mean age, 60 ± 12 years), 30 patients with chronic MI (8 female patients; mean age, 68 ± 13 years), and in 30 subjects (9 female patients; mean age, 44 ± 6 years) without cardiac abnormality, hereafter termed controls. Texture analysis of the left ventricle was performed using free-hand regions of interest, and texture features were classified twice (Model I: controls versus acute MI versus chronic MI; Model II: controls versus acute and chronic MI). For both classifications, 6 commonly used machine learning classifiers were used: decision tree C4.5 (J48), k-nearest neighbors, locally weighted learning, RandomForest, sequential minimal optimization, and an artificial neural network employing deep learning. In addition, 2 blinded, independent readers visually assessed noncontrast CCT images for the presence or absence of MI. In Model I, best classification results were obtained using the k-nearest neighbors classifier (sensitivity, 69%; specificity, 85%; false-positive rate, 0.15). In Model II, the best classification results were found with the locally weighted learning classification (sensitivity, 86%; specificity, 81%; false-positive rate, 0.19) with an area under the curve from receiver operating characteristics analysis of 0.78. In comparison, both readers were not able to identify MI in any of the noncontrast, low radiation dose CCT images. This study indicates the ability of texture analysis and machine learning in detecting MI on noncontrast low radiation dose CCT images being not visible for the radiologists' eye.

Computers in the surgery. The patient's view.

PubMed Central

Pringle, M; Robins, S; Brown, G

1984-01-01

A postal survey sent to 350 patients from two rural practices confirmed that an appreciable minority of patients (17%) were opposed to doctors using computers. The questionnaire distributed had been carefully designed to identify their opposition more specifically. Most of the general concern was accounted for by the 91 patients (31%) who feared that confidentiality of information would be reduced. The sensitive nature of medical information alerts patients to the possibility of diminished security of records and obliges practices considering acquiring a computer to ensure that these fears are not realised. Smaller proportions of patients were found to oppose computers on other grounds--namely, impersonality, economy, and general anxiety. PMID:6419902

Pediatric Chest and Abdominopelvic CT: Organ Dose Estimation Based on 42 Patient Models

PubMed Central

Tian, Xiaoyu; Li, Xiang; Segars, W. Paul; Paulson, Erik K.; Frush, Donald P.

2014-01-01

Purpose To estimate organ dose from pediatric chest and abdominopelvic computed tomography (CT) examinations and evaluate the dependency of organ dose coefficients on patient size and CT scanner models. Materials and Methods The institutional review board approved this HIPAA–compliant study and did not require informed patient consent. A validated Monte Carlo program was used to perform simulations in 42 pediatric patient models (age range, 0–16 years; weight range, 2–80 kg; 24 boys, 18 girls). Multidetector CT scanners were modeled on those from two commercial manufacturers (LightSpeed VCT, GE Healthcare, Waukesha, Wis; SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). Organ doses were estimated for each patient model for routine chest and abdominopelvic examinations and were normalized by volume CT dose index (CTDIvol). The relationships between CTDIvol-normalized organ dose coefficients and average patient diameters were evaluated across scanner models. Results For organs within the image coverage, CTDIvol-normalized organ dose coefficients largely showed a strong exponential relationship with the average patient diameter (R2 > 0.9). The average percentage differences between the two scanner models were generally within 10%. For distributed organs and organs on the periphery of or outside the image coverage, the differences were generally larger (average, 3%–32%) mainly because of the effect of overranging. Conclusion It is feasible to estimate patient-specific organ dose for a given examination with the knowledge of patient size and the CTDIvol. These CTDIvol-normalized organ dose coefficients enable one to readily estimate patient-specific organ dose for pediatric patients in clinical settings. This dose information, and, as appropriate, attendant risk estimations, can provide more substantive information for the individual patient for both clinical and research applications and can yield more expansive information on dose profiles across patient populations within a practice. © RSNA, 2013 PMID:24126364

Evaluation of the UF/NCI hybrid computational phantoms for use in organ dosimetry of pediatric patients undergoing fluoroscopically guided cardiac procedures

NASA Astrophysics Data System (ADS)

Marshall, Emily L.; Borrego, David; Tran, Trung; Fudge, James C.; Bolch, Wesley E.

2018-03-01

Epidemiologic data demonstrate that pediatric patients face a higher relative risk of radiation induced cancers than their adult counterparts at equivalent exposures. Infants and children with congenital heart defects are a critical patient population exposed to ionizing radiation during life-saving procedures. These patients will likely incur numerous procedures throughout their lifespan, each time increasing their cumulative radiation absorbed dose. As continued improvements in long-term prognosis of congenital heart defect patients is achieved, a better understanding of organ radiation dose following treatment becomes increasingly vital. Dosimetry of these patients can be accomplished using Monte Carlo radiation transport simulations, coupled with modern anatomical patient models. The aim of this study was to evaluate the performance of the University of Florida/National Cancer Institute (UF/NCI) pediatric hybrid computational phantom library for organ dose assessment of patients that have undergone fluoroscopically guided cardiac catheterizations. In this study, two types of simulations were modeled. A dose assessment was performed on 29 patient-specific voxel phantoms (taken as representing the patient’s true anatomy), height/weight-matched hybrid library phantoms, and age-matched reference phantoms. Two exposure studies were conducted for each phantom type. First, a parametric study was constructed by the attending pediatric interventional cardiologist at the University of Florida to model the range of parameters seen clinically. Second, four clinical cardiac procedures were simulated based upon internal logfiles captured by a Toshiba Infinix-i Cardiac Bi-Plane fluoroscopic unit. Performance of the phantom library was quantified by computing both the percent difference in individual organ doses, as well as the organ dose root mean square values for overall phantom assessment between the matched phantoms (UF/NCI library or reference) and the patient-specific phantoms. The UF/NCI hybrid phantoms performed at percent differences of between 15% and 30% for the parametric set of irradiation events. Among internal logfile reconstructed procedures, the UF/NCI hybrid phantoms performed with RMS organ dose values between 7% and 29%. Percent improvement in organ dosimetry via the use of hybrid library phantoms over the reference phantoms ranged from 6.6% to 93%. The use of a hybrid phantom library, Monte Carlo radiation transport methods, and clinical information on irradiation events provide a means for tracking organ dose in these radiosensitive patients undergoing fluoroscopically guided cardiac procedures. This work was supported by Advanced Laboratory for Radiation Dosimetry Studies, University of Florida, American Association of University Women, National Cancer Institute Grant 1F31 CA159464.

Patient-specific dose estimation for pediatric chest CT

PubMed Central

Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

2008-01-01

Current methods for organ and effective dose estimations in pediatric CT are largely patient generic. Physical phantoms and computer models have only been developed for standard/limited patient sizes at discrete ages (e.g., 0, 1, 5, 10, 15years old) and do not reflect the variability of patient anatomy and body habitus within the same size/age group. In this investigation, full-body computer models of seven pediatric patients in the same size/protocol group (weight: 11.9–18.2kg) were created based on the patients’ actual multi-detector array CT (MDCT) data. Organs and structures in the scan coverage were individually segmented. Other organs and structures were created by morphing existing adult models (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. Organ and effective dose of these patients from a chest MDCT scan protocol (64 slice LightSpeed VCT scanner, 120kVp, 70 or 75mA, 0.4s gantry rotation period, pitch of 1.375, 20mm beam collimation, and small body scan field-of-view) was calculated using a Monte Carlo program previously developed and validated to simulate radiation transport in the same CT system. The seven patients had normalized effective dose of 3.7–5.3mSv∕100mAs (coefficient of variation: 10.8%). Normalized lung dose and heart dose were 10.4–12.6mGy∕100mAs and 11.2–13.3mGy∕100mAs, respectively. Organ dose variations across the patients were generally small for large organs in the scan coverage (<7%), but large for small organs in the scan coverage (9%–18%) and for partially or indirectly exposed organs (11%–77%). Normalized effective dose correlated weakly with body weight (correlation coefficient:r=−0.80). Normalized lung dose and heart dose correlated strongly with mid-chest equivalent diameter (lung: r=−0.99, heart: r=−0.93); these strong correlation relationships can be used to estimate patient-specific organ dose for any other patient in the same size/protocol group who undergoes the chest scan. In summary, this work reported the first assessment of dose variations across pediatric CT patients in the same size/protocol group due to the variability of patient anatomy and body habitus and provided a previously unavailable method for patient-specific organ dose estimation, which will help in assessing patient risk and optimizing dose reduction strategies, including the development of scan protocols. PMID:19175138

Computational modeling of pedunculopontine nucleus deep brain stimulation

NASA Astrophysics Data System (ADS)

Zitella, Laura M.; Mohsenian, Kevin; Pahwa, Mrinal; Gloeckner, Cory; Johnson, Matthew D.

2013-08-01

Objective. Deep brain stimulation (DBS) near the pedunculopontine nucleus (PPN) has been posited to improve medication-intractable gait and balance problems in patients with Parkinson's disease. However, clinical studies evaluating this DBS target have not demonstrated consistent therapeutic effects, with several studies reporting the emergence of paresthesia and oculomotor side effects. The spatial and pathway-specific extent to which brainstem regions are modulated during PPN-DBS is not well understood. Approach. Here, we describe two computational models that estimate the direct effects of DBS in the PPN region for human and translational non-human primate (NHP) studies. The three-dimensional models were constructed from segmented histological images from each species, multi-compartment neuron models and inhomogeneous finite element models of the voltage distribution in the brainstem during DBS. Main Results. The computational models predicted that: (1) the majority of PPN neurons are activated with -3 V monopolar cathodic stimulation; (2) surgical targeting errors of as little as 1 mm in both species decrement activation selectivity; (3) specifically, monopolar stimulation in caudal, medial, or anterior PPN activates a significant proportion of the superior cerebellar peduncle (up to 60% in the human model and 90% in the NHP model at -3 V) (4) monopolar stimulation in rostral, lateral or anterior PPN activates a large percentage of medial lemniscus fibers (up to 33% in the human model and 40% in the NHP model at -3 V) and (5) the current clinical cylindrical electrode design is suboptimal for isolating the modulatory effects to PPN neurons. Significance. We show that a DBS lead design with radially-segmented electrodes may yield improved functional outcome for PPN-DBS.

eHealth literacy in chronic disease patients: An item response theory analysis of the eHealth literacy scale (eHEALS).

PubMed

Paige, Samantha R; Krieger, Janice L; Stellefson, Michael; Alber, Julia M

2017-02-01

Chronic disease patients are affected by low computer and health literacy, which negatively affects their ability to benefit from access to online health information. To estimate reliability and confirm model specifications for eHealth Literacy Scale (eHEALS) scores among chronic disease patients using Classical Test (CTT) and Item Response Theory techniques. A stratified sample of Black/African American (N=341) and Caucasian (N=343) adults with chronic disease completed an online survey including the eHEALS. Item discrimination was explored using bi-variate correlations and Cronbach's alpha for internal consistency. A categorical confirmatory factor analysis tested a one-factor structure of eHEALS scores. Item characteristic curves, in-fit/outfit statistics, omega coefficient, and item reliability and separation estimates were computed. A 1-factor structure of eHEALS was confirmed by statistically significant standardized item loadings, acceptable model fit indices (CFI/TLI>0.90), and 70% variance explained by the model. Item response categories increased with higher theta levels, and there was evidence of acceptable reliability (ω=0.94; item reliability=89; item separation=8.54). eHEALS scores are a valid and reliable measure of self-reported eHealth literacy among Internet-using chronic disease patients. Providers can use eHEALS to help identify patients' eHealth literacy skills. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Internet-based system for simulation-based medical planning for cardiovascular disease.

PubMed

Steele, Brooke N; Draney, Mary T; Ku, Joy P; Taylor, Charles A

2003-06-01

Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments, which does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described simulation-based medical planning methods to model blood flow in arteries and plan medical treatments based on physiologic models. An important consideration for the design of these patient-specific modeling systems is the accessibility to physicians with modest computational resources. We describe a simulation-based medical planning environment developed for the World Wide Web (WWW) using the Virtual Reality Modeling Language (VRML) and the Java programming language.

Challenges and limitations of patient-specific vascular phantom fabrication using 3D Polyjet printing.

PubMed

Ionita, Ciprian N; Mokin, Maxim; Varble, Nicole; Bednarek, Daniel R; Xiang, Jianping; Snyder, Kenneth V; Siddiqui, Adnan H; Levy, Elad I; Meng, Hui; Rudin, Stephen

2014-03-13

Additive manufacturing (3D printing) technology offers a great opportunity towards development of patient-specific vascular anatomic models, for medical device testing and physiological condition evaluation. However, the development process is not yet well established and there are various limitations depending on the printing materials, the technology and the printer resolution. Patient-specific neuro-vascular anatomy was acquired from computed tomography angiography and rotational digital subtraction angiography (DSA). The volumes were imported into a Vitrea 3D workstation (Vital Images Inc.) and the vascular lumen of various vessels and pathologies were segmented using a "marching cubes" algorithm. The results were exported as Stereo Lithographic (STL) files and were further processed by smoothing, trimming, and wall extrusion (to add a custom wall to the model). The models were printed using a Polyjet printer, Eden 260V (Objet-Stratasys). To verify the phantom geometry accuracy, the phantom was reimaged using rotational DSA, and the new data was compared with the initial patient data. The most challenging part of the phantom manufacturing was removal of support material. This aspect could be a serious hurdle in building very tortuous phantoms or small vessels. The accuracy of the printed models was very good: distance analysis showed average differences of 120 μm between the patient and the phantom reconstructed volume dimensions. Most errors were due to residual support material left in the lumen of the phantom. Despite the post-printing challenges experienced during the support cleaning, this technology could be a tremendous benefit to medical research such as in device development and testing.

Challenges and limitations of patient-specific vascular phantom fabrication using 3D Polyjet printing

NASA Astrophysics Data System (ADS)

Ionita, Ciprian N.; Mokin, Maxim; Varble, Nicole; Bednarek, Daniel R.; Xiang, Jianping; Snyder, Kenneth V.; Siddiqui, Adnan H.; Levy, Elad I.; Meng, Hui; Rudin, Stephen

2014-03-01

Additive manufacturing (3D printing) technology offers a great opportunity towards development of patient-specific vascular anatomic models, for medical device testing and physiological condition evaluation. However, the development process is not yet well established and there are various limitations depending on the printing materials, the technology and the printer resolution. Patient-specific neuro-vascular anatomy was acquired from computed tomography angiography and rotational digital subtraction angiography (DSA). The volumes were imported into a Vitrea 3D workstation (Vital Images Inc.) and the vascular lumen of various vessels and pathologies were segmented using a "marching cubes" algorithm. The results were exported as Stereo Lithographic (STL) files and were further processed by smoothing, trimming, and wall extrusion (to add a custom wall to the model). The models were printed using a Polyjet printer, Eden 260V (Objet-Stratasys). To verify the phantom geometry accuracy, the phantom was reimaged using rotational DSA, and the new data was compared with the initial patient data. The most challenging part of the phantom manufacturing was removal of support material. This aspect could be a serious hurdle in building very tortuous phantoms or small vessels. The accuracy of the printed models was very good: distance analysis showed average differences of 120 μm between the patient and the phantom reconstructed volume dimensions. Most errors were due to residual support material left in the lumen of the phantom. Despite the post-printing challenges experienced during the support cleaning, this technology could be a tremendous benefit to medical research such as in device development and testing.

Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.

PubMed

Chase, J Geoffrey; Preiser, Jean-Charles; Dickson, Jennifer L; Pironet, Antoine; Chiew, Yeong Shiong; Pretty, Christopher G; Shaw, Geoffrey M; Benyo, Balazs; Moeller, Knut; Safaei, Soroush; Tawhai, Merryn; Hunter, Peter; Desaive, Thomas

2018-02-20

Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.

Non-invasive brain stimulation and computational models in post-stroke aphasic patients: single session of transcranial magnetic stimulation and transcranial direct current stimulation. A randomized clinical trial.

PubMed

Santos, Michele Devido Dos; Cavenaghi, Vitor Breseghello; Mac-Kay, Ana Paula Machado Goyano; Serafim, Vitor; Venturi, Alexandre; Truong, Dennis Quangvinh; Huang, Yu; Boggio, Paulo Sérgio; Fregni, Felipe; Simis, Marcel; Bikson, Marom; Gagliardi, Rubens José

2017-01-01

Patients undergoing the same neuromodulation protocol may present different responses. Computational models may help in understanding such differences. The aims of this study were, firstly, to compare the performance of aphasic patients in naming tasks before and after one session of transcranial direct current stimulation (tDCS), transcranial magnetic stimulation (TMS) and sham, and analyze the results between these neuromodulation techniques; and secondly, through computational model on the cortex and surrounding tissues, to assess current flow distribution and responses among patients who received tDCS and presented different levels of results from naming tasks. Prospective, descriptive, qualitative and quantitative, double blind, randomized and placebo-controlled study conducted at Faculdade de Ciências Médicas da Santa Casa de São Paulo. Patients with aphasia received one session of tDCS, TMS or sham stimulation. The time taken to name pictures and the response time were evaluated before and after neuromodulation. Selected patients from the first intervention underwent a computational model stimulation procedure that simulated tDCS. The results did not indicate any statistically significant differences from before to after the stimulation.The computational models showed different current flow distributions. The present study did not show any statistically significant difference between tDCS, TMS and sham stimulation regarding naming tasks. The patients'responses to the computational model showed different patterns of current distribution.

Patient-specific Radiation Dose and Cancer Risk for Pediatric Chest CT

PubMed Central

Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

2011-01-01

Purpose: To estimate patient-specific radiation dose and cancer risk for pediatric chest computed tomography (CT) and to evaluate factors affecting dose and risk, including patient size, patient age, and scanning parameters. Materials and Methods: The institutional review board approved this study and waived informed consent. This study was HIPAA compliant. The study included 30 patients (0–16 years old), for whom full-body computer models were recently created from clinical CT data. A validated Monte Carlo program was used to estimate organ dose from eight chest protocols, representing clinically relevant combinations of bow tie filter, collimation, pitch, and tube potential. Organ dose was used to calculate effective dose and risk index (an index of total cancer incidence risk). The dose and risk estimates before and after normalization by volume-weighted CT dose index (CTDIvol) or dose–length product (DLP) were correlated with patient size and age. The effect of each scanning parameter was studied. Results: Organ dose normalized by tube current–time product or CTDIvol decreased exponentially with increasing average chest diameter. Effective dose normalized by tube current–time product or DLP decreased exponentially with increasing chest diameter. Chest diameter was a stronger predictor of dose than weight and total scan length. Risk index normalized by tube current–time product or DLP decreased exponentially with both chest diameter and age. When normalized by DLP, effective dose and risk index were independent of collimation, pitch, and tube potential (<10% variation). Conclusion: The correlations of dose and risk with patient size and age can be used to estimate patient-specific dose and risk. They can further guide the design and optimization of pediatric chest CT protocols. © RSNA, 2011 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101900/-/DC1 PMID:21467251

Patient-specific radiation dose and cancer risk for pediatric chest CT.

PubMed

Li, Xiang; Samei, Ehsan; Segars, W Paul; Sturgeon, Gregory M; Colsher, James G; Frush, Donald P

2011-06-01

To estimate patient-specific radiation dose and cancer risk for pediatric chest computed tomography (CT) and to evaluate factors affecting dose and risk, including patient size, patient age, and scanning parameters. The institutional review board approved this study and waived informed consent. This study was HIPAA compliant. The study included 30 patients (0-16 years old), for whom full-body computer models were recently created from clinical CT data. A validated Monte Carlo program was used to estimate organ dose from eight chest protocols, representing clinically relevant combinations of bow tie filter, collimation, pitch, and tube potential. Organ dose was used to calculate effective dose and risk index (an index of total cancer incidence risk). The dose and risk estimates before and after normalization by volume-weighted CT dose index (CTDI(vol)) or dose-length product (DLP) were correlated with patient size and age. The effect of each scanning parameter was studied. Organ dose normalized by tube current-time product or CTDI(vol) decreased exponentially with increasing average chest diameter. Effective dose normalized by tube current-time product or DLP decreased exponentially with increasing chest diameter. Chest diameter was a stronger predictor of dose than weight and total scan length. Risk index normalized by tube current-time product or DLP decreased exponentially with both chest diameter and age. When normalized by DLP, effective dose and risk index were independent of collimation, pitch, and tube potential (<10% variation). The correlations of dose and risk with patient size and age can be used to estimate patient-specific dose and risk. They can further guide the design and optimization of pediatric chest CT protocols. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101900/-/DC1. RSNA, 2011

MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, G; Pan, X; Stayman, J

2014-06-15

Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within themore » reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical applications. Learning Objectives: Learn the general methodologies associated with model-based 3D image reconstruction. Learn the potential advantages in image quality and dose associated with model-based image reconstruction. Learn the challenges associated with computational load and image quality assessment for such reconstruction methods. Learn how imaging task can be incorporated as a means to drive optimal image acquisition and reconstruction techniques. Learn how model-based reconstruction methods can incorporate prior information to improve image quality, ease sampling requirements, and reduce dose.« less

A combined learning algorithm for prostate segmentation on 3D CT images.

PubMed

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Schuster, David M; Fei, Baowei

2017-11-01

Segmentation of the prostate on CT images has many applications in the diagnosis and treatment of prostate cancer. Because of the low soft-tissue contrast on CT images, prostate segmentation is a challenging task. A learning-based segmentation method is proposed for the prostate on three-dimensional (3D) CT images. We combine population-based and patient-based learning methods for segmenting the prostate on CT images. Population data can provide useful information to guide the segmentation processing. Because of inter-patient variations, patient-specific information is particularly useful to improve the segmentation accuracy for an individual patient. In this study, we combine a population learning method and a patient-specific learning method to improve the robustness of prostate segmentation on CT images. We train a population model based on the data from a group of prostate patients. We also train a patient-specific model based on the data of the individual patient and incorporate the information as marked by the user interaction into the segmentation processing. We calculate the similarity between the two models to obtain applicable population and patient-specific knowledge to compute the likelihood of a pixel belonging to the prostate tissue. A new adaptive threshold method is developed to convert the likelihood image into a binary image of the prostate, and thus complete the segmentation of the gland on CT images. The proposed learning-based segmentation algorithm was validated using 3D CT volumes of 92 patients. All of the CT image volumes were manually segmented independently three times by two, clinically experienced radiologists and the manual segmentation results served as the gold standard for evaluation. The experimental results show that the segmentation method achieved a Dice similarity coefficient of 87.18 ± 2.99%, compared to the manual segmentation. By combining the population learning and patient-specific learning methods, the proposed method is effective for segmenting the prostate on 3D CT images. The prostate CT segmentation method can be used in various applications including volume measurement and treatment planning of the prostate. © 2017 American Association of Physicists in Medicine.

Patient-specific in silico models can quantify primary implant stability in elderly human bone.

PubMed

Steiner, Juri A; Hofmann, Urs A T; Christen, Patrik; Favre, Jean M; Ferguson, Stephen J; van Lenthe, G Harry

2018-03-01

Secure implant fixation is challenging in osteoporotic bone. Due to the high variability in inter- and intra-patient bone quality, ex vivo mechanical testing of implants in bone is very material- and time-consuming. Alternatively, in silico models could substantially reduce costs and speed up the design of novel implants if they had the capability to capture the intricate bone microstructure. Therefore, the aim of this study was to validate a micro-finite element model of a multi-screw fracture fixation system. Eight human cadaveric humerii were scanned using micro-CT and mechanically tested to quantify bone stiffness. Osteotomy and fracture fixation were performed, followed by mechanical testing to quantify displacements at 12 different locations on the instrumented bone. For each experimental case, a micro-finite element model was created. From the micro-finite element analyses of the intact model, the patient-specific bone tissue modulus was determined such that the simulated apparent stiffness matched the measured stiffness of the intact bone. Similarly, the tissue modulus of a small damage region around each screw was determined for the instrumented bone. For validation, all in silico models were rerun using averaged material properties, resulting in an average coefficient of determination of 0.89 ± 0.04 with a slope of 0.93 ± 0.19 and a mean absolute error of 43 ± 10 μm when correlating in silico marker displacements with the ex vivo test. In conclusion, we validated a patient-specific computer model of an entire organ bone-implant system at the tissue-level at high resolution with excellent overall accuracy. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:954-962, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Subject-specific computer simulation model for determining elbow loading in one-handed tennis backhand groundstrokes.

PubMed

King, Mark A; Glynn, Jonathan A; Mitchell, Sean R

2011-11-01

A subject-specific angle-driven computer model of a tennis player, combined with a forward dynamics, equipment-specific computer model of tennis ball-racket impacts, was developed to determine the effect of ball-racket impacts on loading at the elbow for one-handed backhand groundstrokes. Matching subject-specific computer simulations of a typical topspin/slice one-handed backhand groundstroke performed by an elite tennis player were done with root mean square differences between performance and matching simulations of < 0.5 degrees over a 50 ms period starting from ball impact. Simulation results suggest that for similar ball-racket impact conditions, the difference in elbow loading for a topspin and slice one-handed backhand groundstroke is relatively small. In this study, the relatively small differences in elbow loading may be due to comparable angle-time histories at the wrist and elbow joints with the major kinematic differences occurring at the shoulder. Using a subject-specific angle-driven computer model combined with a forward dynamics, equipment-specific computer model of tennis ball-racket impacts allows peak internal loading, net impulse, and shock due to ball-racket impact to be calculated which would not otherwise be possible without impractical invasive techniques. This study provides a basis for further investigation of the factors that may increase elbow loading during tennis strokes.

Physical validation of a patient-specific contact finite element model of the ankle.

PubMed

Anderson, Donald D; Goldsworthy, Jane K; Li, Wendy; James Rudert, M; Tochigi, Yuki; Brown, Thomas D

2007-01-01

A validation study was conducted to determine the extent to which computational ankle contact finite element (FE) results agreed with experimentally measured tibio-talar contact stress. Two cadaver ankles were loaded in separate test sessions, during which ankle contact stresses were measured with a high-resolution (Tekscan) pressure sensor. Corresponding contact FE analyses were subsequently performed for comparison. The agreement was good between FE-computed and experimentally measured mean (3.2% discrepancy for one ankle, 19.3% for the other) and maximum (1.5% and 6.2%) contact stress, as well as for contact area (1.7% and 14.9%). There was also excellent agreement between histograms of fractional areas of cartilage experiencing specific ranges of contact stress. Finally, point-by-point comparisons between the computed and measured contact stress distributions over the articular surface showed substantial agreement, with correlation coefficients of 90% for one ankle and 86% for the other. In the past, general qualitative, but little direct quantitative agreement has been demonstrated with articular joint contact FE models. The methods used for this validation enable formal comparison of computational and experimental results, and open the way for objective statistical measures of regional correlation between FE-computed contact stress distributions from comparison articular joint surfaces (e.g., those from an intact versus those with residual intra-articular fracture incongruity).

Computational fluid-structure interaction: methods and application to a total cavopulmonary connection

NASA Astrophysics Data System (ADS)

Bazilevs, Yuri; Hsu, M.-C.; Benson, D. J.; Sankaran, S.; Marsden, A. L.

2009-12-01

The Fontan procedure is a surgery that is performed on single-ventricle heart patients, and, due to the wide range of anatomies and variations among patients, lends itself nicely to study by advanced numerical methods. We focus on a patient-specific Fontan configuration, and perform a fully coupled fluid-structure interaction (FSI) analysis of hemodynamics and vessel wall motion. To enable physiologically realistic simulations, a simple approach to constructing a variable-thickness blood vessel wall description is proposed. Rest and exercise conditions are simulated and rigid versus flexible vessel wall simulation results are compared. We conclude that flexible wall modeling plays an important role in predicting quantities of hemodynamic interest in the Fontan connection. To the best of our knowledge, this paper presents the first three-dimensional patient-specific fully coupled FSI analysis of a total cavopulmonary connection that also includes large portions of the pulmonary circulation.

Patient-specific modeling and analysis of dynamic behavior of individual sickle red blood cells under hypoxic conditions

NASA Astrophysics Data System (ADS)

Li, Xuejin; Du, E.; Li, Zhen; Tang, Yu-Hang; Lu, Lu; Dao, Ming; Karniadakis, George

2015-11-01

Sickle cell anemia is an inherited blood disorder exhibiting heterogeneous morphology and abnormal dynamics under hypoxic conditions. We developed a time-dependent cell model that is able to simulate the dynamic processes of repeated sickling and unsickling of red blood cells (RBCs) under physiological conditions. By using the kinetic cell model with parameters derived from patient-specific data, we present a mesoscopic computational study of the dynamic behavior of individual sickle RBCs flowing in a microfluidic channel with multiple microgates. We investigate how individual sickle RBCs behave differently from healthy ones in channel flow, and analyze the alteration of cellular behavior and response to single-cell capillary obstruction induced by cell rheologic rigidification and morphological change due to cell sickling under hypoxic conditions. We also simulate the flow dynamics of sickle RBCs treated with hydroxyurea (HU) and quantify the relative enhancement of hemodynamic performance of HU. This work was supported by the National Institutes of Health (NIH) Grant U01HL114476.

Computer-assisted diagnosis of melanoma.

PubMed

Fuller, Collin; Cellura, A Paul; Hibler, Brian P; Burris, Katy

2016-03-01

The computer-assisted diagnosis of melanoma is an exciting area of research where imaging techniques are combined with diagnostic algorithms in an attempt to improve detection and outcomes for patients with skin lesions suspicious for malignancy. Once an image has been acquired, it undergoes a processing pathway which includes preprocessing, enhancement, segmentation, feature extraction, feature selection, change detection, and ultimately classification. Practicality for everyday clinical use remains a vital question. A successful model must obtain results that are on par or outperform experienced dermatologists, keep costs at a minimum, be user-friendly, and be time efficient with high sensitivity and specificity. ©2015 Frontline Medical Communications.

Tumor Response and Survival Predicted by Post-Therapy FDG-PET/CT in Anal Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schwarz, Julie K.; Siegel, Barry A.; Dehdashti, Farrokh

2008-05-01

Purpose: To evaluate the response to therapy for anal carcinoma using post-therapy imaging with positron emission tomography (PET)/computed tomography and F-18 fluorodeoxyglucose (FDG) and to compare the metabolic response with patient outcome. Patients and Methods: This was a prospective cohort study of 53 consecutive patients with anal cancer. All patients underwent pre- and post-treatment whole-body FDG-PET/computed tomography. Patients had been treated with external beam radiotherapy and concurrent chemotherapy. Whole-body FDG-PET was performed 0.9-5.4 months (mean, 2.1) after therapy completion. Results: The post-therapy PET scan did not show any abnormal FDG uptake (complete metabolic response) in 44 patients. Persistent abnormal FDGmore » uptake (partial metabolic response) was found in the anal tumor in 9 patients. The 2-year cause-specific survival rate was 94% for patients with a complete vs. 39% for patients with a partial metabolic response in the anal tumor (p = 0.0008). The 2-year progression-free survival rate was 95% for patients with a complete vs. 22% for patients with a partial metabolic response in the anal tumor (p < 0.0001). A Cox proportional hazards model of survival outcome indicated that a complete metabolic response was the most significant predictor of progression-free survival in our patient population (p = 0.0003). Conclusions: A partial metabolic response in the anal tumor as determined by post-therapy FDG-PET is predictive of significantly decreased progression-free and cause-specific survival after chemoradiotherapy for anal cancer.« less

Aortic dissection simulation models for clinical support: fluid-structure interaction vs. rigid wall models.

PubMed

Alimohammadi, Mona; Sherwood, Joseph M; Karimpour, Morad; Agu, Obiekezie; Balabani, Stavroula; Díaz-Zuccarini, Vanessa

2015-04-15

The management and prognosis of aortic dissection (AD) is often challenging and the use of personalised computational models is being explored as a tool to improve clinical outcome. Including vessel wall motion in such simulations can provide more realistic and potentially accurate results, but requires significant additional computational resources, as well as expertise. With clinical translation as the final aim, trade-offs between complexity, speed and accuracy are inevitable. The present study explores whether modelling wall motion is worth the additional expense in the case of AD, by carrying out fluid-structure interaction (FSI) simulations based on a sample patient case. Patient-specific anatomical details were extracted from computed tomography images to provide the fluid domain, from which the vessel wall was extrapolated. Two-way fluid-structure interaction simulations were performed, with coupled Windkessel boundary conditions and hyperelastic wall properties. The blood was modelled using the Carreau-Yasuda viscosity model and turbulence was accounted for via a shear stress transport model. A simulation without wall motion (rigid wall) was carried out for comparison purposes. The displacement of the vessel wall was comparable to reports from imaging studies in terms of intimal flap motion and contraction of the true lumen. Analysis of the haemodynamics around the proximal and distal false lumen in the FSI model showed complex flow structures caused by the expansion and contraction of the vessel wall. These flow patterns led to significantly different predictions of wall shear stress, particularly its oscillatory component, which were not captured by the rigid wall model. Through comparison with imaging data, the results of the present study indicate that the fluid-structure interaction methodology employed herein is appropriate for simulations of aortic dissection. Regions of high wall shear stress were not significantly altered by the wall motion, however, certain collocated regions of low and oscillatory wall shear stress which may be critical for disease progression were only identified in the FSI simulation. We conclude that, if patient-tailored simulations of aortic dissection are to be used as an interventional planning tool, then the additional complexity, expertise and computational expense required to model wall motion is indeed justified.

Evaluation of a patient specific femoral alignment guide for hip resurfacing.

PubMed

Olsen, Michael; Naudie, Douglas D; Edwards, Max R; Sellan, Michael E; McCalden, Richard W; Schemitsch, Emil H

2014-03-01

A novel alternative to conventional instrumentation for femoral component insertion in hip resurfacing is a patient specific, computed tomography based femoral alignment guide. A benchside study using cadaveric femora was performed comparing a custom alignment guide to conventional instrumentation and computer navigation. A clinical series of twenty-five hip resurfacings utilizing a custom alignment guide was conducted by three surgeons experienced in hip resurfacing. Using cadaveric femora, the custom guide was comparable to conventional instrumentation with computer navigation proving superior to both. Clinical femoral component alignment accuracy was 3.7° and measured within ± 5° of plan in 20 of 24 cases. Patient specific femoral alignment guides provide a satisfactory level of accuracy and may be a better alternative to conventional instrumentation for initial femoral guidewire placement in hip resurfacing. Crown Copyright © 2014. All rights reserved.

SU-E-T-785: Using Systems Engineering to Design HDR Skin Treatment Operation for Small Lesions to Enhance Patient Safety

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saw, C; Baikadi, M; Peters, C

2015-06-15

Purpose: Using systems engineering to design HDR skin treatment operation for small lesions using shielded applicators to enhance patient safety. Methods: Systems engineering is an interdisciplinary field that offers formal methodologies to study, design, implement, and manage complex engineering systems as a whole over their life-cycles. The methodologies deal with human work-processes, coordination of different team, optimization, and risk management. The V-model of systems engineering emphasize two streams, the specification and the testing streams. The specification stream consists of user requirements, functional requirements, and design specifications while the testing on installation, operational, and performance specifications. In implementing system engineering tomore » this project, the user and functional requirements are (a) HDR unit parameters be downloaded from the treatment planning system, (b) dwell times and positions be generated by treatment planning system, (c) source decay be computer calculated, (d) a double-check system of treatment parameters to comply with the NRC regulation. These requirements are intended to reduce human intervention to improve patient safety. Results: A formal investigation indicated that the user requirements can be satisfied. The treatment operation consists of using the treatment planning system to generate a pseudo plan that is adjusted for different shielded applicators to compute the dwell times. The dwell positions, channel numbers, and the dwell times are verified by the medical physicist and downloaded into the HDR unit. The decayed source strength is transferred to a spreadsheet that computes the dwell times based on the type of applicators and prescribed dose used. Prior to treatment, the source strength, dwell times, dwell positions, and channel numbers are double-checked by the radiation oncologist. No dosimetric parameters are manually calculated. Conclusion: Systems engineering provides methodologies to effectively design the HDR treatment operation that minimize human intervention and improve patient safety.« less

A Multistep Maturity Model for the Implementation of Electronic and Computable Diagnostic Clinical Prediction Rules (eCPRs).

PubMed

Corrigan, Derek; McDonnell, Ronan; Zarabzadeh, Atieh; Fahey, Tom

2015-01-01

The use of Clinical Prediction Rules (CPRs) has been advocated as one way of implementing actionable evidence-based rules in clinical practice. The current highly manual nature of deriving CPRs makes them difficult to use and maintain. Addressing the known limitations of CPRs requires implementing more flexible and dynamic models of CPR development. We describe the application of Information and Communication Technology (ICT) to provide a platform for the derivation and dissemination of CPRs derived through analysis and continual learning from electronic patient data. We propose a multistep maturity model for constructing electronic and computable CPRs (eCPRs). The model has six levels - from the lowest level of CPR maturity (literaturebased CPRs) to a fully electronic and computable service-oriented model of CPRs that are sensitive to specific demographic patient populations. We describe examples of implementations of the core model components - focusing on CPR representation, interoperability, electronic dissemination, CPR learning, and user interface requirements. The traditional focus on derivation and narrow validation of CPRs has severely limited their wider acceptance. The evolution and maturity model described here outlines a progression toward eCPRs consistent with the vision of a learning health system (LHS) - using central repositories of CPR knowledge, accessible open standards, and generalizable models to avoid repetition of previous work. This is useful for developing more ambitious strategies to address limitations of the traditional CPR development life cycle. The model described here is a starting point for promoting discussion about what a more dynamic CPR development process should look like.

Towards an integrative computational model for simulating tumor growth and response to radiation therapy

NASA Astrophysics Data System (ADS)

Marrero, Carlos Sosa; Aubert, Vivien; Ciferri, Nicolas; Hernández, Alfredo; de Crevoisier, Renaud; Acosta, Oscar

2017-11-01

Understanding the response to irradiation in cancer radiotherapy (RT) may help devising new strategies with improved tumor local control. Computational models may allow to unravel the underlying radiosensitive mechanisms intervening in the dose-response relationship. By using extensive simulations a wide range of parameters may be evaluated providing insights on tumor response thus generating useful data to plan modified treatments. We propose in this paper a computational model of tumor growth and radiation response which allows to simulate a whole RT protocol. Proliferation of tumor cells, cell life-cycle, oxygen diffusion, radiosensitivity, RT response and resorption of killed cells were implemented in a multiscale framework. The model was developed in C++, using the Multi-formalism Modeling and Simulation Library (M2SL). Radiosensitivity parameters extracted from literature enabled us to simulate in a regular grid (voxel-wise) a prostate cell tissue. Histopathological specimens with different aggressiveness levels extracted from patients after prostatectomy were used to initialize in silico simulations. Results on tumor growth exhibit a good agreement with data from in vitro studies. Moreover, standard fractionation of 2 Gy/fraction, with a total dose of 80 Gy as a real RT treatment was applied with varying radiosensitivity and oxygen diffusion parameters. As expected, the high influence of these parameters was observed by measuring the percentage of survival tumor cell after RT. This work paves the way to further models allowing to simulate increased doses in modified hypofractionated schemes and to develop new patient-specific combined therapies.

Patient-specific core decompression surgery for early-stage ischemic necrosis of the femoral head

PubMed Central

Wang, Wei; Hu, Wei; Yang, Pei; Dang, Xiao Qian; Li, Xiao Hui; Wang, Kun Zheng

2017-01-01

Introduction Core decompression is an efficient treatment for early stage ischemic necrosis of the femoral head. In conventional procedures, the pre-operative X-ray only shows one plane of the ischemic area, which often results in inaccurate drilling. This paper introduces a new method that uses computer-assisted technology and rapid prototyping to enhance drilling accuracy during core decompression surgeries and presents a validation study of cadaveric tests. Methods Twelve cadaveric human femurs were used to simulate early-stage ischemic necrosis. The core decompression target at the anterolateral femoral head was simulated using an embedded glass ball (target). Three positioning Kirschner wires were drilled into the top and bottom of the large rotor. The specimen was then subjected to computed tomography (CT). A CT image of the specimen was imported into the Mimics software to construct a three-dimensional model including the target. The best core decompression channel was then designed using the 3D model. A navigational template for the specimen was designed using the Pro/E software and manufactured by rapid prototyping technology to guide the drilling channel. The specimen-specific navigation template was installed on the specimen using positioning Kirschner wires. Drilling was performed using a guide needle through the guiding hole on the templates. The distance between the end point of the guide needle and the target was measured to validate the patient-specific surgical accuracy. Results The average distance between the tip of the guide needle drilled through the guiding template and the target was 1.92±0.071 mm. Conclusions Core decompression using a computer-rapid prototyping template is a reliable and accurate technique that could provide a new method of precision decompression for early-stage ischemic necrosis. PMID:28464029

Patient-specific core decompression surgery for early-stage ischemic necrosis of the femoral head.

PubMed

Wang, Wei; Hu, Wei; Yang, Pei; Dang, Xiao Qian; Li, Xiao Hui; Wang, Kun Zheng

2017-01-01

Core decompression is an efficient treatment for early stage ischemic necrosis of the femoral head. In conventional procedures, the pre-operative X-ray only shows one plane of the ischemic area, which often results in inaccurate drilling. This paper introduces a new method that uses computer-assisted technology and rapid prototyping to enhance drilling accuracy during core decompression surgeries and presents a validation study of cadaveric tests. Twelve cadaveric human femurs were used to simulate early-stage ischemic necrosis. The core decompression target at the anterolateral femoral head was simulated using an embedded glass ball (target). Three positioning Kirschner wires were drilled into the top and bottom of the large rotor. The specimen was then subjected to computed tomography (CT). A CT image of the specimen was imported into the Mimics software to construct a three-dimensional model including the target. The best core decompression channel was then designed using the 3D model. A navigational template for the specimen was designed using the Pro/E software and manufactured by rapid prototyping technology to guide the drilling channel. The specimen-specific navigation template was installed on the specimen using positioning Kirschner wires. Drilling was performed using a guide needle through the guiding hole on the templates. The distance between the end point of the guide needle and the target was measured to validate the patient-specific surgical accuracy. The average distance between the tip of the guide needle drilled through the guiding template and the target was 1.92±0.071 mm. Core decompression using a computer-rapid prototyping template is a reliable and accurate technique that could provide a new method of precision decompression for early-stage ischemic necrosis.

Computational models of epilepsy.

PubMed

Stefanescu, Roxana A; Shivakeshavan, R G; Talathi, Sachin S

2012-12-01

Approximately 30% of epilepsy patients suffer from medically refractory epilepsy, in which seizures can not controlled by the use of anti-epileptic drugs (AEDs). Understanding the mechanisms underlying these forms of drug-resistant epileptic seizures and the development of alternative effective treatment strategies are fundamental challenges for modern epilepsy research. In this context, computational modeling has gained prominence as an important tool for tackling the complexity of the epileptic phenomenon. In this review article, we present a survey of computational models of epilepsy from the point of view that epilepsy is a dynamical brain disease that is primarily characterized by unprovoked spontaneous epileptic seizures. We introduce key concepts from the mathematical theory of dynamical systems, such as multi-stability and bifurcations, and explain how these concepts aid in our understanding of the brain mechanisms involved in the emergence of epileptic seizures. We present a literature survey of the different computational modeling approaches that are used in the study of epilepsy. Special emphasis is placed on highlighting the fine balance between the degree of model simplification and the extent of biological realism that modelers seek in order to address relevant questions. In this context, we discuss three specific examples from published literature, which exemplify different approaches used for developing computational models of epilepsy. We further explore the potential of recently developed optogenetics tools to provide novel avenue for seizure control. We conclude with a discussion on the utility of computational models for the development of new epilepsy treatment protocols. Copyright © 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas.

PubMed

Friedman, Robert J; Gutkowicz-Krusin, Dina; Farber, Michele J; Warycha, Melanie; Schneider-Kels, Lori; Papastathis, Nicole; Mihm, Martin C; Googe, Paul; King, Roy; Prieto, Victor G; Kopf, Alfred W; Polsky, David; Rabinovitz, Harold; Oliviero, Margaret; Cognetta, Armand; Rigel, Darrell S; Marghoob, Ashfaq; Rivers, Jason; Johr, Robert; Grant-Kels, Jane M; Tsao, Hensin

2008-04-01

To evaluate the performance of dermoscopists in diagnosing small pigmented skin lesions (diameter

COMPUTATIONAL MITRAL VALVE EVALUATION AND POTENTIAL CLINICAL APPLICATIONS

PubMed Central

Chandran, Krishnan B.; Kim, Hyunggun

2014-01-01

The mitral valve (MV) apparatus consists of the two asymmetric leaflets, the saddle-shaped annulus, the chordae tendineae, and the papillary muscles. MV function over the cardiac cycle involves complex interaction between the MV apparatus components for efficient blood circulation. Common diseases of the MV include valvular stenosis, regurgitation, and prolapse. MV repair is the most popular and most reliable surgical treatment for early MV pathology. One of the unsolved problems in MV repair is to predict the optimal repair strategy for each patient. Although experimental studies have provided valuable information to improve repair techniques, computational simulations are increasingly playing an important role in understanding the complex MV dynamics, particularly with the availability of patient-specific real-time imaging modalities. This work presents a review of computational simulation studies of MV function employing finite element (FE) structural analysis and fluid-structure interaction (FSI) approach reported in the literature to date. More recent studies towards potential applications of computational simulation approaches in the assessment of valvular repair techniques and potential pre-surgical planning of repair strategies are also discussed. It is anticipated that further advancements in computational techniques combined with the next generations of clinical imaging modalities will enable physiologically more realistic simulations. Such advancement in imaging and computation will allow for patient-specific, disease-specific, and case-specific MV evaluation and virtual prediction of MV repair. PMID:25134487

Novel modeling of cancer cell signaling pathways enables systematic drug repositioning for distinct breast cancer metastases.

PubMed

Zhao, Hong; Jin, Guangxu; Cui, Kemi; Ren, Ding; Liu, Timothy; Chen, Peikai; Wong, Solomon; Li, Fuhai; Fan, Yubo; Rodriguez, Angel; Chang, Jenny; Wong, Stephen T C

2013-10-15

A new type of signaling network element, called cancer signaling bridges (CSB), has been shown to have the potential for systematic and fast-tracked drug repositioning. On the basis of CSBs, we developed a computational model to derive specific downstream signaling pathways that reveal previously unknown target-disease connections and new mechanisms for specific cancer subtypes. The model enables us to reposition drugs based on available patient gene expression data. We applied this model to repurpose known or shelved drugs for brain, lung, and bone metastases of breast cancer with the hypothesis that cancer subtypes have their own specific signaling mechanisms. To test the hypothesis, we addressed specific CSBs for each metastasis that satisfy (i) CSB proteins are activated by the maximal number of enriched signaling pathways specific to a given metastasis, and (ii) CSB proteins are involved in the most differential expressed coding genes specific to each breast cancer metastasis. The identified signaling networks for the three types of breast cancer metastases contain 31, 15, and 18 proteins and are used to reposition 15, 9, and 2 drug candidates for the brain, lung, and bone metastases. We conducted both in vitro and in vivo preclinical experiments as well as analysis on patient tumor specimens to evaluate the targets and repositioned drugs. Of special note, we found that the Food and Drug Administration-approved drugs, sunitinib and dasatinib, prohibit brain metastases derived from breast cancer, addressing one particularly challenging aspect of this disease. ©2013 AACR.

A tree-parenchyma coupled model for lung ventilation simulation.

PubMed

Pozin, Nicolas; Montesantos, Spyridon; Katz, Ira; Pichelin, Marine; Vignon-Clementel, Irene; Grandmont, Céline

2017-11-01

In this article, we develop a lung ventilation model. The parenchyma is described as an elastic homogenized media. It is irrigated by a space-filling dyadic resistive pipe network, which represents the tracheobronchial tree. In this model, the tree and the parenchyma are strongly coupled. The tree induces an extra viscous term in the system constitutive relation, which leads, in the finite element framework, to a full matrix. We consider an efficient algorithm that takes advantage of the tree structure to enable a fast matrix-vector product computation. This framework can be used to model both free and mechanically induced respiration, in health and disease. Patient-specific lung geometries acquired from computed tomography scans are considered. Realistic Dirichlet boundary conditions can be deduced from surface registration on computed tomography images. The model is compared to a more classical exit compartment approach. Results illustrate the coupling between the tree and the parenchyma, at global and regional levels, and how conditions for the purely 0D model can be inferred. Different types of boundary conditions are tested, including a nonlinear Robin model of the surrounding lung structures. Copyright © 2017 John Wiley & Sons, Ltd.

Advantages and disadvantages of computer imaging in cosmetic surgery.

PubMed

Koch, R J; Chavez, A; Dagum, P; Newman, J P

1998-02-01

Despite the growing popularity of computer imaging systems, it is not clear whether the medical and legal advantages of using such a system outweigh the disadvantages. The purpose of this report is to evaluate these aspects, and provide some protective guidelines in the use of computer imaging in cosmetic surgery. The positive and negative aspects of computer imaging from a medical and legal perspective are reviewed. Also, specific issues are examined by a legal panel. The greatest advantages are potential problem patient exclusion, and enhanced physician-patient communication. Disadvantages include cost, user learning curve, and potential liability. Careful use of computer imaging should actually reduce one's liability when all aspects are considered. Recommendations for such use and specific legal issues are discussed.

Predicting High Imaging Utilization Based on Initial Radiology Reports: A Feasibility Study of Machine Learning.

PubMed

Hassanpour, Saeed; Langlotz, Curtis P

2016-01-01

Imaging utilization has significantly increased over the last two decades, and is only recently showing signs of moderating. To help healthcare providers identify patients at risk for high imaging utilization, we developed a prediction model to recognize high imaging utilizers based on their initial imaging reports. The prediction model uses a machine learning text classification framework. In this study, we used radiology reports from 18,384 patients with at least one abdomen computed tomography study in their imaging record at Stanford Health Care as the training set. We modeled the radiology reports in a vector space and trained a support vector machine classifier for this prediction task. We evaluated our model on a separate test set of 4791 patients. In addition to high prediction accuracy, in our method, we aimed at achieving high specificity to identify patients at high risk for high imaging utilization. Our results (accuracy: 94.0%, sensitivity: 74.4%, specificity: 97.9%, positive predictive value: 87.3%, negative predictive value: 95.1%) show that a prediction model can enable healthcare providers to identify in advance patients who are likely to be high utilizers of imaging services. Machine learning classifiers developed from narrative radiology reports are feasible methods to predict imaging utilization. Such systems can be used to identify high utilizers, inform future image ordering behavior, and encourage judicious use of imaging. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Patient-specific model-based segmentation of brain tumors in 3D intraoperative ultrasound images.

PubMed

Ilunga-Mbuyamba, Elisee; Avina-Cervantes, Juan Gabriel; Lindner, Dirk; Arlt, Felix; Ituna-Yudonago, Jean Fulbert; Chalopin, Claire

2018-03-01

Intraoperative ultrasound (iUS) imaging is commonly used to support brain tumor operation. The tumor segmentation in the iUS images is a difficult task and still under improvement because of the low signal-to-noise ratio. The success of automatic methods is also limited due to the high noise sensibility. Therefore, an alternative brain tumor segmentation method in 3D-iUS data using a tumor model obtained from magnetic resonance (MR) data for local MR-iUS registration is presented in this paper. The aim is to enhance the visualization of the brain tumor contours in iUS. A multistep approach is proposed. First, a region of interest (ROI) based on the specific patient tumor model is defined. Second, hyperechogenic structures, mainly tumor tissues, are extracted from the ROI of both modalities by using automatic thresholding techniques. Third, the registration is performed over the extracted binary sub-volumes using a similarity measure based on gradient values, and rigid and affine transformations. Finally, the tumor model is aligned with the 3D-iUS data, and its contours are represented. Experiments were successfully conducted on a dataset of 33 patients. The method was evaluated by comparing the tumor segmentation with expert manual delineations using two binary metrics: contour mean distance and Dice index. The proposed segmentation method using local and binary registration was compared with two grayscale-based approaches. The outcomes showed that our approach reached better results in terms of computational time and accuracy than the comparative methods. The proposed approach requires limited interaction and reduced computation time, making it relevant for intraoperative use. Experimental results and evaluations were performed offline. The developed tool could be useful for brain tumor resection supporting neurosurgeons to improve tumor border visualization in the iUS volumes.

Investigation of Patient-Specific Cerebral Aneurysm using Volumetric PIV, CFD, and In Vitro PC-MRI

NASA Astrophysics Data System (ADS)

Brindise, Melissa; Dickerhoff, Ben; Saloner, David; Rayz, Vitaliy; Vlachos, Pavlos

2017-11-01

4D PC-MRI is a modality capable of providing time-resolved velocity fields in cerebral aneurysms in vivo. The MRI-measured velocities and subsequent hemodynamic parameters such as wall shear stress, and oscillatory shear index, can help neurosurgeons decide a course of treatment for a patient, e.g. whether to treat or monitor the aneurysm. However, low spatiotemporal resolution, limited velocity dynamic range, and inherent noise of PC-MRI velocity fields can have a notable effect on subsequent calculations, and should be investigated. In this work, we compare velocity fields obtained with 4D PC-MRI, computational fluid dynamics (CFD) and volumetric particle image velocimetry (PIV), using a patient-specific model of a basilar tip aneurysm. The same in vitro model is used for all three modalities and flow input parameters are controlled. In vivo, PC-MRI data was also acquired for this patient and used for comparison. Specifically, we investigate differences in the resulting velocity fields and biases in subsequent calculations. Further, we explore the effect these errors may have on assessment of the aneurysm progression and seek to develop corrective algorithms and other methodologies that can be used to improve the accuracy of hemodynamic analysis in clinical setting.

Computer-Based Radiographic Quantification of Joint Space Narrowing Progression Using Sequential Hand Radiographs: Validation Study in Rheumatoid Arthritis Patients from Multiple Institutions.

PubMed

Ichikawa, Shota; Kamishima, Tamotsu; Sutherland, Kenneth; Fukae, Jun; Katayama, Kou; Aoki, Yuko; Okubo, Takanobu; Okino, Taichi; Kaneda, Takahiko; Takagi, Satoshi; Tanimura, Kazuhide

2017-10-01

We have developed a refined computer-based method to detect joint space narrowing (JSN) progression with the joint space narrowing progression index (JSNPI) by superimposing sequential hand radiographs. The purpose of this study is to assess the validity of a computer-based method using images obtained from multiple institutions in rheumatoid arthritis (RA) patients. Sequential hand radiographs of 42 patients (37 females and 5 males) with RA from two institutions were analyzed by a computer-based method and visual scoring systems as a standard of reference. The JSNPI above the smallest detectable difference (SDD) defined JSN progression on the joint level. The sensitivity and specificity of the computer-based method for JSN progression was calculated using the SDD and a receiver operating characteristic (ROC) curve. Out of 314 metacarpophalangeal joints, 34 joints progressed based on the SDD, while 11 joints widened. Twenty-one joints progressed in the computer-based method, 11 joints in the scoring systems, and 13 joints in both methods. Based on the SDD, we found lower sensitivity and higher specificity with 54.2 and 92.8%, respectively. At the most discriminant cutoff point according to the ROC curve, the sensitivity and specificity was 70.8 and 81.7%, respectively. The proposed computer-based method provides quantitative measurement of JSN progression using sequential hand radiographs and may be a useful tool in follow-up assessment of joint damage in RA patients.

A combination of three-dimensional printing and computer-assisted virtual surgical procedure for preoperative planning of acetabular fracture reduction.

PubMed

Zeng, Canjun; Xing, Weirong; Wu, Zhanglin; Huang, Huajun; Huang, Wenhua

2016-10-01

Treatment of acetabular fractures remains one of the most challenging tasks that orthopaedic surgeons face. An accurate assessment of the injuries and preoperative planning are essential for an excellent reduction. The purpose of this study was to evaluate the feasibility, accuracy and effectiveness of performing 3D printing technology and computer-assisted virtual surgical procedures for preoperative planning in acetabular fractures. We hypothesised that more accurate preoperative planning using 3D printing models will reduce the operation time and significantly improve the outcome of acetabular fracture repair. Ten patients with acetabular fractures were recruited prospectively and examined by CT scanning. A 3-D model of each acetabular fracture was reconstructed with MIMICS14.0 software from the DICOM file of the CT data. Bone fragments were moved and rotated to simulate fracture reduction and restore the pelvic integrity with virtual fixation. The computer-assisted 3D image of the reduced acetabula was printed for surgery simulation and plate pre-bending. The postoperative CT scan was performed to compare the consistency of the preoperative planning with the surgical implants by 3D-superimposition in MIMICS14.0, and evaluated by Matta's method. Computer-based pre-operations were precisely mimicked and consistent with the actual operations in all cases. The pre-bent fixation plates had an anatomical shape specifically fit to the individual pelvis without further bending or adjustment at the time of surgery and fracture reductions were significantly improved. Seven out of 10 patients had a displacement of fracture reduction of less than 1mm; 3 cases had a displacement of fracture reduction between 1 and 2mm. The 3D printing technology combined with virtual surgery for acetabular fractures is feasible, accurate, and effective leading to improved patient-specific preoperative planning and outcome of real surgery. The results provide useful technical tips in planning pelvic surgeries. Copyright © 2016 Elsevier Ltd. All rights reserved.

A neuropsychological rehabilitation program for patients with Multiple Sclerosis based on the model of the ICF.

PubMed

Pusswald, Gisela; Mildner, Christa; Zebenholzer, Karin; Auff, Eduard; Lehrner, Johann

2014-01-01

Forty to sixty percent of MS patients suffer from cognitive impairments. Cognitive deficits are a great burden for patients affected. In particular they may lead to a reduced quality of life, loss of work and problems with the social environment. The aim of this study was to evaluate a specific neuropsychological rehabilitation program for MS patients according to the ICF to be able to meet more properly individual requirements on the therapy level of function as well as of activities and participation. Forty patients with MS were randomised in an intervention (IG) - and a control group (CG). The outcome measure of the IG, who started an intensive computer based home training of attention and attended psychological counselling was compared to the untrained CG. In specific domains of attention (simple and cued alertness and divided attention) significant group differences between CG and IG could be found. The IG reported an improvement of mental fatigue and retardation. These findings support the idea that a neuropsychological rehabilitation program, which based on the model of ICF, could improve cognitive impairment and could also have a positive influence of activities and participation.

3D printing PLGA: a quantitative examination of the effects of polymer composition and printing parameters on print resolution

PubMed Central

Guo, Ting; Holzberg, Timothy R; Lim, Casey G; Gao, Feng; Gargava, Ankit; Trachtenberg, Jordan E; Mikos, Antonios G; Fisher, John P

2018-01-01

In the past few decades, 3D printing has played a significant role in fabricating scaffolds with consistent, complex structure that meet patient-specific needs in future clinical applications. Although many studies have contributed to this emerging field of additive manufacturing, which includes material development and computer-aided scaffold design, current quantitative analyses do not correlate material properties, printing parameters, and printing outcomes to a great extent. A model that correlates these properties has tremendous potential to standardize 3D printing for tissue engineering and biomaterial science. In this study, we printed poly(lactic-co-glycolic acid) (PLGA) utilizing a direct melt extrusion technique without additional ingredients. We investigated PLGA with various lactic acid: glycolic acid (LA:GA) molecular weight ratios and end caps to demonstrate the dependence of the extrusion process on the polymer composition. Micro-computed tomography was then used to evaluate printed scaffolds containing different LA:GA ratios, composed of different fiber patterns, and processed under different printing conditions. We built a statistical model to reveal the correlation and predominant factors that determine printing precision. Our model showed a strong linear relationship between the actual and predicted precision under different combinations of printing conditions and material compositions. This quantitative examination establishes a significant foreground to 3D print biomaterials following a systematic fabrication procedure. Additionally, our proposed statistical models can be applied to couple specific biomaterials and 3D printing applications for patient implants with particular requirements. PMID:28244880

3D printing PLGA: a quantitative examination of the effects of polymer composition and printing parameters on print resolution.

PubMed

Guo, Ting; Holzberg, Timothy R; Lim, Casey G; Gao, Feng; Gargava, Ankit; Trachtenberg, Jordan E; Mikos, Antonios G; Fisher, John P

2017-04-12

In the past few decades, 3D printing has played a significant role in fabricating scaffolds with consistent, complex structure that meet patient-specific needs in future clinical applications. Although many studies have contributed to this emerging field of additive manufacturing, which includes material development and computer-aided scaffold design, current quantitative analyses do not correlate material properties, printing parameters, and printing outcomes to a great extent. A model that correlates these properties has tremendous potential to standardize 3D printing for tissue engineering and biomaterial science. In this study, we printed poly(lactic-co-glycolic acid) (PLGA) utilizing a direct melt extrusion technique without additional ingredients. We investigated PLGA with various lactic acid:glycolic acid (LA:GA) molecular weight ratios and end caps to demonstrate the dependence of the extrusion process on the polymer composition. Micro-computed tomography was then used to evaluate printed scaffolds containing different LA:GA ratios, composed of different fiber patterns, and processed under different printing conditions. We built a statistical model to reveal the correlation and predominant factors that determine printing precision. Our model showed a strong linear relationship between the actual and predicted precision under different combinations of printing conditions and material compositions. This quantitative examination establishes a significant foreground to 3D print biomaterials following a systematic fabrication procedure. Additionally, our proposed statistical models can be applied to couple specific biomaterials and 3D printing applications for patient implants with particular requirements.

Geometry reconstruction method for patient-specific finite element models for the assessment of tibia fracture risk in osteogenesis imperfecta.

PubMed

Caouette, Christiane; Ikin, Nicole; Villemure, Isabelle; Arnoux, Pierre-Jean; Rauch, Frank; Aubin, Carl-Éric

2017-04-01

Lower limb deformation in children with osteogenesis imperfecta (OI) impairs ambulation and may lead to fracture. Corrective surgery is based on empirical assessment criteria. The objective was to develop a reconstruction method of the tibia for OI patients that could be used as input of a comprehensive finite element model to assess fracture risks. Data were obtained from three children with OI and tibia deformities. Four pQCT scans were registered to biplanar radiographs, and a template mesh was deformed to fit the bone outline. Cortical bone thickness was computed. Sensitivity of the model to missing slices of pQCT was assessed by calculating maximal von Mises stress for a vertical hopping load case. Sensitivity of the model to ±5 % of cortical thickness measurements was assessed by calculating loads at fracture. Difference between the mesh contour and bone outline on the radiographs was below 1 mm. Removal of one pQCT slice increased maximal von Mises stress by up to 10 %. Simulated ±5 % variation of cortical bone thickness leads to variations of up to 4.1 % on predicted fracture loads. Using clinically available tibia imaging from children with OI, the developed reconstruction method allowed the building of patient-specific finite element models.

Haptic simulation framework for determining virtual dental occlusion.

PubMed

Wu, Wen; Chen, Hui; Cen, Yuhai; Hong, Yang; Khambay, Balvinder; Heng, Pheng Ann

2017-04-01

The surgical treatment of many dentofacial deformities is often complex due to its three-dimensional nature. To determine the dental occlusion in the most stable position is essential for the success of the treatment. Computer-aided virtual planning on individualized patient-specific 3D model can help formulate the surgical plan and predict the surgical change. However, in current computer-aided planning systems, it is not possible to determine the dental occlusion of the digital models in the intuitive way during virtual surgical planning because of absence of haptic feedback. In this paper, a physically based haptic simulation framework is proposed, which can provide surgeons with the intuitive haptic feedback to determine the dental occlusion of the digital models in their most stable position. To provide the physically realistic force feedback when the dental models contact each other during the searching process, the contact model is proposed to describe the dynamic and collision properties of the dental models during the alignment. The simulated impulse/contact-based forces are integrated into the unified simulation framework. A validation study has been conducted on fifteen sets of virtual dental models chosen at random and covering a wide range of the dental relationships found clinically. The dental occlusions obtained by an expert were employed as a benchmark to compare the virtual occlusion results. The mean translational and angular deviations of the virtual occlusion results from the benchmark were small. The experimental results show the validity of our method. The simulated forces can provide valuable insights to determine the virtual dental occlusion. The findings of this work and the validation of proposed concept lead the way for full virtual surgical planning on patient-specific virtual models allowing fully customized treatment plans for the surgical correction of dentofacial deformities.

Virtual reality neurosurgery: a simulator blueprint.

PubMed

Spicer, Mark A; van Velsen, Martin; Caffrey, John P; Apuzzo, Michael L J

2004-04-01

This article details preliminary studies undertaken to integrate the most relevant advancements across multiple disciplines in an effort to construct a highly realistic neurosurgical simulator based on a distributed computer architecture. Techniques based on modified computational modeling paradigms incorporating finite element analysis are presented, as are current and projected efforts directed toward the implementation of a novel bidirectional haptic device. Patient-specific data derived from noninvasive magnetic resonance imaging sequences are used to construct a computational model of the surgical region of interest. Magnetic resonance images of the brain may be coregistered with those obtained from magnetic resonance angiography, magnetic resonance venography, and diffusion tensor imaging to formulate models of varying anatomic complexity. The majority of the computational burden is encountered in the presimulation reduction of the computational model and allows realization of the required threshold rates for the accurate and realistic representation of real-time visual animations. Intracranial neurosurgical procedures offer an ideal testing site for the development of a totally immersive virtual reality surgical simulator when compared with the simulations required in other surgical subspecialties. The material properties of the brain as well as the typically small volumes of tissue exposed in the surgical field, coupled with techniques and strategies to minimize computational demands, provide unique opportunities for the development of such a simulator. Incorporation of real-time haptic and visual feedback is approached here and likely will be accomplished soon.

A Physiological Signal Transmission Model to be Used for Specific Diagnosis of Cochlear Impairments

NASA Astrophysics Data System (ADS)

Saremi, Amin; Stenfelt, Stefan

2011-11-01

Many of the sophisticated characteristics of human auditory system are attributed to cochlea. Also, most of patients with a hearing loss suffer from impairments that originate from cochlea (sensorineural). Despite this, today's clinical diagnosis methods do not probe the specific origins of such cochlear lesions. The aim of this research is to introduce a physiological signal transmission model to be clinically used as a tool for diagnosis of cochlear losses. This model enables simulation of different bio-mechano-electrical processes which occur in the auditory organ of Corti inside the cochlea. What makes this model different from many available computational models is its loyalty to physiology since the ultimate goal is to model each single physiological phenomenon. This includes passive BM vibration, outer hair cells' performances such as nonlinear mechanoelectrical transduction (MET), active amplifications by somatic motor, as well as vibration to neural conversion at the inner hair cells.

Patient-Specific Modeling of Interventricular Hemodynamics in Single Ventricle Physiology

NASA Astrophysics Data System (ADS)

Vedula, Vijay; Feinstein, Jeffrey; Marsden, Alison

2016-11-01

Single ventricle (SV) congenital heart defects, in which babies are born with only functional ventricle, lead to significant morbidity and mortality with over 30% of patients developing heart failure prior to adulthood. Newborns with SV physiology typically undergo three palliative surgeries, in which the SV becomes the systemic pumping chamber. Depending on which ventricle performs the systemic function, patients are classified as having either a single left ventricle (SLV) or a single right ventricle (SRV), with SRV patients at higher risk of failure. As the native right ventricles are not designed to meet systemic demands, they undergo remodeling leading to abnormal hemodynamics. The hemodynamic characteristics of SLVs compared with SRVs is not well established. We present a validated computational framework for performing patient-specific modeling of ventricular flows, and apply it across 6 SV patients (3SLV + 3SRV), comparing hemodynamic conditions between the two subgroups. Simulations are performed with a stabilized finite element method coupled with an immersed boundary method for modeling heart valves. We discuss identification of hemodynamic biomarkers of ventricular remodeling for early risk assessment of failure. This research is supported in part by the Stanford Child Health Research Institute and the Stanford NIH-NCATS-CTSA through Grant UL1 TR001085 and due to U.S. National Institute of Health through NIH NHLBI R01 Grants 5R01HL129727-02 and 5R01HL121754-03.

Combined diagnostic performance of coronary computed tomography angiography and computed tomography derived fractional flow reserve for the evaluation of myocardial ischemia: A meta-analysis.

PubMed

Tan, Xiao Wei; Zheng, Qishi; Shi, Luming; Gao, Fei; Allen, John Carson; Coenen, Adriaan; Baumann, Stefan; Schoepf, U Joseph; Kassab, Ghassan S; Lim, Soo Teik; Wong, Aaron Sung Lung; Tan, Jack Wei Chieh; Yeo, Khung Keong; Chin, Chee Tang; Ho, Kay Woon; Tan, Swee Yaw; Chua, Terrance Siang Jin; Chan, Edwin Shih Yen; Tan, Ru San; Zhong, Liang

2017-06-01

To evaluate the combined diagnostic accuracy of coronary computed tomography angiography (CCTA) and computed tomography derived fractional flow reserve (FFRct) in patients with suspected or known coronary artery disease (CAD). PubMed, The Cochrane library, Embase and OpenGray were searched to identify studies comparing diagnostic accuracy of CCTA and FFRct. Diagnostic test measurements of FFRct were either extracted directly from the published papers or calculated from provided information. Bivariate models were conducted to synthesize the diagnostic performance of combined CCTA and FFRct at both "per-vessel" and "per-patient" levels. 7 articles were included for analysis. The combined diagnostic outcomes from "both positive" strategy, i.e. a subject was considered as "positive" only when both CCTA and FFRct were "positive", demonstrated relative high specificity (per-vessel: 0.91; per-patient: 0.81), high positive likelihood ratio (LR+, per-vessel: 7.93; per-patient: 4.26), high negative likelihood ratio (LR-, per-vessel: 0.30; per patient: 0.24) and high accuracy (per-vessel: 0.91; per-patient: 0.81) while "either positive" strategy, i.e. a subject was considered as "positive" when either CCTA or FFRct was "positive", demonstrated relative high sensitivity (per-vessel: 0.97; per-patient: 0.98), low LR+ (per-vessel: 1.50; per-patient: 1.17), low LR- (per-vessel: 0.07; per-patient: 0.09) and low accuracy (per-vessel: 0.57; per-patient: 0.54). "Both positive" strategy showed better diagnostic performance to rule in patients with non-significant stenosis compared to "either positive" strategy, as it efficiently reduces the proportion of testing false positive subjects. Copyright © 2017 Elsevier B.V. All rights reserved.

Patient-specific three-dimensional printing for pre-surgical planning in hepatocellular carcinoma treatment.

PubMed

Perica, Elizabeth; Sun, Zhonghua

2017-12-01

Recently, three-dimensional (3D) printing has shown great interest in medicine, and 3D printed models may be rendered as part of the pre-surgical planning process in order to better understand the complexities of an individual's anatomy. The aim of this study is to investigate the feasibility of utilising 3D printed liver models as clinical tools in pre-operative planning for resectable hepatocellular carcinoma (HCC) lesions. High-resolution contrast-enhanced computed tomography (CT) images were acquired and utilized to generate a patient-specific 3D printed liver model. Hepatic structures were segmented and edited to produce a printable model delineating intrahepatic anatomy and a resectable HCC lesion. Quantitative assessment of 3D model accuracy compared measurements of critical anatomical landmarks acquired from the original CT images, standard tessellation language (STL) files, and the 3D printed liver model. Comparative analysis of surveys completed by two radiologists investigated the clinical value of 3D printed liver models in radiology. The application of utilizing 3D printed liver models as tools in surgical planning for resectable HCC lesions was evaluated through kappa analysis of questionnaires completed by two abdominal surgeons. A scaled down multi-material 3D liver model delineating patient-specific hepatic anatomy and pathology was produced, requiring a total production time of 25.25 hours and costing a total of AUD $1,250. A discrepancy was found in the total mean of measurements at each stage of production, with a total mean of 18.28±9.31 mm for measurements acquired from the original CT data, 15.63±8.06 mm for the STL files, and 14.47±7.71 mm for the 3D printed liver model. The 3D liver model did not enhance the radiologists' perception of patient-specific anatomy or pathology. Kappa analysis of the surgeon's responses to survey questions yielded a percentage agreement of 80%, and a κ value of 0.38 (P=0.24) indicating fair agreement. Study outcomes indicate that there is minimal value in utilizing the 3D printed models in diagnostic radiology. The potential usefulness of utilizing patient-specific 3D printed liver models as tools in surgical planning and intraoperative guidance for HCC treatment is verified. However, the feasibility of this application is currently challenged by identified limitations in 3D model production, including the cost and time required for model production, and inaccuracies potentially introduced at each stage of model fabrication.

A 4D global respiratory motion model of the thorax based on CT images: A proof of concept.

PubMed

Fayad, Hadi; Gilles, Marlene; Pan, Tinsu; Visvikis, Dimitris

2018-05-17

Respiratory motion reduces the sensitivity and specificity of medical images especially in the thoracic and abdominal areas. It may affect applications such as cancer diagnostic imaging and/or radiation therapy (RT). Solutions to this issue include modeling of the respiratory motion in order to optimize both diagnostic and therapeutic protocols. Personalized motion modeling required patient-specific four-dimensional (4D) imaging which in the case of 4D computed tomography (4D CT) acquisition is associated with an increased dose. The goal of this work was to develop a global respiratory motion model capable of relating external patient surface motion to internal structure motion without the need for a patient-specific 4D CT acquisition. The proposed global model is based on principal component analysis and can be adjusted to a given patient anatomy using only one or two static CT images in conjunction with a respiratory synchronized patient external surface motion. It is based on the relation between the internal motion described using deformation fields obtained by registering 4D CT images and patient surface maps obtained either from optical imaging devices or extracted from CT image-based patient skin segmentation. 4D CT images of six patients were used to generate the global motion model which was validated by adapting it on four different patients having skin segmented surfaces and two other patients having time of flight camera acquired surfaces. The reproducibility of the proposed model was also assessed on two patients with two 4D CT series acquired within 2 weeks of each other. Profile comparison shows the efficacy of the global respiratory motion model and an improvement while using two CT images in order to adapt the model. This was confirmed by the correlation coefficient with a mean correlation of 0.9 and 0.95 while using one or two CT images respectively and when comparing acquired to model generated 4D CT images. For the four patients with segmented surfaces, expert validation indicates an error of 2.35 ± 0.26 mm compared to 6.07 ± 0.76 mm when using a simple interpolation between full inspiration (FI) and full expiration (FE) CT only; i.e., without specific modeling of the respiratory motion. For the two patients with acquired surfaces, this error was of 2.48 ± 0.18 mm. In terms of reproducibility, model error changes of 0.12 and 0.17 mm were measured for the two patients concerned. The framework for the derivation of a global respiratory motion model was developed. A single or two static CT images and associated patient surface motion, as a surrogate measure, are only needed to personalize the model. This model accuracy and reproducibility were assessed by comparing acquired vs model generated 4D CT images. Future work will consist of assessing extensively the proposed model for radiotherapy applications. © 2018 American Association of Physicists in Medicine.

Computer Models of Personality: Implications for Measurement

ERIC Educational Resources Information Center

Cranton, P. A.

1976-01-01

Current research on computer models of personality is reviewed and categorized under five headings: (1) models of belief systems; (2) models of interpersonal behavior; (3) models of decision-making processes; (4) prediction models; and (5) theory-based simulations of specific processes. The use of computer models in personality measurement is…

A predictive software tool for optimal timing in contrast enhanced carotid MR angiography

NASA Astrophysics Data System (ADS)

Moghaddam, Abbas N.; Balawi, Tariq; Habibi, Reza; Panknin, Christoph; Laub, Gerhard; Ruehm, Stefan; Finn, J. Paul

2008-03-01

A clear understanding of the first pass dynamics of contrast agents in the vascular system is crucial in synchronizing data acquisition of 3D MR angiography (MRA) with arrival of the contrast bolus in the vessels of interest. We implemented a computational model to simulate contrast dynamics in the vessels using the theory of linear time-invariant systems. The algorithm calculates a patient-specific impulse response for the contrast concentration from time-resolved images following a small test bolus injection. This is performed for a specific region of interest and through deconvolution of the intensity curve using the long division method. Since high spatial resolution 3D MRA is not time-resolved, the method was validated on time-resolved arterial contrast enhancement in Multi Slice CT angiography. For 20 patients, the timing of the contrast enhancement of the main bolus was predicted by our algorithm from the response to the test bolus, and then for each case the predicted time of maximum intensity was compared to the corresponding time in the actual scan which resulted in an acceptable agreement. Furthermore, as a qualitative validation, the algorithm's predictions of the timing of the carotid MRA in 20 patients with high quality MRA were correlated with the actual timing of those studies. We conclude that the above algorithm can be used as a practical clinical tool to eliminate guesswork and to replace empiric formulae by a priori computation of patient-specific timing of data acquisition for MR angiography.

CT-based patient modeling for head and neck hyperthermia treatment planning: manual versus automatic normal-tissue-segmentation.

PubMed

Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M

2014-04-01

Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H&N) carcinoma. Hyperthermia treatment planning (HTP) guided H&N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Automatically generated 3D patient models can be introduced in the clinic for H&N HTP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Computer Model Used to Help Customize Medicine

NASA Technical Reports Server (NTRS)

Stauber, Laurel J.; Veris, Jenise

2001-01-01

Dr. Radhakrishnan, a researcher at the NASA Glenn Research Center, in collaboration with biomedical researchers at the Case Western Reserve University School of Medicine and Rainbow Babies and Children's Hospital, is developing computational models of human physiology that quantitate metabolism and its regulation, in both healthy and pathological states. These models can help predict the effects of stresses or interventions, such as drug therapies, and contribute to the development of customized medicine. Customized medical treatment protocols can give more comprehensive evaluations and lead to more specific and effective treatments for patients, reducing treatment time and cost. Commercial applications of this research may help the pharmaceutical industry identify therapeutic needs and predict drug-drug interactions. Researchers will be able to study human metabolic reactions to particular treatments while in different environments as well as establish more definite blood metabolite concentration ranges in normal and pathological states. These computational models may help NASA provide the background for developing strategies to monitor and safeguard the health of astronauts and civilians in space stations and colonies. They may also help to develop countermeasures that ameliorate the effects of both acute and chronic space exposure.

Computational Modeling of Fluid–Structure–Acoustics Interaction during Voice Production

PubMed Central

Jiang, Weili; Zheng, Xudong; Xue, Qian

2017-01-01

The paper presented a three-dimensional, first-principle based fluid–structure–acoustics interaction computer model of voice production, which employed a more realistic human laryngeal and vocal tract geometries. Self-sustained vibrations, important convergent–divergent vibration pattern of the vocal folds, and entrainment of the two dominant vibratory modes were captured. Voice quality-associated parameters including the frequency, open quotient, skewness quotient, and flow rate of the glottal flow waveform were found to be well within the normal physiological ranges. The analogy between the vocal tract and a quarter-wave resonator was demonstrated. The acoustic perturbed flux and pressure inside the glottis were found to be at the same order with their incompressible counterparts, suggesting strong source–filter interactions during voice production. Such high fidelity computational model will be useful for investigating a variety of pathological conditions that involve complex vibrations, such as vocal fold paralysis, vocal nodules, and vocal polyps. The model is also an important step toward a patient-specific surgical planning tool that can serve as a no-risk trial and error platform for different procedures, such as injection of biomaterials and thyroplastic medialization. PMID:28243588

Trends in radiology and experimental research.

PubMed

Sardanelli, Francesco

2017-01-01

European Radiology Experimental , the new journal launched by the European Society of Radiology, is placed in the context of three general and seven radiology-specific trends. After describing the impact of population aging, personalized/precision medicine, and information technology development, the article considers the following trends: the tension between subspecialties and the unity of the discipline; attention to patient safety; the challenge of reproducibility for quantitative imaging; standardized and structured reporting; search for higher levels of evidence in radiology (from diagnostic performance to patient outcome); the increasing relevance of interventional radiology; and continuous technological evolution. The new journal will publish not only studies on phantoms, cells, or animal models but also those describing development steps of imaging biomarkers or those exploring secondary end-points of large clinical trials. Moreover, consideration will be given to studies regarding: computer modelling and computer aided detection and diagnosis; contrast materials, tracers, and theranostics; advanced image analysis; optical, molecular, hybrid and fusion imaging; radiomics and radiogenomics; three-dimensional printing, information technology, image reconstruction and post-processing, big data analysis, teleradiology, clinical decision support systems; radiobiology; radioprotection; and physics in radiology. The journal aims to establish a forum for basic science, computer and information technology, radiology, and other medical subspecialties.

Application of computer-aided design osteotomy template for treatment of cubitus varus deformity in teenagers: a pilot study.

PubMed

Zhang, Yuan Z; Lu, Sheng; Chen, Bin; Zhao, Jian M; Liu, Rui; Pei, Guo X

2011-01-01

Treatment of cubitus varus deformity from a malunited fracture is a challenge. Anatomically accurate correction is the key to obtaining good functional outcomes after corrective osteotomy. The aim of this study was to attempt to increase the accuracy of treatment by use of 3-dimensional (3D) computer-aided design. We describe a novel method for ensuring an accurate osteotomy method in the treatment of cubitus varus deformity in teenagers by means of 3D reconstruction and reverse engineering. Between January 2006 and May 2008, 12 male and 6 female patients with cubitus varus deformities underwent scanning with spiral computed tomography (CT) preoperatively. The mean age was 15.7 years, ranging from 13 to 19 years. Three-dimensional CT image data of the affected and contralateral normal bones of cubitus were transferred to a computer workstation. Three-dimensional models of cubitus were reconstructed by use of MIMICS software. The 3D models were then processed by Imageware software. An osteotomy template that best fitted the angle and range of osteotomy was "reversely" built from the 3D model. These templates were manufactured by a rapid prototyping machine. The osteotomy templates guide the osteotomy of cubitus. An accurate angle of osteotomy was confirmed by postoperative radiography. After 12 to 24 months' follow-up, the mean postoperative carrying angle in 18 patients with cubitus varus deformity was 7.3° (range, 5° to 11°), with a mean correction of 21.9° (range, 12° to 41°). The patient-specific template technique is easy to use, can simplify the surgical act, and generates highly accurate osteotomy in cubitus varus deformity in teenagers. Copyright © 2011 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Mosby, Inc. All rights reserved.

Computer assisted surgery in preoperative planning of acetabular fracture surgery: state of the art.

PubMed

Boudissa, Mehdi; Courvoisier, Aurélien; Chabanas, Matthieu; Tonetti, Jérôme

2018-01-01

The development of imaging modalities and computer technology provides a new approach in acetabular surgery. Areas covered: This review describes the role of computer-assisted surgery (CAS) in understanding of the fracture patterns, in the virtual preoperative planning of the surgery and in the use of custom-made plates in acetabular fractures with or without 3D printing technologies. A Pubmed internet research of the English literature of the last 20 years was carried out about studies concerning computer-assisted surgery in acetabular fractures. The several steps for CAS in acetabular fracture surgery are presented and commented by the main author regarding to his personal experience. Expert commentary: Computer-assisted surgery in acetabular fractures is still initial experiences with promising results. Patient-specific biomechanical models considering soft tissues should be developed to allow a more realistic planning.

Semantic representation in the white matter pathway

PubMed Central

Fang, Yuxing; Wang, Xiaosha; Zhong, Suyu; Song, Luping; Han, Zaizhu; Gong, Gaolang

2018-01-01

Object conceptual processing has been localized to distributed cortical regions that represent specific attributes. A challenging question is how object semantic space is formed. We tested a novel framework of representing semantic space in the pattern of white matter (WM) connections by extending the representational similarity analysis (RSA) to structural lesion pattern and behavioral data in 80 brain-damaged patients. For each WM connection, a neural representational dissimilarity matrix (RDM) was computed by first building machine-learning models with the voxel-wise WM lesion patterns as features to predict naming performance of a particular item and then computing the correlation between the predicted naming score and the actual naming score of another item in the testing patients. This correlation was used to build the neural RDM based on the assumption that if the connection pattern contains certain aspects of information shared by the naming processes of these two items, models trained with one item should also predict naming accuracy of the other. Correlating the neural RDM with various cognitive RDMs revealed that neural patterns in several WM connections that connect left occipital/middle temporal regions and anterior temporal regions associated with the object semantic space. Such associations were not attributable to modality-specific attributes (shape, manipulation, color, and motion), to peripheral picture-naming processes (picture visual similarity, phonological similarity), to broad semantic categories, or to the properties of the cortical regions that they connected, which tended to represent multiple modality-specific attributes. That is, the semantic space could be represented through WM connection patterns across cortical regions representing modality-specific attributes. PMID:29624578

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging

NASA Astrophysics Data System (ADS)

Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2014-03-01

As an emerging technology, hyperspectral imaging (HSI) combines both the chemical specificity of spectroscopy and the spatial resolution of imaging, which may provide a non-invasive tool for cancer detection and diagnosis. Early detection of malignant lesions could improve both survival and quality of life of cancer patients. In this paper, we introduce a tensor-based computation and modeling framework for the analysis of hyperspectral images to detect head and neck cancer. The proposed classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 96.97% and an average specificity of 91.42% in tumor-bearing mice. The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management.

Uncertainty propagation for SPECT/CT-based renal dosimetry in 177Lu peptide receptor radionuclide therapy

NASA Astrophysics Data System (ADS)

Gustafsson, Johan; Brolin, Gustav; Cox, Maurice; Ljungberg, Michael; Johansson, Lena; Sjögreen Gleisner, Katarina

2015-11-01

A computer model of a patient-specific clinical 177Lu-DOTATATE therapy dosimetry system is constructed and used for investigating the variability of renal absorbed dose and biologically effective dose (BED) estimates. As patient models, three anthropomorphic computer phantoms coupled to a pharmacokinetic model of 177Lu-DOTATATE are used. Aspects included in the dosimetry-process model are the gamma-camera calibration via measurement of the system sensitivity, selection of imaging time points, generation of mass-density maps from CT, SPECT imaging, volume-of-interest delineation, calculation of absorbed-dose rate via a combination of local energy deposition for electrons and Monte Carlo simulations of photons, curve fitting and integration to absorbed dose and BED. By introducing variabilities in these steps the combined uncertainty in the output quantity is determined. The importance of different sources of uncertainty is assessed by observing the decrease in standard deviation when removing a particular source. The obtained absorbed dose and BED standard deviations are approximately 6% and slightly higher if considering the root mean square error. The most important sources of variability are the compensation for partial volume effects via a recovery coefficient and the gamma-camera calibration via the system sensitivity.

Computational modeling of chemo-bio-mechanical coupling: a systems-biology approach toward wound healing.

PubMed

Buganza Tepole, A; Kuhl, E

2016-01-01

Wound healing is a synchronized cascade of chemical, biological, and mechanical phenomena, which act in concert to restore the damaged tissue. An imbalance between these events can induce painful scarring. Despite intense efforts to decipher the mechanisms of wound healing, the role of mechanics remains poorly understood. Here, we establish a computational systems biology model to identify the chemical, biological, and mechanical mechanisms of scar formation. First, we introduce the generic problem of coupled chemo-bio-mechanics. Then, we introduce the model problem of wound healing in terms of a particular chemical signal, inflammation, a particular biological cell type, fibroblasts, and a particular mechanical model, isotropic hyperelasticity. We explore the cross-talk between chemical, biological, and mechanical signals and show that all three fields have a significant impact on scar formation. Our model is the first step toward rigorous multiscale, multifield modeling in wound healing. Our formulation has the potential to improve effective wound management and optimize treatment on an individualized patient-specific basis.

An interface finite element model can be used to predict healing outcome of bone fractures.

PubMed

Alierta, J A; Pérez, M A; García-Aznar, J M

2014-01-01

After fractures, bone can experience different potential outcomes: successful bone consolidation, non-union and bone failure. Although, there are a lot of factors that influence fracture healing, experimental studies have shown that the interfragmentary movement (IFM) is one of the main regulators for the course of bone healing. In this sense, computational models may help to improve the development of mechanical-based treatments for bone fracture healing. Hence, based on this fact, we propose a combined repair-failure mechanistic computational model to describe bone fracture healing. Despite being a simple model, it is able to correctly estimate the time course evolution of the IFM compared to in vivo measurements under different mechanical conditions. Therefore, this mathematical approach is especially suitable for modeling the healing response of bone to fractures treated with different mechanical fixators, simulating realistic clinical conditions. This model will be a useful tool to identify factors and define targets for patient specific therapeutics interventions. © 2013 Published by Elsevier Ltd.

Metabolic flexibility of mitochondrial respiratory chain disorders predicted by computer modelling.

PubMed

Zieliński, Łukasz P; Smith, Anthony C; Smith, Alexander G; Robinson, Alan J

2016-11-01

Mitochondrial respiratory chain dysfunction causes a variety of life-threatening diseases affecting about 1 in 4300 adults. These diseases are genetically heterogeneous, but have the same outcome; reduced activity of mitochondrial respiratory chain complexes causing decreased ATP production and potentially toxic accumulation of metabolites. Severity and tissue specificity of these effects varies between patients by unknown mechanisms and treatment options are limited. So far most research has focused on the complexes themselves, and the impact on overall cellular metabolism is largely unclear. To illustrate how computer modelling can be used to better understand the potential impact of these disorders and inspire new research directions and treatments, we simulated them using a computer model of human cardiomyocyte mitochondrial metabolism containing over 300 characterised reactions and transport steps with experimental parameters taken from the literature. Overall, simulations were consistent with patient symptoms, supporting their biological and medical significance. These simulations predicted: complex I deficiencies could be compensated using multiple pathways; complex II deficiencies had less metabolic flexibility due to impacting both the TCA cycle and the respiratory chain; and complex III and IV deficiencies caused greatest decreases in ATP production with metabolic consequences that parallel hypoxia. Our study demonstrates how results from computer models can be compared to a clinical phenotype and used as a tool for hypothesis generation for subsequent experimental testing. These simulations can enhance understanding of dysfunctional mitochondrial metabolism and suggest new avenues for research into treatment of mitochondrial disease and other areas of mitochondrial dysfunction. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Bilateral Malar Reconstruction Using Patient-Specific Polyether Ether Ketone Implants in Treacher-Collins Syndrome Patients With Absent Zygomas.

PubMed

Sainsbury, David C G; George, Alan; Forrest, Christopher R; Phillips, John H

2017-03-01

The authors performed bilateral malar reconstruction using polyether ether ketone implants in 3 patients with Treacher-Collins syndrome with absent, as opposed to hypoplastic, zygomata. These patient-specific implants were fabricated using computed-aided design software reformatted from three-dimensional bony preoperative computed tomography images. The first time the authors performed this procedure the implant compressed the globe resulting in temporary anisocoria that was quickly recognized intraoperatively. The implant was immediately removed and the patient made a full-recovery with no ocular disturbance. The computer-aided design and manufacturing process was adjusted to include periorbital soft-tissue boundaries to aid in contouring the new implants. The same patient, and 2 further patients, subsequently underwent malar reconstruction using this soft tissue periorbital boundary fabrication process with an additional 2 mm relief removed from the implant's orbital surface. These subsequent procedures were performed without complication and with pleasing aesthetic results. The authors describe their experience and the salutary lessons learnt.

Scan, plan, print, practice, perform: Development and use of a patient-specific 3-dimensional printed model in adult cardiac surgery.

PubMed

Hermsen, Joshua L; Burke, Thomas M; Seslar, Stephen P; Owens, David S; Ripley, Beth A; Mokadam, Nahush A; Verrier, Edward D

2017-01-01

Static 3-dimensional printing is used for operative planning in cases that involve difficult anatomy. An interactive 3D print allowing deliberate surgical practice would represent an advance. Two patients with hypertrophic cardiomyopathy had 3-dimensional prints constructed preoperatively. Stereolithography files were generated by segmentation of chest computed tomographic scans. Prints were made with hydrogel material, yielding tissue-like models that can be surgically manipulated. Septal myectomy of the print was performed preoperatively in the simulation laboratory. Volumetric measures of print and patient resected specimens were compared. An assessment tool was developed and used to rate the utility of this process. Clinical and echocardiographic data were reviewed. There was congruence between volumes of print and patient resection specimens (patient 1, 3.5 cm 3 and 3.0 cm 3 , respectively; patient 2, 4.0 cm 3 and 4.0 cm 3 , respectively). The prints were rated useful (3.5 and 3.6 on a 5-point Likert scale) for preoperative visualization, planning, and practice. Intraoperative echocardiographic assessment showed adequate relief of left ventricular outflow tract obstruction (patient 1, 80 mm Hg to 18 mm Hg; patient 2, 96 mm Hg to 9 mm Hg). Both patients reported symptomatic improvement (New York Heart Association functional class III to class I). Three-dimensional printing of interactive hypertrophic cardiomyopathy heart models allows for patient-specific preoperative simulation. Resection volume relationships were congruous on both specimens and suggest evidence of construct validity. This model also holds educational promise for simulation of a low-volume, high-risk operation that is traditionally difficult to teach. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Role of Statistical Random-Effects Linear Models in Personalized Medicine.

PubMed

Diaz, Francisco J; Yeh, Hung-Wen; de Leon, Jose

2012-03-01

Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regimes that are appropriate for particular patients, not just appropriate for the average patient. In fact, published developments show that random-effects linear models may provide a solid theoretical framework for drug dosage individualization in chronic diseases. In particular, individualized dosages computed with these models by means of an empirical Bayesian approach may produce better results than dosages computed with some methods routinely used in therapeutic drug monitoring. This is further supported by published empirical and theoretical findings that show that random effects linear models may provide accurate representations of phase III and IV steady-state pharmacokinetic data, and may be useful for dosage computations. These models have applications in the design of clinical algorithms for drug dosage individualization in chronic diseases; in the computation of dose correction factors; computation of the minimum number of blood samples from a patient that are necessary for calculating an optimal individualized drug dosage in therapeutic drug monitoring; measure of the clinical importance of clinical, demographic, environmental or genetic covariates; study of drug-drug interactions in clinical settings; the implementation of computational tools for web-site-based evidence farming; design of pharmacogenomic studies; and in the development of a pharmacological theory of dosage individualization.

Investigating relationships between left atrial volume, symmetry, and sphericity

NASA Astrophysics Data System (ADS)

Menon, Prahlad G.; Nedios, Sotiris; Hindricks, Gerhard; Bollmann, Andreas

2016-03-01

Catheter ablation is a safe and effective therapy for drug-refractory patients symptomatic of atrial fibrillation (AF), with up to 80% of patients experiencing long-term arrhythmia-free survival. However, up to 20-40% of patients require more than one procedure in order to become arrhythmia-free. Therefore, appropriate patient selection is paramount to the effective implementation and long-term success of ablation therapy for patients with atrial fibrillation (AF). In this study, as a precursor to evaluating clinical significance of specific LA shape metrics as pre-procedural predictors of AF recurrence following ablative pulmonary vein isolation therapy, we report on a computational geometric analysis in a pilot cohort evaluating relationships between various patient-specific metrics of LA shape which might have such predictive value. This study specifically is focused on establishing the relationship between LA volume and sphericity, using a novel methodology for computing atrial sphericity based on regional shape.

Accuracy of patient-specific guided glenoid baseplate positioning for reverse shoulder arthroplasty.

PubMed

Levy, Jonathan C; Everding, Nathan G; Frankle, Mark A; Keppler, Louis J

2014-10-01

The accuracy of reproducing a surgical plan during shoulder arthroplasty is improved by computer assistance. Intraoperative navigation, however, is challenged by increased surgical time and additional technically difficult steps. Patient-matched instrumentation has the potential to reproduce a similar degree of accuracy without the need for additional surgical steps. The purpose of this study was to examine the accuracy of patient-specific planning and a patient-specific drill guide for glenoid baseplate placement in reverse shoulder arthroplasty. A patient-specific glenoid baseplate drill guide for reverse shoulder arthroplasty was produced for 14 cadaveric shoulders based on a plan developed by a virtual preoperative 3-dimensional planning system using thin-cut computed tomography images. Using this patient-specific guide, high-volume shoulder surgeons exposed the glenoid through a deltopectoral approach and drilled the bicortical pathway defined by the guide. The trajectory of the drill path was compared with the virtual preoperative planned position using similar thin-cut computed tomography images to define accuracy. The drill pathway defined by the patient-matched guide was found to be highly accurate when compared with the preoperative surgical plan. The translational accuracy was 1.2 ± 0.7 mm. The accuracy of inferior tilt was 1.2° ± 1.2°. The accuracy of glenoid version was 2.6° ± 1.7°. The use of patient-specific glenoid baseplate guides is highly accurate in reproducing a virtual 3-dimensional preoperative plan. This technique delivers the accuracy observed using computerized navigation without any additional surgical steps or technical challenges. Copyright © 2014 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

A disease state fingerprint for evaluation of Alzheimer's disease.

PubMed

Mattila, Jussi; Koikkalainen, Juha; Virkki, Arho; Simonsen, Anja; van Gils, Mark; Waldemar, Gunhild; Soininen, Hilkka; Lötjönen, Jyrki

2011-01-01

Diagnostic processes of Alzheimer's disease (AD) are evolving. Knowledge about disease-specific biomarkers is constantly increasing and larger volumes of data are being measured from patients. To gain additional benefits from the collected data, a novel statistical modeling and data visualization system is proposed for supporting clinical diagnosis of AD. The proposed system computes an evidence-based estimate of a patient's AD state by comparing his or her heterogeneous neuropsychological, clinical, and biomarker data to previously diagnosed cases. The AD state in this context denotes a patient's degree of similarity to previously diagnosed disease population. A summary of patient data and results of the computation are displayed in a succinct Disease State Fingerprint (DSF) visualization. The visualization clearly discloses how patient data contributes to the AD state, facilitating rapid interpretation of the information. To model the AD state from complex and heterogeneous patient data, a statistical Disease State Index (DSI) method underlying the DSF has been developed. Using baseline data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the ability of the DSI to model disease progression from elderly healthy controls to AD and its ability to predict conversion from mild cognitive impairment (MCI) to AD were assessed. It was found that the DSI provides well-behaving AD state estimates, corresponding well with the actual diagnoses. For predicting conversion from MCI to AD, the DSI attains performance similar to state-of-the-art reference classifiers. The results suggest that the DSF establishes an effective decision support and data visualization framework for improving AD diagnostics, allowing clinicians to rapidly analyze large quantities of diverse patient data.

Identifying and Investigating Unexpected Response to Treatment: A Diabetes Case Study.

PubMed

Ozery-Flato, Michal; Ein-Dor, Liat; Parush-Shear-Yashuv, Naama; Aharonov, Ranit; Neuvirth, Hani; Kohn, Martin S; Hu, Jianying

2016-09-01

The availability of electronic health records creates fertile ground for developing computational models of various medical conditions. We present a new approach for detecting and analyzing patients with unexpected responses to treatment, building on machine learning and statistical methodology. Given a specific patient, we compute a statistical score for the deviation of the patient's response from responses observed in other patients having similar characteristics and medication regimens. These scores are used to define cohorts of patients showing deviant responses. Statistical tests are then applied to identify clinical features that correlate with these cohorts. We implement this methodology in a tool that is designed to assist researchers in the pharmaceutical field to uncover new features associated with reduced response to a treatment. It can also aid physicians by flagging patients who are not responding to treatment as expected and hence deserve more attention. The tool provides comprehensive visualizations of the analysis results and the supporting data, both at the cohort level and at the level of individual patients. We demonstrate the utility of our methodology and tool in a population of type II diabetic patients, treated with antidiabetic drugs, and monitored by the HbA1C test.

Ku-Band rendezvous radar performance computer simulation model

NASA Technical Reports Server (NTRS)

Magnusson, H. G.; Goff, M. F.

1984-01-01

All work performed on the Ku-band rendezvous radar performance computer simulation model program since the release of the preliminary final report is summarized. Developments on the program fall into three distinct categories: (1) modifications to the existing Ku-band radar tracking performance computer model; (2) the addition of a highly accurate, nonrealtime search and acquisition performance computer model to the total software package developed on this program; and (3) development of radar cross section (RCS) computation models for three additional satellites. All changes in the tracking model involved improvements in the automatic gain control (AGC) and the radar signal strength (RSS) computer models. Although the search and acquisition computer models were developed under the auspices of the Hughes Aircraft Company Ku-Band Integrated Radar and Communications Subsystem program office, they have been supplied to NASA as part of the Ku-band radar performance comuter model package. Their purpose is to predict Ku-band acquisition performance for specific satellite targets on specific missions. The RCS models were developed for three satellites: the Long Duration Exposure Facility (LDEF) spacecraft, the Solar Maximum Mission (SMM) spacecraft, and the Space Telescopes.

Ku-Band rendezvous radar performance computer simulation model

NASA Astrophysics Data System (ADS)

Magnusson, H. G.; Goff, M. F.

1984-06-01

All work performed on the Ku-band rendezvous radar performance computer simulation model program since the release of the preliminary final report is summarized. Developments on the program fall into three distinct categories: (1) modifications to the existing Ku-band radar tracking performance computer model; (2) the addition of a highly accurate, nonrealtime search and acquisition performance computer model to the total software package developed on this program; and (3) development of radar cross section (RCS) computation models for three additional satellites. All changes in the tracking model involved improvements in the automatic gain control (AGC) and the radar signal strength (RSS) computer models. Although the search and acquisition computer models were developed under the auspices of the Hughes Aircraft Company Ku-Band Integrated Radar and Communications Subsystem program office, they have been supplied to NASA as part of the Ku-band radar performance comuter model package. Their purpose is to predict Ku-band acquisition performance for specific satellite targets on specific missions. The RCS models were developed for three satellites: the Long Duration Exposure Facility (LDEF) spacecraft, the Solar Maximum Mission (SMM) spacecraft, and the Space Telescopes.

Cartilage Dysfunction in ALS Patients as Side Effect of Motion Loss: 3D Mechano-Electrochemical Computational Model

PubMed Central

Gaffney, Eamonn A.; Doblaré, Manuel

2014-01-01

Amyotrophic lateral sclerosis (ALS) is a debilitating motor neuron disease characterized by progressive weakness, muscle atrophy, and fasciculation. This fact results in a continuous degeneration and dysfunction of articular soft tissues. Specifically, cartilage is an avascular and nonneural connective tissue that allows smooth motion in diarthrodial joints. Due to the avascular nature of cartilage tissue, cells nutrition and by-product exchange are intermittently occurring during joint motions. Reduced mobility results in a change of proteoglycan density, osmotic pressure, and permeability of the tissue. This work aims to demonstrate the abnormal cartilage deformation in progressive immobilized articular cartilage for ALS patients. For this aim a novel 3D mechano-electrochemical model based on the triphasic theory for charged hydrated soft tissues is developed. ALS patient parameters such as tissue porosity, osmotic coefficient, and fixed anions were incorporated. Considering different mobility reduction of each phase of the disease, results predicted the degree of tissue degeneration and the reduction of its capacity for deformation. The present model can be a useful tool to predict the evolution of joints in ALS patients and the necessity of including specific cartilage protectors, drugs, or maintenance physical activities as part of the symptomatic treatment in amyotrophic lateral sclerosis. PMID:24991537

Modeling of endoluminal and interstitial ultrasound hyperthermia and thermal ablation: applications to device design, feedback control, and treatment planning

PubMed Central

Prakash, Punit; Salgaonkar, Vasant A.; Diederich, Chris J.

2014-01-01

Endoluminal and catheter-based ultrasound applicators are currently under development and are in clinical use for minimally invasive hyperthermia and thermal ablation of various tissue targets. Computational models play a critical role in in device design and optimization, assessment of therapeutic feasibility and safety, devising treatment monitoring and feedback control strategies, and performing patient-specific treatment planning with this technology. The critical aspects of theoretical modeling, applied specifically to endoluminal and interstitial ultrasound thermotherapy, are reviewed. Principles and practical techniques for modeling acoustic energy deposition, bioheat transfer, thermal tissue damage, and dynamic changes in the physical and physiological state of tissue are reviewed. The integration of these models and applications of simulation techniques in identification of device design parameters, development of real time feedback-control platforms, assessing the quality and safety of treatment delivery strategies, and optimization of inverse treatment plans are presented. PMID:23738697

Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes

NASA Astrophysics Data System (ADS)

Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.

2013-12-01

Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.

Analysis of SEER Adenosquamous Carcinoma Data to Identify Cause Specific Survival Predictors and Socioeconomic Disparities.

PubMed

Cheung, Rex

2016-01-01

This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

The impact of comorbid disease history on all-cause and cancer-specific mortality in myeloid leukemia and myeloma - a Swedish population-based study.

PubMed

Mohammadi, Mohammad; Cao, Yang; Glimelius, Ingrid; Bottai, Matteo; Eloranta, Sandra; Smedby, Karin E

2015-11-05

Comorbidity increases overall mortality in patients diagnosed with hematological malignancies. The impact of comorbidity on cancer-specific mortality, taking competing risks into account, has not been evaluated. Using the Swedish Cancer Register, we identified patients aged >18 years with a first diagnosis of acute myeloid leukemia (AML, N = 2,550), chronic myeloid leukemia (CML, N = 1,000) or myeloma (N = 4,584) 2002-2009. Comorbid disease history was assessed through in- and out-patient care as defined in the Charlson comorbidity index. Mortality rate ratios (MRR) were estimated through 2012 using Poisson regression. Probabilities of cancer-specific death were computed using flexible parametric survival models. Comorbidity was associated with increased all-cause as well as cancer-specific mortality (cancer-specific MRR: AML = 1.27, 95 % CI: 1.15-1.40; CML = 1.28, 0.96-1.70; myeloma = 1.17, 1.08-1.28) compared with patients without comorbidity. Disorders associated with higher cancer-specific mortality were renal disease (in patients with AML, CML and myeloma), cerebrovascular conditions, dementia, psychiatric disease (AML, myeloma), liver and rheumatic disease (AML), cardiovascular and pulmonary disease (myeloma). The difference in the probability of cancer-specific death, comparing patients with and without comorbidity, was largest among AML patients <70 years, whereas in myeloma the difference did not vary by age among the elderly. The probability of cancer-specific death was generally higher than other-cause death even in older age groups, irrespective of comorbidity. Comorbidities associated with organ failure or cognitive function are associated with poorer prognosis in several hematological malignancies, likely due to lower treatment tolerability. The results highlight the need for a better balance between treatment toxicity and efficacy in comorbid and elderly AML, CML and myeloma patients.

Computed Tomography-Derived Fractional Flow Reserve in the Detection of Lesion-Specific Ischemia: An Integrated Analysis of 3 Pivotal Trials.

PubMed

Xu, Rende; Li, Chenguang; Qian, Juying; Ge, Junbo

2015-11-01

Invasive fractional flow reserve (FFR) is the gold standard for the determination of physiologic stenosis severity and the need for revascularization. FFR computed from standard acquired coronary computed tomographic angiography datasets (FFRCT) is an emerging technology which allows calculation of FFR using resting image data from coronary computed tomographic angiography (CCTA). However, the diagnostic accuracy of FFRCT in the evaluation of lesion-specific myocardial ischemia remains to be confirmed, especially in patients with intermediate coronary stenosis. We performed an integrated analysis of data from 3 prospective, international, and multicenter trials, which assessed the diagnostic performance of FFRCT using invasive FFR as a reference standard. Three studies evaluating 609 patients and 1050 vessels were included. The total calculated sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of FFRCT were 82.8%, 77.7%, 60.8%, 91.6%, and 79.2%, respectively, for the per-vessel analysis, and 89.4%, 70.5%, 69.7%, 89.7%, and 78.7%, respectively, for the per-patient analysis. Compared with CCTA alone, FFRCT demonstrated significantly improved accuracy (P < 0.001) in detecting lesion-specific ischemia. In patients with intermediate coronary stenosis, FFRCT remained both highly sensitive and specific with respect to the diagnosis of ischemia. In conclusion, FFRCT appears to be a reliable noninvasive alternative to invasive FFR, as it demonstrates high accuracy in the determination of anatomy and lesion-specific ischemia, which justifies the performance of additional randomized controlled trials to evaluate both the clinical benefits and the cost-effectiveness of FFRCT-guided coronary revascularization.

A vessel length-based method to compute coronary fractional flow reserve from optical coherence tomography images.

PubMed

Lee, Kyung Eun; Lee, Seo Ho; Shin, Eun-Seok; Shim, Eun Bo

2017-06-26

Hemodynamic simulation for quantifying fractional flow reserve (FFR) is often performed in a patient-specific geometry of coronary arteries reconstructed from the images from various imaging modalities. Because optical coherence tomography (OCT) images can provide more precise vascular lumen geometry, regardless of stenotic severity, hemodynamic simulation based on OCT images may be effective. The aim of this study is to perform OCT-FFR simulations by coupling a 3D CFD model from geometrically correct OCT images with a LPM based on vessel lengths extracted from CAG data with clinical validations for the present method. To simulate coronary hemodynamics, we developed a fast and accurate method that combined a computational fluid dynamics (CFD) model of an OCT-based region of interest (ROI) with a lumped parameter model (LPM) of the coronary microvasculature and veins. Here, the LPM was based on vessel lengths extracted from coronary X-ray angiography (CAG) images. Based on a vessel length-based approach, we describe a theoretical formulation for the total resistance of the LPM from a three-dimensional (3D) CFD model of the ROI. To show the utility of this method, we present calculated examples of FFR from OCT images. To validate the OCT-based FFR calculation (OCT-FFR) clinically, we compared the computed OCT-FFR values for 17 vessels of 13 patients with clinically measured FFR (M-FFR) values. A novel formulation for the total resistance of LPM is introduced to accurately simulate a 3D CFD model of the ROI. The simulated FFR values compared well with clinically measured ones, showing the accuracy of the method. Moreover, the present method is fast in terms of computational time, enabling clinicians to provide solutions handled within the hospital.

Interventions to Improve Patient Education Regarding Multifactorial Genetic Conditions: A Systematic Review

PubMed Central

Meilleur, Katherine G.; Littleton-Kearney, Marguerite T.

2009-01-01

The careful education of patients with complex genetic disease is essential. However, healthcare providers often have limited time to spend providing thorough genetic education. Furthermore, the number of healthcare professionals possessing strong genetics training may be inadequate to meet increasing patient demands. Due to such constraints, several interventions have been investigated over the past decade to identify potential resources for the facilitation of this specific type of patient education. This systematic literature review of these interventions for patient education attempts to elucidate the answer to the question: is there sufficient evidence for best practice for delivering genetic information to patients with multifactorial conditions? The various interventions (CD-ROM, group counseling, video/decision aid, and miscellaneous) were analyzed in terms of quality criteria and achievement of specific outcomes and were rated according to the Stetler model for evidence based practice. Seven main outcomes were evaluated: 1. objective and subjective knowledge assessment 2. psychological measures (general anxiety, depression, stress, cancer worry) 3. satisfaction/effectiveness of intervention 4. time spent in counseling (time spent on basic genetic information vs. specific concerns) 5. decision making/intent to undergo genetic testing 6. treatment choice and value of that choice, and, finally 7. risk perception. Overall, the computer interventions resulted in more significant findings that were beneficial than any other category followed by the video category, although the group and miscellaneous categories did not measure all of the outcomes reported by the other two categories. Nevertheless, while these groups had neutral or negative findings in some of the outcomes, the computer intervention group showed significant improvement in genetics knowledge, psychological measures, satisfaction/effectiveness, time spent with counselor, and decision/intent to undergo testing. PMID:19291763

Patient-specific radiation dose and cancer risk estimation in pediatric chest CT: a study in 30 patients

NASA Astrophysics Data System (ADS)

Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

2010-04-01

Radiation-dose awareness and optimization in CT can greatly benefit from a dosereporting system that provides radiation dose and cancer risk estimates specific to each patient and each CT examination. Recently, we reported a method for estimating patientspecific dose from pediatric chest CT. The purpose of this study is to extend that effort to patient-specific risk estimation and to a population of pediatric CT patients. Our study included thirty pediatric CT patients (16 males and 14 females; 0-16 years old), for whom full-body computer models were recently created based on the patients' clinical CT data. Using a validated Monte Carlo program, organ dose received by the thirty patients from a chest scan protocol (LightSpeed VCT, 120 kVp, 1.375 pitch, 40-mm collimation, pediatric body scan field-of-view) was simulated and used to estimate patient-specific effective dose. Risks of cancer incidence were calculated for radiosensitive organs using gender-, age-, and tissue-specific risk coefficients and were used to derive patientspecific effective risk. The thirty patients had normalized effective dose of 3.7-10.4 mSv/100 mAs and normalized effective risk of 0.5-5.8 cases/1000 exposed persons/100 mAs. Normalized lung dose and risk of lung cancer correlated strongly with average chest diameter (correlation coefficient: r = -0.98 to -0.99). Normalized effective risk also correlated strongly with average chest diameter (r = -0.97 to -0.98). These strong correlations can be used to estimate patient-specific dose and risk prior to or after an imaging study to potentially guide healthcare providers in justifying CT examinations and to guide individualized protocol design and optimization.

D Modelling and Rapid Prototyping for Cardiovascular Surgical Planning - Two Case Studies

NASA Astrophysics Data System (ADS)

Nocerino, E.; Remondino, F.; Uccheddu, F.; Gallo, M.; Gerosa, G.

2016-06-01

In the last years, cardiovascular diagnosis, surgical planning and intervention have taken advantages from 3D modelling and rapid prototyping techniques. The starting data for the whole process is represented by medical imagery, in particular, but not exclusively, computed tomography (CT) or multi-slice CT (MCT) and magnetic resonance imaging (MRI). On the medical imagery, regions of interest, i.e. heart chambers, valves, aorta, coronary vessels, etc., are segmented and converted into 3D models, which can be finally converted in physical replicas through 3D printing procedure. In this work, an overview on modern approaches for automatic and semiautomatic segmentation of medical imagery for 3D surface model generation is provided. The issue of accuracy check of surface models is also addressed, together with the critical aspects of converting digital models into physical replicas through 3D printing techniques. A patient-specific 3D modelling and printing procedure (Figure 1), for surgical planning in case of complex heart diseases was developed. The procedure was applied to two case studies, for which MCT scans of the chest are available. In the article, a detailed description on the implemented patient-specific modelling procedure is provided, along with a general discussion on the potentiality and future developments of personalized 3D modelling and printing for surgical planning and surgeons practice.

Efficacy, Predictive Factors, and Prediction Nomograms for 68Ga-labeled Prostate-specific Membrane Antigen-ligand Positron-emission Tomography/Computed Tomography in Early Biochemical Recurrent Prostate Cancer After Radical Prostatectomy.

PubMed

Rauscher, Isabel; Düwel, Charlotte; Haller, Bernhard; Rischpler, Christoph; Heck, Matthias M; Gschwend, Jürgen E; Schwaiger, Markus; Maurer, Tobias; Eiber, Matthias

2018-05-01

Recently, 68 Ga-labeled prostate-specific membrane antigen (PSMA)-ligand positron-emission tomography (PET) imaging has been shown to improve detection rates in recurrent prostate cancer (PC). However, published studies include only small patient numbers at low prostate-specific antigen (PSA) values. For this study, 272 consecutive patients with biochemical recurrence after radical prostatectomy and PSA value between 0.2 and 1ng/ml were included. The 68 Ga-PSMA-ligand PET/computed tomography (CT) was evaluated, and detection rates were determined and correlated to various clinical variables using univariate and multivariable analyses. Subgroups of patients with very low (0.2-0.5ng/ml) and low (>0.5-1.0ng/ml) PSA values were analyzed. In total, lesions indicative of PC recurrence were detected in 55% (74/134) and 74% (102/138) with very low and low PSA values, respectively. Main sites of recurrence were pelvic or retroperitoneal lymph nodes metastases, followed by local recurrence and bone metastases with higher probability in the low versus very low PSA subgroup. Detection rates significantly increased with higher PSA values, primary pT≥3a, primary pN+ disease, grade group ≥4, previous radiation therapy, and concurrent androgen deprivation therapy (ADT) in univariate analysis. In a multivariable logistic regression model, concurrent ADT and PSA values were identified as most relevant predictors of positive 68 Ga-PSMA-ligand PET/CT. Further, prediction nomograms were established, which may help in estimating pretest PSMA-ligand PET positivity in clinical practice. In our study, 68 Ga-labeled prostate-specific membrane antigen (PSMA)-ligand positron-emission tomography (PET)/computed tomography (CT) detected recurrent disease after radical prostatectomy in 55% (74/134) and 74% (102/138) of patients with very low (0.2-0.5ng/ml) and low (>0.5-1.0ng/ml) prostate-specific antigen values, respectively. On the basis of these data, it seems reasonable to perform 68 Ga-PSMA-ligand PET/CT also in patients with early biochemical recurrence, as it can tailor further therapy decisions (eg, local vs systemic treatment). The established prediction nomograms can further assist urologists in discussions on the use of 68 Ga-PSMA-ligand PET/CT with their patients in specific clinical settings. Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy.

PubMed

Brogden, Kim A; Parashar, Deepak; Hallier, Andrea R; Braun, Terry; Qian, Fang; Rizvi, Naiyer A; Bossler, Aaron D; Milhem, Mohammed M; Chan, Timothy A; Abbasi, Taher; Vali, Shireen

2018-02-27

Programmed Death Ligand 1 (PD-L1) is a co-stimulatory and immune checkpoint protein. PD-L1 expression in non-small cell lung cancers (NSCLC) is a hallmark of adaptive resistance and its expression is often used to predict the outcome of Programmed Death 1 (PD-1) and PD-L1 immunotherapy treatments. However, clinical benefits do not occur in all patients and new approaches are needed to assist in selecting patients for PD-1 or PD-L1 immunotherapies. Here, we hypothesized that patient tumor cell genomics influenced cell signaling and expression of PD-L1, chemokines, and immunosuppressive molecules and these profiles could be used to predict patient clinical responses. We used a recent dataset from NSCLC patients treated with pembrolizumab. Deleterious gene mutational profiles in patient exomes were identified and annotated into a cancer network to create NSCLC patient-specific predictive computational simulation models. Validation checks were performed on the cancer network, simulation model predictions, and PD-1 match rates between patient-specific predicted and clinical responses. Expression profiles of these 24 chemokines and immunosuppressive molecules were used to identify patients who would or would not respond to PD-1 immunotherapy. PD-L1 expression alone was not sufficient to predict which patients would or would not respond to PD-1 immunotherapy. Adding chemokine and immunosuppressive molecule expression profiles allowed patient models to achieve a greater than 85.0% predictive correlation among predicted and reported patient clinical responses. Our results suggested that chemokine and immunosuppressive molecule expression profiles can be used to accurately predict clinical responses thus differentiating among patients who would and would not benefit from PD-1 or PD-L1 immunotherapies.

Prosthetically guided maxillofacial surgery: evaluation of the accuracy of a surgical guide and custom-made bone plate in oncology patients after mandibular reconstruction.

PubMed

Mazzoni, Simona; Marchetti, Claudio; Sgarzani, Rossella; Cipriani, Riccardo; Scotti, Roberto; Ciocca, Leonardo

2013-06-01

The aim of the present study was to evaluate the accuracy of prosthetically guided maxillofacial surgery in reconstructing the mandible with a free vascularized flap using custom-made bone plates and a surgical guide to cut the mandible and fibula. The surgical protocol was applied in a study group of seven consecutive mandibular-reconstructed patients who were compared with a control group treated using the standard preplating technique on stereolithographic models (indirect computer-aided design/computer-aided manufacturing method). The precision of both surgical techniques (prosthetically guided maxillofacial surgery and indirect computer-aided design/computer-aided manufacturing procedure) was evaluated by comparing preoperative and postoperative computed tomographic data and assessment of specific landmarks. With regard to midline deviation, no significant difference was documented between the test and control groups. With regard to mandibular angle shift, only one left angle shift on the lateral plane showed a statistically significant difference between the groups. With regard to angular deviation of the body axis, the data showed a significant difference in the arch deviation. All patients in the control group registered greater than 8 degrees of deviation, determining a facial contracture of the external profile at the lower margin of the mandible. With regard to condylar position, the postoperative condylar position was better in the test group than in the control group, although no significant difference was detected. The new protocol for mandibular reconstruction using computer-aided design/computer-aided manufacturing prosthetically guided maxillofacial surgery to construct custom-made guides and plates may represent a viable method of reproducing the patient's anatomical contour, giving the surgeon better procedural control and reducing procedure time. Therapeutic, III.

Examining the Role of Religiosity in Moral Cognition, Specifically in the Formation of Sacred Values, and Researching Computational Models for Analyzing Sacred Rhetoric and its Consequential Emotions

DTIC Science & Technology

2015-08-13

AFRL-AFOSR-VA-TR-2015-0270 Examining the Role of Religiosity in Moral Cognition, Specifically in the Formation of Sacred Values, and Researching...Computational Models for Analyzing Sacred Rhetoric and its Consequential Emotions Morteza Dehghani UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES Final...SUBTITLE (YIP-12) Examining the Role of Religiosity in Moral Cognition, Specifically in the Formation of Sacred Values, and Researching Computational

Patient-specific analysis of blood stasis in the left atrium

NASA Astrophysics Data System (ADS)

Flores, Oscar; Gonzalo, Alejandro; Garcia-Villalba, Manuel; Rossini, Lorenzo; Hsiao, Albert; McVeigh, Elliot; Kahn, Andrew M.; Del Alamo, Juan C.

2016-11-01

Atrial fibrillation (AF) is a common arrhythmia in which the left atrium (LA) beats rapidly and irregularly. Patients with AF are at increased risk of thromboembolic events (TE), particularly stroke. Anticoagulant therapy can reduce the risk of TE in AF, but it can also increase the risks of adverse events such as internal bleeding. The current lack of tools to predict each patient's risk of LA thrombogenesis makes it difficult to decide whether to anticoagulate patients with AF. The aim of this work is to evaluate blood stasis in patient-specific models of the LA, because stasis is a known thrombogenesis risk factor. To achieve our aim, we performed direct numerical simulations of left atrial flow using an immersed boundary solver developed at the UC3M, coupled to a 0D model for the pulmonary circulation. The LA geometry is obtained from time-resolved CT scans and the parameters of the 0D model are found by fitting pulmonary vein flow data obtained by 4D phase contrast MRI. Blood stasis is evaluated from the flow data by computing blood residence time together with other kinematic indices of the velocity field (e.g. strain and kinetic energy). We focus on the flow in the left atrial appendage, including a sensitivity analysis of the effect of the parameters of the 0D model. Funded by the Spanish MECD, the Clinical and Translational Research Institute at UCSD and the American Heart Association.

Computed Tomography Imaging Features in Acute Uncomplicated Stanford Type-B Aortic Dissection Predict Late Adverse Events.

PubMed

Sailer, Anna M; van Kuijk, Sander M J; Nelemans, Patricia J; Chin, Anne S; Kino, Aya; Huininga, Mark; Schmidt, Johanna; Mistelbauer, Gabriel; Bäumler, Kathrin; Chiu, Peter; Fischbein, Michael P; Dake, Michael D; Miller, D Craig; Schurink, Geert Willem H; Fleischmann, Dominik

2017-04-01

Medical treatment of initially uncomplicated acute Stanford type-B aortic dissection is associated with a high rate of late adverse events. Identification of individuals who potentially benefit from preventive endografting is highly desirable. The association of computed tomography imaging features with late adverse events was retrospectively assessed in 83 patients with acute uncomplicated Stanford type-B aortic dissection, followed over a median of 850 (interquartile range 247-1824) days. Adverse events were defined as fatal or nonfatal aortic rupture, rapid aortic growth (>10 mm/y), aneurysm formation (≥6 cm), organ or limb ischemia, or new uncontrollable hypertension or pain. Five significant predictors were identified using multivariable Cox regression analysis: connective tissue disease (hazard ratio [HR] 2.94, 95% confidence interval [CI]: 1.29-6.72; P =0.01), circumferential extent of false lumen in angular degrees (HR 1.03 per degree, 95% CI: 1.01-1.04, P =0.003), maximum aortic diameter (HR 1.10 per mm, 95% CI: 1.02-1.18, P =0.015), false lumen outflow (HR 0.999 per mL/min, 95% CI: 0.998-1.000; P =0.055), and number of intercostal arteries (HR 0.89 per n, 95% CI: 0.80-0.98; P =0.024). A prediction model was constructed to calculate patient specific risk at 1, 2, and 5 years and to stratify patients into high-, intermediate-, and low-risk groups. The model was internally validated by bootstrapping and showed good discriminatory ability with an optimism-corrected C statistic of 70.1%. Computed tomography imaging-based morphological features combined into a prediction model may be able to identify patients at high risk for late adverse events after an initially uncomplicated type-B aortic dissection. © 2017 American Heart Association, Inc.

Highlighting the medical applications of 3D printing in Egypt

PubMed Central

Abdelghany, Khaled; Hamza, Hosamuddin

2015-01-01

Computer-assisted designing/computer-assisted manufacturing (CAD/CAM) technology has enabled medical practitioners to tailor physical models in a patient and purpose-specific fashion. It allows the designing and manufacturing of templates, appliances and devices with a high range of accuracy using biocompatible materials. The technique, nevertheless, relies on digital scanning (e.g., using intraoral scanners) and/or digital imaging (e.g., CT and MRI). In developing countries, there are some technical and financial limitations of implementing such advanced tools as an essential portion of medical applications. This paper focuses on the surgical and dental use of 3D printing technology in Egypt as a developing country. PMID:26807414

Informatics in radiology: an information model of the DICOM standard.

PubMed

Kahn, Charles E; Langlotz, Curtis P; Channin, David S; Rubin, Daniel L

2011-01-01

The Digital Imaging and Communications in Medicine (DICOM) Standard is a key foundational technology for radiology. However, its complexity creates challenges for information system developers because the current DICOM specification requires human interpretation and is subject to nonstandard implementation. To address this problem, a formally sound and computationally accessible information model of the DICOM Standard was created. The DICOM Standard was modeled as an ontology, a machine-accessible and human-interpretable representation that may be viewed and manipulated by information-modeling tools. The DICOM Ontology includes a real-world model and a DICOM entity model. The real-world model describes patients, studies, images, and other features of medical imaging. The DICOM entity model describes connections between real-world entities and the classes that model the corresponding DICOM information entities. The DICOM Ontology was created to support the Cancer Biomedical Informatics Grid (caBIG) initiative, and it may be extended to encompass the entire DICOM Standard and serve as a foundation of medical imaging systems for research and patient care. RSNA, 2010

Linking DMN connectivity to episodic memory capacity: What can we learn from patients with medial temporal lobe damage?

PubMed Central

McCormick, Cornelia; Protzner, Andrea B.; Barnett, Alexander J.; Cohn, Melanie; Valiante, Taufik A.; McAndrews, Mary Pat

2014-01-01

Computational models predict that focal damage to the Default Mode Network (DMN) causes widespread decreases and increases of functional DMN connectivity. How such alterations impact functioning in a specific cognitive domain such as episodic memory remains relatively unexplored. Here, we show in patients with unilateral medial temporal lobe epilepsy (mTLE) that focal structural damage leads indeed to specific patterns of DMN functional connectivity alterations, specifically decreased connectivity between both medial temporal lobes (MTLs) and the posterior part of the DMN and increased intrahemispheric anterior–posterior connectivity. Importantly, these patterns were associated with better and worse episodic memory capacity, respectively. These distinct patterns, shown here for the first time, suggest that a close dialogue between both MTLs and the posterior components of the DMN is required to fully express the extensive repertoire of episodic memory abilities. PMID:25068108

The effect of diagnosis-specific computerized discharge instructions on 72-hour return visits to the pediatric emergency department.

PubMed

Lawrence, Laurie M; Jenkins, Cathy A; Zhou, Chuan; Givens, Timothy G

2009-11-01

The number of patients returning to the pediatric emergency department (PED) within 72 hours of discharge is frequently cited as a benchmark for quality patient care. The purpose of this study was to determine whether the introduction of diagnosis-specific computer-generated discharge instructions would decrease the number of medically unnecessary return visits to the PED. A retrospective chart review of patients who returned to the PED within 72 hours of discharge was performed. Charts were reviewed from 2 comparable periods: September 2004 to February 2005, when handwritten discharge instructions were issued to each patient, and September 2005 to February 2006, when each patient received computer-generated diagnosis-specific discharge instructions. The patient's age, primary care provider, insurance status, chief complaint, vital signs, history, physical examination, plan of care, and diagnosis at each visit were recorded. Cases were excluded if the patient left against medical advice or without being seen, was admitted to the hospital on the first visit, or had incomplete or missing records. The medical necessity of the return visit was rated as "yes," "no," or "indeterminate" based on review of the visit noting reason for return, history and physical examination, diagnosis, and interventions or changes in the initial care plan. Of all return visits to the PED within 72 hours of discharge, 13% were deemed unnecessary for patients receiving handwritten instructions compared with 15% for patients receiving computer-generated instructions (P = 0.5, not significant). For each additional year of age, the return visit was 1.07 times as likely to be medically appropriate (95% confidence interval, 1.03-1.12; P = 0.002). Patients who returned to the PED more than once were 2.69 times more likely to have a medically appropriate visit as were those with only 1 return visit (95% confidence interval, 0.95-7.58; P = 0.062). Computer-generated diagnosis-specific discharge instructions do not decrease the number of medically unnecessary repeat visits to the PED.

From guideline modeling to guideline execution: defining guideline-based decision-support services.

PubMed Central

Tu, S. W.; Musen, M. A.

2000-01-01

We describe our task-based approach to defining the guideline-based decision-support services that the EON system provides. We categorize uses of guidelines in patient-specific decision support into a set of generic tasks--making of decisions, specification of work to be performed, interpretation of data, setting of goals, and issuance of alert and reminders--that can be solved using various techniques. Our model includes constructs required for representing the knowledge used by these techniques. These constructs form a toolkit from which developers can select modeling solutions for guideline task. Based on the tasks and the guideline model, we define a guideline-execution architecture and a model of interactions between a decision-support server and clients that invoke services provided by the server. These services use generic interfaces derived from guideline tasks and their associated modeling constructs. We describe two implementations of these decision-support services and discuss how this work can be generalized. We argue that a well-defined specification of guideline-based decision-support services will facilitate sharing of tools that implement computable clinical guidelines. PMID:11080007

Representation primitives, process models and patient data in computer-interpretable clinical practice guidelines: a literature review of guideline representation models.

PubMed

Wang, Dongwen; Peleg, Mor; Tu, Samson W; Boxwala, Aziz A; Greenes, Robert A; Patel, Vimla L; Shortliffe, Edward H

2002-12-18

Representation of clinical practice guidelines in a computer-interpretable format is a critical issue for guideline development, implementation, and evaluation. We studied 11 types of guideline representation models that can be used to encode guidelines in computer-interpretable formats. We have consistently found in all reviewed models that primitives for representation of actions and decisions are necessary components of a guideline representation model. Patient states and execution states are important concepts that closely relate to each other. Scheduling constraints on representation primitives can be modeled as sequences, concurrences, alternatives, and loops in a guideline's application process. Nesting of guidelines provides multiple views to a guideline with different granularities. Integration of guidelines with electronic medical records can be facilitated by the introduction of a formal model for patient data. Data collection, decision, patient state, and intervention constitute four basic types of primitives in a guideline's logic flow. Decisions clarify our understanding on a patient's clinical state, while interventions lead to the change from one patient state to another.

An imaging-based stochastic model for simulation of tumour vasculature

NASA Astrophysics Data System (ADS)

Adhikarla, Vikram; Jeraj, Robert

2012-10-01

A mathematical model which reconstructs the structure of existing vasculature using patient-specific anatomical, functional and molecular imaging as input was developed. The vessel structure is modelled according to empirical vascular parameters, such as the mean vessel branching angle. The model is calibrated such that the resultant oxygen map modelled from the simulated microvasculature stochastically matches the input oxygen map to a high degree of accuracy (R2 ≈ 1). The calibrated model was successfully applied to preclinical imaging data. Starting from the anatomical vasculature image (obtained from contrast-enhanced computed tomography), a representative map of the complete vasculature was stochastically simulated as determined by the oxygen map (obtained from hypoxia [64Cu]Cu-ATSM positron emission tomography). The simulated microscopic vasculature and the calculated oxygenation map successfully represent the imaged hypoxia distribution (R2 = 0.94). The model elicits the parameters required to simulate vasculature consistent with imaging and provides a key mathematical relationship relating the vessel volume to the tissue oxygen tension. Apart from providing an excellent framework for visualizing the imaging gap between the microscopic and macroscopic imagings, the model has the potential to be extended as a tool to study the dynamics between the tumour and the vasculature in a patient-specific manner and has an application in the simulation of anti-angiogenic therapies.

The role of digital imaging and communications in medicine in an evolving healthcare computing environment: the model is the message.

PubMed

Bidgood, W D; alSafadi, Y; Tucker, M; Prior, F; Hagan, G; Mattison, J E

1998-02-01

The decision to use Digital Imaging and Communications in Medicine (DICOM), Health Level 7 (HL7), a common object broker such as the Common Object Request Brokering Architecture (CORBA) or ActiveX (Microsoft Corp, Redmond, WA) or any other protocol for the transfer of DICOM data depends on the requirements of a particular implementation. The selection of protocol is independent of the information model. Our goal as message standards developers is to design a data interchange infrastructure that will faithfully convey the computer-based patient record and make it available to authorized health care providers when and where it is needed for patient care. DICOM accurately and expressively represents the clinically significant properties of images and the semantics of image-related information. The DICOM data model is small and well-defined. The model can be expressed in Standard Generalized Markup Language (SGML) or Object Management Group Interface Definition Language or other common syntax-and can be implemented using any reliable communications protocol. Therefore our opinion is that the DICOM semantic data model should serve as the basis for a logically equivalent set of specifications in HL7, CORBA, ActiveX, and SGML for the interchange of biomedical images and image-related information.

Nonlinear digital signal processing in mental health: characterization of major depression using instantaneous entropy measures of heartbeat dynamics.

PubMed

Valenza, Gaetano; Garcia, Ronald G; Citi, Luca; Scilingo, Enzo P; Tomaz, Carlos A; Barbieri, Riccardo

2015-01-01

Nonlinear digital signal processing methods that address system complexity have provided useful computational tools for helping in the diagnosis and treatment of a wide range of pathologies. More specifically, nonlinear measures have been successful in characterizing patients with mental disorders such as Major Depression (MD). In this study, we propose the use of instantaneous measures of entropy, namely the inhomogeneous point-process approximate entropy (ipApEn) and the inhomogeneous point-process sample entropy (ipSampEn), to describe a novel characterization of MD patients undergoing affective elicitation. Because these measures are built within a nonlinear point-process model, they allow for the assessment of complexity in cardiovascular dynamics at each moment in time. Heartbeat dynamics were characterized from 48 healthy controls and 48 patients with MD while emotionally elicited through either neutral or arousing audiovisual stimuli. Experimental results coming from the arousing tasks show that ipApEn measures are able to instantaneously track heartbeat complexity as well as discern between healthy subjects and MD patients. Conversely, standard heart rate variability (HRV) analysis performed in both time and frequency domains did not show any statistical significance. We conclude that measures of entropy based on nonlinear point-process models might contribute to devising useful computational tools for care in mental health.

Role of Statistical Random-Effects Linear Models in Personalized Medicine

PubMed Central

Diaz, Francisco J; Yeh, Hung-Wen; de Leon, Jose

2012-01-01

Some empirical studies and recent developments in pharmacokinetic theory suggest that statistical random-effects linear models are valuable tools that allow describing simultaneously patient populations as a whole and patients as individuals. This remarkable characteristic indicates that these models may be useful in the development of personalized medicine, which aims at finding treatment regimes that are appropriate for particular patients, not just appropriate for the average patient. In fact, published developments show that random-effects linear models may provide a solid theoretical framework for drug dosage individualization in chronic diseases. In particular, individualized dosages computed with these models by means of an empirical Bayesian approach may produce better results than dosages computed with some methods routinely used in therapeutic drug monitoring. This is further supported by published empirical and theoretical findings that show that random effects linear models may provide accurate representations of phase III and IV steady-state pharmacokinetic data, and may be useful for dosage computations. These models have applications in the design of clinical algorithms for drug dosage individualization in chronic diseases; in the computation of dose correction factors; computation of the minimum number of blood samples from a patient that are necessary for calculating an optimal individualized drug dosage in therapeutic drug monitoring; measure of the clinical importance of clinical, demographic, environmental or genetic covariates; study of drug-drug interactions in clinical settings; the implementation of computational tools for web-site-based evidence farming; design of pharmacogenomic studies; and in the development of a pharmacological theory of dosage individualization. PMID:23467392

[Software for performing a global phenotypic and genotypic nutritional assessment].

PubMed

García de Diego, L; Cuervo, M; Martínez, J A

2013-01-01

The nutritional assessment of a patient needs the simultaneous managing a extensive information and a great number of databases, as both aspects of the process of nutrition and the clinical situation of the patient are analyzed. The introduction of computers in the nutritional area constitutes an extraordinary advance in the administration of nutrition information, providing a complete assessment of nutritional aspects in a quick and easy way. To develop a computer program that can be used as a tool for assessing the nutritional status of the patient, the education of clinical staff, for epidemiological studies and for educational purposes. Based on a computer program which assists the health specialist to perform a full nutritional evaluation of the patient, through the registration and assessment of the phenotypic and genotypic features. The application provides nutritional prognosis based on anthropometric and biochemical parameters, images of states of malnutrition, questionnaires to characterize diseases, diagnostic criteria, identification of alleles associated with the development of specific metabolic illnesses and questionnaires of quality of life, for a custom actuation. The program includes, as part of the nutritional assessment of the patient, food intake analysis, design of diets and promotion of physical activity, introducing food frequency questionnaires, dietary recalls, healthy eating indexes, model diets, fitness tests, and recommendations, recalls and questionnaires of physical activity. A computer program performed under Java Swing, using SQLite database and some external libraries such as JfreeChart for plotting graphs. This brand new designed software is composed of five blocks categorized into ten modules named: Patients, Anthropometry, Clinical History, Biochemistry, Dietary History, Diagnostic (with genetic make up), Quality of life, Physical activity, Energy expenditure and Diets. Each module has a specific function which evaluates a different aspect of the nutritional status of the patient. UNyDIET is a global computer program, customized and upgradeable, easy to use and versatile, aimed to health specialists, medical staff, dietitians, nutritionists, scientists and educators. This tool can be used as a working instrument in programs promoting health, nutritional and clinical assessments as well as in the evaluation of health care quality, in epidemiological studies, in nutrition intervention programs and teaching. Copyright © AULA MEDICA EDICIONES 2013. Published by AULA MEDICA. All rights reserved.

Probabilistic techniques for obtaining accurate patient counts in Clinical Data Warehouses

PubMed Central

Myers, Risa B.; Herskovic, Jorge R.

2011-01-01

Proposal and execution of clinical trials, computation of quality measures and discovery of correlation between medical phenomena are all applications where an accurate count of patients is needed. However, existing sources of this type of patient information, including Clinical Data Warehouses (CDW) may be incomplete or inaccurate. This research explores applying probabilistic techniques, supported by the MayBMS probabilistic database, to obtain accurate patient counts from a clinical data warehouse containing synthetic patient data. We present a synthetic clinical data warehouse (CDW), and populate it with simulated data using a custom patient data generation engine. We then implement, evaluate and compare different techniques for obtaining patients counts. We model billing as a test for the presence of a condition. We compute billing’s sensitivity and specificity both by conducting a “Simulated Expert Review” where a representative sample of records are reviewed and labeled by experts, and by obtaining the ground truth for every record. We compute the posterior probability of a patient having a condition through a “Bayesian Chain”, using Bayes’ Theorem to calculate the probability of a patient having a condition after each visit. The second method is a “one-shot” approach that computes the probability of a patient having a condition based on whether the patient is ever billed for the condition Our results demonstrate the utility of probabilistic approaches, which improve on the accuracy of raw counts. In particular, the simulated review paired with a single application of Bayes’ Theorem produces the best results, with an average error rate of 2.1% compared to 43.7% for the straightforward billing counts. Overall, this research demonstrates that Bayesian probabilistic approaches improve patient counts on simulated patient populations. We believe that total patient counts based on billing data are one of the many possible applications of our Bayesian framework. Use of these probabilistic techniques will enable more accurate patient counts and better results for applications requiring this metric. PMID:21986292

Using features of Arden Syntax with object-oriented medical data models for guideline modeling.

PubMed

Peleg, M; Ogunyemi, O; Tu, S; Boxwala, A A; Zeng, Q; Greenes, R A; Shortliffe, E H

2001-01-01

Computer-interpretable guidelines (CIGs) can deliver patient-specific decision support at the point of care. CIGs base their recommendations on eligibility and decision criteria that relate medical concepts to patient data. CIG models use expression languages for specifying these criteria, and define models for medical data to which the expressions can refer. In developing version 3 of the GuideLine Interchange Format (GLIF3), we used existing standards as the medical data model and expression language. We investigated the object-oriented HL7 Reference Information Model (RIM) as a default data model. We developed an expression language, called GEL, based on Arden Syntax's logic grammar. Together with other GLIF constructs, GEL reconciles incompatibilities between the data models of Arden Syntax and the HL7 RIM. These incompatibilities include Arden's lack of support for complex data types and time intervals, and the mismatch between Arden's single primary time and multiple time attributes of the HL7 RIM.

A neurocomputational account of cognitive deficits in Parkinson’s disease

PubMed Central

Hélie, Sébastien; Paul, Erick J.; Ashby, F. Gregory

2014-01-01

Parkinson’s disease (PD) is caused by the accelerated death of dopamine (DA) producing neurons. Numerous studies documenting cognitive deficits of PD patients have revealed impairments in a variety of tasks related to memory, learning, visuospatial skills, and attention. While there have been several studies documenting cognitive deficits of PD patients, very few computational models have been proposed. In this article, we use the COVIS model of category learning to simulate DA depletion and show that the model suffers from cognitive symptoms similar to those of human participants affected by PD. Specifically, DA depletion in COVIS produced deficits in rule-based categorization, non-linear information-integration categorization, probabilistic classification, rule maintenance, and rule switching. These were observed by simulating results from younger controls, older controls, PD patients, and severe PD patients in five well-known tasks. Differential performance among the different age groups and clinical populations was modeled simply by changing the amount of DA available in the model. This suggests that COVIS may not only be an adequate model of the simulated tasks and phenomena but also more generally of the role of DA in these tasks and phenomena. PMID:22683450

Patient-specific bone modeling and analysis: the role of integration and automation in clinical adoption.

PubMed

Zadpoor, Amir A; Weinans, Harrie

2015-03-18

Patient-specific analysis of bones is considered an important tool for diagnosis and treatment of skeletal diseases and for clinical research aimed at understanding the etiology of skeletal diseases and the effects of different types of treatment on their progress. In this article, we discuss how integration of several important components enables accurate and cost-effective patient-specific bone analysis, focusing primarily on patient-specific finite element (FE) modeling of bones. First, the different components are briefly reviewed. Then, two important aspects of patient-specific FE modeling, namely integration of modeling components and automation of modeling approaches, are discussed. We conclude with a section on validation of patient-specific modeling results, possible applications of patient-specific modeling procedures, current limitations of the modeling approaches, and possible areas for future research. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases

PubMed Central

Wooden, Benjamin; Goossens, Nicolas; Hoshida, Yujin; Friedman, Scott L.

2016-01-01

Technologies such as genome sequencing, gene expression profiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health information have produced large amounts of data, from various populations, cell types, and disorders (big data). However, these data must be integrated and analyzed if they are to produce models or concepts about physiologic function or mechanisms of pathogenesis. Many of these data are available to the public, allowing researchers anywhere to search for markers of specific biologic processes or therapeutic targets for specific diseases or patient types. We review recent advances in the fields of computational and systems biology, and highlight opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology, to complement traditional means of diagnostic and therapeutic discovery. PMID:27773806

Stratifying Parkinson's Patients With STN-DBS Into High-Frequency or 60 Hz-Frequency Modulation Using a Computational Model.

PubMed

Khojandi, Anahita; Shylo, Oleg; Mannini, Lucia; Kopell, Brian H; Ramdhani, Ritesh A

2017-07-01

High frequency stimulation (HFS) of the subthalamic nucleus (STN) is a well-established therapy for Parkinson's disease (PD), particularly the cardinal motor symptoms and levodopa induced motor complications. Recent studies have suggested the possible role of 60 Hz stimulation in STN-deep brain stimulation (DBS) for patients with gait disorder. The objective of this study was to develop a computational model, which stratifies patients a priori based on symptomatology into different frequency settings (i.e., high frequency or 60 Hz). We retrospectively analyzed preoperative MDS-Unified Parkinson's Disease Rating Scale III scores (32 indicators) collected from 20 PD patients implanted with STN-DBS at Mount Sinai Medical Center on either 60 Hz stimulation (ten patients) or HFS (130-185 Hz) (ten patients) for an average of 12 months. Predictive models using the Random Forest classification algorithm were built to associate patient/disease characteristics at surgery to the stimulation frequency. These models were evaluated objectively using leave-one-out cross-validation approach. The computational models produced, stratified patients into 60 Hz or HFS (130-185 Hz) with 95% accuracy. The best models relied on two or three predictors out of the 32 analyzed for classification. Across all predictors, gait and rest tremor of the right hand were consistently the most important. Computational models were developed using preoperative clinical indicators in PD patients treated with STN-DBS. These models were able to accurately stratify PD patients into 60 Hz stimulation or HFS (130-185 Hz) groups a priori, offering a unique potential to enhance the utilization of this therapy based on clinical subtypes. © 2017 International Neuromodulation Society.

47 CFR 73.151 - Field strength measurements to establish performance of directional antennas.

Code of Federal Regulations, 2010 CFR

2010-10-01

... verified either by field strength measurement or by computer modeling and sampling system verification. (a... specifically identified by the Commission. (c) Computer modeling and sample system verification of modeled... performance verified by computer modeling and sample system verification. (1) A matrix of impedance...

High resolution, MRI-based, segmented, computerized head phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zubal, I.G.; Harrell, C.R.; Smith, E.O.

1999-01-01

The authors have created a high-resolution software phantom of the human brain which is applicable to voxel-based radiation transport calculations yielding nuclear medicine simulated images and/or internal dose estimates. A software head phantom was created from 124 transverse MRI images of a healthy normal individual. The transverse T2 slices, recorded in a 256x256 matrix from a GE Signa 2 scanner, have isotropic voxel dimensions of 1.5 mm and were manually segmented by the clinical staff. Each voxel of the phantom contains one of 62 index numbers designating anatomical, neurological, and taxonomical structures. The result is stored as a 256x256x128 bytemore » array. Internal volumes compare favorably to those described in the ICRP Reference Man. The computerized array represents a high resolution model of a typical human brain and serves as a voxel-based anthropomorphic head phantom suitable for computer-based modeling and simulation calculations. It offers an improved realism over previous mathematically described software brain phantoms, and creates a reference standard for comparing results of newly emerging voxel-based computations. Such voxel-based computations lead the way to developing diagnostic and dosimetry calculations which can utilize patient-specific diagnostic images. However, such individualized approaches lack fast, automatic segmentation schemes for routine use; therefore, the high resolution, typical head geometry gives the most realistic patient model currently available.« less

Optimal Control Based Stiffness Identification of an Ankle-Foot Orthosis Using a Predictive Walking Model

PubMed Central

Sreenivasa, Manish; Millard, Matthew; Felis, Martin; Mombaur, Katja; Wolf, Sebastian I.

2017-01-01

Predicting the movements, ground reaction forces and neuromuscular activity during gait can be a valuable asset to the clinical rehabilitation community, both to understand pathology, as well as to plan effective intervention. In this work we use an optimal control method to generate predictive simulations of pathological gait in the sagittal plane. We construct a patient-specific model corresponding to a 7-year old child with gait abnormalities and identify the optimal spring characteristics of an ankle-foot orthosis that minimizes muscle effort. Our simulations include the computation of foot-ground reaction forces, as well as the neuromuscular dynamics using computationally efficient muscle torque generators and excitation-activation equations. The optimal control problem (OCP) is solved with a direct multiple shooting method. The solution of this problem is physically consistent synthetic neural excitation commands, muscle activations and whole body motion. Our simulations produced similar changes to the gait characteristics as those recorded on the patient. The orthosis-equipped model was able to walk faster with more extended knees. Notably, our approach can be easily tuned to simulate weakened muscles, produces physiologically realistic ground reaction forces and smooth muscle activations and torques, and can be implemented on a standard workstation to produce results within a few hours. These results are an important contribution toward bridging the gap between research methods in computational neuromechanics and day-to-day clinical rehabilitation. PMID:28450833

Validation of computational fluid dynamics-based analysis to evaluate hemodynamic significance of access stenosis.

PubMed

Hoganson, David M; Hinkel, Cameron J; Chen, Xiaomin; Agarwal, Ramesh K; Shenoy, Surendra

2014-01-01

Stenosis in a vascular access circuit is the predominant cause of access dysfunction. Hemodynamic significance of a stenosis identified by angiography in an access circuit is uncertain. This study utilizes computational fluid dynamics (CFD) to model flow through arteriovenous fistula to predict the functional significance of stenosis in vascular access circuits. Three-dimensional models of fistulas were created with a range of clinically relevant stenoses using SolidWorks. Stenoses diameters ranged from 1.0 to 3.0 mm and lengths from 5 to 60 mm within a fistula diameter of 7 mm. CFD analyses were performed using a blood model over a range of blood pressures. Eight patient-specific stenoses were also modeled and analyzed with CFD and the resulting blood flow calculations were validated by comparison with brachial artery flow measured by duplex ultrasound. Predicted flow rates were derived from CFD analysis of a range of stenoses. These stenoses were modeled by CFD and correlated with the ultrasound measured flow rate through the fistula of eight patients. The calculated flow rate using CFD correlated within 20% of ultrasound measured flow for five of eight patients. The mean difference was 17.2% (ranged from 1.3% to 30.1%). CFD analysis-generated flow rate tables provide valuable information to assess the functional significance of stenosis detected during imaging studies. The CFD study can help in determining the clinical relevance of a stenosis in access dysfunction and guide the need for intervention.

A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

PubMed

Liu, Zitao; Hauskrecht, Milos

2017-11-01

Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

Multi-channel MRI segmentation of eye structures and tumors using patient-specific features

PubMed Central

Ciller, Carlos; De Zanet, Sandro; Kamnitsas, Konstantinos; Maeder, Philippe; Glocker, Ben; Munier, Francis L.; Rueckert, Daniel; Thiran, Jean-Philippe

2017-01-01

Retinoblastoma and uveal melanoma are fast spreading eye tumors usually diagnosed by using 2D Fundus Image Photography (Fundus) and 2D Ultrasound (US). Diagnosis and treatment planning of such diseases often require additional complementary imaging to confirm the tumor extend via 3D Magnetic Resonance Imaging (MRI). In this context, having automatic segmentations to estimate the size and the distribution of the pathological tissue would be advantageous towards tumor characterization. Until now, the alternative has been the manual delineation of eye structures, a rather time consuming and error-prone task, to be conducted in multiple MRI sequences simultaneously. This situation, and the lack of tools for accurate eye MRI analysis, reduces the interest in MRI beyond the qualitative evaluation of the optic nerve invasion and the confirmation of recurrent malignancies below calcified tumors. In this manuscript, we propose a new framework for the automatic segmentation of eye structures and ocular tumors in multi-sequence MRI. Our key contribution is the introduction of a pathological eye model from which Eye Patient-Specific Features (EPSF) can be computed. These features combine intensity and shape information of pathological tissue while embedded in healthy structures of the eye. We assess our work on a dataset of pathological patient eyes by computing the Dice Similarity Coefficient (DSC) of the sclera, the cornea, the vitreous humor, the lens and the tumor. In addition, we quantitatively show the superior performance of our pathological eye model as compared to the segmentation obtained by using a healthy model (over 4% DSC) and demonstrate the relevance of our EPSF, which improve the final segmentation regardless of the classifier employed. PMID:28350816

A finite element model of myocardial infarction using a composite material approach.

PubMed

Haddad, Seyyed M H; Samani, Abbas

2018-01-01

Computational models are effective tools to study cardiac mechanics under normal and pathological conditions. They can be used to gain insight into the physiology of the heart under these conditions while they are adaptable to computer assisted patient-specific clinical diagnosis and therapeutic procedures. Realistic cardiac mechanics models incorporate tissue active/passive response in conjunction with hyperelasticity and anisotropy. Conventional formulation of such models leads to mathematically-complex problems usually solved by custom-developed non-linear finite element (FE) codes. With a few exceptions, such codes are not available to the research community. This article describes a computational cardiac mechanics model developed such that it can be implemented using off-the-shelf FE solvers while tissue pathologies can be introduced in the model in a straight-forward manner. The model takes into account myocardial hyperelasticity, anisotropy, and active contraction forces. It follows a composite tissue modeling approach where the cardiac tissue is decomposed into two major parts: background and myofibers. The latter is modelled as rebars under initial stresses mimicking the contraction forces. The model was applied in silico to study the mechanics of infarcted left ventricle (LV) of a canine. End-systolic strain components, ejection fraction, and stress distribution attained using this LV model were compared quantitatively and qualitatively to corresponding data obtained from measurements as well as to other corresponding LV mechanics models. This comparison showed very good agreement.

Relative category-specific preservation in semantic dementia? Evidence from 35 cases.

PubMed

Merck, Catherine; Jonin, Pierre-Yves; Vichard, Hélène; Boursiquot, Sandrine Le Moal; Leblay, Virginie; Belliard, Serge

2013-03-01

Category-specific deficits have rarely been reported in semantic dementia (SD). To our knowledge, only four previous studies have documented category-specific deficits, and these have focused on the living versus non-living things contrast rather than on more fine-grained semantic categories. This study aimed to determine whether a category-specific effect could be highlighted by a semantic sorting task administered to 35 SD patients once at baseline and again after 2 years and to 10 Alzheimer's disease patients (AD). We found a relative preservation of fruit and vegetables only in SD. This relative preservation of fruit and vegetables could be considered with regard to the importance of color knowledge in their discrimination. Indeed, color knowledge retrieval is known to depend on the left posterior fusiform gyrus which is relatively spared in SD. Finally, according to predictions of semantic memory models, our findings best fitted the Devlin and Gonnerman's computational account. Copyright © 2013 Elsevier Inc. All rights reserved.

A computational model to protect patient data from location-based re-identification.

PubMed

Malin, Bradley

2007-07-01

Health care organizations must preserve a patient's anonymity when disclosing personal data. Traditionally, patient identity has been protected by stripping identifiers from sensitive data such as DNA. However, simple automated methods can re-identify patient data using public information. In this paper, we present a solution to prevent a threat to patient anonymity that arises when multiple health care organizations disclose data. In this setting, a patient's location visit pattern, or "trail", can re-identify seemingly anonymous DNA to patient identity. This threat exists because health care organizations (1) cannot prevent the disclosure of certain types of patient information and (2) do not know how to systematically avoid trail re-identification. In this paper, we develop and evaluate computational methods that health care organizations can apply to disclose patient-specific DNA records that are impregnable to trail re-identification. To prevent trail re-identification, we introduce a formal model called k-unlinkability, which enables health care administrators to specify different degrees of patient anonymity. Specifically, k-unlinkability is satisfied when the trail of each DNA record is linkable to no less than k identified records. We present several algorithms that enable health care organizations to coordinate their data disclosure, so that they can determine which DNA records can be shared without violating k-unlinkability. We evaluate the algorithms with the trails of patient populations derived from publicly available hospital discharge databases. Algorithm efficacy is evaluated using metrics based on real world applications, including the number of suppressed records and the number of organizations that disclose records. Our experiments indicate that it is unnecessary to suppress all patient records that initially violate k-unlinkability. Rather, only portions of the trails need to be suppressed. For example, if each hospital discloses 100% of its data on patients diagnosed with cystic fibrosis, then 48% of the DNA records are 5-unlinkable. A naïve solution would suppress the 52% of the DNA records that violate 5-unlinkability. However, by applying our protection algorithms, the hospitals can disclose 95% of the DNA records, all of which are 5-unlinkable. Similar findings hold for all populations studied. This research demonstrates that patient anonymity can be formally protected in shared databases. Our findings illustrate that significant quantities of patient-specific data can be disclosed with provable protection from trail re-identification. The configurability of our methods allows health care administrators to quantify the effects of different levels of privacy protection and formulate policy accordingly.

64 slice-coronary computed tomography sensitivity and specificity in the evaluation of coronary artery bypass graft stenosis: A meta-analysis.

PubMed

Barbero, Umberto; Iannaccone, Mario; d'Ascenzo, Fabrizio; Barbero, Cristina; Mohamed, Abdirashid; Annone, Umberto; Benedetto, Sara; Celentani, Dario; Gagliardi, Marco; Moretti, Claudio; Gaita, Fiorenzo

2016-08-01

A non-invasive approach to define grafts patency and stenosis in the follow-up of coronary artery bypass graft (CABG) patients may be an interesting alternative to coronary angiography. 64-slice-coronary computed tomography is nowadays a diffused non-invasive method that permits an accurate evaluation of coronary stenosis, due to a high temporal and spatial resolution. However, its sensitivity and specificity in CABG evaluation has to be clearly defined, since published studies used different protocols and scanners. We collected all studies investigating patients with stable symptoms and previous CABG and reporting the comparison between diagnostic performances of invasive coronary angiography and 64-slice-coronary computed tomography. As a result, sensitivity and specificity of 64-slice-coronary computed tomography for CABG occlusion were 0.99 (95% CI 0.97-1.00) and 0.99 (95% CI: 0.99-1.00) with an area under the curve (AUC) of 0.99. 64-slice-coronary computed tomography sensitivity and specificity for the presence of any CABG stenosis >50% were 0.98 (95% CI: 0.97-0.99) and 0.98 (95% CI: 0.96-0.98), while AUC was 0.99. At meta-regression, neither the age nor the time from graft implantation had effect on sensitivity and specificity of 64-slice-coronary computed tomography detection of significant CABG stenosis or occlusion. In conclusion 64-slice-coronary computed tomography confirmed its high sensitivity and specificity in CABG stenosis or occlusion evaluation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Sensitivity and Specificity of CT and Its signs for Diagnosis of Strangulation in Patients with Acute Small Bowel Obstruction.

PubMed

Jha, Ashwini Kumar; Tang, Wen Hao; Bai, Zhi Bin; Xiao, Jia Quan

2014-01-01

To perform a meta-analysis to review the sensitivity and specificity of computed tomography and different known computed yomography signs for the diagnosis of strangulation in patients with acute small bowel obstruction. A comprehensive Pubmed search was performed for all reports that evaluated the use of CT and discussed different CT criteria for the diagnosis of acute SBO. Articles published in English language from January 1978 to June 2008 were included. Review articles, case reports, pictorial essays and articles without original data were excluded. The bivariate random effect model was used to obtain pooled sensitivity and pooled specificity. Summary receiver operating curve was calculated using Meta-Disc. Software Openbugs 3.0.3 was used to summarize the data. A total of 12 studies fulfilled the inclusion criteria. The pooled sensitivity and specificity of CT in the diagnosis of strangulation was 0.720 (95% CI 0.674 to 0.763) and 0.866 (95% CI 0.837 to 0.892) respectively. Among different CT signs, mesenteric edema had highest Pooled sensitivity of 0. 741 and lack of bowel wall enhancement had highest pooled specificity of 0.991. This review demonstrates that CT is highly sensitive as well as specific in the preoperative diagnosis of strangulation SBO which are in accordance with the published studies. Our analysis also shows that "presence of mesenteric fluid" is most sensitive, and "lack of bowel wall enhancement" is most specific CT sign of strangulation, and also justifies need of large scale prospective studies to validate the results obtained as well as to determine a clinical protocol.

Three-dimensional simulation, surgical navigation and thoracoscopic lung resection

PubMed Central

Kanzaki, Masato; Kikkawa, Takuma; Sakamoto, Kei; Maeda, Hideyuki; Wachi, Naoko; Komine, Hiroshi; Oyama, Kunihiro; Murasugi, Masahide; Onuki, Takamasa

2013-01-01

This report describes a 3-dimensional (3-D) video-assisted thoracoscopic lung resection guided by a 3-D video navigation system having a patient-specific 3-D reconstructed pulmonary model obtained by preoperative simulation. A 78-year-old man was found to have a small solitary pulmonary nodule in the left upper lobe in chest computed tomography. By a virtual 3-D pulmonary model the tumor was found to be involved in two subsegments (S1 + 2c and S3a). Complete video-assisted thoracoscopic surgery bi-subsegmentectomy was selected in simulation and was performed with lymph node dissection. A 3-D digital vision system was used for 3-D thoracoscopic performance. Wearing 3-D glasses, the patient's actual reconstructed 3-D model on 3-D liquid-crystal displays was observed, and the 3-D intraoperative field and the picture of 3-D reconstructed pulmonary model were compared. PMID:24964426

Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling.

PubMed

Tesche, Christian; De Cecco, Carlo N; Baumann, Stefan; Renker, Matthias; McLaurin, Tindal W; Duguay, Taylor M; Bayer, Richard R; Steinberg, Daniel H; Grant, Katharine L; Canstein, Christian; Schwemmer, Chris; Schoebinger, Max; Itu, Lucian M; Rapaka, Saikiran; Sharma, Puneet; Schoepf, U Joseph

2018-04-10

Purpose To compare two technical approaches for determination of coronary computed tomography (CT) angiography-derived fractional flow reserve (FFR)-FFR derived from coronary CT angiography based on computational fluid dynamics (hereafter, FFR CFD ) and FFR derived from coronary CT angiography based on machine learning algorithm (hereafter, FFR ML )-against coronary CT angiography and quantitative coronary angiography (QCA). Materials and Methods A total of 85 patients (mean age, 62 years ± 11 [standard deviation]; 62% men) who had undergone coronary CT angiography followed by invasive FFR were included in this single-center retrospective study. FFR values were derived on-site from coronary CT angiography data sets by using both FFR CFD and FFR ML . The performance of both techniques for detecting lesion-specific ischemia was compared against visual stenosis grading at coronary CT angiography, QCA, and invasive FFR as the reference standard. Results On a per-lesion and per-patient level, FFR ML showed a sensitivity of 79% and 90% and a specificity of 94% and 95%, respectively, for detecting lesion-specific ischemia. Meanwhile, FFR CFD resulted in a sensitivity of 79% and 89% and a specificity of 93% and 93%, respectively, on a per-lesion and per-patient basis (P = .86 and P = .92). On a per-lesion level, the area under the receiver operating characteristics curve (AUC) of 0.89 for FFR ML and 0.89 for FFR CFD showed significantly higher discriminatory power for detecting lesion-specific ischemia compared with that of coronary CT angiography (AUC, 0.61) and QCA (AUC, 0.69) (all P < .0001). Also, on a per-patient level, FFR ML (AUC, 0.91) and FFR CFD (AUC, 0.91) performed significantly better than did coronary CT angiography (AUC, 0.65) and QCA (AUC, 0.68) (all P < .0001). Processing time for FFR ML was significantly shorter compared with that of FFR CFD (40.5 minutes ± 6.3 vs 43.4 minutes ± 7.1; P = .042). Conclusion The FFR ML algorithm performs equally in detecting lesion-specific ischemia when compared with the FFR CFD approach. Both methods outperform accuracy of coronary CT angiography and QCA in the detection of flow-limiting stenosis. © RSNA, 2018.

Convolution-based estimation of organ dose in tube current modulated CT

NASA Astrophysics Data System (ADS)

Tian, Xiaoyu; Segars, W. Paul; Dixon, Robert L.; Samei, Ehsan

2016-05-01

Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460-7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18-70 years, weight range: 60-180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients ({{h}\\text{Organ}} ) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} with the organ dose coefficients ({{h}\\text{Organ}} ). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The discrepancy between the estimated organ dose and dose simulated using TCM Monte Carlo program was quantified. We further compared the convolution-based organ dose estimation method with two other strategies with different approaches of quantifying the irradiation field. The proposed convolution-based estimation method showed good accuracy with the organ dose simulated using the TCM Monte Carlo simulation. The average percentage error (normalized by CTDIvol) was generally within 10% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. This study developed an improved method that accurately quantifies the irradiation field under TCM scans. The results suggested that organ dose could be estimated in real-time both prospectively (with the localizer information only) and retrospectively (with acquired CT data).

Simulation based planning of surgical interventions in pediatric cardiology

NASA Astrophysics Data System (ADS)

Marsden, Alison L.

2013-10-01

Hemodynamics plays an essential role in the progression and treatment of cardiovascular disease. However, while medical imaging provides increasingly detailed anatomical information, clinicians often have limited access to hemodynamic data that may be crucial to patient risk assessment and treatment planning. Computational simulations can now provide detailed hemodynamic data to augment clinical knowledge in both adult and pediatric applications. There is a particular need for simulation tools in pediatric cardiology, due to the wide variation in anatomy and physiology in congenital heart disease patients, necessitating individualized treatment plans. Despite great strides in medical imaging, enabling extraction of flow information from magnetic resonance and ultrasound imaging, simulations offer predictive capabilities that imaging alone cannot provide. Patient specific simulations can be used for in silico testing of new surgical designs, treatment planning, device testing, and patient risk stratification. Furthermore, simulations can be performed at no direct risk to the patient. In this paper, we outline the current state of the art in methods for cardiovascular blood flow simulation and virtual surgery. We then step through pressing challenges in the field, including multiscale modeling, boundary condition selection, optimization, and uncertainty quantification. Finally, we summarize simulation results of two representative examples from pediatric cardiology: single ventricle physiology, and coronary aneurysms caused by Kawasaki disease. These examples illustrate the potential impact of computational modeling tools in the clinical setting.

Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis.

PubMed

Luo, Xin; Zang, Xiao; Yang, Lin; Huang, Junzhou; Liang, Faming; Rodriguez-Canales, Jaime; Wistuba, Ignacio I; Gazdar, Adi; Xie, Yang; Xiao, Guanghua

2017-03-01

Pathological examination of histopathological slides is a routine clinical procedure for lung cancer diagnosis and prognosis. Although the classification of lung cancer has been updated to become more specific, only a small subset of the total morphological features are taken into consideration. The vast majority of the detailed morphological features of tumor tissues, particularly tumor cells' surrounding microenvironment, are not fully analyzed. The heterogeneity of tumor cells and close interactions between tumor cells and their microenvironments are closely related to tumor development and progression. The goal of this study is to develop morphological feature-based prediction models for the prognosis of patients with lung cancer. We developed objective and quantitative computational approaches to analyze the morphological features of pathological images for patients with NSCLC. Tissue pathological images were analyzed for 523 patients with adenocarcinoma (ADC) and 511 patients with squamous cell carcinoma (SCC) from The Cancer Genome Atlas lung cancer cohorts. The features extracted from the pathological images were used to develop statistical models that predict patients' survival outcomes in ADC and SCC, respectively. We extracted 943 morphological features from pathological images of hematoxylin and eosin-stained tissue and identified morphological features that are significantly associated with prognosis in ADC and SCC, respectively. Statistical models based on these extracted features stratified NSCLC patients into high-risk and low-risk groups. The models were developed from training sets and validated in independent testing sets: a predicted high-risk group versus a predicted low-risk group (for patients with ADC: hazard ratio = 2.34, 95% confidence interval: 1.12-4.91, p = 0.024; for patients with SCC: hazard ratio = 2.22, 95% confidence interval: 1.15-4.27, p = 0.017) after adjustment for age, sex, smoking status, and pathologic tumor stage. The results suggest that the quantitative morphological features of tumor pathological images predict prognosis in patients with lung cancer. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Computational models of aortic coarctation in hypoplastic left heart syndrome: considerations on validation of a detailed 3D model.

PubMed

Biglino, Giovanni; Corsini, Chiara; Schievano, Silvia; Dubini, Gabriele; Giardini, Alessandro; Hsia, Tain-Yen; Pennati, Giancarlo; Taylor, Andrew M

2014-05-01

Reliability of computational models for cardiovascular investigations strongly depends on their validation against physical data. This study aims to experimentally validate a computational model of complex congenital heart disease (i.e., surgically palliated hypoplastic left heart syndrome with aortic coarctation) thus demonstrating that hemodynamic information can be reliably extrapolated from the model for clinically meaningful investigations. A patient-specific aortic arch model was tested in a mock circulatory system and the same flow conditions were re-created in silico, by setting an appropriate lumped parameter network (LPN) attached to the same three-dimensional (3D) aortic model (i.e., multi-scale approach). The model included a modified Blalock-Taussig shunt and coarctation of the aorta. Different flow regimes were tested as well as the impact of uncertainty in viscosity. Computational flow and pressure results were in good agreement with the experimental signals, both qualitatively, in terms of the shape of the waveforms, and quantitatively (mean aortic pressure 62.3 vs. 65.1 mmHg, 4.8% difference; mean aortic flow 28.0 vs. 28.4% inlet flow, 1.4% difference; coarctation pressure drop 30.0 vs. 33.5 mmHg, 10.4% difference), proving the reliability of the numerical approach. It was observed that substantial changes in fluid viscosity or using a turbulent model in the numerical simulations did not significantly affect flows and pressures of the investigated physiology. Results highlighted how the non-linear fluid dynamic phenomena occurring in vitro must be properly described to ensure satisfactory agreement. This study presents methodological considerations for using experimental data to preliminarily set up a computational model, and then simulate a complex congenital physiology using a multi-scale approach.

Predicting clinical outcome of neuroblastoma patients using an integrative network-based approach.

PubMed

Tranchevent, Léon-Charles; Nazarov, Petr V; Kaoma, Tony; Schmartz, Georges P; Muller, Arnaud; Kim, Sang-Yoon; Rajapakse, Jagath C; Azuaje, Francisco

2018-06-07

One of the main current challenges in computational biology is to make sense of the huge amounts of multidimensional experimental data that are being produced. For instance, large cohorts of patients are often screened using different high-throughput technologies, effectively producing multiple patient-specific molecular profiles for hundreds or thousands of patients. We propose and implement a network-based method that integrates such patient omics data into Patient Similarity Networks. Topological features derived from these networks were then used to predict relevant clinical features. As part of the 2017 CAMDA challenge, we have successfully applied this strategy to a neuroblastoma dataset, consisting of genomic and transcriptomic data. In particular, we observe that models built on our network-based approach perform at least as well as state of the art models. We furthermore explore the effectiveness of various topological features and observe, for instance, that redundant centrality metrics can be combined to build more powerful models. We demonstrate that the networks inferred from omics data contain clinically relevant information and that patient clinical outcomes can be predicted using only network topological data. This article was reviewed by Yang-Yu Liu, Tomislav Smuc and Isabel Nepomuceno.

Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI.

PubMed

Dikaios, Nikolaos; Alkalbani, Jokha; Sidhu, Harbir Singh; Fujiwara, Taiki; Abd-Alazeez, Mohamed; Kirkham, Alex; Allen, Clare; Ahmed, Hashim; Emberton, Mark; Freeman, Alex; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit

2015-02-01

We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI). One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance. Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively. LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists. • MRI helps find prostate cancer in the anterior of the gland • Logistic regression models based on mp-MRI can classify prostate cancer • Computers can help confirm cancer in areas doctors are uncertain about.

Reconstruction of the Upper Cervical Spine Using a Personalized 3D-Printed Vertebral Body in an Adolescent With Ewing Sarcoma.

PubMed

Xu, Nanfang; Wei, Feng; Liu, Xiaoguang; Jiang, Liang; Cai, Hong; Li, Zihe; Yu, Miao; Wu, Fengliang; Liu, Zhongjun

2016-01-01

Case report. To describe a three-dimensional (3D) printed axial vertebral body used in upper cervical spine reconstruction after a C2 Ewing sarcoma resection in an adolescent boy. Ewing sarcoma is a malignant musculoskeletal neoplasm with a peak incidence in adolescents. Cervical spine as the primary site of the tumor has been related to a worse prognosis. Tumor resection is particularly challenging in the atlantoaxial region due to complexity of the anatomy, necessity for extensive resection according to oncological principles, and a lack of specialized implants for reconstruction. 3D printing refers to a process where 3D objects are created through successive layering of material under computer control. Although this technology potentially enables accurate fabrication of patient-specific orthopedic implants, literature on its utilization in this regard is rare. A 12-year-old boy with a C2 Ewing sarcoma underwent a staged spondylectomy. Wide resection of the posterior elements was first performed. Two weeks later, a high anterior retropharyngeal approach was taken to remove the remains of the C2 vertebra. A customized artificial vertebral body fabricated according to a computer model using titanium alloy powder was inserted to replace the defect between C1 and C3. The microstructure of the implant was optimized for better biomechanical stability and enhanced bone healing. Patient had an uneventful recovery and began to ambulate on postoperative day 7. Adjuvant treatment commenced 3 weeks after the surgery. He was tumor-free at the 1-year follow-up. Computed tomography studies revealed evidence of implant osseointegration and no subsidence or displacement of the construct. This is a case example on the concept of personalized precision medicine in a surgical setting and demonstrates how 3D-printed, patient-specific implants may bring individualized solutions to rare problems wherein restoration of the specific anatomy of each patient is a key prognostic factor.

CFD and PIV Analysis of Hemodynamics in a Growing Intracranial Aneurysm

PubMed Central

Raschi, Marcelo; Mut, Fernando; Byrne, Greg; Putman, Christopher M.; Tateshima, Satoshi; Viñuela, Fernando; Tanoue, Tetsuya; Tanishita, Kazuo; Cebral, Juan R.

2011-01-01

Hemodynamics is thought to be a fundamental factor in the formation, progression and rupture of cerebral aneurysms. Understanding these mechanisms is important to improve their rupture risk assessment and treatment. In this study we analyze the blood flow field in a growing cerebral aneurysm using experimental particle image velocimetry (PIV) and computational fluid dynamics (CFD) techniques. Patient-specific models were constructed from longitudinal 3D computed tomography angiography (CTA) images acquired at one-year intervals. Physical silicone models were constructed from the CTA images using rapid prototyping techniques and pulsatile flow fields were measured with PIV. Corresponding CFD models were created and run under matching flow conditions. Both flow fields were aligned, interpolated, and compared qualitatively by inspection and quantitatively by defining similarity measures between the PIV and CFD vector fields. Results showed that both flow fields were in good agreement. Specifically, both techniques provided consistent representations of the main intra-aneurysmal flow structures, and their change during the geometric evolution of the aneurysm. Despite differences observed mainly in the near wall region and the inherent limitations of each technique, the information derived is consistent and can be used to study the role of hemodynamics in the natural history of intracranial aneurysms. PMID:22548127

Mathematical modeling of coupled drug and drug-encapsulated nanoparticle transport in patient-specific coronary artery walls

NASA Astrophysics Data System (ADS)

Hossain, Shaolie S.; Hossainy, Syed F. A.; Bazilevs, Yuri; Calo, Victor M.; Hughes, Thomas J. R.

2012-02-01

The majority of heart attacks occur when there is a sudden rupture of atherosclerotic plaque, exposing prothrombotic emboli to coronary blood flow, forming clots that can cause blockages of the arterial lumen. Diseased arteries can be treated with drugs delivered locally to vulnerable plaques. The objective of this work was to develop a computational tool-set to support the design and analysis of a catheter-based nanoparticulate drug delivery system to treat vulnerable plaques and diffuse atherosclerosis. A three-dimensional mathematical model of coupled mass transport of drug and drug-encapsulated nanoparticles was developed and solved numerically utilizing isogeometric finite element analysis. Simulations were run on a patient-specific multilayered coronary artery wall segment with a vulnerable plaque and the effect of artery and plaque inhomogeneity was analyzed. The method captured trends observed in local drug delivery and demonstrated potential for optimizing drug design parameters, including delivery location, nanoparticle surface properties, and drug release rate.

3D-Printed Patient-Specific ACL Femoral Tunnel Guide from MRI.

PubMed

Rankin, Iain; Rehman, Haroon; Frame, Mark

2018-01-01

Traditional ACL reconstruction with non-anatomic techniques can demonstrate unsatisfactory long-term outcomes with regards instability and the degenerative knee changes observed with these results. Anatomic ACL reconstruction attempts to closely reproduce the patient's individual anatomic characteristics with the aim of restoring knee kinematics, in order to improve patient short and long-term outcomes. We designed an arthroscopic, patient-specific, ACL femoral tunnel guide to aid anatomical placement of the ACL graft within the femoral tunnel. The guide design was based on MRI scan of the subject's uninjured contralateral knee, identifying the femoral footprint and its anatomical position relative to the borders of the femoral articular cartilage. Image processing software was used to create a 3D computer aided design which was subsequently exported to a 3D-printing service. Transparent acrylic based photopolymer, PA220 plastic and 316L stainless steel patient-specific ACL femoral tunnel guides were created; the models produced were accurate with no statistical difference in size and positioning of the center of the ACL femoral footprint guide to MRI ( p =0.344, p =0.189, p =0.233 respectively). The guides aim to provide accurate marking of the starting point of the femoral tunnel in arthroscopic ACL reconstruction. This study serves as a proof of concept for the accurate creation of 3D-printed patient-specific guides for the anatomical placement of the femoral tunnel during ACL reconstruction.

Development of the voxel computational phantoms of pediatric patients and their application to organ dose assessment

NASA Astrophysics Data System (ADS)

Lee, Choonik

A series of realistic voxel computational phantoms of pediatric patients were developed and then used for the radiation risk assessment for various exposure scenarios. The high-resolution computed tomographic images of live patients were utilized for the development of the five voxel phantoms of pediatric patients, 9-month male, 4-year female, 8-year female, 11-year male, and 14-year male. The phantoms were first developed as head and torso phantoms and then extended into whole body phantoms by utilizing computed tomographic images of a healthy adult volunteer. The whole body phantom series was modified to have the same anthropometrics with the most recent reference data reported by the international commission on radiological protection. The phantoms, named as the University of Florida series B, are the first complete set of the pediatric voxel phantoms having reference organ masses and total heights. As part of the dosimetry study, the investigation on skeletal tissue dosimetry methods was performed for better understanding of the radiation dose to the active bone marrow and bone endosteum. All of the currently available methodologies were inter-compared and benchmarked with the paired-image radiation transport model. The dosimetric characteristics of the phantoms were investigated by using Monte Carlo simulation of the broad parallel beams of external phantom in anterior-posterior, posterior-anterior, left lateral, right lateral, rotational, and isotropic angles. Organ dose conversion coefficients were calculated for extensive photon energies and compared with the conventional stylized pediatric phantoms of Oak Ridge National Laboratory. The multi-slice helical computed tomography exams were simulated using Monte Carlo simulation code for various exams protocols, head, chest, abdomen, pelvis, and chest-abdomen-pelvis studies. Results have found realistic estimates of the effective doses for frequently used protocols in pediatric radiology. The results were very crucial in understanding the radiation risks of the patients undergoing computed tomography. Finally, nuclear medicine simulations were performed by calculating specific absorbed fractions for multiple target-source organ pairs via Monte Carlo simulations. Specific absorbed fractions were calculated for both photon and electron so that they can be used to calculated radionuclide S-values. All of the results were tabulated for future uses and example dose assessment was performed for selected nuclides administered in nuclear medicine.

Impact of temporal probability in 4D dose calculation for lung tumors.

PubMed

Rouabhi, Ouided; Ma, Mingyu; Bayouth, John; Xia, Junyi

2015-11-08

The purpose of this study was to evaluate the dosimetric uncertainty in 4D dose calculation using three temporal probability distributions: uniform distribution, sinusoidal distribution, and patient-specific distribution derived from the patient respiratory trace. Temporal probability, defined as the fraction of time a patient spends in each respiratory amplitude, was evaluated in nine lung cancer patients. Four-dimensional computed tomography (4D CT), along with deformable image registration, was used to compute 4D dose incorporating the patient's respiratory motion. First, the dose of each of 10 phase CTs was computed using the same planning parameters as those used in 3D treatment planning based on the breath-hold CT. Next, deformable image registration was used to deform the dose of each phase CT to the breath-hold CT using the deformation map between the phase CT and the breath-hold CT. Finally, the 4D dose was computed by summing the deformed phase doses using their corresponding temporal probabilities. In this study, 4D dose calculated from the patient-specific temporal probability distribution was used as the ground truth. The dosimetric evaluation matrix included: 1) 3D gamma analysis, 2) mean tumor dose (MTD), 3) mean lung dose (MLD), and 4) lung V20. For seven out of nine patients, both uniform and sinusoidal temporal probability dose distributions were found to have an average gamma passing rate > 95% for both the lung and PTV regions. Compared with 4D dose calculated using the patient respiratory trace, doses using uniform and sinusoidal distribution showed a percentage difference on average of -0.1% ± 0.6% and -0.2% ± 0.4% in MTD, -0.2% ± 1.9% and -0.2% ± 1.3% in MLD, 0.09% ± 2.8% and -0.07% ± 1.8% in lung V20, -0.1% ± 2.0% and 0.08% ± 1.34% in lung V10, 0.47% ± 1.8% and 0.19% ± 1.3% in lung V5, respectively. We concluded that four-dimensional dose computed using either a uniform or sinusoidal temporal probability distribution can approximate four-dimensional dose computed using the patient-specific respiratory trace.

A New Socio-technical Model for Studying Health Information Technology in Complex Adaptive Healthcare Systems

PubMed Central

Sittig, Dean F.; Singh, Hardeep

2011-01-01

Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). This manuscript introduces an 8-dimensional model specifically designed to address the socio-technical challenges involved in design, development, implementation, use, and evaluation of HIT within complex adaptive healthcare systems. The 8 dimensions are not independent, sequential, or hierarchical, but rather are interdependent and interrelated concepts similar to compositions of other complex adaptive systems. Hardware and software computing infrastructure refers to equipment and software used to power, support, and operate clinical applications and devices. Clinical content refers to textual or numeric data and images that constitute the “language” of clinical applications. The human computer interface includes all aspects of the computer that users can see, touch, or hear as they interact with it. People refers to everyone who interacts in some way with the system, from developer to end-user, including potential patient-users. Workflow and communication are the processes or steps involved in assuring that patient care tasks are carried out effectively. Two additional dimensions of the model are internal organizational features (e.g., policies, procedures, and culture) and external rules and regulations, both of which may facilitate or constrain many aspects of the preceding dimensions. The final dimension is measurement and monitoring, which refers to the process of measuring and evaluating both intended and unintended consequences of HIT implementation and use. We illustrate how our model has been successfully applied in real-world complex adaptive settings to understand and improve HIT applications at various stages of development and implementation. PMID:20959322

A new sociotechnical model for studying health information technology in complex adaptive healthcare systems.

PubMed

Sittig, Dean F; Singh, Hardeep

2010-10-01

Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). This manuscript introduces an eight-dimensional model specifically designed to address the sociotechnical challenges involved in design, development, implementation, use and evaluation of HIT within complex adaptive healthcare systems. The eight dimensions are not independent, sequential or hierarchical, but rather are interdependent and inter-related concepts similar to compositions of other complex adaptive systems. Hardware and software computing infrastructure refers to equipment and software used to power, support and operate clinical applications and devices. Clinical content refers to textual or numeric data and images that constitute the 'language' of clinical applications. The human--computer interface includes all aspects of the computer that users can see, touch or hear as they interact with it. People refers to everyone who interacts in some way with the system, from developer to end user, including potential patient-users. Workflow and communication are the processes or steps involved in ensuring that patient care tasks are carried out effectively. Two additional dimensions of the model are internal organisational features (eg, policies, procedures and culture) and external rules and regulations, both of which may facilitate or constrain many aspects of the preceding dimensions. The final dimension is measurement and monitoring, which refers to the process of measuring and evaluating both intended and unintended consequences of HIT implementation and use. We illustrate how our model has been successfully applied in real-world complex adaptive settings to understand and improve HIT applications at various stages of development and implementation.

Integrating Cloud-Computing-Specific Model into Aircraft Design

NASA Astrophysics Data System (ADS)

Zhimin, Tian; Qi, Lin; Guangwen, Yang

Cloud Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many types of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of cloud services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate cloud computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.

A computational study of liposome logic: towards cellular computing from the bottom up

PubMed Central

Smaldon, James; Romero-Campero, Francisco J.; Fernández Trillo, Francisco; Gheorghe, Marian; Alexander, Cameron

2010-01-01

In this paper we propose a new bottom-up approach to cellular computing, in which computational chemical processes are encapsulated within liposomes. This “liposome logic” approach (also called vesicle computing) makes use of supra-molecular chemistry constructs, e.g. protocells, chells, etc. as minimal cellular platforms to which logical functionality can be added. Modeling and simulations feature prominently in “top-down” synthetic biology, particularly in the specification, design and implementation of logic circuits through bacterial genome reengineering. The second contribution in this paper is the demonstration of a novel set of tools for the specification, modelling and analysis of “bottom-up” liposome logic. In particular, simulation and modelling techniques are used to analyse some example liposome logic designs, ranging from relatively simple NOT gates and NAND gates to SR-Latches, D Flip-Flops all the way to 3 bit ripple counters. The approach we propose consists of specifying, by means of P systems, gene regulatory network-like systems operating inside proto-membranes. This P systems specification can be automatically translated and executed through a multiscaled pipeline composed of dissipative particle dynamics (DPD) simulator and Gillespie’s stochastic simulation algorithm (SSA). Finally, model selection and analysis can be performed through a model checking phase. This is the first paper we are aware of that brings to bear formal specifications, DPD, SSA and model checking to the problem of modeling target computational functionality in protocells. Potential chemical routes for the laboratory implementation of these simulations are also discussed thus for the first time suggesting a potentially realistic physiochemical implementation for membrane computing from the bottom-up. PMID:21886681

Haemodynamics of giant cerebral aneurysm: A comparison between the rigid-wall, one-way and two-way FSI models

NASA Astrophysics Data System (ADS)

Khe, A. K.; Cherevko, A. A.; Chupakhin, A. P.; Bobkova, M. S.; Krivoshapkin, A. L.; Orlov, K. Yu

2016-06-01

In this paper a computer simulation of a blood flow in cerebral vessels with a giant saccular aneurysm at the bifurcation of the basilar artery is performed. The modelling is based on patient-specific clinical data (both flow domain geometry and boundary conditions for the inlets and outlets). The hydrodynamic and mechanical parameters are calculated in the frameworks of three models: rigid-wall assumption, one-way FSI approach, and full (two-way) hydroelastic model. A comparison of the numerical solutions shows that mutual fluid- solid interaction can result in qualitative changes in the structure of the fluid flow. Other characteristics of the flow (pressure, stress, strain and displacement) qualitatively agree with each other in different approaches. However, the quantitative comparison shows that accounting for the flow-vessel interaction, in general, decreases the absolute values of these parameters. Solving of the hydroelasticity problem gives a more detailed solution at a cost of highly increased computational time.

A database perspective of the transition from single-use (ancillary-based) systems to integrated models supporting clinical care and research in a MUMPS-based system.

PubMed

Siegel, J; Kirkland, D

1991-01-01

The Composite Health Care System (CHCS), a MUMPS-based hospital information system (HIS), has evolved from the Decentralized Hospital Computer Program (DHCP) installed within VA Hospitals. The authors explore the evolution of an ancillary-based system toward an integrated model with a look at its current state and possible future. The history and relationships between orders of different types tie specific patient-related data into a logical and temporal model. Diagrams demonstrate how the database structure has evolved to support clinical needs for integration. It is suggested that a fully integrated model is capable of meeting traditional HIS needs.

The circadian profile of epilepsy improves seizure forecasting.

PubMed

Karoly, Philippa J; Ung, Hoameng; Grayden, David B; Kuhlmann, Levin; Leyde, Kent; Cook, Mark J; Freestone, Dean R

2017-08-01

It is now established that epilepsy is characterized by periodic dynamics that increase seizure likelihood at certain times of day, and which are highly patient-specific. However, these dynamics are not typically incorporated into seizure prediction algorithms due to the difficulty of estimating patient-specific rhythms from relatively short-term or unreliable data sources. This work outlines a novel framework to develop and assess seizure forecasts, and demonstrates that the predictive power of forecasting models is improved by circadian information. The analyses used long-term, continuous electrocorticography from nine subjects, recorded for an average of 320 days each. We used a large amount of out-of-sample data (a total of 900 days for algorithm training, and 2879 days for testing), enabling the most extensive post hoc investigation into seizure forecasting. We compared the results of an electrocorticography-based logistic regression model, a circadian probability, and a combined electrocorticography and circadian model. For all subjects, clinically relevant seizure prediction results were significant, and the addition of circadian information (combined model) maximized performance across a range of outcome measures. These results represent a proof-of-concept for implementing a circadian forecasting framework, and provide insight into new approaches for improving seizure prediction algorithms. The circadian framework adds very little computational complexity to existing prediction algorithms, and can be implemented using current-generation implant devices, or even non-invasively via surface electrodes using a wearable application. The ability to improve seizure prediction algorithms through straightforward, patient-specific modifications provides promise for increased quality of life and improved safety for patients with epilepsy. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Computer-Aided Clinical Trial Recruitment Based on Domain-Specific Language Translation: A Case Study of Retinopathy of Prematurity

PubMed Central

2017-01-01

Reusing the data from healthcare information systems can effectively facilitate clinical trials (CTs). How to select candidate patients eligible for CT recruitment criteria is a central task. Related work either depends on DBA (database administrator) to convert the recruitment criteria to native SQL queries or involves the data mapping between a standard ontology/information model and individual data source schema. This paper proposes an alternative computer-aided CT recruitment paradigm, based on syntax translation between different DSLs (domain-specific languages). In this paradigm, the CT recruitment criteria are first formally represented as production rules. The referenced rule variables are all from the underlying database schema. Then the production rule is translated to an intermediate query-oriented DSL (e.g., LINQ). Finally, the intermediate DSL is directly mapped to native database queries (e.g., SQL) automated by ORM (object-relational mapping). PMID:29065644

Computer-Aided Clinical Trial Recruitment Based on Domain-Specific Language Translation: A Case Study of Retinopathy of Prematurity.

PubMed

Zhang, Yinsheng; Zhang, Guoming; Shang, Qian

2017-01-01

Reusing the data from healthcare information systems can effectively facilitate clinical trials (CTs). How to select candidate patients eligible for CT recruitment criteria is a central task. Related work either depends on DBA (database administrator) to convert the recruitment criteria to native SQL queries or involves the data mapping between a standard ontology/information model and individual data source schema. This paper proposes an alternative computer-aided CT recruitment paradigm, based on syntax translation between different DSLs (domain-specific languages). In this paradigm, the CT recruitment criteria are first formally represented as production rules. The referenced rule variables are all from the underlying database schema. Then the production rule is translated to an intermediate query-oriented DSL (e.g., LINQ). Finally, the intermediate DSL is directly mapped to native database queries (e.g., SQL) automated by ORM (object-relational mapping).

Patient-specific stress analyses in the ascending thoracic aorta using a finite-element implementation of the constrained mixture theory.

PubMed

Mousavi, S Jamaleddin; Avril, Stéphane

2017-10-01

It is now a rather common approach to perform patient-specific stress analyses of arterial walls using finite-element models reconstructed from gated medical images. However, this requires to compute for every Gauss point the deformation gradient between the current configuration and a stress-free reference configuration. It is technically difficult to define such a reference configuration, and there is actually no guarantee that a stress-free configuration is physically attainable due to the presence of internal stresses in unloaded soft tissues. An alternative framework was proposed by Bellini et al. (Ann Biomed Eng 42(3):488-502, 2014). It consists of computing the deformation gradients between the current configuration and a prestressed reference configuration. We present here the first finite-element results based on this concept using the Abaqus software. The reference configuration is set arbitrarily to the in vivo average geometry of the artery, which is obtained from gated medical images and is assumed to be mechanobiologically homeostatic. For every Gauss point, the stress is split additively into the contributions of each individual load-bearing constituent of the tissue, namely elastin, collagen, smooth muscle cells. Each constituent is assigned an independent prestretch in the reference configuration, named the deposition stretch. The outstanding advantage of the present approach is that it simultaneously computes the in situ stresses existing in the reference configuration and predicts the residual stresses that occur after removing the different loadings applied onto the artery (pressure and axial load). As a proof of concept, we applied it on an ideal thick-wall cylinder and showed that the obtained results were consistent with corresponding experimental and analytical results of the well-known literature. In addition, we developed a patient-specific model of a human ascending thoracic aneurysmal aorta and demonstrated the utility in predicting the wall stress distribution in vivo under the effects of physiological pressure. Finally, we simulated the whole process preceding traditional in vitro uniaxial tensile testing of arteries, including excision from the body, radial cutting, flattening and subsequent tensile loading, showing how this process may impact the final mechanical properties derived from these in vitro tests.

The importance of bony impingement in restricting flexion after total knee arthroplasty: computer simulation model with clinical correlation.

PubMed

Mizu-Uchi, Hideki; Colwell, Clifford W; Fukagawa, Shingo; Matsuda, Shuichi; Iwamoto, Yukihide; D'Lima, Darryl D

2012-10-01

We constructed patient-specific models from computed tomography data after total knee arthroplasty to predict knee flexion based on implant-bone impingement. The maximum flexion before impingement between the femur and the tibial insert was computed using a musculoskeletal modeling program (KneeSIM; LifeModeler, Inc, San Clemente, California) during a weight-bearing deep knee bend. Postoperative flexion was measured in a clinical cohort of 21 knees (low-flex group: 6 knees with <100° of flexion and high-flex group: 15 size-matched knees with >125° of flexion at 2 years). Average predicted flexion angles were within 2° of clinical measurements for the high-flex group. In the low-flex group, 4 cases had impingement involving the bone cut at the posterior condyle, and the average predicted knee flexion was 102° compared with 93° measured clinically. These results indicate that the level of the distal femoral resection should be carefully planned and that exposed bone proximal to the tips of the posterior condyles of the femoral component should be removed if there is risk of impingement. Copyright © 2012 Elsevier Inc. All rights reserved.

In Vitro Simulation and Validation of the Circulation with Congenital Heart Defects

PubMed Central

Figliola, Richard S.; Giardini, Alessandro; Conover, Tim; Camp, Tiffany A.; Biglino, Giovanni; Chiulli, John; Hsia, Tain-Yen

2010-01-01

Despite the recent advances in computational modeling, experimental simulation of the circulation with congenital heart defect using mock flow circuits remains an important tool for device testing, and for detailing the probable flow consequences resulting from surgical and interventional corrections. Validated mock circuits can be applied to qualify the results from novel computational models. New mathematical tools, coupled with advanced clinical imaging methods, allow for improved assessment of experimental circuit performance relative to human function, as well as the potential for patient-specific adaptation. In this review, we address the development of three in vitro mock circuits specific for studies of congenital heart defects. Performance of an in vitro right heart circulation circuit through a series of verification and validation exercises is described, including correlations with animal studies, and quantifying the effects of circuit inertiance on test results. We present our experience in the design of mock circuits suitable for investigations of the characteristics of the Fontan circulation. We use one such mock circuit to evaluate the accuracy of Doppler predictions in the presence of aortic coarctation. PMID:21218147

Development of a parametric kinematic model of the human hand and a novel robotic exoskeleton.

PubMed

Burton, T M W; Vaidyanathan, R; Burgess, S C; Turton, A J; Melhuish, C

2011-01-01

This paper reports the integration of a kinematic model of the human hand during cylindrical grasping, with specific focus on the accurate mapping of thumb movement during grasping motions, and a novel, multi-degree-of-freedom assistive exoskeleton mechanism based on this model. The model includes thumb maximum hyper-extension for grasping large objects (~> 50 mm). The exoskeleton includes a novel four-bar mechanism designed to reproduce natural thumb opposition and a novel synchro-motion pulley mechanism for coordinated finger motion. A computer aided design environment is used to allow the exoskeleton to be rapidly customized to the hand dimensions of a specific patient. Trials comparing the kinematic model to observed data of hand movement show the model to be capable of mapping thumb and finger joint flexion angles during grasping motions. Simulations show the exoskeleton to be capable of reproducing the complex motion of the thumb to oppose the fingers during cylindrical and pinch grip motions. © 2011 IEEE

Seizure Control in a Computational Model Using a Reinforcement Learning Stimulation Paradigm.

PubMed

Nagaraj, Vivek; Lamperski, Andrew; Netoff, Theoden I

2017-11-01

Neuromodulation technologies such as vagus nerve stimulation and deep brain stimulation, have shown some efficacy in controlling seizures in medically intractable patients. However, inherent patient-to-patient variability of seizure disorders leads to a wide range of therapeutic efficacy. A patient specific approach to determining stimulation parameters may lead to increased therapeutic efficacy while minimizing stimulation energy and side effects. This paper presents a reinforcement learning algorithm that optimizes stimulation frequency for controlling seizures with minimum stimulation energy. We apply our method to a computational model called the epileptor. The epileptor model simulates inter-ictal and ictal local field potential data. In order to apply reinforcement learning to the Epileptor, we introduce a specialized reward function and state-space discretization. With the reward function and discretization fixed, we test the effectiveness of the temporal difference reinforcement learning algorithm (TD(0)). For periodic pulsatile stimulation, we derive a relation that describes, for any stimulation frequency, the minimal pulse amplitude required to suppress seizures. The TD(0) algorithm is able to identify parameters that control seizures quickly. Additionally, our results show that the TD(0) algorithm refines the stimulation frequency to minimize stimulation energy thereby converging to optimal parameters reliably. An advantage of the TD(0) algorithm is that it is adaptive so that the parameters necessary to control the seizures can change over time. We show that the algorithm can converge on the optimal solution in simulation with slow and fast inter-seizure intervals.

Use of regional mechanical properties of abdominal aortic aneurysms to advance finite element modeling of rupture risk.

PubMed

Tierney, Áine P; Callanan, Anthony; McGloughlin, Timothy M

2012-02-01

To investigate the use of regional variations in the mechanical properties of abdominal aortic aneurysms (AAA) in finite element (FE) modeling of AAA rupture risk, which has heretofore assumed homogeneous mechanical tissue properties. Electrocardiogram-gated computed tomography scans from 3 male patients with known infrarenal AAA were used to characterize the behavior of the aneurysm in 4 different segments (posterior, anterior, and left and right lateral) at maximum diameter and above the infrarenal aorta. The elasticity of the aneurysm (circumferential cyclic strain, compliance, and the Hudetz incremental modulus) was calculated for each segment and the aneurysm as a whole. The FE analysis inclusive of prestress (pre-existing tensile stress) produced a detailed stress pattern on each of the aneurysm models under pressure loading. The 4 largest areas of stress in each region were considered in conjunction with the local regional properties of the segment to define a specific regional prestress rupture index (RPRI). In terms of elasticity, there were average reductions of 68% in circumferential cyclic strain and 63% in compliance, with a >5-fold increase in incremental modulus, between the healthy and the aneurysmal aorta for each patient. There were also regional variations in all elastic properties in each individual patient. The average difference in total stress inclusive of prestress was 59%, 67%, and 15%, respectively, for the 3 patients. Comparing the strain from FE models with the CT scans revealed an average difference in strain of 1.55% for the segmented models and 3.61% for the homogeneous models, which suggests that the segmented models more accurately reflect in vivo behavior. RPRI values were calculated for each segment for all patients. A greater understanding of the local material properties and their use in FE models is essential for greater accuracy in rupture prediction. Quantifying the regional behavior will yield insight into the changes in patient-specific aneurysms and increase understanding about the progression of aneurysmal disease.

A new cognitive rehabilitation programme for patients with multiple sclerosis: the 'MS-line! Project'.

PubMed

Gich, Jordi; Freixenet, Jordi; Garcia, Rafael; Vilanova, Joan Carles; Genís, David; Silva, Yolanda; Montalban, Xavier; Ramió-Torrentà, Lluís

2015-09-01

Cognitive rehabilitation is often delayed in multiple sclerosis (MS). To develop a free and specific cognitive rehabilitation programme for MS patients to be used from early stages that does not interfere with daily living activities. MS-line!, cognitive rehabilitation materials consisting of written, manipulative and computer-based materials with difficulty levels developed by a multidisciplinary team. Mathematical, problem-solving and word-based exercises were designed. Physical materials included spatial, coordination and reasoning games. Computer-based material included logic and reasoning, working memory and processing speed games. Cognitive rehabilitation exercises that are specific for MS patients have been successfully developed. © The Author(s), 2014.

Using discrete event computer simulation to improve patient flow in a Ghanaian acute care hospital.

PubMed

Best, Allyson M; Dixon, Cinnamon A; Kelton, W David; Lindsell, Christopher J; Ward, Michael J

2014-08-01

Crowding and limited resources have increased the strain on acute care facilities and emergency departments worldwide. These problems are particularly prevalent in developing countries. Discrete event simulation is a computer-based tool that can be used to estimate how changes to complex health care delivery systems such as emergency departments will affect operational performance. Using this modality, our objective was to identify operational interventions that could potentially improve patient throughput of one acute care setting in a developing country. We developed a simulation model of acute care at a district level hospital in Ghana to test the effects of resource-neutral (eg, modified staff start times and roles) and resource-additional (eg, increased staff) operational interventions on patient throughput. Previously captured deidentified time-and-motion data from 487 acute care patients were used to develop and test the model. The primary outcome was the modeled effect of interventions on patient length of stay (LOS). The base-case (no change) scenario had a mean LOS of 292 minutes (95% confidence interval [CI], 291-293). In isolation, adding staffing, changing staff roles, and varying shift times did not affect overall patient LOS. Specifically, adding 2 registration workers, history takers, and physicians resulted in a 23.8-minute (95% CI, 22.3-25.3) LOS decrease. However, when shift start times were coordinated with patient arrival patterns, potential mean LOS was decreased by 96 minutes (95% CI, 94-98), and with the simultaneous combination of staff roles (registration and history taking), there was an overall mean LOS reduction of 152 minutes (95% CI, 150-154). Resource-neutral interventions identified through discrete event simulation modeling have the potential to improve acute care throughput in this Ghanaian municipal hospital. Discrete event simulation offers another approach to identifying potentially effective interventions to improve patient flow in emergency and acute care in resource-limited settings. Copyright © 2014 Elsevier Inc. All rights reserved.

Fluid-structure Interaction Modeling of Aneurysmal Conditions with High and Normal Blood Pressures

NASA Astrophysics Data System (ADS)

Torii, Ryo; Oshima, Marie; Kobayashi, Toshio; Takagi, Kiyoshi; Tezduyar, Tayfun E.

2006-09-01

Hemodynamic factors like the wall shear stress play an important role in cardiovascular diseases. To investigate the influence of hemodynamic factors in blood vessels, the authors have developed a numerical fluid-structure interaction (FSI) analysis technique. The objective is to use numerical simulation as an effective tool to predict phenomena in a living human body. We applied the technique to a patient-specific arterial model, and with that we showed the effect of wall deformation on the WSS distribution. In this paper, we compute the interaction between the blood flow and the arterial wall for a patient-specific cerebral aneurysm with various hemodynamic conditions, such as hypertension. We particularly focus on the effects of hypertensive blood pressure on the interaction and the WSS, because hypertension is reported to be a risk factor in rupture of aneurysms. We also aim to show the possibility of FSI computations with hemodynamic conditions representing those risk factors in cardiovascular disease. The simulations show that the transient behavior of the interaction under hypertensive blood pressure is significantly different from the interaction under normal blood pressure. The transient behavior of the blood-flow velocity, and the resulting WSS and the mechanical stress in the aneurysmal wall, are significantly affected by hypertension. The results imply that hypertension affects the growth of an aneurysm and the damage in arterial tissues.

TU-H-207A-09: An Automated Technique for Estimating Patient-Specific Regional Imparted Energy and Dose From TCM CT Exams Across 13 Protocols

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanders, J; Tian, X; Segars, P

2016-06-15

Purpose: To develop an automated technique for estimating patient-specific regional imparted energy and dose from tube current modulated (TCM) computed tomography (CT) exams across a diverse set of head and body protocols. Methods: A library of 58 adult computational anthropomorphic extended cardiac-torso (XCAT) phantoms were used to model a patient population. A validated Monte Carlo program was used to simulate TCM CT exams on the entire library of phantoms for three head and 10 body protocols. The net imparted energy to the phantoms, normalized by dose length product (DLP), and the net tissue mass in each of the scan regionsmore » were computed. A knowledgebase containing relationships between normalized imparted energy and scanned mass was established. An automated computer algorithm was written to estimate the scanned mass from actual clinical CT exams. The scanned mass estimate, DLP of the exam, and knowledgebase were used to estimate the imparted energy to the patient. The algorithm was tested on 20 chest and 20 abdominopelvic TCM CT exams. Results: The normalized imparted energy increased with increasing kV for all protocols. However, the normalized imparted energy was relatively unaffected by the strength of the TCM. The average imparted energy was 681 ± 376 mJ for abdominopelvic exams and 274 ± 141 mJ for chest exams. Overall, the method was successful in providing patientspecific estimates of imparted energy for 98% of the cases tested. Conclusion: Imparted energy normalized by DLP increased with increasing tube potential. However, the strength of the TCM did not have a significant effect on the net amount of energy deposited to tissue. The automated program can be implemented into the clinical workflow to provide estimates of regional imparted energy and dose across a diverse set of clinical protocols.« less

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

Design optimization for accurate flow simulations in 3D printed vascular phantoms derived from computed tomography angiography

NASA Astrophysics Data System (ADS)

Sommer, Kelsey; Izzo, Rick L.; Shepard, Lauren; Podgorsak, Alexander R.; Rudin, Stephen; Siddiqui, Adnan H.; Wilson, Michael F.; Angel, Erin; Said, Zaid; Springer, Michael; Ionita, Ciprian N.

2017-03-01

3D printing has been used to create complex arterial phantoms to advance device testing and physiological condition evaluation. Stereolithographic (STL) files of patient-specific cardiovascular anatomy are acquired to build cardiac vasculature through advanced mesh-manipulation techniques. Management of distal branches in the arterial tree is important to make such phantoms practicable. We investigated methods to manage the distal arterial flow resistance and pressure thus creating physiologically and geometrically accurate phantoms that can be used for simulations of image-guided interventional procedures with new devices. Patient specific CT data were imported into a Vital Imaging workstation, segmented, and exported as STL files. Using a mesh-manipulation program (Meshmixer) we created flow models of the coronary tree. Distal arteries were connected to a compliance chamber. The phantom was then printed using a Stratasys Connex3 multimaterial printer: the vessel in TangoPlus and the fluid flow simulation chamber in Vero. The model was connected to a programmable pump and pressure sensors measured flow characteristics through the phantoms. Physiological flow simulations for patient-specific vasculature were done for six cardiac models (three different vasculatures comparing two new designs). For the coronary phantom we obtained physiologically relevant waves which oscillated between 80 and 120 mmHg and a flow rate of 125 ml/min, within the literature reported values. The pressure wave was similar with those acquired in human patients. Thus we demonstrated that 3D printed phantoms can be used not only to reproduce the correct patient anatomy for device testing in image-guided interventions, but also for physiological simulations. This has great potential to advance treatment assessment and diagnosis.

Novel Solution for Massive Glenoid Defects in Shoulder Arthroplasty: A Patient-Specific Glenoid Vault Reconstruction System.

PubMed

Dines, David M; Gulotta, Lawrence; Craig, Edward V; Dines, Joshua S

Complex glenoid deformities present the most difficult challenges in shoulder arthroplasty. These deformities may be caused by severe degenerative or congenital deformity, posttraumatic anatomy, tumor, or, in most cases, bone loss after glenoid failure in anatomical total shoulder arthroplasty. Methods of treating severe bone loss have included inlay and onlay bone-graft options with augmented fixation and, in severe cases, salvage hemiarthroplasty with limited goal expectations. Unfortunately, none of these methods has provided consistently satisfactory reproducible results. In fact, each has had high rates of failure and complications. Borrowing from hip and knee arthroplasty surgeons' experience in using CAD/CAM (computer-aided design/computer-aided manufacturing) patient-specific implants to fill significant bony defects, Dr. D. M. Dines developed a glenoid vault reconstruction system (VRS) in conjunction with the Comprehensive Shoulder Arthroplasty System (Zimmer Biomet) to treat severe glenoid bone deficiency. The VRS is patient-specific; each case involves making a preoperative plan based on 3-dimensional reconstruction of a 2-dimensional computed tomography scan. The patient-specific implant and instrumentation that are created are used to reconstruct the deformed glenoid in an anatomical position without the need for additional bone graft. In this article, we describe the implant and its indications, technical aspects of production, and surgical technique.

Patient-specific coronary territory maps

NASA Astrophysics Data System (ADS)

Beliveau, Pascale; Setser, Randolph; Cheriet, Farida; O'Donnell, Thomas

2007-03-01

It is standard practice for physicians to rely on empirical, population based models to define the relationship between regions of left ventricular (LV) myocardium and the coronary arteries which supply them with blood. Physicians use these models to infer the presence and location of disease within the coronary arteries based on the condition of the myocardium within their distribution (which can be established non-invasively using imaging techniques such as ultrasound or magnetic resonance imaging). However, coronary artery anatomy often varies from the assumed model distribution in the individual patient; thus, a non-invasive method to determine the correspondence between coronary artery anatomy and LV myocardium would have immediate clinical impact. This paper introduces an image-based rendering technique for visualizing maps of coronary distribution in a patient-specific approach. From an image volume derived from computed tomography (CT) images, a segmentation of the LV epicardial surface, as well as the paths of the coronary arteries, is obtained. These paths form seed points for a competitive region growing algorithm applied to the surface of the LV. A ray casting procedure in spherical coordinates from the center of the LV is then performed. The cast rays are mapped to a two-dimensional circular based surface forming our coronary distribution map. We applied our technique to a patient with known coronary artery disease and a qualitative evaluation by an expert in coronary cardiac anatomy showed promising results.

Systematic Review of Patient-Specific Surgical Simulation: Toward Advancing Medical Education.

PubMed

Ryu, Won Hyung A; Dharampal, Navjit; Mostafa, Ahmed E; Sharlin, Ehud; Kopp, Gail; Jacobs, William Bradley; Hurlbert, Robin John; Chan, Sonny; Sutherland, Garnette R

Simulation-based education has been shown to be an effective tool to teach foundational technical skills in various surgical specialties. However, most of the current simulations are limited to generic scenarios and do not allow continuation of the learning curve beyond basic technical skills to prepare for more advanced expertise, such as patient-specific surgical planning. The objective of this study was to evaluate the current medical literature with respect to the utilization and educational value of patient-specific simulations for surgical training. We performed a systematic review of the literature using Pubmed, Embase, and Scopus focusing on themes of simulation, patient-specific, surgical procedure, and education. The study included randomized controlled trials, cohort studies, and case-control studies published between 2005 and 2016. Two independent reviewers (W.H.R. and N.D) conducted the study appraisal, data abstraction, and quality assessment of the studies. The search identified 13 studies that met the inclusion criteria; 7 studies employed computer simulations and 6 studies used 3-dimensional (3D) synthetic models. A number of surgical specialties evaluated patient-specific simulation, including neurosurgery, vascular surgery, orthopedic surgery, and interventional radiology. However, most studies were small in size and primarily aimed at feasibility assessments and early validation. Early evidence has shown feasibility and utility of patient-specific simulation for surgical education. With further development of this technology, simulation-based education may be able to support training of higher-level competencies outside the clinical settingto aid learners in their development of surgical skills. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Estimation of left ventricular blood flow parameters: clinical application of patient-specific CFD simulations from 4D echocardiography

NASA Astrophysics Data System (ADS)

Larsson, David; Spühler, Jeannette H.; Günyeli, Elif; Weinkauf, Tino; Hoffman, Johan; Colarieti-Tosti, Massimiliano; Winter, Reidar; Larsson, Matilda

2017-03-01

Echocardiography is the most commonly used image modality in cardiology, assessing several aspects of cardiac viability. The importance of cardiac hemodynamics and 4D blood flow motion has recently been highlighted, however such assessment is still difficult using routine echo-imaging. Instead, combining imaging with computational fluid dynamics (CFD)-simulations has proven valuable, but only a few models have been applied clinically. In the following, patient-specific CFD-simulations from transthoracic dobutamin stress echocardiography have been used to analyze the left ventricular 4D blood flow in three subjects: two with normal and one with reduced left ventricular function. At each stress level, 4D-images were acquired using a GE Vivid E9 (4VD, 1.7MHz/3.3MHz) and velocity fields simulated using a presented pathway involving endocardial segmentation, valve position identification, and solution of the incompressible Navier-Stokes equation. Flow components defined as direct flow, delayed ejection flow, retained inflow, and residual volume were calculated by particle tracing using 4th-order Runge-Kutta integration. Additionally, systolic and diastolic average velocity fields were generated. Results indicated no major changes in average velocity fields for any of the subjects. For the two subjects with normal left ventricular function, increased direct flow, decreased delayed ejection flow, constant retained inflow, and a considerable drop in residual volume was seen at increasing stress. Contrary, for the subject with reduced left ventricular function, the delayed ejection flow increased whilst the retained inflow decreased at increasing stress levels. This feasibility study represents one of the first clinical applications of an echo-based patient-specific CFD-model at elevated stress levels, and highlights the potential of using echo-based models to capture highly transient flow events, as well as the ability of using simulation tools to study clinically complex phenomena. With larger patient studies planned for the future, and with the possibility of adding more anatomical features into the model framework, the current work demonstrates the potential of patient-specific CFD-models as a tool for quantifying 4D blood flow in the heart.

Towards an interactive electromechanical model of the heart

PubMed Central

Talbot, Hugo; Marchesseau, Stéphanie; Duriez, Christian; Sermesant, Maxime; Cotin, Stéphane; Delingette, Hervé

2013-01-01

In this work, we develop an interactive framework for rehearsal of and training in cardiac catheter ablation, and for planning cardiac resynchronization therapy. To this end, an interactive and real-time electrophysiology model of the heart is developed to fit patient-specific data. The proposed interactive framework relies on two main contributions. First, an efficient implementation of cardiac electrophysiology is proposed, using the latest graphics processing unit computing techniques. Second, a mechanical simulation is then coupled to the electrophysiological signals to produce realistic motion of the heart. We demonstrate that pathological mechanical and electrophysiological behaviour can be simulated. PMID:24427533

Directly executable formal models of middleware for MANET and Cloud Networking and Computing

NASA Astrophysics Data System (ADS)

Pashchenko, D. V.; Sadeq Jaafar, Mustafa; Zinkin, S. A.; Trokoz, D. A.; Pashchenko, T. U.; Sinev, M. P.

2016-04-01

The article considers some “directly executable” formal models that are suitable for the specification of computing and networking in the cloud environment and other networks which are similar to wireless networks MANET. These models can be easily programmed and implemented on computer networks.

Diagnostic accuracy and image quality of cardiac dual-source computed tomography in patients with arrhythmia.

PubMed

Tsiflikas, Ilias; Drosch, Tanja; Brodoefel, Harald; Thomas, Christoph; Reimann, Anja; Till, Alexander; Nittka, Daniel; Kopp, Andreas F; Schroeder, Stephen; Heuschmid, Martin; Burgstahler, Christof

2010-08-06

Cardiac multi-detector computed tomography (MDCT) permits accurate visualization of high-grade coronary artery stenosis. However, in patients with heart rate irregularities, MDCT was found to have limitations. Thus, the aim of the present study was to evaluate the diagnostic accuracy of a new dual-source computed tomography (DSCT) scanner generation with 83 ms temporal resolution in patients without stable sinus rhythm. 44 patients (31 men, mean age 67.5+/-9.2 years) without stable sinus rhythm and scheduled for invasive coronary angiography (ICA) because of suspected (n=17) or known coronary artery disease (CAD, n=27) were included in this study. All patients were examined with DSCT (Somatom Definition, Siemens). Besides assessment of total calcium score, all coronary segments were analyzed with regard to the presence of significant coronary artery lesions (>50%). The findings were compared to ICA in a blinded fashion. During CT examination, heart rhythm was as follows: 25 patients (57%) atrial fibrillation, 7 patients (16%) ventricular extrasystoles (two of them with atrial fibrillation), 4 patients (9%) supraventricular extrasystoles, 10 patients (23%) sinus arrhythmia (heart rate variability>10 bpm). Mean heart rate was 69+/-14 bpm, median 65 bpm. Mean Agatston score equivalent (ASE) was 762, ranging from 0 to 4949.7 ASE. Prevalence of CAD was 68% (30/44). 155 segments (27%) showed "step-ladder" artifacts and 28 segments (5%) could not be visualized by DSCT. Only 70 segments (12%) were completely imaged without any artifacts. Based on a coronary segment model, sensitivity was 73%, specificity 91%, positive predictive value 63%, and negative predictive value 94% for the detection of significant lesions (>or=50% diameter stenosis). Overall accuracy was 88%. In patients with heart rate irregularities, including patients with atrial fibrillation and a high prevalence of coronary artery disease, the diagnostic yield of dual-source computed tomography is still hampered due to a high number of segments with "step-ladder" artifacts. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Development of a method for fabricating polypropylene non-articulated dorsiflexion assist ankle foot orthoses with predetermined stiffness.

PubMed

Ramsey, Jason Allan

2011-03-01

A non-articulated plantarflexion resist ankle foot orthosis (AFO), commonly known as a posterior leaf spring AFO, is indicated for patients with motor impairment to the dorsiflexors. The AFO is often custom molded to a patient's lower limb anatomy and fabricated from polypropylene. There are no established guidelines for fabricating this type of AFO with predetermined stiffness of the ankle region for normal walking speeds. Therefore an AFO may not meet the biomechanical needs of the patient. Quantify the biomechanical ankle stiffness requirement for an individual with complete dorsiflexor impairment and develop a method for fabricating an AFO with ankle stiffness to meet that requirement. Experimental, bench research. The literature on sagittal biomechanics of non-pathological adults was reviewed to derive the stiffness of the ankle during loading response. Computer models of 144 AFOs were created with geometric variations to account for differences in human anthropometrics. Computer-based finite element analysis was employed to determine the stiffness and safety factor of the models. Stiffness of the AFOs ranged from 0.04 to 1.8 Nm/deg. This ample range is expected to account for the stiffness required for most adults with complete dorsiflexor impairment. At 5° deflection the factor of safety (ratio of strength to stress) ranged from 2.8 to 9.1. A computer program was generated that computes AFO stiffness from user-input variables of AFO geometry. The stiffness is compared to a theoretically appropriate stiffness based on the patient mass. The geometric variables can be modified until there is a close match, resulting in AFO design specification that is appropriate for the patient. Through validation on human subjects, this method may benefit patient outcomes in clinical practice by avoiding the current uncertainty surrounding AFO performance and reducing the labor and time involved in rectifying a custom AFO post-fabrication. This method provides an avenue for improving patient outcomes by avoiding the current uncertainty surrounding non-articulated plantarflexion resist ankle foot orthosis performance. The ability to quantify the biomechanical ankle stiffness requirement for an individual with complete dorsiflexor impairment provides insight into how other AFO types should be designed as well.

Left ventricular fluid mechanics: the long way from theoretical models to clinical applications.

PubMed

Pedrizzetti, Gianni; Domenichini, Federico

2015-01-01

The flow inside the left ventricle is characterized by the formation of vortices that smoothly accompany blood from the mitral inlet to the aortic outlet. Computational fluid dynamics permitted to shed some light on the fundamental processes involved with vortex motion. More recently, patient-specific numerical simulations are becoming an increasingly feasible tool that can be integrated with the developing imaging technologies. The existing computational methods are reviewed in the perspective of their potential role as a novel aid for advanced clinical analysis. The current results obtained by simulation methods either alone or in combination with medical imaging are summarized. Open problems are highlighted and perspective clinical applications are discussed.

Computational Evaluation of Cochlear Implant Surgery Outcomes Accounting for Uncertainty and Parameter Variability.

PubMed

Mangado, Nerea; Pons-Prats, Jordi; Coma, Martí; Mistrík, Pavel; Piella, Gemma; Ceresa, Mario; González Ballester, Miguel Á

2018-01-01

Cochlear implantation (CI) is a complex surgical procedure that restores hearing in patients with severe deafness. The successful outcome of the implanted device relies on a group of factors, some of them unpredictable or difficult to control. Uncertainties on the electrode array position and the electrical properties of the bone make it difficult to accurately compute the current propagation delivered by the implant and the resulting neural activation. In this context, we use uncertainty quantification methods to explore how these uncertainties propagate through all the stages of CI computational simulations. To this end, we employ an automatic framework, encompassing from the finite element generation of CI models to the assessment of the neural response induced by the implant stimulation. To estimate the confidence intervals of the simulated neural response, we propose two approaches. First, we encode the variability of the cochlear morphology among the population through a statistical shape model. This allows us to generate a population of virtual patients using Monte Carlo sampling and to assign to each of them a set of parameter values according to a statistical distribution. The framework is implemented and parallelized in a High Throughput Computing environment that enables to maximize the available computing resources. Secondly, we perform a patient-specific study to evaluate the computed neural response to seek the optimal post-implantation stimulus levels. Considering a single cochlear morphology, the uncertainty in tissue electrical resistivity and surgical insertion parameters is propagated using the Probabilistic Collocation method, which reduces the number of samples to evaluate. Results show that bone resistivity has the highest influence on CI outcomes. In conjunction with the variability of the cochlear length, worst outcomes are obtained for small cochleae with high resistivity values. However, the effect of the surgical insertion length on the CI outcomes could not be clearly observed, since its impact may be concealed by the other considered parameters. Whereas the Monte Carlo approach implies a high computational cost, Probabilistic Collocation presents a suitable trade-off between precision and computational time. Results suggest that the proposed framework has a great potential to help in both surgical planning decisions and in the audiological setting process.

Scapular notching in reverse shoulder arthroplasty: validation of a computer impingement model.

PubMed

Roche, Christopher P; Marczuk, Yann; Wright, Thomas W; Flurin, Pierre-Henri; Grey, Sean G; Jones, Richard B; Routman, Howard D; Gilot, Gregory J; Zuckerman, Joseph D

2013-01-01

The purpose of this study is to validate a reverse shoulder computer impingement model and quantify the impact of implant position on scapular impingement by comparing it to that of a radiographic analysis of 256 patients who received the same prosthesis and were followed postoperatively for an average of 22.2 months. A geometric computer analysis quantified anterior and posterior scapular impingement as the humerus was internally and externally rotated at varying levels of abduction and adduction relative to a fixed scapula at defined glenoid implant positions. These impingement results were compared to radiographic study of 256 patients who were analyzed for notching, glenoid baseplate position, and glenosphere overhang. The computer model predicted no impingement at 0° humeral abduction in the scapular plane for the 38 mm, 42 mm, and 46 mm devices when the glenoid baseplate cage peg is positioned 18.6 mm, 20.4 mm, and 22.7 mm from the inferior glenoid rim (of the reamed glenoid) or when glenosphere overhang of 4.6 mm, 4.7 mm, and 4.5 mm was obtained with each size glenosphere, respectively. When compared to the radiographic analysis, the computer model correctly predicted impingement based upon glenoid base- plate position in 18 of 26 patients with scapular notching and based upon glenosphere overhang in 15 of 26 patients with scapular notching. Reverse shoulder implant positioning plays an important role in scapular notching. The results of this study demonstrate that the computer impingement model can effectively predict impingement based upon implant positioning in a majority of patients who developed scapular notching clinically. This computer analysis provides guidance to surgeons on implant positions that reduce scapular notching, a well-documented complication of reverse shoulder arthroplasty.

Prevalence of monosodium urate deposits in a population of rheumatoid arthritis patients with hyperuricemia.

PubMed

Petsch, Christina; Araujo, Elizabeth G; Englbrecht, Matthias; Bayat, Sara; Cavallaro, Alexander; Hueber, Axel J; Lell, Michael; Schett, Georg; Manger, Bernhard; Rech, Juergen

2016-06-01

To investigate the prevalence of monosodium urate (MSU) crystal deposits, indicative for gout, in a population of rheumatoid arthritis (RA) patients with concomitant hyperuricemia and to analyze the clinical and disease-specific characteristics of RA patients who exhibit MSU crystal deposits. Overall, 100 consecutive patients with the diagnosis of RA and a serum urate level above 6mg/dl underwent dual energy computed tomography (DECT) of both feet and hands to search for MSU crystals in a prospective study between October 2011 and July 2013. Presence and extent of MSU crystal deposits on DECT was assessed by automated volume measurement. Demographic and disease-specific characteristics were recorded and included into two logistic regression models to test for the factors associated with MSU crystal deposits in RA. Hyperuricemic RA patients were mostly male (55%), over 60 years of age (63 ± 11 years), had established disease (8.7 ± 10.5 years) and a mean disease activity score 28 (DAS 28) of 3.2. In total, 20 out of 100 patients displayed MSU crystal deposits in DECT. Interestingly, the majority (70%) of the RA patients positive for MSU crystal deposits were seronegative RA patients. Hence, every third seronegative RA patient had MSU crystal deposits. According to logistic regression model analysis, seronegative status correlated positively with presence of urate deposits (p = 0.019). These data show that a considerable number of RA patients display periarticular MSU crystal deposits. Seronegative patients were shown to be predominantly affected with every third patient being positive for urate deposits. Copyright © 2016 Elsevier Inc. All rights reserved.

Single-scan patient-specific scatter correction in computed tomography using peripheral detection of scatter and compressed sensing scatter retrieval

PubMed Central

Meng, Bowen; Lee, Ho; Xing, Lei; Fahimian, Benjamin P.

2013-01-01

Purpose: X-ray scatter results in a significant degradation of image quality in computed tomography (CT), representing a major limitation in cone-beam CT (CBCT) and large field-of-view diagnostic scanners. In this work, a novel scatter estimation and correction technique is proposed that utilizes peripheral detection of scatter during the patient scan to simultaneously acquire image and patient-specific scatter information in a single scan, and in conjunction with a proposed compressed sensing scatter recovery technique to reconstruct and correct for the patient-specific scatter in the projection space. Methods: The method consists of the detection of patient scatter at the edges of the field of view (FOV) followed by measurement based compressed sensing recovery of the scatter through-out the projection space. In the prototype implementation, the kV x-ray source of the Varian TrueBeam OBI system was blocked at the edges of the projection FOV, and the image detector in the corresponding blocked region was used for scatter detection. The design enables image data acquisition of the projection data on the unblocked central region of and scatter data at the blocked boundary regions. For the initial scatter estimation on the central FOV, a prior consisting of a hybrid scatter model that combines the scatter interpolation method and scatter convolution model is estimated using the acquired scatter distribution on boundary region. With the hybrid scatter estimation model, compressed sensing optimization is performed to generate the scatter map by penalizing the L1 norm of the discrete cosine transform of scatter signal. The estimated scatter is subtracted from the projection data by soft-tuning, and the scatter-corrected CBCT volume is obtained by the conventional Feldkamp-Davis-Kress algorithm. Experimental studies using image quality and anthropomorphic phantoms on a Varian TrueBeam system were carried out to evaluate the performance of the proposed scheme. Results: The scatter shading artifacts were markedly suppressed in the reconstructed images using the proposed method. On the Catphan©504 phantom, the proposed method reduced the error of CT number to 13 Hounsfield units, 10% of that without scatter correction, and increased the image contrast by a factor of 2 in high-contrast regions. On the anthropomorphic phantom, the spatial nonuniformity decreased from 10.8% to 6.8% after correction. Conclusions: A novel scatter correction method, enabling unobstructed acquisition of the high frequency image data and concurrent detection of the patient-specific low frequency scatter data at the edges of the FOV, is proposed and validated in this work. Relative to blocker based techniques, rather than obstructing the central portion of the FOV which degrades and limits the image reconstruction, compressed sensing is used to solve for the scatter from detection of scatter at the periphery of the FOV, enabling for the highest quality reconstruction in the central region and robust patient-specific scatter correction. PMID:23298098

Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases.

PubMed

Wooden, Benjamin; Goossens, Nicolas; Hoshida, Yujin; Friedman, Scott L

2017-01-01

Technologies such as genome sequencing, gene expression profiling, proteomic and metabolomic analyses, electronic medical records, and patient-reported health information have produced large amounts of data from various populations, cell types, and disorders (big data). However, these data must be integrated and analyzed if they are to produce models or concepts about physiological function or mechanisms of pathogenesis. Many of these data are available to the public, allowing researchers anywhere to search for markers of specific biological processes or therapeutic targets for specific diseases or patient types. We review recent advances in the fields of computational and systems biology and highlight opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology to complement traditional means of diagnostic and therapeutic discovery. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Skin dose mapping for fluoroscopically guided interventions.

PubMed

Johnson, Perry B; Borrego, David; Balter, Stephen; Johnson, Kevin; Siragusa, Daniel; Bolch, Wesley E

2011-10-01

To introduce a new skin dose mapping software system for interventional fluoroscopy dose assessment and to analyze the benefits and limitations of patient-phantom matching. In this study, a new software system was developed for visualizing patient skin dose during interventional fluoroscopy procedures. The system works by translating the reference point air kerma to the location of the patient's skin, which is represented by a computational model. In order to orient the model with the x-ray source, geometric parameters found within the radiation dose structured report (RDSR) are used along with a limited number of in-clinic measurements. The output of the system is a visual indication of skin dose mapped onto an anthropomorphic model at a resolution of 5 mm. In order to determine if patient-dependent and patient-sculpted models increase accuracy, peak skin dose was calculated for each of 26 patient-specific models and compared with doses calculated using an elliptical stylized model, a reference hybrid model, a matched patient-dependent model and one patient-sculpted model. Results were analyzed in terms of a percent difference using the doses calculated using the patient-specific model as the true standard. Anthropometric matching, including the use of both patient-dependent and patient-sculpted phantoms, was shown most beneficial for left lateral and anterior-posterior projections. In these cases, the percent difference using a reference model was between 8 and 20%, using a patient-dependent model between 7 and 15%, and using a patient-sculpted model between 3 and 7%. Under the table tube configurations produced errors less than 5% in most situations due to the flattening affects of the table and pad, and the fact that table height is the main determination of source-to-skin distance for these configurations. In addition to these results, several skin dose maps were produced and a prototype display system was placed on the in-clinic monitor of an interventional fluoroscopy system. The skin dose mapping program developed in this work represents a new tool that, as the RDSR becomes available through automated export or real-time streaming, can provide the interventional physician information needed to modify behavior when clinically appropriate. The program is nonproprietary and transferable, and also functions independent to the software systems already installed on the control room workstation. The next step will be clinical implementation where the workflow will be optimized along with further analysis of real-time capabilities.

Computerized patient identification for the EMBRACA clinical trial using real-time data from the PRAEGNANT network for metastatic breast cancer patients.

PubMed

Hein, Alexander; Gass, Paul; Walter, Christina Barbara; Taran, Florin-Andrei; Hartkopf, Andreas; Overkamp, Friedrich; Kolberg, Hans-Christian; Hadji, Peyman; Tesch, Hans; Ettl, Johannes; Wuerstlein, Rachel; Lounsbury, Debra; Lux, Michael P; Lüftner, Diana; Wallwiener, Markus; Müller, Volkmar; Belleville, Erik; Janni, Wolfgang; Fehm, Tanja N; Wallwiener, Diethelm; Ganslandt, Thomas; Ruebner, Matthias; Beckmann, Matthias W; Schneeweiss, Andreas; Fasching, Peter A; Brucker, Sara Y

2016-07-01

As breast cancer is a diverse disease, clinical trials are becoming increasingly diversified and are consequently being conducted in very small subgroups of patients, making study recruitment increasingly difficult. The aim of this study was to assess the use of data from a remote data entry system that serves a large national registry for metastatic breast cancer. The PRAEGNANT network is a real-time registry with an integrated biomaterials bank that was designed as a scientific study and as a means of identifying patients who are eligible for clinical trials, based on clinical and molecular information. Here, we report on the automated use of the clinical data documented to identify patients for a clinical trial (EMBRACA) for patients with metastatic breast cancer. The patients' charts were assessed by two independent physicians involved in the clinical trial and also by a computer program that tested patients for eligibility using a structured query language script. In all, 326 patients from two study sites in the PRAEGNANT network were included in the analysis. Using expert assessment, 120 of the 326 patients (37 %) appeared to be eligible for inclusion in the EMBRACA study; with the computer algorithm assessment, a total of 129 appeared to be eligible. The sensitivity of the computer algorithm was 0.87 and its specificity was 0.88. Using computer-based identification of patients for clinical trials appears feasible. With the instrument's high specificity, its application in a large cohort of patients appears to be feasible, and the workload for reassessing the patients is limited.

Paradigm of pretest risk stratification before coronary computed tomography.

PubMed

Jensen, Jesper Møller; Ovrehus, Kristian A; Nielsen, Lene H; Jensen, Jesper K; Larsen, Henrik M; Nørgaard, Bjarne L

2009-01-01

The optimal method of determining the pretest risk of coronary artery disease as a patient selection tool before coronary multidetector computed tomography (MDCT) is unknown. We investigated the ability of 3 different clinical risk scores to predict the outcome of coronary MDCT. This was a retrospective study of 551 patients consecutively referred for coronary MDCT on a suspicion of coronary artery disease. Diamond-Forrester, Duke, and Morise risk models were used to predict coronary artery stenosis (>50%) as assessed by coronary MDCT. The models were compared by receiver operating characteristic analysis. The distribution of low-, intermediate-, and high-risk persons, respectively, was established and compared for each of the 3 risk models. Overall, all risk prediction models performed equally well. However, the Duke risk model classified the low-risk patients more correctly than did the other models (P < 0.01). In patients without coronary artery calcification (CAC), the predictive value of the Duke risk model was superior to the other risk models (P < 0.05). Currently available risk prediction models seem to perform better in patients without CAC. Between the risk prediction models, there was a significant discrepancy in the distribution of patients at low, intermediate, or high risk (P < 0.01). The 3 risk prediction models perform equally well, although the Duke risk score may have advantages in subsets of patients. The choice of risk prediction model affects the referral pattern to MDCT. Copyright (c) 2009 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Craniofacial Reconstruction by a Cost-Efficient Template-Based Process Using 3D Printing

PubMed Central

Beiglboeck, Fabian; Honigmann, Philipp; Jaquiéry, Claude; Thieringer, Florian

2017-01-01

Summary: Craniofacial defects often result in aesthetic and functional deficits, which affect the patient’s psyche and wellbeing. Patient-specific implants remain the optimal solution, but their use is limited or impractical due to their high costs. This article describes a fast and cost-efficient workflow of in-house manufactured patient-specific implants for craniofacial reconstruction and cranioplasty. As a proof of concept, we present a case of reconstruction of a craniofacial defect with involvement of the supraorbital rim. The following hybrid manufacturing process combines additive manufacturing with silicone molding and an intraoperative, manual fabrication process. A computer-aided design template is 3D printed from thermoplastics by a fused deposition modeling 3D printer and then silicone molded manually. After sterilization of the patient-specific mold, it is used intraoperatively to produce an implant from polymethylmethacrylate. Due to the combination of these 2 straightforward processes, the procedure can be kept very simple, and no advanced equipment is needed, resulting in minimal financial expenses. The whole fabrication of the mold is performed within approximately 2 hours depending on the template’s size and volume. This reliable technique is easy to adopt and suitable for every health facility, especially those with limited financial resources in less privileged countries, enabling many more patients to profit from patient-specific treatment. PMID:29263977

Ontological approach for safe and effective polypharmacy prescription

PubMed Central

Grando, Adela; Farrish, Susan; Boyd, Cynthia; Boxwala, Aziz

2012-01-01

The intake of multiple medications in patients with various medical conditions challenges the delivery of medical care. Initial empirical studies and pilot implementations seem to indicate that generic safe and effective multi-drug prescription principles could be defined and reused to reduce adverse drug events and to support compliance with medical guidelines and drug formularies. Given that ontologies are known to provide well-principled, sharable, setting-independent and machine-interpretable declarative specification frameworks for modeling and reasoning on biomedical problems, we explore here their use in the context of multi-drug prescription. We propose an ontology for modeling drug-related knowledge and a repository of safe and effective generic prescription principles. To test the usability and the level of granularity of the developed ontology-based specification models and heuristic we implemented a tool that computes the complexity of multi-drug treatments, and a decision aid to check the safeness and effectiveness of prescribed multi-drug treatments. PMID:23304299

Formal specification and verification of a fault-masking and transient-recovery model for digital flight-control systems

NASA Technical Reports Server (NTRS)

Rushby, John

1991-01-01

The formal specification and mechanically checked verification for a model of fault-masking and transient-recovery among the replicated computers of digital flight-control systems are presented. The verification establishes, subject to certain carefully stated assumptions, that faults among the component computers are masked so that commands sent to the actuators are the same as those that would be sent by a single computer that suffers no failures.

Reliability model derivation of a fault-tolerant, dual, spare-switching, digital computer system

NASA Technical Reports Server (NTRS)

1974-01-01

A computer based reliability projection aid, tailored specifically for application in the design of fault-tolerant computer systems, is described. Its more pronounced characteristics include the facility for modeling systems with two distinct operational modes, measuring the effect of both permanent and transient faults, and calculating conditional system coverage factors. The underlying conceptual principles, mathematical models, and computer program implementation are presented.

Cognitive Model Exploration and Optimization: A New Challenge for Computational Science

DTIC Science & Technology

2010-01-01

Introduction Research in cognitive science often involves the generation and analysis of computational cognitive models to explain various...HPC) clusters and volunteer computing for large-scale computational resources. The majority of applications on the Department of Defense HPC... clusters focus on solving partial differential equations (Post, 2009). These tend to be lean, fast models with little noise. While we lack specific

Designing a training tool for imaging mental models

NASA Technical Reports Server (NTRS)

Dede, Christopher J.; Jayaram, Geetha

1990-01-01

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network.

3D segmentation of annulus fibrosus and nucleus pulposus from T2-weighted magnetic resonance images

NASA Astrophysics Data System (ADS)

Castro-Mateos, Isaac; Pozo, Jose M.; Eltes, Peter E.; Del Rio, Luis; Lazary, Aron; Frangi, Alejandro F.

2014-12-01

Computational medicine aims at employing personalised computational models in diagnosis and treatment planning. The use of such models to help physicians in finding the best treatment for low back pain (LBP) is becoming popular. One of the challenges of creating such models is to derive patient-specific anatomical and tissue models of the lumbar intervertebral discs (IVDs), as a prior step. This article presents a segmentation scheme that obtains accurate results irrespective of the degree of IVD degeneration, including pathological discs with protrusion or herniation. The segmentation algorithm, employing a novel feature selector, iteratively deforms an initial shape, which is projected into a statistical shape model space at first and then, into a B-Spline space to improve accuracy. The method was tested on a MR dataset of 59 patients suffering from LBP. The images follow a standard T2-weighted protocol in coronal and sagittal acquisitions. These two image volumes were fused in order to overcome large inter-slice spacing. The agreement between expert-delineated structures, used here as gold-standard, and our automatic segmentation was evaluated using Dice Similarity Index and surface-to-surface distances, obtaining a mean error of 0.68 mm in the annulus segmentation and 1.88 mm in the nucleus, which are the best results with respect to the image resolution in the current literature.

Consistency, precision, and accuracy of optical and electromagnetic shape-capturing systems for digital measurement of residual-limb anthropometrics of persons with transtibial amputation.

PubMed

Geil, Mark D

2007-01-01

Computer-aided design (CAD) and computer-aided manufacturing systems have been adapted for specific use in prosthetics, providing practitioners with a means to digitally capture the shape of a patient's limb, modify the socket model using software, and automatically manufacture either a positive model to be used in the fabrication of a socket or the socket itself. The digital shape captured is a three-dimensional (3-D) model from which standard anthropometric measures can be easily obtained. This study recorded six common anthropometric dimensions from CAD shape files of three foam positive models of the residual limbs of persons with transtibial amputations. Two systems were used to obtain 3-D models of the residual limb, a noncontact optical system and a contact-based electromagnetic field system, and both experienced practitioners and prosthetics students conducted measurements. Measurements were consistent; the mean range (difference of maximum and minimum) across all measurements was 0.96 cm. Both systems provided similar results, and both groups used the systems consistently. Students were slightly more consistent than practitioners but not to a clinically significant degree. Results also compared favorably with traditional measurement, with differences versus hand measurements about 5 mm. These results suggest the routine use of digital shape capture for collection of patient volume information.

A biomechanical approach for in vivo diaphragm muscle motion prediction during normal respiration

NASA Astrophysics Data System (ADS)

Coelho, Brett; Karami, Elham; Haddad, Seyyed M. H.; Seify, Behzad; Samani, Abbas

2017-03-01

Lung cancer is one of the leading causes of cancer death in men and women. External Beam Radiation Therapy (EBRT) is a commonly used primary treatment for the condition. A major challenge with such treatments is the delivery of sufficient radiation dose to the lung tumor while ensuring that surrounding healthy lung parenchyma receives only minimal dose. This can be achieved by coupling EBRT with respiratory computer models which can predict the tumour location as a function of phase during the breathing cycle1. The diaphragm muscle contraction is mainly responsible for a large portion of the lung tumor motion during normal breathing, especially when tumours are in the lower lobes, therefore the importance of accurately modelling the diaphragm is paramount in lung tumour motion prediction. The goal of this research is to develop a biomechanical model of the diaphragm, including its active and passive response, using detailed geometric, biomechanical and anatomical information that mimics the diaphragmatic behaviour in a patient specific manner. For this purpose, a Finite Element Model (FEM) of the diaphragm was developed in order to predict the in vivo motion of the diaphragm, paving the way for computer assisted lung cancer tumor tracking in EBRT. Preliminary results obtained from the proposed model are promising and they indicate that it can be used as a plausible tool for effective lung cancer EBRT to improve patient care.

E-pharmacovigilance: development and implementation of a computable knowledge base to identify adverse drug reactions.

PubMed

Neubert, Antje; Dormann, Harald; Prokosch, Hans-Ulrich; Bürkle, Thomas; Rascher, Wolfgang; Sojer, Reinhold; Brune, Kay; Criegee-Rieck, Manfred

2013-09-01

Computer-assisted signal generation is an important issue for the prevention of adverse drug reactions (ADRs). However, due to poor standardization of patients' medical data and a lack of computable medical drug knowledge the specificity of computerized decision support systems for early ADR detection is too low and thus those systems are not yet implemented in daily clinical practice. We report on a method to formalize knowledge about ADRs based on the Summary of Product Characteristics (SmPCs) and linking them with structured patient data to generate safety signals automatically and with high sensitivity and specificity. A computable ADR knowledge base (ADR-KB) that inherently contains standardized concepts for ADRs (WHO-ART), drugs (ATC) and laboratory test results (LOINC) was built. The system was evaluated in study populations of paediatric and internal medicine inpatients. A total of 262 different ADR concepts related to laboratory findings were linked to 212 LOINC terms. The ADR knowledge base was retrospectively applied to a study population of 970 admissions (474 internal and 496 paediatric patients), who underwent intensive ADR surveillance. The specificity increased from 7% without ADR-KB up to 73% in internal patients and from 19.6% up to 91% in paediatric inpatients, respectively. This study shows that contextual linkage of patients' medication data with laboratory test results is a useful and reasonable instrument for computer-assisted ADR detection and a valuable step towards a systematic drug safety process. The system enables automated detection of ADRs during clinical practice with a quality close to intensive chart review. © 2013 The Authors. British Journal of Clinical Pharmacology © 2013 The British Pharmacological Society.

Reproducibility of risk figures in 2nd-trimester maternal serum screening for down syndrome: comparison of 2 laboratories.

PubMed

Benn, Peter A; Makowski, Gregory S; Egan, James F X; Wright, Dave

2006-11-01

Analytical error affects 2nd-trimester maternal serum screening for Down syndrome risk estimation. We analyzed the between-laboratory reproducibility of risk estimates from 2 laboratories. Laboratory 1 used Bayer ACS180 immunoassays for alpha-fetoprotein (AFP) and human chorionic gonadotropin (hCG), Diagnostic Systems Laboratories (DSL) RIA for unconjugated estriol (uE3), and DSL enzyme immunoassay for inhibin-A (INH-A). Laboratory 2 used Beckman immunoassays for AFP, hCG, and uE3, and DSL enzyme immunoassay for INH-A. Analyte medians were separately established for each laboratory. We used the same computational algorithm for all risk calculations, and we used Monte Carlo methods for computer modeling. For 462 samples tested, risk figures from the 2 laboratories differed >2-fold for 44.7%, >5-fold for 7.1%, and >10-fold for 1.7%. Between-laboratory differences in analytes were greatest for uE3 and INH-A. The screen-positive rates were 9.3% for laboratory 1 and 11.5% for laboratory 2, with a significant difference in the patients identified as screen-positive vs screen-negative (McNemar test, P<0.001). Computer modeling confirmed the large between-laboratory risk differences. Differences in performance of assays and laboratory procedures can have a large effect on patient-specific risks. Screening laboratories should minimize test imprecision and ensure that each assay performs in a manner similar to that assumed in the risk computational algorithm.

A comparison of bivariate, multivariate random-effects, and Poisson correlated gamma-frailty models to meta-analyze individual patient data of ordinal scale diagnostic tests.

PubMed

Simoneau, Gabrielle; Levis, Brooke; Cuijpers, Pim; Ioannidis, John P A; Patten, Scott B; Shrier, Ian; Bombardier, Charles H; de Lima Osório, Flavia; Fann, Jesse R; Gjerdingen, Dwenda; Lamers, Femke; Lotrakul, Manote; Löwe, Bernd; Shaaban, Juwita; Stafford, Lesley; van Weert, Henk C P M; Whooley, Mary A; Wittkampf, Karin A; Yeung, Albert S; Thombs, Brett D; Benedetti, Andrea

2017-11-01

Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Impact of isotropic constitutive descriptions on the predicted peak wall stress in abdominal aortic aneurysms.

PubMed

Man, V; Polzer, S; Gasser, T C; Novotny, T; Bursa, J

2018-03-01

Biomechanics-based assessment of Abdominal Aortic Aneurysm (AAA) rupture risk has gained considerable scientific and clinical momentum. However, computation of peak wall stress (PWS) using state-of-the-art finite element models is time demanding. This study investigates which features of the constitutive description of AAA wall are decisive for achieving acceptable stress predictions in it. Influence of five different isotropic constitutive descriptions of AAA wall is tested; models reflect realistic non-linear, artificially stiff non-linear, or artificially stiff pseudo-linear constitutive descriptions of AAA wall. Influence of the AAA wall model is tested on idealized (n=4) and patient-specific (n=16) AAA geometries. Wall stress computations consider a (hypothetical) load-free configuration and include residual stresses homogenizing the stresses across the wall. Wall stress differences amongst the different descriptions were statistically analyzed. When the qualitatively similar non-linear response of the AAA wall with low initial stiffness and subsequent strain stiffening was taken into consideration, wall stress (and PWS) predictions did not change significantly. Keeping this non-linear feature when using an artificially stiff wall can save up to 30% of the computational time, without significant change in PWS. In contrast, a stiff pseudo-linear elastic model may underestimate the PWS and is not reliable for AAA wall stress computations. Copyright © 2018 IPEM. Published by Elsevier Ltd. All rights reserved.

Computational Fluid Dynamics Modeling of the Human Pulmonary Arteries with Experimental Validation.

PubMed

Bordones, Alifer D; Leroux, Matthew; Kheyfets, Vitaly O; Wu, Yu-An; Chen, Chia-Yuan; Finol, Ender A

2018-05-21

Pulmonary hypertension (PH) is a chronic progressive disease characterized by elevated pulmonary arterial pressure, caused by an increase in pulmonary arterial impedance. Computational fluid dynamics (CFD) can be used to identify metrics representative of the stage of PH disease. However, experimental validation of CFD models is often not pursued due to the geometric complexity of the model or uncertainties in the reproduction of the required flow conditions. The goal of this work is to validate experimentally a CFD model of a pulmonary artery phantom using a particle image velocimetry (PIV) technique. Rapid prototyping was used for the construction of the patient-specific pulmonary geometry, derived from chest computed tomography angiography images. CFD simulations were performed with the pulmonary model with a Reynolds number matching those of the experiments. Flow rates, the velocity field, and shear stress distributions obtained with the CFD simulations were compared to their counterparts from the PIV flow visualization experiments. Computationally predicted flow rates were within 1% of the experimental measurements for three of the four branches of the CFD model. The mean velocities in four transversal planes of study were within 5.9 to 13.1% of the experimental mean velocities. Shear stresses were qualitatively similar between the two methods with some discrepancies in the regions of high velocity gradients. The fluid flow differences between the CFD model and the PIV phantom are attributed to experimental inaccuracies and the relative compliance of the phantom. This comparative analysis yielded valuable information on the accuracy of CFD predicted hemodynamics in pulmonary circulation models.

Computer navigation for total knee arthroplasty achieves better postoperative alignment compared to conventional and patient-specific instrumentation in a low-volume setting.

PubMed

Suero, Eduardo M; Lueke, Ulrich; Stuebig, Timo; Hawi, Nael; Krettek, Christian; Liodakis, Emmanouil

2018-04-25

Procedure volume is an important determinant of total knee arthroplasty (TKA) outcomes. We aimed to determine whether computer navigation or patient-specific instrumentation (PSI) would improve postoperative alignment in a low-volume setting. PSI for TKA achieves better limb and implant alignment compared to conventional TKA and to computer navigated TKA. This is a retrospective cohort study of 385 primary TKAs (Women=59%. Mean age=67years. Mean BMI=30.1kg/m 2 ), which were performed using conventional instrumentation (n=117; 30%), computer navigation (n=209; 54%), or patient-specific instrumentation (n=59; 15%) in a low-volume center (<50 TKAs/year). The risk of postoperative leg and implant mechanical alignment outliers in the coronal plane (>3° from neutral), average alignment and operation time were assessed. The risk of postoperative mechanical alignment outliers (>3°) was reduced by 89% in the navigated group (4% outliers) compared to the conventional group (35%) (RR=0.11; p<0.0001). No significant improvement was observed in the PSI group (27%) (RR=0.91; p=0.772). The risk of postoperative femoral component coronal alignment outliers was reduced by 63% in the navigated group (11%) compared to the conventional group (31%) (RR=0.37; p=0.018). No significant reduction in outliers was observed in the PSI group (32%) (RR=1.08; p=0.816). There was a reduction in the risk of tibial component coronal malalignment of 66% in the navigated group (5%) compared to the conventional group (13%) (RR=0.33; p=0.070). There was a two-fold increase in the risk of tibial component alignment outliers in the PSI group (29%) (RR=1.94; p=0.110). Computer navigation improved postoperative alignment in TKA. No evidence of improved alignment was seen with patient-specific instrumentation. The routine use of patient-specific instrumentation in low-volume centers is not supported by the currently available data. Retrospective cohort study. Level IV. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Assessment of students' ability to incorporate a computer into increasingly complex simulated patient encounters.

PubMed

Ray, Sarah; Valdovinos, Katie

Pharmacy students should be exposed to and offered opportunities to practice the skill of incorporating a computer into a patient interview in the didactic setting. Faculty sought to improve retention of student ability to incorporate computers into their patient-pharmacist communication. Students were required to utilize a computer to document clinical information gathered during a simulated patient encounter (SPE). Students utilized electronic worksheets and were evaluated by instructors on their ability to effectively incorporate a computer into a SPE using a rubric. Students received specific instruction on effective computer use during patient encounters. Students were then re-evaluated by an instructor during subsequent SPEs of increasing complexity using standardized rubrics blinded from the students. Pre-instruction, 45% of students effectively incorporated a computer into a SPE. After receiving instruction, 67% of students were effective in their use of a computer during a SPE of performing a pharmaceutical care assessment for a patient with chronic obstructive pulmonary disease (COPD) (p < 0.05 compared to pre-instruction), and 58% of students were effective in their use of a computer during a SPE of retrieving a medication list and social history from a simulated alcohol-impaired patient (p = 0.087 compared to pre-instruction). Instruction can improve pharmacy students' ability to incorporate a computer into SPEs, a critical skill in building and maintaining rapport with patients and improving efficiency of patient visits. Complex encounters may affect students' ability to utilize a computer appropriately. Students may benefit from repeated practice with this skill, especially with SPEs of increasing complexity. Copyright © 2016 Elsevier Inc. All rights reserved.

Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma.

PubMed

Tadeo, Irene; Piqueras, Marta; Montaner, David; Villamón, Eva; Berbegall, Ana P; Cañete, Adela; Navarro, Samuel; Noguera, Rosa

2014-02-01

Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient's organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators. A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma. New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies. The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma.

Preliminary application of computer-assisted patient-specific acetabular navigational template for total hip arthroplasty in adult single development dysplasia of the hip.

PubMed

Zhang, Yuan Z; Chen, Bin; Lu, Sheng; Yang, Yong; Zhao, Jian M; Liu, Rui; Li, Yan B; Pei, Guo X

2011-12-01

The considerable variation in anatomical abnormalities of hip joints associated with different types of developmental dysplasia of hip (DDH) makes reconstruction in total hip arthroplasty (THA) difficult. It is desirable to create patient-specific designs for THA procedures. In the cases of adult single DDH, an accuracy-improved method has been developed for acetabular cup prosthesis implantation of hip arthroplasty. From October 2007 to November 2008, 22 patients with single DDH (according to the Crowe standard, all dysplasia hips were classified as type I) were scanned with spiral CT pre-operatively. These patients scheduled for THA were randomly assigned to undergo either conventional THA (control group, n = 11) or navigation template implantation (NT group, n = 11). In the NT group, three-dimensional (3D) CT pelvis image data were transferred to a computer workstation and 3D models of the hip were reconstructed using the Mimics software. The 3D models were then processed by the Imageware software. In brief, a template that best fitted the location and shape of the acetabular cup was 'reversely' built from the 3D model, the rotation centre of the pathological hip determined by mirroring that of the healthy site, and a guiding hole in the template was then designed. The navigational templates were manufactured using a rapid prototyping machine. These navigation templates guide acetabular component placement. Based on the predetermined abduction angle 45° and anteversion angle 18°, after 1 year follow-up, the NT group showed significantly smaller differences (1.6° ± 0.4°, 1.9° ± 1.1°) from the predetermined angles than those in the control group (5.8° ± 2.9°, 3.9° ± 2.5°) (P < 0.05). The template designs facilitated accurate placement of acetabular components in dysplasia of acetabulum. The hip's center of rotation in DDH could be established using computer-aided design, which provides a useful method for the accurate location of prosthesis with a low cost-performance ratio without excessive technical workload on the surgical team. Copyright © 2011 John Wiley & Sons, Ltd.

The Primary Care Computer Simulation: Optimal Primary Care Manager Empanelment.

DTIC Science & Technology

1997-05-01

explored in which a team consisted of two providers, two nurses, and a nurse aide . Each team had a specific exam room assigned to them. Additionally, a...team consisting of one provider, one nurse, and one nurse aide was simulated. The model also examined the effects of adding two exam rooms. The study...minutes. The optimal solution, which reduced patient time to below 90 minutes, was the mix of one provider, a nurse, and a nurse aide in which each

SU-F-T-114: A Novel Anatomically Predictive Extension Model of Computational Human Phantoms for Dose Reconstruction in Retrospective Epidemiological Studies of Second Cancer Risks in Radiotherapy Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuzmin, G; Lee, C; Lee, C

Purpose: Recent advances in cancer treatments have greatly increased the likelihood of post-treatment patient survival. Secondary malignancies, however, have become a growing concern. Epidemiological studies determining secondary effects in radiotherapy patients require assessment of organ-specific dose both inside and outside the treatment field. An essential input for Monte Carlo modeling of particle transport is radiological images showing full patient anatomy. However, in retrospective studies it is typical to only have partial anatomy from CT scans used during treatment planning. In this study, we developed a multi-step method to extend such limited patient anatomy to full body anatomy for estimating dosemore » to normal tissues located outside the CT scan coverage. Methods: The first step identified a phantom from a library of body size-dependent computational human phantoms by matching the height and weight of patients. Second, a Python algorithm matched the patient CT coverage location in relation to the whole body phantom. Third, an algorithm cut the whole body phantom and scaled them to match the size of the patient. Then, merged the two anatomies into one whole body. We entitled this new approach, Anatomically Predictive Extension (APE). Results: The APE method was examined by comparing the original chest-abdomen-pelvis CT images of the five patients with the APE phantoms developed from only the chest part of the CAP images and whole body phantoms. We achieved average percent differences of tissue volumes of 25.7%, 34.2%, 16.5%, 26.8%, and 31.6% with an average of 27% across all patients. Conclusion: Our APE method extends the limited CT patient anatomy to whole body anatomy by using image processing and computational human phantoms. Our ongoing work includes evaluating the accuracy of these APE phantoms by comparing normal tissue doses in the APE phantoms and doses calculated for the original full CAP images under generic radiotherapy simulations. This research was supported by the NIH Intramural Research Program.« less

Fluid-structure interaction including volumetric coupling with homogenised subdomains for modeling respiratory mechanics.

PubMed

Yoshihara, Lena; Roth, Christian J; Wall, Wolfgang A

2017-04-01

In this article, a novel approach is presented for combining standard fluid-structure interaction with additional volumetric constraints to model fluid flow into and from homogenised solid domains. The proposed algorithm is particularly interesting for investigations in the field of respiratory mechanics as it enables the mutual coupling of airflow in the conducting part and local tissue deformation in the respiratory part of the lung by means of a volume constraint. In combination with a classical monolithic fluid-structure interaction approach, a comprehensive model of the human lung can be established that will be useful to gain new insights into respiratory mechanics in health and disease. To illustrate the validity and versatility of the novel approach, three numerical examples including a patient-specific lung model are presented. The proposed algorithm proves its capability of computing clinically relevant airflow distribution and tissue strain data at a level of detail that is not yet achievable, neither with current imaging techniques nor with existing computational models. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Drawing Nomograms with R: applications to categorical outcome and survival data.

PubMed

Zhang, Zhongheng; Kattan, Michael W

2017-05-01

Outcome prediction is a major task in clinical medicine. The standard approach to this work is to collect a variety of predictors and build a model of appropriate type. The model is a mathematical equation that connects the outcome of interest with the predictors. A new patient with given clinical characteristics can be predicted for outcome with this model. However, the equation describing the relationship between predictors and outcome is often complex and the computation requires software for practical use. There is another method called nomogram which is a graphical calculating device allowing an approximate graphical computation of a mathematical function. In this article, we describe how to draw nomograms for various outcomes with nomogram() function. Binary outcome is fit by logistic regression model and the outcome of interest is the probability of the event of interest. Ordinal outcome variable is also discussed. Survival analysis can be fit with parametric model to fully describe the distributions of survival time. Statistics such as the median survival time, survival probability up to a specific time point are taken as the outcome of interest.