Key elements of optimal treatment decision-making for surgeons and older patients with colorectal or pancreatic cancer: A qualitative study.

PubMed

Geessink, Noralie H; Schoon, Yvonne; van Herk, Hanneke C P; van Goor, Harry; Olde Rikkert, Marcel G M

2017-03-01

To identify key elements of optimal treatment decision-making for surgeons and older patients with colorectal (CRC) or pancreatic cancer (PC). Six focus groups with different participants were performed: three with older CRC/PC patients and relatives, and three with physicians. Supplementary in-depth interviews were conducted in another seven patients. Framework analysis was used to identify key elements in decision-making. 23 physicians, 22 patients and 14 relatives participated. Three interacting components were revealed: preconditions, content and facilitators of decision-making. To provide optimal information about treatments' impact on an older patient's daily life, physicians should obtain an overall picture and take into account patients' frailty. Depending on patients' preferences and capacities, dividing decision-making into more sessions will be helpful and simultaneously emphasize patients' own responsibility. GPs may have a valuable contribution because of their background knowledge and supportive role. Stakeholders identified several crucial elements in the complex surgical decision-making of older CRC/PC patients. Structured qualitative research may also be of great help in optimizing other treatment directed decision-making processes. Surgeons should be trained in examining preconditions and useful facilitators in decision-making in older CRC/PC patients to optimize its content and to improve the quality of shared care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

On optimizing the treatment of exchange perturbations

NASA Technical Reports Server (NTRS)

Hirschfelder, J. O.; Chipman, D. M.

1972-01-01

A method using the zeroth plus first order wave functions, obtained by optimizing the basic equation used in exchange perturbation treatments, is utilized in an attempt to determine the exact energy and wave function in the exchange process. Attempts to determine the first order perturbation solution by optimizing the sum of the first and second order energies were unsuccessful.

Automated geometric optimization for robotic HIFU treatment of liver tumors.

PubMed

Williamson, Tom; Everitt, Scott; Chauhan, Sunita

2018-05-01

High intensity focused ultrasound (HIFU) represents a non-invasive method for the destruction of cancerous tissue within the body. Heating of targeted tissue by focused ultrasound transducers results in the creation of ellipsoidal lesions at the target site, the locations of which can have a significant impact on treatment outcomes. Towards this end, this work describes a method for the optimization of lesion positions within arbitrary tumors, with specific anatomical constraints. A force-based optimization framework was extended to the case of arbitrary tumor position and constrained orientation. Analysis of the approximate reachable treatment volume for the specific case of treatment of liver tumors was performed based on four transducer configurations and constraint conditions derived. Evaluation was completed utilizing simplified spherical and ellipsoidal tumor models and randomly generated tumor volumes. The total volume treated, lesion overlap and healthy tissue ablated was evaluated. Two evaluation scenarios were defined and optimized treatment plans assessed. The optimization framework resulted in improvements of up to 10% in tumor volume treated, and reductions of up to 20% in healthy tissue ablated as compared to the standard lesion rastering approach. Generation of optimized plans proved feasible for both sub- and intercostally located tumors. This work describes an optimized method for the planning of lesion positions during HIFU treatment of liver tumors. The approach allows the determination of optimal lesion locations and orientations, and can be applied to arbitrary tumor shapes and sizes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Functional Recovery in Major Depressive Disorder: Focus on Early Optimized Treatment.

PubMed

Habert, Jeffrey; Katzman, Martin A; Oluboka, Oloruntoba J; McIntyre, Roger S; McIntosh, Diane; MacQueen, Glenda M; Khullar, Atul; Milev, Roumen V; Kjernisted, Kevin D; Chokka, Pratap R; Kennedy, Sidney H

2016-09-01

This article presents the case that a more rapid, individualized approach to treating major depressive disorder (MDD) may increase the likelihood of achieving full symptomatic and functional recovery for individual patients and that studies show it is possible to make earlier decisions about appropriateness of treatment in order to rapidly optimize that treatment. A PubMed search was conducted using terms including major depressive disorder, early improvement, predictor, duration of untreated illness, and function. English-language articles published before September 2015 were included. Additional studies were found within identified research articles and reviews. Thirty antidepressant studies reporting predictor criteria and outcome measures are included in this review. Studies were reviewed to extract definitions of predictors, outcome measures, and results of the predictor analysis. Results were summarized separately for studies reporting effects of early improvement, baseline characteristics, and duration of untreated depression. Shorter duration of the current depressive episode and duration of untreated depression are associated with better symptomatic and functional outcomes in MDD. Early improvement of depressive symptoms predicts positive symptomatic outcomes (response and remission), and early functional improvement predicts an increased likelihood of functional remission. The approach to treatment of depression that exhibits the greatest potential for achieving full symptomatic and functional recovery is early optimized treatment: early diagnosis followed by rapid individualized treatment. Monitoring symptoms and function early in treatment is crucial to ensuring that patients do not remain on ineffective or poorly tolerated treatment, which may delay recovery and heighten the risk of residual functional deficits. © Copyright 2016 Physicians Postgraduate Press, Inc.

Risk factors for the treatment outcome of retreated pulmonary tuberculosis patients in China: an optimized prediction model.

PubMed

Wang, X-M; Yin, S-H; Du, J; Du, M-L; Wang, P-Y; Wu, J; Horbinski, C M; Wu, M-J; Zheng, H-Q; Xu, X-Q; Shu, W; Zhang, Y-J

2017-07-01

Retreatment of tuberculosis (TB) often fails in China, yet the risk factors associated with the failure remain unclear. To identify risk factors for the treatment failure of retreated pulmonary tuberculosis (PTB) patients, we analyzed the data of 395 retreated PTB patients who received retreatment between July 2009 and July 2011 in China. PTB patients were categorized into 'success' and 'failure' groups by their treatment outcome. Univariable and multivariable logistic regression were used to evaluate the association between treatment outcome and socio-demographic as well as clinical factors. We also created an optimized risk score model to evaluate the predictive values of these risk factors on treatment failure. Of 395 patients, 99 (25·1%) were diagnosed as retreatment failure. Our results showed that risk factors associated with treatment failure included drug resistance, low education level, low body mass index (6 months), standard treatment regimen, retreatment type, positive culture result after 2 months of treatment, and the place where the first medicine was taken. An Optimized Framingham risk model was then used to calculate the risk scores of these factors. Place where first medicine was taken (temporary living places) received a score of 6, which was highest among all the factors. The predicted probability of treatment failure increases as risk score increases. Ten out of 359 patients had a risk score >9, which corresponded to an estimated probability of treatment failure >70%. In conclusion, we have identified multiple clinical and socio-demographic factors that are associated with treatment failure of retreated PTB patients. We also created an optimized risk score model that was effective in predicting the retreatment failure. These results provide novel insights for the prognosis and improvement of treatment for retreated PTB patients.

Optimized Non-Obstructive Particle Damping (NOPD) Treatment for Composite Honeycomb Structures

NASA Technical Reports Server (NTRS)

Panossian, H.

2008-01-01

Non-Obstructive Particle Damping (NOPD) technology is a passive vibration damping approach whereby metallic or non-metallic particles in spherical or irregular shapes, of heavy or light consistency, and even liquid particles are placed inside cavities or attached to structures by an appropriate means at strategic locations, to absorb vibration energy. The objective of the work described herein is the development of a design optimization procedure and discussion of test results for such a NOPD treatment on honeycomb (HC) composite structures, based on finite element modeling (FEM) analyses, optimization and tests. Modeling and predictions were performed and tests were carried out to correlate the test data with the FEM. The optimization procedure consisted of defining a global objective function, using finite difference methods, to determine the optimal values of the design variables through quadratic linear programming. The optimization process was carried out by targeting the highest dynamic displacements of several vibration modes of the structure and finding an optimal treatment configuration that will minimize them. An optimal design was thus derived and laboratory tests were conducted to evaluate its performance under different vibration environments. Three honeycomb composite beams, with Nomex core and aluminum face sheets, empty (untreated), uniformly treated with NOPD, and optimally treated with NOPD, according to the analytically predicted optimal design configuration, were tested in the laboratory. It is shown that the beam with optimal treatment has the lowest response amplitude. Described below are results of modal vibration tests and FEM analyses from predictions of the modal characteristics of honeycomb beams under zero, 50% uniform treatment and an optimal NOPD treatment design configuration and verification with test data.

Relationships among optimism, well-being, self-transcendence, coping, and social support in women during treatment for breast cancer.

PubMed

Matthews, Ellyn E; Cook, Paul F

2009-07-01

The impact of diagnosis and treatment for breast cancer, stressors that affect emotional well-being, is influenced by several psychosocial factors and the relationships among them. The purpose of this study was to investigate the relationship between optimism and emotional well-being (EWB) and the individual and combined mediation of this relationship by perceived social support (SS), problem focused coping (PFC), and self-transcendence in women with breast cancer during radiation therapy. Ninety-three women receiving radiation treatment for breast cancer completed questionnaires that measured EWB, optimism, SS, PFC, and self-transcendence. Correlational and multiple regression analysis revealed that optimism was positively related to EWB. Of the three mediators, self-transcendence alone was found to partially mediate the relationship between optimism and EWB. The relationship between optimism and PFC was not significant. Optimism was related to SS, but its indirect effect on EWB through SS did not reach significance. During breast cancer treatment, the positive effects of optimism on EWB are partially mediated by a woman's level of self-transcendence. Brief screening of women's optimism may help identify women at risk for psychological distress. Early detection and interventions to promote psychological adjustment throughout the cancer trajectory (e.g. enhancing self-transcendence) should receive attention in future research. (c) 2008 John Wiley & Sons, Ltd.

Optimizing patient treatment decisions in an era of rapid technological advances: the case of hepatitis C treatment.

PubMed

Liu, Shan; Brandeau, Margaret L; Goldhaber-Fiebert, Jeremy D

2017-03-01

How long should a patient with a treatable chronic disease wait for more effective treatments before accepting the best available treatment? We develop a framework to guide optimal treatment decisions for a deteriorating chronic disease when treatment technologies are improving over time. We formulate an optimal stopping problem using a discrete-time, finite-horizon Markov decision process. The goal is to maximize a patient's quality-adjusted life expectancy. We derive structural properties of the model and analytically solve a three-period treatment decision problem. We illustrate the model with the example of treatment for chronic hepatitis C virus (HCV). Chronic HCV affects 3-4 million Americans and has been historically difficult to treat, but increasingly effective treatments have been commercialized in the past few years. We show that the optimal treatment decision is more likely to be to accept currently available treatment-despite expectations for future treatment improvement-for patients who have high-risk history, who are older, or who have more comorbidities. Insights from this study can guide HCV treatment decisions for individual patients. More broadly, our model can guide treatment decisions for curable chronic diseases by finding the optimal treatment policy for individual patients in a heterogeneous population.

Optimizing Patient Treatment Decisions in an Era of Rapid Technological Advances: The Case of Hepatitis C Treatment

PubMed Central

Liu, Shan; Goldhaber-Fiebert, Jeremy D.; Brandeau, Margaret L.

2015-01-01

How long should a patient with a treatable chronic disease wait for more effective treatments before accepting the best available treatment? We develop a framework to guide optimal treatment decisions for a deteriorating chronic disease when treatment technologies are improving over time. We formulate an optimal stopping problem using a discrete-time, finite-horizon Markov decision process. The goal is to maximize a patient’s quality-adjusted life expectancy. We derive structural properties of the model and analytically solve a three-period treatment decision problem. We illustrate the model with the example of treatment for chronic hepatitis C virus (HCV). Chronic HCV affects 3–4 million Americans and has been historically difficult to treat, but increasingly effective treatments have been commercialized in the past few years. We show that the optimal treatment decision is more likely to be to accept currently available treatment—despite expectations for future treatment improvement—for patients who have high-risk history, who are older, or who have more comorbidities. Insights from this study can guide HCV treatment decisions for individual patients. More broadly, our model can guide treatment decisions for curable chronic diseases by finding the optimal treatment policy for individual patients in a heterogeneous population. PMID:26188961

Assessing the Value of Information for Identifying Optimal Floodplain Management Portfolios

NASA Astrophysics Data System (ADS)

Read, L.; Bates, M.; Hui, R.; Lund, J. R.

2014-12-01

Floodplain management is a complex portfolio problem that can be analyzed from an integrated perspective incorporating traditionally structural and nonstructural options. One method to identify effective strategies for preparing, responding to, and recovering from floods is to optimize for a portfolio of temporary (emergency) and permanent floodplain management options. A risk-based optimization approach to this problem assigns probabilities to specific flood events and calculates the associated expected damages. This approach is currently limited by: (1) the assumption of perfect flood forecast information, i.e. implementing temporary management activities according to the actual flood event may differ from optimizing based on forecasted information and (2) the inability to assess system resilience across a range of possible future events (risk-centric approach). Resilience is defined here as the ability of a system to absorb and recover from a severe disturbance or extreme event. In our analysis, resilience is a system property that requires integration of physical, social, and information domains. This work employs a 3-stage linear program to identify the optimal mix of floodplain management options using conditional probabilities to represent perfect and imperfect flood stages (forecast vs. actual events). We assess the value of information in terms of minimizing damage costs for two theoretical cases - urban and rural systems. We use portfolio analysis to explore how the set of optimal management options differs depending on whether the goal is for the system to be risk-adverse to a specified event or resilient over a range of events.

Residential treatment for combat-related posttraumatic stress disorder: identifying trajectories of change and predictors of treatment response.

PubMed

Currier, Joseph M; Holland, Jason M; Drescher, Kent D

2014-01-01

Combat-related posttraumatic stress disorder (PTSD) can be a difficult condition to treat and has been associated with serious medical and economic issues among U.S. military veterans. Distinguishing between treatment responders vs. non-responders in this population has become an important public health priority. This study was conducted to identify pre-treatment characteristics of U.S. veterans with combat-related PTSD that might contribute to favorable and unfavorable responses to high value treatments for this condition. This study focused on 805 patients who completed a VHA PTSD residential program between 2000 and 2007. These patients completed the PTSD Clinical Checklist at pre-treatment, post-treatment, and a four-month follow-up assessment. Latent growth curve analysis (LCGA) was incorporated to determine trajectories of changes in PTSD across these assessments and whether several key clinical concerns for this population were associated with their treatment responses. LCGA indicated three distinct trajectories in PTSD outcomes and identified several clinical factors that were prospectively linked with changes in veterans' posttraumatic symptomatology. When compared to a group with high PTSD symptom severity that decreased over the program but relapsed at follow-up (41%), the near half (48.8%) of the sample with an improving trajectory had less combat exposure and superior physical/mental health. However, when compared to a minority (10.2%) with relatively low symptomatology that also remained somewhat stable, patients in the improving group were younger and also reported greater combat exposure, poorer physical/mental health status, and more problems with substance abuse before the start of treatment. Findings suggest that veterans are most likely to benefit from residential treatment in an intermediate range of symptoms and risk factors, including PTSD symptom severity, history of combat exposure, and comorbid issues with physical/mental health

Optimal Corrosion Control Treatment Evaluation Technical Recommendations

EPA Pesticide Factsheets

This document provides technical recommendations that both systems and primacy agencies can use to comply with LCR CCT requirements and effective evaluation and designation of optimal corrosion control treatment (OCCT).

State-of-the-Art Diagnosis and Treatment of Melanoma: Optimal Multidetector Computed Tomographic Practice to Identify Metastatic Disease and Review of Innovative Therapeutic Agents.

PubMed

Jones, Blake C; Lipson, Evan J; Childers, Brandon; Fishman, Elliot K; Johnson, Pamela T

The incidence of melanoma has risen dramatically over the past several decades. Oncologists rely on the ability of radiologists to identify subtle radiographic changes representing metastatic and recurrent melanoma in uncommon locations on multidetector computed tomography (MDCT) as the front-line imaging surveillance tool. To accomplish this goal, MDCT acquisition and display must be optimized and radiologist interpretation and search patterns must be tailored to identify the unique and often subtle metastatic lesions of melanoma. This article describes MDCT acquisition and display techniques that optimize the visibility of melanoma lesions, such as high-contrast display windows and multiplanar reconstructions. In addition, innovative therapies for melanoma, such as immunotherapy and small-molecule therapy, have altered clinical management and outcomes and have also changed the spectrum of therapeutic complications that can be detected on MDCT. Recent advances in melanoma therapy and potential complications that the radiologist can identify on MDCT are reviewed.

Relationships among optimism, well-being, self-transcendence, coping, and social support in women during treatment for breast cancer

PubMed Central

Matthews, Ellyn E.; Cook, Paul F.

2011-01-01

Objective The impact of diagnosis and treatment for breast cancer, stressors that affect emotional well-being, is influenced by several psychosocial factors and the relationships among them. The purpose of this study was to investigate the relationship between optimism and emotional well-being (EWB) and the individual and combined mediation of this relationship by perceived social support (SS), problem focused coping (PFC), and self-transcendence in women with breast cancer during radiation therapy. Methods Ninety-three women receiving radiation treatment for breast cancer completed questionnaires that measured EWB, optimism, SS, PFC, and self-transcendence. Results Correlational and multiple regression analysis revealed that optimism was positively related to EWB. Of the three mediators, self-transcendence alone was found to partially mediate the relationship between optimism and EWB. The relationship between optimism and PFC was not significant. Optimism was related to SS, but its indirect effect on EWB through SS did not reach significance. Conclusions and implications During breast cancer treatment, the positive effects of optimism on EWB are partially mediated by a woman’s level of self-transcendence. Brief screening of women’s optimism may help identify women at risk for psychological distress. Early detection and interventions to promote psychological adjustment throughout the cancer trajectory (e.g. enhancing self-transcendence) should receive attention in future research. PMID:19034884

International Study to Predict Optimized Treatment for Depression (iSPOT-D), a randomized clinical trial: rationale and protocol.

PubMed

Williams, Leanne M; Rush, A John; Koslow, Stephen H; Wisniewski, Stephen R; Cooper, Nicholas J; Nemeroff, Charles B; Schatzberg, Alan F; Gordon, Evian

2011-01-05

Clinically useful treatment moderators of Major Depressive Disorder (MDD) have not yet been identified, though some baseline predictors of treatment outcome have been proposed. The aim of iSPOT-D is to identify pretreatment measures that predict or moderate MDD treatment response or remission to escitalopram, sertraline or venlafaxine; and develop a model that incorporates multiple predictors and moderators. The International Study to Predict Optimized Treatment - in Depression (iSPOT-D) is a multi-centre, international, randomized, prospective, open-label trial. It is enrolling 2016 MDD outpatients (ages 18-65) from primary or specialty care practices (672 per treatment arm; 672 age-, sex- and education-matched healthy controls). Study-eligible patients are antidepressant medication (ADM) naïve or willing to undergo a one-week wash-out of any non-protocol ADM, and cannot have had an inadequate response to protocol ADM. Baseline assessments include symptoms; distress; daily function; cognitive performance; electroencephalogram and event-related potentials; heart rate and genetic measures. A subset of these baseline assessments are repeated after eight weeks of treatment. Outcomes include the 17-item Hamilton Rating Scale for Depression (primary) and self-reported depressive symptoms, social functioning, quality of life, emotional regulation, and side-effect burden (secondary). Participants may then enter a naturalistic telephone follow-up at weeks 12, 16, 24 and 52. The first half of the sample will be used to identify potential predictors and moderators, and the second half to replicate and confirm. First enrolment was in December 2008, and is ongoing. iSPOT-D evaluates clinical and biological predictors of treatment response in the largest known sample of MDD collected worldwide. International Study to Predict Optimised Treatment - in Depression (iSPOT-D) ClinicalTrials.gov Identifier: NCT00693849. URL: http://clinicaltrials.gov/ct2/show/NCT00693849?term=International+Study+to+Predict+Optimized+Treatment

Identifying Optimal Measurement Subspace for the Ensemble Kalman Filter

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

Zhou, Ning; Huang, Zhenyu; Welch, Greg

2012-05-24

To reduce the computational load of the ensemble Kalman filter while maintaining its efficacy, an optimization algorithm based on the generalized eigenvalue decomposition method is proposed for identifying the most informative measurement subspace. When the number of measurements is large, the proposed algorithm can be used to make an effective tradeoff between computational complexity and estimation accuracy. This algorithm also can be extended to other Kalman filters for measurement subspace selection.

Determining a sustainable and economically optimal wastewater treatment and discharge strategy.

PubMed

Hardisty, Paul E; Sivapalan, Mayuran; Humphries, Robert

2013-01-15

Options for treatment and discharge of wastewater in regional Western Australia (WA) are examined from the perspective of overall sustainability and social net benefit. Current practice in the state has typically involved a basic standard of treatment deemed to be protective of human health, followed by discharge to surface water bodies. Community and regulatory pressure to move to higher standards of treatment is based on the presumption that a higher standard of treatment is more protective of the environment and society, and thus is more sustainable. This analysis tests that hypothesis for Western Australian conditions. The merits of various wastewater treatment and discharge strategies are examined by quantifying financial costs (capital and operations), and by monetising the wider environmental and social costs and benefits of each option over an expanded planning horizon (30 years). Six technical treatment-disposal options were assessed at a test site, all of which met the fundamental criterion of protecting human health. From a financial perspective, the current business-as-usual option is preferred - it is the least cost solution. However, valuing externalities such as water, greenhouse gases, ecological impacts and community amenity, the status quo is revealed as sub-optimal. Advanced secondary treatment with stream disposal improves water quality and provides overall net benefit to society. All of the other options were net present value (NPV) negative. Sensitivity analysis shows that the favoured option outperforms all of the others under a wide range of financial and externality values and assumptions. Expanding the findings across the state reveals that moving from the identified socially optimal level of treatment to higher (tertiary) levels of treatment would result in a net loss to society equivalent to several hundred million dollars. In other words, everyone benefits from improving treatment to the optimum point. But society, the environment, and

Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL).

PubMed

Koestler, Devin C; Jones, Meaghan J; Usset, Joseph; Christensen, Brock C; Butler, Rondi A; Kobor, Michael S; Wiencke, John K; Kelsey, Karl T

2016-03-08

Confounding due to cellular heterogeneity represents one of the foremost challenges currently facing Epigenome-Wide Association Studies (EWAS). Statistical methods leveraging the tissue-specificity of DNA methylation for deconvoluting the cellular mixture of heterogenous biospecimens offer a promising solution, however the performance of such methods depends entirely on the library of methylation markers being used for deconvolution. Here, we introduce a novel algorithm for Identifying Optimal Libraries (IDOL) that dynamically scans a candidate set of cell-specific methylation markers to find libraries that optimize the accuracy of cell fraction estimates obtained from cell mixture deconvolution. Application of IDOL to training set consisting of samples with both whole-blood DNA methylation data (Illumina HumanMethylation450 BeadArray (HM450)) and flow cytometry measurements of cell composition revealed an optimized library comprised of 300 CpG sites. When compared existing libraries, the library identified by IDOL demonstrated significantly better overall discrimination of the entire immune cell landscape (p = 0.038), and resulted in improved discrimination of 14 out of the 15 pairs of leukocyte subtypes. Estimates of cell composition across the samples in the training set using the IDOL library were highly correlated with their respective flow cytometry measurements, with all cell-specific R (2)>0.99 and root mean square errors (RMSEs) ranging from [0.97 % to 1.33 %] across leukocyte subtypes. Independent validation of the optimized IDOL library using two additional HM450 data sets showed similarly strong prediction performance, with all cell-specific R (2)>0.90 and R M S E<4.00 %. In simulation studies, adjustments for cell composition using the IDOL library resulted in uniformly lower false positive rates compared to competing libraries, while also demonstrating an improved capacity to explain epigenome-wide variation in DNA methylation within two large

Characteristics of psychiatric patients for whom financial considerations affect optimal treatment provision.

PubMed

West, Joyce C; Pingitore, David; Zarin, Deborah A

2002-12-01

This study assessed characteristics of psychiatric patients for whom financial considerations affected the provision of "optimal" treatment. Psychiatrists reported that for 33.8 percent of 1,228 patients from a national sample, financial considerations such as managed care limitations, the patient's personal finances, and limitations inherent in the public care system adversely affected the provision of optimal treatment. Patients were more likely to have their treatment adversely affected by financial considerations if they were more severely ill, had more than one behavioral health disorder or a psychosocial problem, or were receiving treatment under managed care arrangements. Patients for whom financial considerations affect the provision of optimal treatment represent a population for whom access to treatment may be particularly important.

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part I: main content.

PubMed

Orellana, Liliana; Rotnitzky, Andrea; Robins, James M

2010-01-01

Dynamic treatment regimes are set rules for sequential decision making based on patient covariate history. Observational studies are well suited for the investigation of the effects of dynamic treatment regimes because of the variability in treatment decisions found in them. This variability exists because different physicians make different decisions in the face of similar patient histories. In this article we describe an approach to estimate the optimal dynamic treatment regime among a set of enforceable regimes. This set is comprised by regimes defined by simple rules based on a subset of past information. The regimes in the set are indexed by a Euclidean vector. The optimal regime is the one that maximizes the expected counterfactual utility over all regimes in the set. We discuss assumptions under which it is possible to identify the optimal regime from observational longitudinal data. Murphy et al. (2001) developed efficient augmented inverse probability weighted estimators of the expected utility of one fixed regime. Our methods are based on an extension of the marginal structural mean model of Robins (1998, 1999) which incorporate the estimation ideas of Murphy et al. (2001). Our models, which we call dynamic regime marginal structural mean models, are specially suitable for estimating the optimal treatment regime in a moderately small class of enforceable regimes of interest. We consider both parametric and semiparametric dynamic regime marginal structural models. We discuss locally efficient, double-robust estimation of the model parameters and of the index of the optimal treatment regime in the set. In a companion paper in this issue of the journal we provide proofs of the main results.

Optimizing global liver function in radiation therapy treatment planning

NASA Astrophysics Data System (ADS)

Wu, Victor W.; Epelman, Marina A.; Wang, Hesheng; Romeijn, H. Edwin; Feng, Mary; Cao, Yue; Ten Haken, Randall K.; Matuszak, Martha M.

2016-09-01

Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose (\\ell \\text{EUD} ) (conventional ‘\\ell \\text{EUD} model’), the so-called perfusion-weighted \\ell \\text{EUD} (\\text{fEUD} ) (proposed ‘fEUD model’), and post-treatment global liver function (GLF) (proposed ‘GLF model’), predicted by a new liver-perfusion-based dose-response model. The resulting \\ell \\text{EUD} , fEUD, and GLF plans delivering the same target \\ell \\text{EUD} are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to 4.6 % ≤ft(7.5 % \\right) more liver function than the fEUD (\\ell \\text{EUD} ) plan does in 2D cases, and up to 4.5 % ≤ft(5.6 % \\right) in 3D cases. The GLF and fEUD plans worsen in \\ell \\text{EUD} of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Behavioral Domain.

PubMed

Lytle, Leslie A; Nicastro, Holly L; Roberts, Susan B; Evans, Mary; Jakicic, John M; Laposky, Aaron D; Loria, Catherine M

2018-04-01

The ability to identify and measure behaviors that are related to weight loss and the prevention of weight regain is crucial to understanding the variability in response to obesity treatment and the development of tailored treatments. The overarching goal of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project is to provide obesity researchers with guidance on a set of constructs and measures that are related to weight control and that span and integrate obesity-related behavioral, biological, environmental, and psychosocial domains. This article describes how the behavioral domain subgroup identified the initial list of high-priority constructs and measures to be included, and it describes practical considerations for assessing the following four behavioral areas: eating, activity, sleep, and self-monitoring of weight. Challenges and considerations for advancing the science related to weight loss and maintenance behaviors are also discussed. Assessing a set of core behavioral measures in combination with those from other ADOPT domains is critical to improve our understanding of individual variability in response to adult obesity treatment. The selection of behavioral measures is based on the current science, although there continues to be much work needed in this field. © 2018 The Obesity Society.

Optimization of spatiotemporally fractionated radiotherapy treatments with bounds on the achievable benefit

NASA Astrophysics Data System (ADS)

Gaddy, Melissa R.; Yıldız, Sercan; Unkelbach, Jan; Papp, Dávid

2018-01-01

Spatiotemporal fractionation schemes, that is, treatments delivering different dose distributions in different fractions, can potentially lower treatment side effects without compromising tumor control. This can be achieved by hypofractionating parts of the tumor while delivering approximately uniformly fractionated doses to the surrounding tissue. Plan optimization for such treatments is based on biologically effective dose (BED); however, this leads to computationally challenging nonconvex optimization problems. Optimization methods that are in current use yield only locally optimal solutions, and it has hitherto been unclear whether these plans are close to the global optimum. We present an optimization framework to compute rigorous bounds on the maximum achievable normal tissue BED reduction for spatiotemporal plans. The approach is demonstrated on liver tumors, where the primary goal is to reduce mean liver BED without compromising any other treatment objective. The BED-based treatment plan optimization problems are formulated as quadratically constrained quadratic programming (QCQP) problems. First, a conventional, uniformly fractionated reference plan is computed using convex optimization. Then, a second, nonconvex, QCQP model is solved to local optimality to compute a spatiotemporally fractionated plan that minimizes mean liver BED, subject to the constraints that the plan is no worse than the reference plan with respect to all other planning goals. Finally, we derive a convex relaxation of the second model in the form of a semidefinite programming problem, which provides a rigorous lower bound on the lowest achievable mean liver BED. The method is presented on five cases with distinct geometries. The computed spatiotemporal plans achieve 12-35% mean liver BED reduction over the optimal uniformly fractionated plans. This reduction corresponds to 79-97% of the gap between the mean liver BED of the uniform reference plans and our lower bounds on the lowest

Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial

PubMed Central

2013-01-01

Background Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD. Methods/Design The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n = 102), test the

Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial.

PubMed

Grieve, Stuart M; Korgaonkar, Mayuresh S; Etkin, Amit; Harris, Anthony; Koslow, Stephen H; Wisniewski, Stephen; Schatzberg, Alan F; Nemeroff, Charles B; Gordon, Evian; Williams, Leanne M

2013-07-18

Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD. The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n=102), test the findings in the second half, and

Combined treatment: impact of optimal psychotherapy and medication in bipolar disorder.

PubMed

Parikh, Sagar V; Hawke, Lisa D; Velyvis, Vytas; Zaretsky, Ari; Beaulieu, Serge; Patelis-Siotis, Irene; MacQueen, Glenda; Young, L Trevor; Yatham, Lakshmi N; Cervantes, Pablo

2015-02-01

The current study investigated the longitudinal course of symptoms in bipolar disorder among individuals receiving optimal treatment combining pharmacotherapy and psychotherapy, as well as predictors of the course of illness. A total of 160 participants with bipolar disorder (bipolar I disorder: n = 115; bipolar II disorder: n = 45) received regular pharmacological treatment, complemented by a manualized, evidence-based psychosocial treatment - that is, cognitive behavioral therapy or psychoeducation. Participants were assessed at baseline and prospectively for 72 weeks using the Longitudinal Interval Follow-up Evaluation (LIFE) scale scores for mania/hypomania and depression, as well as comparison measures (clinicaltrials.gov identifier: NCT00188838). Over a 72-week period, patients spent a clear majority (about 65%) of time euthymic. Symptoms were experienced more than 50% of the time by only a quarter of the sample. Depressive symptoms strongly dominated over (hypo)manic symptoms, while subsyndromal symptoms were more common than full diagnosable episodes for both polarities. Mixed symptoms were rare, but present for a minority of participants. Individuals experienced approximately six significant mood changes per year, with a full relapse on average every 7.5 months. Participants who had fewer depressive symptoms at intake, a later age at onset, and no history of psychotic symptoms spent more weeks well over the course of the study. Combined pharmacological and adjunctive psychosocial treatments appeared to provide an improved course of illness compared to the results of previous studies. Efforts to further improve the course of illness beyond that provided by current optimal treatment regimens will require a substantial focus on both subsyndromal and syndromal depressive symptoms. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Optimizing treatment of hypothyroidism.

PubMed

Clarke, Nick; Kabadi, Udaya M

2004-01-01

Several thyroid hormone preparations are currently available, including levothyroxine sodium (thyroxine), liothyronine (triiodothyronine), and desiccated thyroid extract, as well as a combination of levothyroxine sodium and liothyronine. Levothyroxine sodium monotherapy at an appropriate daily dose provides uniform levels of both thyroxine and triiodothyronine in the circulation without diurnal variation. Therefore, it is the preparation of choice in most patients with hypothyroidism of both the primary and central types. A normal thyrotropin (TSH) level of 1-2 mU/L is considered the determinant of optimal daily levothyroxine sodium dose in patients with primary hypothyroidism, whereas normal thyroxine and triiodothyronine levels in the mid or upper normal range may denote optimal replacement in patients with central hypothyroidism. Optimal daily levothyroxine sodium dose may be determined according to serum TSH level at the time of diagnosis of primary hypothyroidism. Initial administration of close to the full calculated dose of levothyroxine sodium is appropriate for younger patients, reducing the need for follow-up visits and repeated laboratory testing for dose titration. In the elderly and in patients with a history of coronary artery disease (CAD), the well established approach of starting with a low dose and gradually titrating to the full calculated dose is always the best option. Levothyroxine sodium can and should be continued in patients receiving treatment for CAD. Even minor over-replacement during initial titration of levothyroxine sodium should be avoided, because of the risk of cardiac events. Chronic over-replacement may induce osteoporosis, particularly in postmenopausal women, and should also be avoided.

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Psychosocial Domain.

PubMed

Sutin, Angelina R; Boutelle, Kerri; Czajkowski, Susan M; Epel, Elissa S; Green, Paige A; Hunter, Christine M; Rice, Elise L; Williams, David M; Young-Hyman, Deborah; Rothman, Alexander J

2018-04-01

Within the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, the psychosocial domain addresses how psychosocial processes underlie the influence of obesity treatment strategies on weight loss and weight maintenance. The subgroup for the psychosocial domain identified an initial list of high-priority constructs and measures that ranged from relatively stable characteristics about the person (cognitive function, personality) to dynamic characteristics that may change over time (motivation, affect). This paper describes (a) how the psychosocial domain fits into the broader model of weight loss and weight maintenance as conceptualized by ADOPT; (b) the guiding principles used to select constructs and measures for recommendation; (c) the high-priority constructs recommended for inclusion; (d) domain-specific issues for advancing the science; and (e) recommendations for future research. The inclusion of similar measures across trials will help to better identify how psychosocial factors mediate and moderate the weight loss and weight maintenance process, facilitate research into dynamic interactions with factors in the other ADOPT domains, and ultimately improve the design and delivery of effective interventions. © 2018 The Obesity Society.

Identifying Efficacious Treatment Components of Panic Control Treatment for Adolescents: A Preliminary Examination

ERIC Educational Resources Information Center

Micco, Jamie A.; Choate-Summers, Molly L.; Ehrenreich, Jill T.; Pincus, Donna B.; Mattis, Sara G.

2007-01-01

Panic Control Treatment for Adolescents (PCT-A) is a developmentally sensitive and efficacious treatment for adolescents with panic disorder. The present study is a preliminary examination of the relative efficacy of individual treatment components in PCT-A in a sample of treatment completers; the study identified when rapid improvements in panic…

Optimization of personalized therapies for anticancer treatment.

PubMed

Vazquez, Alexei

2013-04-12

As today, there are hundreds of targeted therapies for the treatment of cancer, many of which have companion biomarkers that are in use to inform treatment decisions. If we would consider this whole arsenal of targeted therapies as a treatment option for every patient, very soon we will reach a scenario where each patient is positive for several markers suggesting their treatment with several targeted therapies. Given the documented side effects of anticancer drugs, it is clear that such a strategy is unfeasible. Here, we propose a strategy that optimizes the design of combinatorial therapies to achieve the best response rates with the minimal toxicity. In this methodology markers are assigned to drugs such that we achieve a high overall response rate while using personalized combinations of minimal size. We tested this methodology in an in silico cancer patient cohort, constructed from in vitro data for 714 cell lines and 138 drugs reported by the Sanger Institute. Our analysis indicates that, even in the context of personalized medicine, combinations of three or more drugs are required to achieve high response rates. Furthermore, patient-to-patient variations in pharmacokinetics have a significant impact in the overall response rate. A 10 fold increase in the pharmacokinetics variations resulted in a significant drop the overall response rate. The design of optimal combinatorial therapy for anticancer treatment requires a transition from the one-drug/one-biomarker approach to global strategies that simultaneously assign makers to a catalog of drugs. The methodology reported here provides a framework to achieve this transition.

Optimal CINAHL search strategies for identifying therapy studies and review articles.

PubMed

Wong, Sharon S L; Wilczynski, Nancy L; Haynes, R Brian

2006-01-01

To design optimal search strategies for locating sound therapy studies and review articles in CiNAHL in the year 2000. An analytic survey was conducted, comparing hand searches of 75 journals with retrievals from CINAHL for 5,020 candidate search terms and 17,900 combinations for therapy and 5,977 combinations for review articles. All articles were rated with purpose and quality indicators. Candidate search strategies were used in CINAHL, and the retrievals were compared with results of the hand searches. The proposed search strategies were treated as "diagnostic tests" for sound studies and the manual review of the literature was treated as the "gold standard." Operating characteristics of the search strategies were calculated. Of the 1,383 articles about treatment, 506 (36.6%) met basic criteria for scientific merit and 127 (17.9%) of the 711 articles classified as a review met the criteria for systematic reviews. For locating sound treatment studies, a three-term strategy maximized sensitivity at 99.4% but with compromised specificity at 58.3%, and a two-term strategy maximized specificity at 98.5% but with compromised sensitivity at 52.0%. For detecting systematic reviews, a three-term strategy maximized sensitivity at 91.3% while keeping specificity high at 95.4%, and a single-term strategy maximized specificity at 99.6% but with compromised sensitivity at 42.5%. Three-term search strategies optimizing sensitivity and specificity achieved these values over 91% for detecting sound treatment studies and over 76% for detecting systematic reviews. Search strategies combining indexing terms and text words can achieve high sensitivity and specificity for retrieving sound treatment studies and review articles in CINAHL.

HIV Treatment and Prevention: A Simple Model to Determine Optimal Investment.

PubMed

Juusola, Jessie L; Brandeau, Margaret L

2016-04-01

To create a simple model to help public health decision makers determine how to best invest limited resources in HIV treatment scale-up and prevention. A linear model was developed for determining the optimal mix of investment in HIV treatment and prevention, given a fixed budget. The model incorporates estimates of secondary health benefits accruing from HIV treatment and prevention and allows for diseconomies of scale in program costs and subadditive benefits from concurrent program implementation. Data sources were published literature. The target population was individuals infected with HIV or at risk of acquiring it. Illustrative examples of interventions include preexposure prophylaxis (PrEP), community-based education (CBE), and antiretroviral therapy (ART) for men who have sex with men (MSM) in the US. Outcome measures were incremental cost, quality-adjusted life-years gained, and HIV infections averted. Base case analysis indicated that it is optimal to invest in ART before PrEP and to invest in CBE before scaling up ART. Diseconomies of scale reduced the optimal investment level. Subadditivity of benefits did not affect the optimal allocation for relatively low implementation levels. The sensitivity analysis indicated that investment in ART before PrEP was optimal in all scenarios tested. Investment in ART before CBE became optimal when CBE reduced risky behavior by 4% or less. Limitations of the study are that dynamic effects are approximated with a static model. Our model provides a simple yet accurate means of determining optimal investment in HIV prevention and treatment. For MSM in the US, HIV control funds should be prioritized on inexpensive, effective programs like CBE, then on ART scale-up, with only minimal investment in PrEP. © The Author(s) 2015.

Tool Steel Heat Treatment Optimization Using Neural Network Modeling

NASA Astrophysics Data System (ADS)

Podgornik, Bojan; Belič, Igor; Leskovšek, Vojteh; Godec, Matjaz

2016-11-01

Optimization of tool steel properties and corresponding heat treatment is mainly based on trial and error approach, which requires tremendous experimental work and resources. Therefore, there is a huge need for tools allowing prediction of mechanical properties of tool steels as a function of composition and heat treatment process variables. The aim of the present work was to explore the potential and possibilities of artificial neural network-based modeling to select and optimize vacuum heat treatment conditions depending on the hot work tool steel composition and required properties. In the current case training of the feedforward neural network with error backpropagation training scheme and four layers of neurons (8-20-20-2) scheme was based on the experimentally obtained tempering diagrams for ten different hot work tool steel compositions and at least two austenitizing temperatures. Results show that this type of modeling can be successfully used for detailed and multifunctional analysis of different influential parameters as well as to optimize heat treatment process of hot work tool steels depending on the composition. In terms of composition, V was found as the most beneficial alloying element increasing hardness and fracture toughness of hot work tool steel; Si, Mn, and Cr increase hardness but lead to reduced fracture toughness, while Mo has the opposite effect. Optimum concentration providing high KIc/HRC ratios would include 0.75 pct Si, 0.4 pct Mn, 5.1 pct Cr, 1.5 pct Mo, and 0.5 pct V, with the optimum heat treatment performed at lower austenitizing and intermediate tempering temperatures.

EPA Optimal Corrosion Control Treatment Regional Training Workshops

EPA Pesticide Factsheets

EPA is hosting face-to-face regional training workshops throughout 2016-2017 on optimal corrosion control treatment (OCCT). These will be held at each of the Regions and is intended for primacy agency staff and technical assistance providers.

The Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures Project: Rationale and Approach.

PubMed

MacLean, Paul S; Rothman, Alexander J; Nicastro, Holly L; Czajkowski, Susan M; Agurs-Collins, Tanya; Rice, Elise L; Courcoulas, Anita P; Ryan, Donna H; Bessesen, Daniel H; Loria, Catherine M

2018-04-01

Individual variability in response to multiple modalities of obesity treatment is well documented, yet our understanding of why some individuals respond while others do not is limited. The etiology of this variability is multifactorial; however, at present, we lack a comprehensive evidence base to identify which factors or combination of factors influence treatment response. This paper provides an overview and rationale of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, which aims to advance the understanding of individual variability in response to adult obesity treatment. This project provides an integrated model for how factors in the behavioral, biological, environmental, and psychosocial domains may influence obesity treatment responses and identify a core set of measures to be used consistently across adult weight-loss trials. This paper provides the foundation for four companion papers that describe the core measures in detail. The accumulation of data on factors across the four ADOPT domains can inform the design and delivery of effective, tailored obesity treatments. ADOPT provides a framework for how obesity researchers can collectively generate this evidence base and is a first step in an ongoing process that can be refined as the science advances. © 2018 The Obesity Society.

Optimism, Symptom Distress, Illness Appraisal, and Coping in Patients With Advanced-Stage Cancer Diagnoses Undergoing Chemotherapy Treatment.

PubMed

Sumpio, Catherine; Jeon, Sangchoon; Northouse, Laurel L; Knobf, M Tish

2017-05-01

To explore the relationships between optimism, self-efficacy, symptom distress, treatment complexity, illness appraisal, coping, and mood disturbance in patients with advanced-stage cancer.
. Cross-sectional study.
. Smilow Cancer Hospital at Yale New Haven in Connecticut, an outpatient comprehensive cancer center.
. A convenience sample of 121 adult patients with stages III-IV cancer undergoing active chemotherapy.
. Participants completed common self-report questionnaires to measure variables. Treatment hours and visits were calculated from data retrieved from medical record review. Mediation and path analysis were conducted to identify direct and indirect pathways from the significant antecedent variables to mood disturbance.
. Dispositional optimism, self-efficacy, social support, treatment complexity, symptom distress, illness appraisal, coping, and mood disturbance.
. Greater optimism and self-efficacy were associated with less negative illness appraisal, less avoidant coping, and decreased mood disturbance. Conversely, greater symptom distress was associated with greater negative illness appraisal, greater avoidant coping, and greater mood disturbance. In the final model, optimism and symptom distress had direct and indirect effects on mood disturbance. Indirect effects were partially mediated by illness appraisal.
. Mood disturbance resulted from an interaction of disease stressors, personal resources, and cognitive appraisal of illness. Avoidant coping was associated with greater disturbed mood, but neither avoidant nor active coping had a significant effect on mood in the multivariate model. 
. Illness appraisal, coping style, and symptom distress are important targets for intervention. Optimism is a beneficial trait and should be included, along with coping style, in comprehensive nursing assessments of patients with cancer.

Refusal of treatment, leading to death: towards optimization of informed consent.

PubMed

Trevor-Deutsch, B; Nelson, R F

1996-12-01

Few medical decisions create more anguish than ones involving cessation of treatment, resulting in the death of a patient. In this article, the ethical and legal aspects of the withdrawal of treatment are examined with respect to a case of a 67-year-old man who fell and sustained a fracture of his second cervical vertebra, rendering him paralysed and respirator-dependent. He immediately requested the withdrawal of treatment, but his family baulked. Ethics consultation recommended delaying the decision, to give the patient enough time to foster optimal comprehension and synthesis of information related to his condition and the consequences; we refer to this process as "optimization of informed consent." When the patient was informed of the delay and the reasons for it, he was assured (and subsequently repeatedly reassured) of his ultimate right to refuse treatment at a future date. On balance, optimization of informed consent promotes patients' autonomy, even though it involves suspending this autonomy for a time. It is also consistent with physicians' responsibility to promote life and avoid premature death.

Methylphenidate dose optimization for ADHD treatment: review of safety, efficacy, and clinical necessity

PubMed Central

Huss, Michael; Duhan, Praveen; Gandhi, Preetam; Chen, Chien-Wei; Spannhuth, Carsten; Kumar, Vinod

2017-01-01

Attention-deficit/hyperactivity disorder (ADHD) is a chronic psychiatric disorder characterized by hyperactivity and/or inattention and is often associated with a substantial impact on psychosocial functioning. Methylphenidate (MPH), a central nervous system stimulant, is commonly used for pharmacological treatment of adults and children with ADHD. Current practice guidelines recommend optimizing MPH dosage to individual patient needs; however, the clinical benefits of individual dose optimization compared with fixed-dose regimens remain unclear. Here we review the available literature on MPH dose optimization from clinical trials and real-world experience on ADHD management. In addition, we report safety and efficacy data from the largest MPH modified-release long-acting Phase III clinical trial conducted to examine benefits of dose optimization in adults with ADHD. Overall, MPH is an effective ADHD treatment with a good safety profile; data suggest that dose optimization may enhance the safety and efficacy of treatment. Further research is required to establish the extent to which short-term clinical benefits of MPH dose optimization translate into improved long-term outcomes for patients with ADHD. PMID:28740389

Methylphenidate dose optimization for ADHD treatment: review of safety, efficacy, and clinical necessity.

PubMed

Huss, Michael; Duhan, Praveen; Gandhi, Preetam; Chen, Chien-Wei; Spannhuth, Carsten; Kumar, Vinod

2017-01-01

Attention-deficit/hyperactivity disorder (ADHD) is a chronic psychiatric disorder characterized by hyperactivity and/or inattention and is often associated with a substantial impact on psychosocial functioning. Methylphenidate (MPH), a central nervous system stimulant, is commonly used for pharmacological treatment of adults and children with ADHD. Current practice guidelines recommend optimizing MPH dosage to individual patient needs; however, the clinical benefits of individual dose optimization compared with fixed-dose regimens remain unclear. Here we review the available literature on MPH dose optimization from clinical trials and real-world experience on ADHD management. In addition, we report safety and efficacy data from the largest MPH modified-release long-acting Phase III clinical trial conducted to examine benefits of dose optimization in adults with ADHD. Overall, MPH is an effective ADHD treatment with a good safety profile; data suggest that dose optimization may enhance the safety and efficacy of treatment. Further research is required to establish the extent to which short-term clinical benefits of MPH dose optimization translate into improved long-term outcomes for patients with ADHD.

Optimization of chitosan treatments for managing microflora in lettuce seeds without affecting germination.

PubMed

Goñi, M G; Moreira, M R; Viacava, G E; Roura, S I

2013-01-30

Many studies have focused on seed decontamination but no one has been capable of eliminating all pathogenic bacteria. Two objectives were followed. First, to assess the in vitro antimicrobial activity of chitosan against: (a) Escherichia coli O157:H7, (b) native microflora of lettuce and (c) native microflora of lettuce seeds. Second, to evaluate the efficiency of chitosan on reducing microflora on lettuce seeds. The overall goal was to find a combination of contact time and chitosan concentration that reduces the microflora of lettuce seeds, without affecting germination. After treatment lettuce seeds presented no detectable microbial counts (<10(2)CFU/50 seeds) for all populations. Moreover, chitosan eliminated E. coli. Regardless of the reduction in the microbial load, a 90% reduction on germination makes imbibition with chitosan, uneconomical. Subsequent treatments identified the optimal treatment as 10 min contact with a 10 g/L chitosan solution, which maintained the highest germination percentage. Copyright © 2012 Elsevier Ltd. All rights reserved.

Discrete particle swarm optimization for identifying community structures in signed social networks.

PubMed

Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng

2014-10-01

Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ensemble of surrogates-based optimization for identifying an optimal surfactant-enhanced aquifer remediation strategy at heterogeneous DNAPL-contaminated sites

NASA Astrophysics Data System (ADS)

Jiang, Xue; Lu, Wenxi; Hou, Zeyu; Zhao, Haiqing; Na, Jin

2015-11-01

The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

Ensemble of Surrogates-based Optimization for Identifying an Optimal Surfactant-enhanced Aquifer Remediation Strategy at Heterogeneous DNAPL-contaminated Sites

NASA Astrophysics Data System (ADS)

Lu, W., Sr.; Xin, X.; Luo, J.; Jiang, X.; Zhang, Y.; Zhao, Y.; Chen, M.; Hou, Z.; Ouyang, Q.

2015-12-01

The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

[Optimal duration of anticoagulant treatment after venous thromboembolic disease].

PubMed

Tromeur, Cécile; Couturaud, Francis

2015-01-01

Determination of the optimal duration of anticoagulant treatment for venous thromboembolic disease (VTED) is a major step in the management of patients with this disease. The assessment depends on the identification of two sets of risk factors: those for recurrence after anticoagulant treatment is stopped and those for hemorrhage in cases of prolonged treatment. Nonetheless, the determination of the optimal duration remains controversial. Recent data finally make it possible to clarify this decision. Recent treatment trials demonstrate that patients at high risk of recurrence receive no sustained benefit from a prolonged but limited anticoagulant treatment. In other words, the choice is simplified: either the risk is low, and treatment for 3months is sufficient, or the risk is high, and treatment must be envisioned for an unlimited duration. Adequate identification of patients eligible for short or unlimited treatment is more crucial than ever and depends on the presence of determinant clinical variables, as the information from laboratory or morphologic tests is generally marginal. The risk of thromboembolic recurrence is low when the initial episode is triggered by a major reversible factor, and a short treatment of 3months is thus indicated. These inducing factors are mainly surgery, lower limb injuries, immobilization for a medical condition, pregnancy, or use of combined estrogen-progestin contraceptives. Among patients with VTED not induced by these factors, the risk of recurrence is high and requires planning anticoagulant treatment for an unlimited duration. Nonetheless, the risk of hemorrhage is a major constraint to such unlimited treatment. Accordingly, the perspectives for secondary prevention that is equally effective but has a lower risk of hemorrhage are currently under evaluation. Finally, patients with cancer are in a separate category, with a very high risk of recurrence that justifies treatment for at least 6months. Copyright © 2015 Elsevier

Model-based optimization of G-CSF treatment during cytotoxic chemotherapy.

PubMed

Schirm, Sibylle; Engel, Christoph; Loibl, Sibylle; Loeffler, Markus; Scholz, Markus

2018-02-01

Although G-CSF is widely used to prevent or ameliorate leukopenia during cytotoxic chemotherapies, its optimal use is still under debate and depends on many therapy parameters such as dosing and timing of cytotoxic drugs and G-CSF, G-CSF pharmaceuticals used and individual risk factors of patients. We integrate available biological knowledge and clinical data regarding cell kinetics of bone marrow granulopoiesis, the cytotoxic effects of chemotherapy and pharmacokinetics and pharmacodynamics of G-CSF applications (filgrastim or pegfilgrastim) into a comprehensive model. The model explains leukocyte time courses of more than 70 therapy scenarios comprising 10 different cytotoxic drugs. It is applied to develop optimized G-CSF schedules for a variety of clinical scenarios. Clinical trial results showed validity of model predictions regarding alternative G-CSF schedules. We propose modifications of G-CSF treatment for the chemotherapies 'BEACOPP escalated' (Hodgkin's disease), 'ETC' (breast cancer), and risk-adapted schedules for 'CHOP-14' (aggressive non-Hodgkin's lymphoma in elderly patients). We conclude that we established a model of human granulopoiesis under chemotherapy which allows predictions of yet untested G-CSF schedules, comparisons between them, and optimization of filgrastim and pegfilgrastim treatment. As a general rule of thumb, G-CSF treatment should not be started too early and patients could profit from filgrastim treatment continued until the end of the chemotherapy cycle.

SU-F-BRD-08: Guaranteed Epsilon-Optimal Treatment Plans with Minimum Number of Beams for SBRT Using RayStation

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

Yarmand, H; Winey, B; Craft, D

2014-06-15

Purpose: To efficiently find quality-guaranteed treatment plans with the minimum number of beams for stereotactic body radiation therapy using RayStation. Methods: For a pre-specified pool of candidate beams we use RayStation (a treatment planning software for clinical use) to identify the deliverable plan which uses all the beams with the minimum dose to organs at risk (OARs) and dose to the tumor and other structures in specified ranges. Then use the dose matrix information for the generated apertures from RayStation to solve a linear program to find the ideal plan with the same objective and constraints allowing use of allmore » beams. Finally we solve a mixed integer programming formulation of the beam angle optimization problem (BAO) with the objective of minimizing the number of beams while remaining in a predetermined epsilon-optimality of the ideal plan with respect to the dose to OARs. Since the treatment plan optimization is a multicriteria optimization problem, the planner can exploit the multicriteria optimization capability of RayStation to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing quality. For the numerical experiments two liver cases and one lung case with 33 non-coplanar beams are considered. Results: The ideal plan uses an impractically large number of beams. The proposed technique reduces the number of beams to the range of practical application (5 to 9 beams) while remaining in the epsilon-optimal range of 1% to 5% optimality gap. Conclusion: The proposed method can be integrated into a general algorithm for fast navigation of the ideal dose distribution Pareto surface and finding the treatment plan with the minimum number of beams, which corresponds to the delivery time, in epsilon-optimality range of the desired ideal plan. The project was supported by the Federal Share of program

Response surface methodology for the optimization of sludge solubilization by ultrasonic pre-treatment

NASA Astrophysics Data System (ADS)

Zheng, Mingyue; Zhang, Xiaohui; Lu, Peng; Cao, Qiguang; Yuan, Yuan; Yue, Mingxing; Fu, Yiwei; Wu, Libin

2018-02-01

The present study examines the optimization of the ultrasonic pre-treatment conditions with response surface experimental design in terms of sludge disintegration efficiency (solubilisation of organic components). Ultrasonic pre-treatment for the maximum solubilization with residual sludge enhanced the SCOD release. Optimization of the ultrasonic pre-treatment was conducted through a Box-Behnken design (three variables, a total of 17 experiments) to determine the effects of three independent variables (power, residence time and TS) on COD solubilization of sludge. The optimal COD was obtained at 17349.4mg/L, when the power was 534.67W, the time was 10.77, and TS was 2%, while the SE of this condition was 28792J/kg TS.

A fast optimization approach for treatment planning of volumetric modulated arc therapy.

PubMed

Yan, Hui; Dai, Jian-Rong; Li, Ye-Xiong

2018-05-30

Volumetric modulated arc therapy (VMAT) is widely used in clinical practice. It not only significantly reduces treatment time, but also produces high-quality treatment plans. Current optimization approaches heavily rely on stochastic algorithms which are time-consuming and less repeatable. In this study, a novel approach is proposed to provide a high-efficient optimization algorithm for VMAT treatment planning. A progressive sampling strategy is employed for beam arrangement of VMAT planning. The initial beams with equal-space are added to the plan in a coarse sampling resolution. Fluence-map optimization and leaf-sequencing are performed for these beams. Then, the coefficients of fluence-maps optimization algorithm are adjusted according to the known fluence maps of these beams. In the next round the sampling resolution is doubled and more beams are added. This process continues until the total number of beams arrived. The performance of VMAT optimization algorithm was evaluated using three clinical cases and compared to those of a commercial planning system. The dosimetric quality of VMAT plans is equal to or better than the corresponding IMRT plans for three clinical cases. The maximum dose to critical organs is reduced considerably for VMAT plans comparing to those of IMRT plans, especially in the head and neck case. The total number of segments and monitor units are reduced for VMAT plans. For three clinical cases, VMAT optimization takes < 5 min accomplished using proposed approach and is 3-4 times less than that of the commercial system. The proposed VMAT optimization algorithm is able to produce high-quality VMAT plans efficiently and consistently. It presents a new way to accelerate current optimization process of VMAT planning.

MO-B-BRB-00: Optimizing the Treatment Planning Process

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

NONE

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequentialmore » events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d

Lack of Clinical Pharmacokinetic Studies to Optimize the Treatment of Neglected Tropical Diseases: A Systematic Review.

PubMed

Verrest, Luka; Dorlo, Thomas P C

2017-06-01

Neglected tropical diseases (NTDs) affect more than one billion people, mainly living in developing countries. For most of these NTDs, treatment is suboptimal. To optimize treatment regimens, clinical pharmacokinetic studies are required where they have not been previously conducted to enable the use of pharmacometric modeling and simulation techniques in their application, which can provide substantial advantages. Our aim was to provide a systematic overview and summary of all clinical pharmacokinetic studies in NTDs and to assess the use of pharmacometrics in these studies, as well as to identify which of the NTDs or which treatments have not been sufficiently studied. PubMed was systematically searched for all clinical trials and case reports until the end of 2015 that described the pharmacokinetics of a drug in the context of treating any of the NTDs in patients or healthy volunteers. Eighty-two pharmacokinetic studies were identified. Most studies included small patient numbers (only five studies included >50 subjects) and only nine (11 %) studies included pediatric patients. A large part of the studies was not very recent; 56 % of studies were published before 2000. Most studies applied non-compartmental analysis methods for pharmacokinetic analysis (62 %). Twelve studies used population-based compartmental analysis (15 %) and eight (10 %) additionally performed simulations or extrapolation. For ten out of the 17 NTDs, none or only very few pharmacokinetic studies could be identified. For most NTDs, adequate pharmacokinetic studies are lacking and population-based modeling and simulation techniques have not generally been applied. Pharmacokinetic clinical trials that enable population pharmacokinetic modeling are needed to make better use of the available data. Simulation-based studies should be employed to enable the design of improved dosing regimens and more optimally use the limited resources to effectively provide therapy in this neglected area.

An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

PubMed

Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

2017-08-17

It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.

A computational method for optimizing fuel treatment locations

Treesearch

Mark A. Finney

2006-01-01

Modeling and experiments have suggested that spatial fuel treatment patterns can influence the movement of large fires. On simple theoretical landscapes consisting of two fuel types (treated and untreated) optimal patterns can be analytically derived that disrupt fire growth efficiently (i.e. with less area treated than random patterns). Although conceptually simple,...

Model to Determine the Optimal Dietary Elimination Strategy for Treatment of Eosinophilic Esophagitis.

PubMed

Zhan, Tiannan; Ali, Ayman; Choi, Jin G; Lee, Minyi; Leung, John; Dellon, Evan S; Garber, John J; Hur, Chin

2018-05-03

Elimination diets are effective treatments for eosinophilic esophagitis (EoE), but foods that activate esophagitis are identified empirically, via a process that involves multiple esophagogastroduodenoscopies (EGDs). No optimized approach has been developed to identify foods that activate EoE. We aimed to compare clinical strategies to provide data to guide treatment. We developed a computer-based simulation model to determine the optimal empiric elimination strategy based on reported prevalence values for foods that activate EoE. These were identified in a systematic review, searching PubMed through October 1, 2017 for prospective and retrospective studies of EoE and diet. Each patient in our virtual cohort was assigned profile comprising as many as 12 foods known to induce EoE, including dairy, wheat, eggs, soy, nuts, seafood, beef, corn, chicken, potato, pork, and/or rice. To balance the strategy success rate with the number of EGDs required for food identification, we applied an efficiency frontier approach. Strategies on the frontier were the most efficient, requiring fewer EGDs for higher or equivalent success rates relative to their comparable, neighboring strategies. In all simulations, we found the 1,4,8-food and 1,3-food strategies to be the most efficient in identifying foods that induce EoE, resulting in the highest rate of the correct identification of food triggers balanced by the number of EGDs required to complete the food elimination strategy. Both strategies begin with elimination of dairy; if EoE remission is not achieved, the 1,3 diet proceeds to eliminate wheat and eggs in addition to dairy, and the 1,4,8 strategy removes wheat, eggs, dairy, and soy. In the case of persistent EoE after the second round of food elimination, the 1,3-food strategy terminates, whereas the 1,4,8-food diet eliminates corn, chicken, beef, and pork. The 1,4,8-food resulted in correct identification of foods that activated esophagitis in 76.68% of patients, with a mean

Consumer-identified barriers and strategies for optimizing technology use in the workplace.

PubMed

De Jonge, Desleigh M; Rodger, Sylvia A

2006-01-01

This article explores the experiences of 26 assistive technology (AT) users having a range of physical impairments as they optimized their use of technology in the workplace. A qualitative research design was employed using in-depth, open-ended interviews and observations of AT users in the workplace. Participants identified many factors that limited their use of technology such as discomfort and pain, limited knowledge of the technology's features, and the complexity of the technology. The amount of time required for training, limited work time available for mastery, cost of training and limitations of the training provided, resulted in an over-reliance on trial and error and informal support networks and a sense of isolation. AT users enhanced their use of technology by addressing the ergonomics of the workstation and customizing the technology to address individual needs and strategies. Other key strategies included tailored training and learning support as well as opportunities to practice using the technology and explore its features away from work demands. This research identified structures important for effective AT use in the workplace which need to be put in place to ensure that AT users are able to master and optimize their use of technology.

Identifying Molecular Targets for PTSD Treatment Using Single Prolonged Stress

DTIC Science & Technology

2015-10-01

1 AWARD NUMBER: W81XWH-13-1-0377 TITLE: Identifying Molecular Targets For PTSD Treatment Using Single Prolonged Stress PRINCIPAL...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-13-1-0377 Identifying Molecular Targets For PTSD Treatment Using Single Prolonged Stress 5b. GRANT...brain GR and β-AR expression alters glutamatergic and GABAergic function in neural circuits that mediate SPS-induced deficits in extinction retention

Optimization and experimental validation of a thermal cycle that maximizes entropy coefficient fisher identifiability for lithium iron phosphate cells

NASA Astrophysics Data System (ADS)

Mendoza, Sergio; Rothenberger, Michael; Hake, Alison; Fathy, Hosam

2016-03-01

This article presents a framework for optimizing the thermal cycle to estimate a battery cell's entropy coefficient at 20% state of charge (SOC). Our goal is to maximize Fisher identifiability: a measure of the accuracy with which a parameter can be estimated. Existing protocols in the literature for estimating entropy coefficients demand excessive laboratory time. Identifiability optimization makes it possible to achieve comparable accuracy levels in a fraction of the time. This article demonstrates this result for a set of lithium iron phosphate (LFP) cells. We conduct a 24-h experiment to obtain benchmark measurements of their entropy coefficients. We optimize a thermal cycle to maximize parameter identifiability for these cells. This optimization proceeds with respect to the coefficients of a Fourier discretization of this thermal cycle. Finally, we compare the estimated parameters using (i) the benchmark test, (ii) the optimized protocol, and (iii) a 15-h test from the literature (by Forgez et al.). The results are encouraging for two reasons. First, they confirm the simulation-based prediction that the optimized experiment can produce accurate parameter estimates in 2 h, compared to 15-24. Second, the optimized experiment also estimates a thermal time constant representing the effects of thermal capacitance and convection heat transfer.

Intraprocedural yttrium-90 positron emission tomography/CT for treatment optimization of yttrium-90 radioembolization.

PubMed

Bourgeois, Austin C; Chang, Ted T; Bradley, Yong C; Acuff, Shelley N; Pasciak, Alexander S

2014-02-01

Radioembolization with yttrium-90 ((90)Y) microspheres relies on delivery of appropriate treatment activity to ensure patient safety and optimize treatment efficacy. We report a case in which (90)Y positron emission tomography (PET)/computed tomography (CT) was performed to optimize treatment planning during a same-day, three-part treatment session. This treatment consisted of (i) an initial (90)Y infusion with a dosage determined using an empiric treatment planning model, (ii) quantitative (90)Y PET/CT imaging, and (iii) a secondary infusion with treatment planning based on quantitative imaging data with the goal of delivering a specific total tumor absorbed dose. © 2014 SIR Published by SIR All rights reserved.

Optimizing Multi-Station Template Matching to Identify and Characterize Induced Seismicity in Ohio

NASA Astrophysics Data System (ADS)

Brudzinski, M. R.; Skoumal, R.; Currie, B. S.

2014-12-01

As oil and gas well completions utilizing multi-stage hydraulic fracturing have become more commonplace, the potential for seismicity induced by the deep disposal of frac-related flowback waters and the hydraulic fracturing process itself has become increasingly important. While it is rare for these processes to induce felt seismicity, the recent increase in the number of deep injection wells and volumes injected have been suspected to have contributed to a substantial increase of events = M 3 in the continental U.S. over the past decade. Earthquake template matching using multi-station waveform cross-correlation is an adept tool for investigating potentially induced sequences due to its proficiency at identifying similar/repeating seismic events. We have sought to refine this approach by investigating a variety of seismic sequences and determining the optimal parameters (station combinations, template lengths and offsets, filter frequencies, data access method, etc.) for identifying induced seismicity. When applied to a sequence near a wastewater injection well in Youngstown, Ohio, our optimized template matching routine yielded 566 events while other template matching studies found ~100-200 events. We also identified 77 events on 4-12 March 2014 that are temporally and spatially correlated with active hydraulic fracturing in Poland Township, Ohio. We find similar improvement in characterizing sequences in Washington and Harrison Counties, which appear to be related to wastewater injection and hydraulic fracturing, respectively. In the Youngstown and Poland Township cases, focal mechanisms and double difference relocation using the cross-correlation matrix finds left-lateral faults striking roughly east-west near the top of the basement. We have also used template matching to determine isolated earthquakes near several other wastewater injection wells are unlikely to be induced based on a lack of similar/repeating sequences. Optimized template matching utilizes

Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

PubMed

Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

2016-07-01

The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Geographic information system-based healthcare waste management planning for treatment site location and optimal transportation routeing.

PubMed

Shanmugasundaram, Jothiganesh; Soulalay, Vongdeuane; Chettiyappan, Visvanathan

2012-06-01

In Lao People's Democratic Republic (Lao PDR), a growth of healthcare centres, and the environmental hazards and public health risks typically accompanying them, increased the need for healthcare waste (HCW) management planning. An effective planning of an HCW management system including components such as the treatment plant siting and an optimized routeing system for collection and transportation of waste is deemed important. National government offices at developing countries often lack the proper tools and methodologies because of the high costs usually associated with them. However, this study attempts to demonstrate the use of an inexpensive GIS modelling tool for healthcare waste management in the country. Two areas were designed for this study on HCW management, including: (a) locating centralized treatment plants and designing optimum travel routes for waste collection from nearby healthcare facilities; and (b) utilizing existing hospital incinerators and designing optimum routes for collecting waste from nearby healthcare facilities. Spatial analysis paved the way to understand the spatial distribution of healthcare wastes and to identify hotspots of higher waste generating locations. Optimal route models were designed for collecting and transporting HCW to treatment plants, which also highlights constraints in collecting and transporting waste for treatment and disposal. The proposed model can be used as a decision support tool for the efficient management of hospital wastes by government healthcare waste management authorities and hospitals.

A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning

NASA Astrophysics Data System (ADS)

Guthier, C.; Aschenbrenner, K. P.; Buergy, D.; Ehmann, M.; Wenz, F.; Hesser, J. W.

2015-03-01

This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced.

A new optimization method using a compressed sensing inspired solver for real-time LDR-brachytherapy treatment planning.

PubMed

Guthier, C; Aschenbrenner, K P; Buergy, D; Ehmann, M; Wenz, F; Hesser, J W

2015-03-21

This work discusses a novel strategy for inverse planning in low dose rate brachytherapy. It applies the idea of compressed sensing to the problem of inverse treatment planning and a new solver for this formulation is developed. An inverse planning algorithm was developed incorporating brachytherapy dose calculation methods as recommended by AAPM TG-43. For optimization of the functional a new variant of a matching pursuit type solver is presented. The results are compared with current state-of-the-art inverse treatment planning algorithms by means of real prostate cancer patient data. The novel strategy outperforms the best state-of-the-art methods in speed, while achieving comparable quality. It is able to find solutions with comparable values for the objective function and it achieves these results within a few microseconds, being up to 542 times faster than competing state-of-the-art strategies, allowing real-time treatment planning. The sparse solution of inverse brachytherapy planning achieved with methods from compressed sensing is a new paradigm for optimization in medical physics. Through the sparsity of required needles and seeds identified by this method, the cost of intervention may be reduced.

Pain in children--are we accomplishing the optimal pain treatment?

PubMed

Lundeberg, Stefan

2015-01-01

Morphine, paracetamol and local anesthetics have for a long time been the foremost used analgesics in the pediatric patient by tradition but not always enough effective and associated with side effects. The purpose with this article is to propose alternative approaches in pain management, not always supported up by substantial scientific work but from a combination of science and clinical experience in the field. The scientific literature has been reviewed in parts regarding different aspects of pain assessment and analgesics used for treatment of diverse pain conditions with focus on procedural and acute pain. Clinical experience has been added to form the suggested improvements in accomplishing an improved pain management in pediatric patients. The aim with pain management in children should be a tailored analgesic medication with an individual acceptable pain level and optimal degree of mobilization with as little side effects as possible. Simple techniques of pain control are as effective as and complex techniques in pediatrics but the technique used is not of the highest importance in achieving a good pain management. Increased interest and improved education of the doctors prescribing analgesics is important in accomplishing a better pain management. The optimal treatment with analgesics is depending on the analysis of pain origin and analgesics used should be adjusted thereafter. A multimodal treatment regime is advocated for optimal analgesic effect. © 2014 John Wiley & Sons Ltd.

Treatment planning, optimization, and beam delivery technqiues for intensity modulated proton therapy

NASA Astrophysics Data System (ADS)

Sengbusch, Evan R.

Physical properties of proton interactions in matter give them a theoretical advantage over photons in radiation therapy for cancer treatment, but they are seldom used relative to photons. The primary barriers to wider acceptance of proton therapy are the technical feasibility, size, and price of proton therapy systems. Several aspects of the proton therapy landscape are investigated, and new techniques for treatment planning, optimization, and beam delivery are presented. The results of these investigations suggest a means by which proton therapy can be delivered more efficiently, effectively, and to a much larger proportion of eligible patients. An analysis of the existing proton therapy market was performed. Personal interviews with over 30 radiation oncology leaders were conducted with regard to the current and future use of proton therapy. In addition, global proton therapy market projections are presented. The results of these investigations serve as motivation and guidance for the subsequent development of treatment system designs and treatment planning, optimization, and beam delivery methods. A major factor impacting the size and cost of proton treatment systems is the maximum energy of the accelerator. Historically, 250 MeV has been the accepted value, but there is minimal quantitative evidence in the literature that supports this standard. A retrospective study of 100 patients is presented that quantifies the maximum proton kinetic energy requirements for cancer treatment, and the impact of those results with regard to treatment system size, cost, and neutron production is discussed. This study is subsequently expanded to include 100 cranial stereotactic radiosurgery (SRS) patients, and the results are discussed in the context of a proposed dedicated proton SRS treatment system. Finally, novel proton therapy optimization and delivery techniques are presented. Algorithms are developed that optimize treatment plans over beam angle, spot size, spot spacing

The Survey of Treatment Entry Pressures (STEP): identifying client's reasons for entering substance abuse treatment.

PubMed

Dugosh, Karen Leggett; Festinger, David S; Lynch, Kevin G; Marlowe, Douglas B

2014-10-01

Systematically identifying reasons that clients enter substance abuse treatment may allow clinicians to immediately focus on issues of greatest relevance to the individual and enhance treatment engagement. We developed the Survey of Treatment Entry Pressures (STEP) to identify the specific factors that precipitated an individual's treatment entry. The instrument contains 121 items from 6 psychosocial domains (i.e., family, financial, social, medical, psychiatric, legal). The current study examined the STEP's psychometric properties. A total of 761 participants from various treatment settings and modalities completed the STEP prior to treatment admission and 4-7 days later. Analyses were performed to examine the instrument's psychometric properties including item response rates, test-retest reliability, internal consistency, and factor structure. The items displayed adequate test-retest reliability and internal consistency within each psychosocial domain. Generally, results from exploratory and confirmatory factor analyses support a 2-factor structure reflecting type of reinforcement schedule. The study provides preliminary support for the psychometric properties of the STEP. The STEP may provide a reliable way for clinicians to characterize and capitalize on a client's treatment motivation early on which may serve to improve treatment retention and therapeutic outcomes. © 2014 Wiley Periodicals, Inc.

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

PubMed Central

Haanstra, Tsjitske M.; Tilbury, Claire; Kamper, Steven J.; Tordoir, Rutger L.; Vliet Vlieland, Thea P. M.; Nelissen, Rob G. H. H.; Cuijpers, Pim; de Vet, Henrica C. W.; Dekker, Joost; Knol, Dirk L.; Ostelo, Raymond W.

2015-01-01

Objectives The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting. Methods Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA) (Total N = 361; 182 THA; 179 TKA), completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models. Results The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors) a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor. Conclusion Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance. PMID:26214176

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

PubMed

Haanstra, Tsjitske M; Tilbury, Claire; Kamper, Steven J; Tordoir, Rutger L; Vliet Vlieland, Thea P M; Nelissen, Rob G H H; Cuijpers, Pim; de Vet, Henrica C W; Dekker, Joost; Knol, Dirk L; Ostelo, Raymond W

2015-01-01

The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting. Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA) (Total N = 361; 182 THA; 179 TKA), completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models. The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors) a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor. Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance.

Expected treatment dose construction and adaptive inverse planning optimization: Implementation for offline head and neck cancer adaptive radiotherapy

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

Yan Di; Liang Jian

Purpose: To construct expected treatment dose for adaptive inverse planning optimization, and evaluate it on head and neck (h and n) cancer adaptive treatment modification. Methods: Adaptive inverse planning engine was developed and integrated in our in-house adaptive treatment control system. The adaptive inverse planning engine includes an expected treatment dose constructed using the daily cone beam (CB) CT images in its objective and constrains. Feasibility of the adaptive inverse planning optimization was evaluated retrospectively using daily CBCT images obtained from the image guided IMRT treatment of 19 h and n cancer patients. Adaptive treatment modification strategies with respect tomore » the time and the number of adaptive inverse planning optimization during the treatment course were evaluated using the cumulative treatment dose in organs of interest constructed using all daily CBCT images. Results: Expected treatment dose was constructed to include both the delivered dose, to date, and the estimated dose for the remaining treatment during the adaptive treatment course. It was used in treatment evaluation, as well as in constructing the objective and constraints for adaptive inverse planning optimization. The optimization engine is feasible to perform planning optimization based on preassigned treatment modification schedule. Compared to the conventional IMRT, the adaptive treatment for h and n cancer illustrated clear dose-volume improvement for all critical normal organs. The dose-volume reductions of right and left parotid glands, spine cord, brain stem and mandible were (17 {+-} 6)%, (14 {+-} 6)%, (11 {+-} 6)%, (12 {+-} 8)%, and (5 {+-} 3)% respectively with the single adaptive modification performed after the second treatment week; (24 {+-} 6)%, (22 {+-} 8)%, (21 {+-} 5)%, (19 {+-} 8)%, and (10 {+-} 6)% with three weekly modifications; and (28 {+-} 5)%, (25 {+-} 9)%, (26 {+-} 5)%, (24 {+-} 8)%, and (15 {+-} 9)% with five weekly modifications

Optimizing the patient for surgical treatment of the wound.

PubMed

Myers, Wesley T; Leong, Mimi; Phillips, Linda G

2007-10-01

Plastic surgeons are consulted often to close wounds that fail or are difficult to heal. Optimizing the patient's medical condition before surgical closure of a wound can mean the difference between a successful outcome and an undesirable one. It is imperative that plastic surgeons have an extensive knowledge of the modifiable risk factors affecting the wound-healing process and their subsequent complications. This knowledge allows the surgeon to tailor the treatment options and intervene when appropriate to optimize outcomes for successful surgical closure of a wound. Whether the impairments to wound healing and closure are local or systemic, they must be addressed appropriately.

Automated medial axis seeding and guided evolutionary simulated annealing for optimization of gamma knife radiosurgery treatment plans

NASA Astrophysics Data System (ADS)

Zhang, Pengpeng

The Leksell Gamma KnifeRTM (LGK) is a tool for providing accurate stereotactic radiosurgical treatment of brain lesions, especially tumors. Currently, the treatment planning team "forward" plans radiation treatment parameters while viewing a series of 2D MR scans. This primarily manual process is cumbersome and time consuming because the difficulty in visualizing the large search space for the radiation parameters (i.e., shot overlap, number, location, size, and weight). I hypothesize that a computer-aided "inverse" planning procedure that utilizes tumor geometry and treatment goals could significantly improve the planning process and therapeutic outcome of LGK radiosurgery. My basic observation is that the treatment team is best at identification of the location of the lesion and prescribing a lethal, yet safe, radiation dose. The treatment planning computer is best at determining both the 3D tumor geometry and optimal LGK shot parameters necessary to deliver a desirable dose pattern to the tumor while sparing adjacent normal tissue. My treatment planning procedure asks the neurosurgeon to identify the tumor and critical structures in MR images and the oncologist to prescribe a tumoricidal radiation dose. Computer-assistance begins with geometric modeling of the 3D tumor's medial axis properties. This begins with a new algorithm, a Gradient-Phase Plot (G-P Plot) decomposition of the tumor object's medial axis. I have found that medial axis seeding, while insufficient in most cases to produce an acceptable treatment plan, greatly reduces the solution space for Guided Evolutionary Simulated Annealing (GESA) treatment plan optimization by specifying an initial estimate for shot number, size, and location, but not weight. They are used to generate multiple initial plans which become initial seed plans for GESA. The shot location and weight parameters evolve and compete in the GESA procedure. The GESA objective function optimizes tumor irradiation (i.e., as close to

Geometric parameter analysis to predetermine optimal radiosurgery technique for the treatment of arteriovenous malformation

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

Mestrovic, Ante; Clark, Brenda G.; Department of Medical Physics, British Columbia Cancer Agency, Vancouver, British Columbia

2005-11-01

Purpose: To develop a method of predicting the values of dose distribution parameters of different radiosurgery techniques for treatment of arteriovenous malformation (AVM) based on internal geometric parameters. Methods and Materials: For each of 18 previously treated AVM patients, four treatment plans were created: circular collimator arcs, dynamic conformal arcs, fixed conformal fields, and intensity-modulated radiosurgery. An algorithm was developed to characterize the target and critical structure shape complexity and the position of the critical structures with respect to the target. Multiple regression was employed to establish the correlation between the internal geometric parameters and the dose distribution for differentmore » treatment techniques. The results from the model were applied to predict the dosimetric outcomes of different radiosurgery techniques and select the optimal radiosurgery technique for a number of AVM patients. Results: Several internal geometric parameters showing statistically significant correlation (p < 0.05) with the treatment planning results for each technique were identified. The target volume and the average minimum distance between the target and the critical structures were the most effective predictors for normal tissue dose distribution. The structure overlap volume with the target and the mean distance between the target and the critical structure were the most effective predictors for critical structure dose distribution. The predicted values of dose distribution parameters of different radiosurgery techniques were in close agreement with the original data. Conclusions: A statistical model has been described that successfully predicts the values of dose distribution parameters of different radiosurgery techniques and may be used to predetermine the optimal technique on a patient-to-patient basis.« less

SU-D-BRD-01: Cloud-Based Radiation Treatment Planning: Performance Evaluation of Dose Calculation and Plan Optimization

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

Na, Y; Kapp, D; Kim, Y

2014-06-01

Purpose: To report the first experience on the development of a cloud-based treatment planning system and investigate the performance improvement of dose calculation and treatment plan optimization of the cloud computing platform. Methods: A cloud computing-based radiation treatment planning system (cc-TPS) was developed for clinical treatment planning. Three de-identified clinical head and neck, lung, and prostate cases were used to evaluate the cloud computing platform. The de-identified clinical data were encrypted with 256-bit Advanced Encryption Standard (AES) algorithm. VMAT and IMRT plans were generated for the three de-identified clinical cases to determine the quality of the treatment plans and computationalmore » efficiency. All plans generated from the cc-TPS were compared to those obtained with the PC-based TPS (pc-TPS). The performance evaluation of the cc-TPS was quantified as the speedup factors for Monte Carlo (MC) dose calculations and large-scale plan optimizations, as well as the performance ratios (PRs) of the amount of performance improvement compared to the pc-TPS. Results: Speedup factors were improved up to 14.0-fold dependent on the clinical cases and plan types. The computation times for VMAT and IMRT plans with the cc-TPS were reduced by 91.1% and 89.4%, respectively, on average of the clinical cases compared to those with pc-TPS. The PRs were mostly better for VMAT plans (1.0 ≤ PRs ≤ 10.6 for the head and neck case, 1.2 ≤ PRs ≤ 13.3 for lung case, and 1.0 ≤ PRs ≤ 10.3 for prostate cancer cases) than for IMRT plans. The isodose curves of plans on both cc-TPS and pc-TPS were identical for each of the clinical cases. Conclusion: A cloud-based treatment planning has been setup and our results demonstrate the computation efficiency of treatment planning with the cc-TPS can be dramatically improved while maintaining the same plan quality to that obtained with the pc-TPS. This work was supported in part by the National Cancer

Obtaining the Optimal Dose in Alcohol Dependence Studies

PubMed Central

Wages, Nolan A.; Liu, Lei; O’Quigley, John; Johnson, Bankole A.

2012-01-01

In alcohol dependence studies, the treatment effect at different dose levels remains to be ascertained. Establishing this effect would aid us in identifying the best dose that has satisfactory efficacy while minimizing the rate of adverse events. We advocate the use of dose-finding methodology that has been successfully implemented in the cancer and HIV settings to identify the optimal dose in a cost-effective way. Specifically, we describe the continual reassessment method (CRM), an adaptive design proposed for cancer trials to reconcile the needs of dose-finding experiments with the ethical demands of established medical practice. We are applying adaptive designs for identifying the optimal dose of medications for the first time in the context of pharmacotherapy research in alcoholism. We provide an example of a topiramate trial as an illustration of how adaptive designs can be used to locate the optimal dose in alcohol treatment trials. It is believed that the introduction of adaptive design methods will enable the development of medications for the treatment of alcohol dependence to be accelerated. PMID:23189064

Optimization of a thermal hydrolysis process for sludge pre-treatment.

PubMed

Sapkaite, I; Barrado, E; Fdz-Polanco, F; Pérez-Elvira, S I

2017-05-01

At industrial scale, thermal hydrolysis is the most used process to enhance biodegradability of the sludge produced in wastewater treatment plants. Through statistically guided Box-Behnken experimental design, the present study analyses the effect of TH as pre-treatment applied to activated sludge. The selected process variables were temperature (130-180 °C), time (5-50 min) and decompression mode (slow or steam-explosion effect), and the parameters evaluated were sludge solubilisation and methane production by anaerobic digestion. A quadratic polynomial model was generated to compare the process performance for the 15 different combinations of operation conditions by modifying the process variables evaluated. The statistical analysis performed exhibited that methane production and solubility were significantly affected by pre-treatment time and temperature. During high intensity pre-treatment (high temperature and long times), the solubility increased sharply while the methane production exhibited the opposite behaviour, indicating the formation of some soluble but non-biodegradable materials. Therefore, solubilisation is not a reliable parameter to quantify the efficiency of a thermal hydrolysis pre-treatment, since it is not directly related to methane production. Based on the operational parameters optimization, the estimated optimal thermal hydrolysis conditions to enhance of sewage sludge digestion were: 140-170 °C heating temperature, 5-35min residence time, and one sudden decompression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational design of treatment strategies for proactive therapy on atopic dermatitis using optimal control theory

PubMed Central

Christodoulides, Panayiotis; Hirata, Yoshito; Domínguez-Hüttinger, Elisa; Danby, Simon G.; Cork, Michael J.; Williams, Hywel C.; Aihara, Kazuyuki

2017-01-01

Atopic dermatitis (AD) is a common chronic skin disease characterized by recurrent skin inflammation and a weak skin barrier, and is known to be a precursor to other allergic diseases such as asthma. AD affects up to 25% of children worldwide and the incidence continues to rise. There is still uncertainty about the optimal treatment strategy in terms of choice of treatment, potency, duration and frequency. This study aims to develop a computational method to design optimal treatment strategies for the clinically recommended ‘proactive therapy’ for AD. Proactive therapy aims to prevent recurrent flares once the disease has been brought under initial control. Typically, this is done by using an anti-inflammatory treatment such as a potent topical corticosteroid intensively for a few weeks to ‘get control’, followed by intermittent weekly treatment to suppress subclinical inflammation to ‘keep control’. Using a hybrid mathematical model of AD pathogenesis that we recently proposed, we computationally derived the optimal treatment strategies for individual virtual patient cohorts, by recursively solving optimal control problems using a differential evolution algorithm. Our simulation results suggest that such an approach can inform the design of optimal individualized treatment schedules that include application of topical corticosteroids and emollients, based on the disease status of patients observed on their weekly hospital visits. We demonstrate the potential and the gaps of our approach to be applied to clinical settings. This article is part of the themed issue ‘Mathematical methods in medicine: neuroscience, cardiology and pathology’. PMID:28507230

Optimization of wastewater treatment alternative selection by hierarchy grey relational analysis.

PubMed

Zeng, Guangming; Jiang, Ru; Huang, Guohe; Xu, Min; Li, Jianbing

2007-01-01

This paper describes an innovative systematic approach, namely hierarchy grey relational analysis for optimal selection of wastewater treatment alternatives, based on the application of analytic hierarchy process (AHP) and grey relational analysis (GRA). It can be applied for complicated multicriteria decision-making to obtain scientific and reasonable results. The effectiveness of this approach was verified through a real case study. Four wastewater treatment alternatives (A(2)/O, triple oxidation ditch, anaerobic single oxidation ditch and SBR) were evaluated and compared against multiple economic, technical and administrative performance criteria, including capital cost, operation and maintenance (O and M) cost, land area, removal of nitrogenous and phosphorous pollutants, sludge disposal effect, stability of plant operation, maturity of technology and professional skills required for O and M. The result illustrated that the anaerobic single oxidation ditch was the optimal scheme and would obtain the maximum general benefits for the wastewater treatment plant to be constructed.

Therapists' perspectives on optimal treatment for pathological narcissism.

PubMed

Kealy, David; Goodman, Geoff; Rasmussen, Brian; Weideman, Rene; Ogrodniczuk, John S

2017-01-01

This study used Q methodology to explore clinicians' perspectives regarding optimal psychotherapy process in the treatment of pathological narcissism, a syndrome of impaired self-regulation. Participants were 34 psychotherapists of various disciplines and theoretical orientations who reviewed 3 clinical vignettes portraying hypothetical cases of grandiose narcissism, vulnerable narcissism, and panic disorder without pathological narcissism. Participants then used the Psychotherapy Process Q set, a 100-item Q-sort instrument, to indicate their views regarding optimal therapy process for each hypothetical case. By-person principal components analysis with varimax rotation was conducted on all 102 Q-sorts, revealing 4 components representing clinicians' perspectives on ideal therapy processes for narcissistic and non-narcissistic patients. These perspectives were then analyzed regarding their relationship to established therapy models. The first component represented an introspective, relationally oriented therapy process and was strongly correlated with established psychodynamic treatments. The second component, most frequently endorsed for the panic disorder vignette, consisted of a cognitive and alliance-building approach that correlated strongly with expert-rated cognitive-behavioral therapy. The third and fourth components involved therapy processes focused on the challenging interpersonal behaviors associated with narcissistic vulnerability and grandiosity, respectively. The perspectives on therapy processes that emerged in this study reflect different points of emphasis in the treatment of pathological narcissism, and may serve as prototypes of therapist-generated approaches to patients suffering from this issue. The findings suggest several areas for further empirical inquiry regarding psychotherapy with this population. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Patient specific optimization-based treatment planning for catheter-based ultrasound hyperthermia and thermal ablation

NASA Astrophysics Data System (ADS)

Prakash, Punit; Chen, Xin; Wootton, Jeffery; Pouliot, Jean; Hsu, I.-Chow; Diederich, Chris J.

2009-02-01

A 3D optimization-based thermal treatment planning platform has been developed for the application of catheter-based ultrasound hyperthermia in conjunction with high dose rate (HDR) brachytherapy for treating advanced pelvic tumors. Optimal selection of applied power levels to each independently controlled transducer segment can be used to conform and maximize therapeutic heating and thermal dose coverage to the target region, providing significant advantages over current hyperthermia technology and improving treatment response. Critical anatomic structures, clinical target outlines, and implant/applicator geometries were acquired from sequential multi-slice 2D images obtained from HDR treatment planning and used to reconstruct patient specific 3D biothermal models. A constrained optimization algorithm was devised and integrated within a finite element thermal solver to determine a priori the optimal applied power levels and the resulting 3D temperature distributions such that therapeutic heating is maximized within the target, while placing constraints on maximum tissue temperature and thermal exposure of surrounding non-targeted tissue. This optimizationbased treatment planning and modeling system was applied on representative cases of clinical implants for HDR treatment of cervix and prostate to evaluate the utility of this planning approach. The planning provided significant improvement in achievable temperature distributions for all cases, with substantial increase in T90 and thermal dose (CEM43T90) coverage to the hyperthermia target volume while decreasing maximum treatment temperature and reducing thermal dose exposure to surrounding non-targeted tissues and thermally sensitive rectum and bladder. This optimization based treatment planning platform with catheter-based ultrasound applicators is a useful tool that has potential to significantly improve the delivery of hyperthermia in conjunction with HDR brachytherapy. The planning platform has been extended

A two‐point scheme for optimal breast IMRT treatment planning

PubMed Central

2013-01-01

We propose an approach to determining optimal beam weights in breast/chest wall IMRT treatment plans. The goal is to decrease breathing effect and to maximize skin dose if the skin is included in the target or, otherwise, to minimize the skin dose. Two points in the target are utilized to calculate the optimal weights. The optimal plan (i.e., the plan with optimal beam weights) consists of high energy unblocked beams, low energy unblocked beams, and IMRT beams. Six breast and five chest wall cases were retrospectively planned with this scheme in Eclipse, including one breast case where CTV was contoured by the physician. Compared with 3D CRT plans composed of unblocked and field‐in‐field beams, the optimal plans demonstrated comparable or better dose uniformity, homogeneity, and conformity to the target, especially at beam junction when supraclavicular nodes are involved. Compared with nonoptimal plans (i.e., plans with nonoptimized weights), the optimal plans had better dose distributions at shallow depths close to the skin, especially in cases where breathing effect was taken into account. This was verified with experiments using a MapCHECK device attached to a motion simulation table (to mimic motion caused by breathing). PACS number: 87.55 de PMID:24257291

Identifying an optimal cutpoint value for the diagnosis of hypertriglyceridemia in the nonfasting state

PubMed Central

White, Khendi T.; Moorthy, M.V.; Akinkuolie, Akintunde O.; Demler, Olga; Ridker, Paul M; Cook, Nancy R.; Mora, Samia

2015-01-01

Background Nonfasting triglycerides are similar to or superior to fasting triglycerides at predicting cardiovascular events. However, diagnostic cutpoints are based on fasting triglycerides. We examined the optimal cutpoint for increased nonfasting triglycerides. Methods Baseline nonfasting (<8 hours since last meal) samples were obtained from 6,391 participants in the Women’s Health Study, followed prospectively for up to 17 years. The optimal diagnostic threshold for nonfasting triglycerides, determined by logistic regression models using c-statistics and Youden index (sum of sensitivity and specificity minus one), was used to calculate hazard ratios for incident cardiovascular events. Performance was compared to thresholds recommended by the American Heart Association (AHA) and European guidelines. Results The optimal threshold was 175 mg/dL (1.98 mmol/L), corresponding to a c-statistic of 0.656 that was statistically better than the AHA cutpoint of 200 mg/dL (c-statistic of 0.628). For nonfasting triglycerides above and below 175 mg/dL, adjusting for age, hypertension, smoking, hormone use, and menopausal status, the hazard ratio for cardiovascular events was 1.88 (95% CI, 1.52–2.33, P<0.001), and for triglycerides measured at 0–4 and 4–8 hours since last meal, hazard ratios (95%CIs) were 2.05 (1.54– 2.74) and 1.68 (1.21–2.32), respectively. Performance of this optimal cutpoint was validated using ten-fold cross-validation and bootstrapping of multivariable models that included standard risk factors plus total and HDL cholesterol, diabetes, body-mass index, and C-reactive protein. Conclusions In this study of middle aged and older apparently healthy women, we identified a diagnostic threshold for nonfasting hypertriglyceridemia of 175 mg/dL (1.98 mmol/L), with the potential to more accurately identify cases than the currently recommended AHA cutpoint. PMID:26071491

Managing vegetation in surface-flow wastewater-treatment wetlands for optimal treatment performance

USGS Publications Warehouse

Thullen, J.S.; Sartoris, J.J.; Nelson, S.M.

2005-01-01

Constructed wetlands that mimic natural marshes have been used as low-cost alternatives to conventional secondary or tertiary wastewater treatment in the U.S. for at least 30 years. However, the general level of understanding of internal treatment processes and their relation to vegetation and habitat quality has not grown in proportion to the popularity of these systems. We have studied internal processes in surface-flow constructed wastewater-treatment wetlands throughout the southwestern U.S. since 1990. At any given time, the water quality, hydraulics, water temperature, soil chemistry, available oxygen, microbial communities, macroinvertebrates, and vegetation each greatly affect the treatment capabilities of the wetland. Inside the wetland, each of these components plays a functional role and the treatment outcome depends upon how the various components interact. Vegetation plays a uniquely important role in water treatment due to the large number of functions it supports, particularly with regard to nitrogen transformations. However, it has been our experience that vegetation management is critical for achieving and sustaining optimal treatment function. Effective water treatment function and good wildlife quality within a surface-flow constructed wetland depend upon the health and sustainability of the vegetation. We suggest that an effective tool to manage and sustain healthy vegetation is the use of hummocks, which are shallow emergent plant beds within the wetland, positioned perpendicular to the water flow path and surrounded by water sufficiently deep to limit further emergent vegetation expansion. In this paper, we describe the use of a hummock configuration, in conjunction with seasonal water level fluctuations, to manage the vegetation and maintain the treatment function of wastewater-treatment wetlands on a sustainable basis.

Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

PubMed

Hager, Rebecca; Tsiatis, Anastasios A; Davidian, Marie

2018-05-18

Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment options at each decision point, and thus formalizes this process. An optimal regime is one leading to the most beneficial outcome on average if used to select treatment for the patient population. We propose a method for estimation of an optimal regime involving two decision points when the outcome of interest is a censored survival time, which is based on maximizing a locally efficient, doubly robust, augmented inverse probability weighted estimator for average outcome over a class of regimes. By casting this optimization as a classification problem, we exploit well-studied classification techniques such as support vector machines to characterize the class of regimes and facilitate implementation via a backward iterative algorithm. Simulation studies of performance and application of the method to data from a sequential, multiple assignment randomized clinical trial in acute leukemia are presented. © 2018, The International Biometric Society.

Reducing Dropout in Treatment for Depression: Translating Dropout Predictors Into Individualized Treatment Recommendations.

PubMed

Zilcha-Mano, Sigal; Keefe, John R; Chui, Harold; Rubin, Avinadav; Barrett, Marna S; Barber, Jacques P

2016-12-01

Premature discontinuation of therapy is a widespread problem that hampers the delivery of mental health treatment. A high degree of variability has been found among rates of premature treatment discontinuation, suggesting that rates may differ depending on potential moderators. In the current study, our aim was to identify demographic and interpersonal variables that moderate the association between treatment assignment and dropout. Data from a randomized controlled trial conducted from November 2001 through June 2007 (N = 156) comparing supportive-expressive therapy, antidepressant medication, and placebo for the treatment of depression (based on DSM-IV criteria) were used. Twenty prerandomization variables were chosen based on previous literature. These variables were subjected to exploratory bootstrapped variable selection and included in the logistic regression models if they passed variable selection. Three variables were found to moderate the association between treatment assignment and dropout: age, pretreatment therapeutic alliance expectations, and the presence of vindictive tendencies in interpersonal relationships. When patients were divided into those randomly assigned to their optimal treatment and those assigned to their least optimal treatment, dropout rates in the optimal treatment group (24.4%) were significantly lower than those in the least optimal treatment group (47.4%; P = .03). Present findings suggest that a patient's age and pretreatment interpersonal characteristics predict the association between common depression treatments and dropout rate. If validated by further studies, these characteristics can assist in reducing dropout through targeted treatment assignment. Secondary analysis of data from ClinicalTrials.gov identifier: NCT00043550. © Copyright 2016 Physicians Postgraduate Press, Inc.

On optimizing the treatment of exchange perturbations.

NASA Technical Reports Server (NTRS)

Hirschfelder, J. O.; Chipman, D. M.

1972-01-01

Most theories of exchange perturbations would give the exact energy and wave function if carried out to an infinite order. However, the different methods give different values for the second-order energy, and different values for E(1), the expectation value of the Hamiltonian corresponding to the zeroth- plus first-order wave function. In the presented paper, it is shown that the zeroth- plus first-order wave function obtained by optimizing the basic equation which is used in most exchange perturbation treatments is the exact wave function for the perturbation system and E(1) is the exact energy.

Hydraulic design to optimize the treatment capacity of Multi-Stage Filtration units

NASA Astrophysics Data System (ADS)

Mushila, C. N.; Ochieng, G. M.; Otieno, F. A. O.; Shitote, S. M.; Sitters, C. W.

2016-04-01

Multi-Stage Filtration (MSF) can provide a robust treatment alternative for surface water sources of variable water quality in rural communities at low operation and maintenance costs. MSF is a combination of Slow Sand Filters (SSFs) and Pre-treatment systems. The general objective of this research was to optimize the treatment capacity of MSF. A pilot plant study was undertaken to meet this objective. The pilot plant was monitored for a continuous 98 days from commissioning till the end of the project. Three main stages of MSF namely: The Dynamic Gravel Filter (DGF), Horizontal-flow Roughing Filter (HRF) and SSF were identified, designed and built. The response of the respective MSF units in removal of selected parameters guiding drinking water quality such as microbiological (Faecal and Total coliform), Suspended Solids, Turbidity, PH, Temperature, Iron and Manganese was investigated. The benchmark was the Kenya Bureau (KEBS) and World Health Organization (WHO) Standards for drinking water quality. With respect to microbiological raw water quality improvement, MSF units achieved on average 98% Faecal and 96% Total coliform removal. Results obtained indicate that implementation of MSF in rural communities has the potential to increase access to portable water to the rural populace with a probable consequent decrease in waterborne diseases. With a reduced down time due to illness, more time would be spent in undertaking other economic activities.

Optimizing prescribed fire allocation for managing fire risk in central Catalonia.

PubMed

Alcasena, Fermín J; Ager, Alan A; Salis, Michele; Day, Michelle A; Vega-Garcia, Cristina

2018-04-15

We used spatial optimization to allocate and prioritize prescribed fire treatments in the fire-prone Bages County, central Catalonia (northeastern Spain). The goal of this study was to identify suitable strategic locations on forest lands for fuel treatments in order to: 1) disrupt major fire movements, 2) reduce ember emissions, and 3) reduce the likelihood of large fires burning into residential communities. We first modeled fire spread, hazard and exposure metrics under historical extreme fire weather conditions, including node influence grid for surface fire pathways, crown fraction burned and fire transmission to residential structures. Then, we performed an optimization analysis on individual planning areas to identify production possibility frontiers for addressing fire exposure and explore alternative prescribed fire treatment configurations. The results revealed strong trade-offs among different fire exposure metrics, showed treatment mosaics that optimize the allocation of prescribed fire, and identified specific opportunities to achieve multiple objectives. Our methods can contribute to improving the efficiency of prescribed fire treatment investments and wildfire management programs aimed at creating fire resilient ecosystems, facilitating safe and efficient fire suppression, and safeguarding rural communities from catastrophic wildfires. The analysis framework can be used to optimally allocate prescribed fire in other fire-prone areas within the Mediterranean region and elsewhere. Copyright © 2017 Elsevier B.V. All rights reserved.

MO-B-BRB-01: Optimize Treatment Planning Process in Clinical Environment

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

Feng, W.

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequentialmore » events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d

Optimal in vitro fertilization in 2020 should reduce treatment burden and enhance care delivery for patients and staff.

PubMed

Gameiro, Sofia; Boivin, Jacky; Domar, Alice

2013-08-01

This review argues that optimal in vitro fertilization in 2020 should include a way of enhancing the delivery of treatment for patients and staff by the minimization of patient, treatment, and clinic sources of burden. Two specific sources of burden are addressed. First, patient vulnerability can be tackled by implementation of pretreatment evidence-based screening for psychological distress, appropriate referral for support, elimination of barriers to acceptance of psychosocial support, and implementation of a routine care flowchart that identifies the specific stages of treatment when psychosocial support should be provided. Second, negative patient-staff interactions can be avoided by training staff in communication/interaction skills, promoting shared decision making, prioritizing psychological interventions that address aspects of care equally problematic for patients and staff, and monitoring the impact of change on patient, staff, and clinic outcomes. In addition, optimal in vitro fertilization should ensure now that the future generations of young adults know what "achieving parenthood" actually entails in the context of the many desired goals of adulthood, greater variety of reproductive techniques available, later age of first births, and, consequently, longer exposure to risk factors (e.g., smoking) that affect fertility. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Identifying energy and carbon footprint optimization potentials of a sludge treatment line with Life Cycle Assessment.

PubMed

Remy, C; Lesjean, B; Waschnewski, J

2013-01-01

This study exemplifies the use of Life Cycle Assessment (LCA) as a tool to quantify the environmental impacts of processes for wastewater treatment. In a case study, the sludge treatment line of a large wastewater treatment plant (WWTP) is analysed in terms of cumulative energy demand and the emission of greenhouse gases (carbon footprint). Sludge treatment consists of anaerobic digestion, dewatering, drying, and disposal of stabilized sludge in mono- or co-incineration in power plants or cement kilns. All relevant forms of energy demand (electricity, heat, chemicals, fossil fuels, transport) and greenhouse gas emissions (fossil CO(2), CH(4), N(2)O) are accounted in the assessment, including the treatment of return liquor from dewatering in the WWTP. Results show that the existing process is positive in energy balance (-162 MJ/PE(COD) * a) and carbon footprint (-11.6 kg CO(2)-eq/PE(COD) * a) by supplying secondary products such as electricity from biogas production or mono-incineration and substituting fossil fuels in co-incineration. However, disposal routes for stabilized sludge differ considerably in their energy and greenhouse gas profiles. In total, LCA proves to be a suitable tool to support future investment decisions with information of environmental relevance on the impact of wastewater treatment, but also urban water systems in general.

Mathematical Analysis for the Optimization of Wastewater Treatment Systems in Facultative Pond Indicator Organic Matter

NASA Astrophysics Data System (ADS)

Sunarsih; Widowati; Kartono; Sutrisno

2018-02-01

Stabilization ponds are easy to operate and their maintenance is simple. Treatment is carried out naturally and they are recommended in developing countries. The main disadvantage of these systems is large land area they occupy. The aim of this study was to perform an optimization of the wastewater treatment systems in a facultative pond, considering a mathematical analysis of the methodology to determine the model constrains organic matter. Matlab optimization toolbox was used for non linear programming. A facultative pond with the method was designed and then the optimization system was applied. The analyse meet the treated water quality requirements for the discharge to the water bodies. The results show a reduction of hydraulic retention time by 4.83 days, and the efficiency of of wastewater treatment of 84.16 percent.

Explicit optimization of plan quality measures in intensity-modulated radiation therapy treatment planning.

PubMed

Engberg, Lovisa; Forsgren, Anders; Eriksson, Kjell; Hårdemark, Björn

2017-06-01

To formulate convex planning objectives of treatment plan multicriteria optimization with explicit relationships to the dose-volume histogram (DVH) statistics used in plan quality evaluation. Conventional planning objectives are designed to minimize the violation of DVH statistics thresholds using penalty functions. Although successful in guiding the DVH curve towards these thresholds, conventional planning objectives offer limited control of the individual points on the DVH curve (doses-at-volume) used to evaluate plan quality. In this study, we abandon the usual penalty-function framework and propose planning objectives that more closely relate to DVH statistics. The proposed planning objectives are based on mean-tail-dose, resulting in convex optimization. We also demonstrate how to adapt a standard optimization method to the proposed formulation in order to obtain a substantial reduction in computational cost. We investigated the potential of the proposed planning objectives as tools for optimizing DVH statistics through juxtaposition with the conventional planning objectives on two patient cases. Sets of treatment plans with differently balanced planning objectives were generated using either the proposed or the conventional approach. Dominance in the sense of better distributed doses-at-volume was observed in plans optimized within the proposed framework. The initial computational study indicates that the DVH statistics are better optimized and more efficiently balanced using the proposed planning objectives than using the conventional approach. © 2017 American Association of Physicists in Medicine.

Development and application of computer assisted optimal method for treatment of femoral neck fracture.

PubMed

Wang, Monan; Zhang, Kai; Yang, Ning

2018-04-09

To help doctors decide their treatment from the aspect of mechanical analysis, the work built a computer assisted optimal system for treatment of femoral neck fracture oriented to clinical application. The whole system encompassed the following three parts: Preprocessing module, finite element mechanical analysis module, post processing module. Preprocessing module included parametric modeling of bone, parametric modeling of fracture face, parametric modeling of fixed screw and fixed position and input and transmission of model parameters. Finite element mechanical analysis module included grid division, element type setting, material property setting, contact setting, constraint and load setting, analysis method setting and batch processing operation. Post processing module included extraction and display of batch processing operation results, image generation of batch processing operation, optimal program operation and optimal result display. The system implemented the whole operations from input of fracture parameters to output of the optimal fixed plan according to specific patient real fracture parameter and optimal rules, which demonstrated the effectiveness of the system. Meanwhile, the system had a friendly interface, simple operation and could improve the system function quickly through modifying single module.

Maximum likelihood identification and optimal input design for identifying aircraft stability and control derivatives

NASA Technical Reports Server (NTRS)

Stepner, D. E.; Mehra, R. K.

1973-01-01

A new method of extracting aircraft stability and control derivatives from flight test data is developed based on the maximum likelihood cirterion. It is shown that this new method is capable of processing data from both linear and nonlinear models, both with and without process noise and includes output error and equation error methods as special cases. The first application of this method to flight test data is reported for lateral maneuvers of the HL-10 and M2/F3 lifting bodies, including the extraction of stability and control derivatives in the presence of wind gusts. All the problems encountered in this identification study are discussed. Several different methods (including a priori weighting, parameter fixing and constrained parameter values) for dealing with identifiability and uniqueness problems are introduced and the results given. The method for the design of optimal inputs for identifying the parameters of linear dynamic systems is also given. The criterion used for the optimization is the sensitivity of the system output to the unknown parameters. Several simple examples are first given and then the results of an extensive stability and control dervative identification simulation for a C-8 aircraft are detailed.

Multiple response optimization of the coagulation process for upgrading the quality of effluent from municipal wastewater treatment plant

NASA Astrophysics Data System (ADS)

Li, Na; Hu, Yi; Lu, Yong-Ze; Zeng, Raymond J.; Sheng, Guo-Ping

2016-05-01

To meet the high quality standard of receiving water, the coagulation process using polyferric chloride (PFC) was used to further improve the water quality of effluent from wastewater treatment plants. Uniform design (UD) coupled with response surface methodology (RSM) was adopted to assess the effects of the main influence factors: coagulant dosage, pH and basicity, on the removal of total organic carbon (TOC), NH4+-N and PO43--P. A desirability function approach was used to effectively optimize the coagulation process for the comprehensive removal of TOC, NH4+-N and PO43--P to upgrade the effluent quality in practical application. The optimized operating conditions were: dosage 28 mg/L, pH 8.5 and basicity 0.001. The corresponding removal efficiencies for TOC, NH4+-N and PO43--P were 77.2%, 94.6% and 20.8%, respectively. More importantly, the effluent quality could upgrade to surface water Class V of China through coagulation under optimal region. In addition, grey relational analysis (GRA) prioritized these three factors as: pH > basicity > dosage (for TOC), basicity > dosage > pH (for NH4+-N), pH > dosage > basicity (for PO43--P), which would help identify the most important factor to control the treatment efficiency of various effluent quality indexes by PFC coagulation.

Vaccination and treatment as control interventions in an infectious disease model with their cost optimization

NASA Astrophysics Data System (ADS)

Kumar, Anuj; Srivastava, Prashant K.

2017-03-01

In this work, an optimal control problem with vaccination and treatment as control policies is proposed and analysed for an SVIR model. We choose vaccination and treatment as control policies because both these interventions have their own practical advantage and ease in implementation. Also, they are widely applied to control or curtail a disease. The corresponding total cost incurred is considered as weighted combination of costs because of opportunity loss due to infected individuals and costs incurred in providing vaccination and treatment. The existence of optimal control paths for the problem is established and guaranteed. Further, these optimal paths are obtained analytically using Pontryagin's Maximum Principle. We analyse our results numerically to compare three important strategies of proposed controls, viz.: vaccination only; with both treatment and vaccination; and treatment only. We note that first strategy (vaccination only) is less effective as well as expensive. Though, for a highly effective vaccine, vaccination alone may also work well in comparison with treatment only strategy. Among all the strategies, we observe that implementation of both treatment and vaccination is most effective and less expensive. Moreover, in this case the infective population is found to be relatively very low. Thus, we conclude that the comprehensive effect of vaccination and treatment not only minimizes cost burden due to opportunity loss and applied control policies but also keeps a tab on infective population.

Optimal primary surgical treatment for advanced epithelial ovarian cancer.

PubMed

Elattar, Ahmed; Bryant, Andrew; Winter-Roach, Brett A; Hatem, Mohamed; Naik, Raj

2011-08-10

-based chemotherapy. We only included studies that defined optimal cytoreduction as surgery leading to residual tumours with a maximum diameter of any threshold up to 2 cm. Two review authors independently abstracted data and assessed risk of bias. Where possible, the data were synthesised in a meta-analysis. There were no RCTs or prospective non-RCTs identified that were designed to evaluate the effectiveness of surgery when performed as a primary procedure in advanced stage ovarian cancer.We found 11 retrospective studies that included a multivariate analysis that met our inclusion criteria. Analyses showed the prognostic importance of complete cytoreduction, where the residual disease was microscopic that is no visible disease, as overall (OS) and progression-free survival (PFS) were significantly prolonged in these groups of women. PFS was not reported in all of the studies but was sufficiently documented to allow firm conclusions to be drawn.When we compared suboptimal (> 1 cm) versus optimal (< 1 cm) cytoreduction the survival estimates were attenuated but remained statistically significant in favour of the lower volume disease group There was no significant difference in OS and only a borderline difference in PFS when residual disease of > 2 cm and < 2 cm were compared (hazard ratio (HR) 1.65, 95% CI 0.82 to 3.31; and HR 1.27, 95% CI 1.00 to 1.61, P = 0.05 for OS and PFS respectively).There was a high risk of bias due to the retrospective nature of these studies where, despite statistical adjustment for important prognostic factors, selection bias was still likely to be of particular concern.Adverse events, quality of life (QoL) and cost-effectiveness were not reported by treatment arm or to a satisfactory level in any of the studies. During primary surgery for advanced stage epithelial ovarian cancer all attempts should be made to achieve complete cytoreduction. When this is not achievable, the surgical goal should be optimal (< 1 cm) residual disease. Due to the high risk of

A systematic review of optimal treatment strategies for localized Ewing's sarcoma of bone after neo-adjuvant chemotherapy.

PubMed

Werier, Joel; Yao, Xiaomei; Caudrelier, Jean-Michel; Di Primio, Gina; Ghert, Michelle; Gupta, Abha A; Kandel, Rita; Verma, Shailendra

2016-03-01

To perform a systematic review to investigate the optimal treatment strategy among the options of surgery alone, radiotherapy (RT) alone, and the combination of RT plus surgery in the management of localized Ewing's sarcoma of bone following neo-adjuvant chemotherapy. MEDLINE and EMBASE (1999 to February 2015), the Cochrane Library, and relevant conferences were searched. Two systematic reviews and eight full texts met the pre-planned study selection criteria. When RT was compared with surgery, a meta-analysis combining two papers showed that surgery resulted in a higher event-free survival (EFS) than RT in any location (HR = 1.50, 95% CI 1.12-2.00; p = 0.007). However another paper did not find a statistically significant difference in patients with pelvic disease, and no papers identified a significant difference in overall survival. When surgery plus RT was compared with surgery alone, a meta-analysis did not demonstrate a statistically significant difference for EFS between the two groups (HR = 1.21, 95% CI 0.90-1.63). Both surgical morbidities and radiation toxicities were reported. The existing evidence is based on very low aggregate quality as assessed by the GRADE approach. In patients with localized Ewing's sarcoma, either surgery alone (if complete surgical excision with clear margin can be achieved) or RT alone may be a reasonable treatment option. The optimal local treatment for an individual patient should be decided through consideration of patient characteristics, the potential benefit and harm of the treatment options, and patient preference. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Ultrafast treatment plan optimization for volumetric modulated arc therapy (VMAT)

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

Men Chunhua; Romeijn, H. Edwin; Jia Xun

2010-11-15

Purpose: To develop a novel aperture-based algorithm for volumetric modulated arc therapy (VMAT) treatment plan optimization with high quality and high efficiency. Methods: The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. The authors consider a cost function consisting two terms, the first enforcing a desired dose distribution and the second guaranteeing a smooth dose rate variation between successive gantry angles. A gantry rotation is discretized into 180 beam angles and for each beam angle, only one MLC aperture is allowed. The apertures are generated one by one in a sequentialmore » way. At each iteration of the column generation method, a deliverable MLC aperture is generated for one of the unoccupied beam angles by solving a subproblem with the consideration of MLC mechanic constraints. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. When all 180 beam angles are occupied, the optimization completes, yielding a set of deliverable apertures and associated dose rates that produce a high quality plan. Results: The algorithm was preliminarily tested on five prostate and five head-and-neck clinical cases, each with one full gantry rotation without any couch/collimator rotations. High quality VMAT plans have been generated for all ten cases with extremely high efficiency. It takes only 5-8 min on CPU (MATLAB code on an Intel Xeon 2.27 GHz CPU) and 18-31 s on GPU (CUDA code on an NVIDIA Tesla C1060 GPU card) to generate such plans. Conclusions: The authors have developed an aperture-based VMAT optimization algorithm which can generate clinically deliverable high quality treatment plans at very high efficiency.« less

Ultrafast treatment plan optimization for volumetric modulated arc therapy (VMAT).

PubMed

Men, Chunhua; Romeijn, H Edwin; Jia, Xun; Jiang, Steve B

2010-11-01

To develop a novel aperture-based algorithm for volumetric modulated are therapy (VMAT) treatment plan optimization with high quality and high efficiency. The VMAT optimization problem is formulated as a large-scale convex programming problem solved by a column generation approach. The authors consider a cost function consisting two terms, the first enforcing a desired dose distribution and the second guaranteeing a smooth dose rate variation between successive gantry angles. A gantry rotation is discretized into 180 beam angles and for each beam angle, only one MLC aperture is allowed. The apertures are generated one by one in a sequential way. At each iteration of the column generation method, a deliverable MLC aperture is generated for one of the unoccupied beam angles by solving a subproblem with the consideration of MLC mechanic constraints. A subsequent master problem is then solved to determine the dose rate at all currently generated apertures by minimizing the cost function. When all 180 beam angles are occupied, the optimization completes, yielding a set of deliverable apertures and associated dose rates that produce a high quality plan. The algorithm was preliminarily tested on five prostate and five head-and-neck clinical cases, each with one full gantry rotation without any couch/collimator rotations. High quality VMAT plans have been generated for all ten cases with extremely high efficiency. It takes only 5-8 min on CPU (MATLAB code on an Intel Xeon 2.27 GHz CPU) and 18-31 s on GPU (CUDA code on an NVIDIA Tesla C1060 GPU card) to generate such plans. The authors have developed an aperture-based VMAT optimization algorithm which can generate clinically deliverable high quality treatment plans at very high efficiency.

Fabrication and Optimal Design of Biodegradable Polymeric Stents for Aneurysms Treatments

PubMed Central

Han, Xue; Wu, Xia; Kelly, Michael; Chen, Xiongbiao

2017-01-01

An aneurysm is a balloon-like bulge in the wall of blood vessels, occurring in major arteries of the heart and brain. Biodegradable polymeric stent-assisted coiling is expected to be the ideal treatment of wide-neck complex aneurysms. This paper presents the development of methods to fabricate and optimally design biodegradable polymeric stents for aneurysms treatment. Firstly, a dispensing-based rapid prototyping (DBRP) system was developed to fabricate coil and zigzag structures of biodegradable polymeric stents. Then, compression testing was carried out to characterize the radial deformation of the stents fabricated with the coil or zigzag structure. The results illustrated the stent with a zigzag structure has a stronger radial stiffness than the one with a coil structure. On this basis, the stent with a zigzag structure was chosen for the development of a finite element model for simulating the real compression tests. The result showed the finite element model of biodegradable polymeric stents is acceptable within a range of radial deformation around 20%. Furthermore, the optimization of the zigzag structure was performed with ANSYS DesignXplorer, and the results indicated that the total deformation could be decreased by 35.7% by optimizing the structure parameters, which would represent a significant advance of the radial stiffness of biodegradable polymeric stents. PMID:28264515

Multi-point optimization of recirculation flow type casing treatment in centrifugal compressors

NASA Astrophysics Data System (ADS)

Tun, Min Thaw; Sakaguchi, Daisaku

2016-06-01

High-pressure ratio and wide operating range are highly required for a turbocharger in diesel engines. A recirculation flow type casing treatment is effective for flow range enhancement of centrifugal compressors. Two ring grooves on a suction pipe and a shroud casing wall are connected by means of an annular passage and stable recirculation flow is formed at small flow rates from the downstream groove toward the upstream groove through the annular bypass. The shape of baseline recirculation flow type casing is modified and optimized by using a multi-point optimization code with a metamodel assisted evolutionary algorithm embedding a commercial CFD code CFX from ANSYS. The numerical optimization results give the optimized design of casing with improving adiabatic efficiency in wide operating flow rate range. Sensitivity analysis of design parameters as a function of efficiency has been performed. It is found that the optimized casing design provides optimized recirculation flow rate, in which an increment of entropy rise is minimized at grooves and passages of the rotating impeller.

Functional Recovery in Major Depressive Disorder: Providing Early Optimal Treatment for the Individual Patient

PubMed Central

Katzman, Martin A; Habert, Jeffrey; McIntosh, Diane; MacQueen, Glenda M; Milev, Roumen V; McIntyre, Roger S; Blier, Pierre

2018-01-01

Abstract Major depressive disorder is an often chronic and recurring illness. Left untreated, major depressive disorder may result in progressive alterations in brain morphometry and circuit function. Recent findings, however, suggest that pharmacotherapy may halt and possibly reverse those effects. These findings, together with evidence that a delay in treatment is associated with poorer clinical outcomes, underscore the urgency of rapidly treating depression to full recovery. Early optimized treatment, using measurement-based care and customizing treatment to the individual patient, may afford the best possible outcomes for each patient. The aim of this article is to present recommendations for using a patient-centered approach to rapidly provide optimal pharmacological treatment to patients with major depressive disorder. Offering major depressive disorder treatment determined by individual patient characteristics (e.g., predominant symptoms, medical history, comorbidities), patient preferences and expectations, and, critically, their own definition of wellness provides the best opportunity for full functional recovery. PMID:29024974

Functional Recovery in Major Depressive Disorder: Providing Early Optimal Treatment for the Individual Patient.

PubMed

Oluboka, Oloruntoba J; Katzman, Martin A; Habert, Jeffrey; McIntosh, Diane; MacQueen, Glenda M; Milev, Roumen V; McIntyre, Roger S; Blier, Pierre

2018-02-01

Major depressive disorder is an often chronic and recurring illness. Left untreated, major depressive disorder may result in progressive alterations in brain morphometry and circuit function. Recent findings, however, suggest that pharmacotherapy may halt and possibly reverse those effects. These findings, together with evidence that a delay in treatment is associated with poorer clinical outcomes, underscore the urgency of rapidly treating depression to full recovery. Early optimized treatment, using measurement-based care and customizing treatment to the individual patient, may afford the best possible outcomes for each patient. The aim of this article is to present recommendations for using a patient-centered approach to rapidly provide optimal pharmacological treatment to patients with major depressive disorder. Offering major depressive disorder treatment determined by individual patient characteristics (e.g., predominant symptoms, medical history, comorbidities), patient preferences and expectations, and, critically, their own definition of wellness provides the best opportunity for full functional recovery. © The Author(s) 2017. Published by Oxford University Press on behalf of CINP.

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Environmental Domain.

PubMed

Saelens, Brian E; Arteaga, S Sonia; Berrigan, David; Ballard, Rachel M; Gorin, Amy A; Powell-Wiley, Tiffany M; Pratt, Charlotte; Reedy, Jill; Zenk, Shannon N

2018-04-01

There is growing interest in how environment is related to adults' weight and activity and eating behaviors. However, little is known about whether environmental factors are related to the individual variability seen in adults' intentional weight loss or maintenance outcomes. The environmental domain subgroup of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project sought to identify a parsimonious set of objective and perceived neighborhood and social environment constructs and corresponding measures to include in the assessment of response to adult weight-loss treatment. Starting with the home address, the environmental domain subgroup recommended for inclusion in future weight-loss or maintenance studies constructs and measures related to walkability, perceived land use mix, food outlet accessibility (perceived and objective), perceived food availability, socioeconomics, and crime-related safety (perceived and objective) to characterize the home neighborhood environment. The subgroup also recommended constructs and measures related to social norms (perceived and objective) and perceived support to characterize an individual's social environment. The 12 neighborhood and social environment constructs and corresponding measures provide a succinct and comprehensive set to allow for more systematic examination of the impact of environment on adults' weight loss and maintenance. © 2018 The Obesity Society.

Measurement of the main and critical parameters for optimal laser treatment of heart disease

NASA Astrophysics Data System (ADS)

Kabeya, FB; Abrahamse, H.; Karsten, AE

2017-10-01

Laser light is frequently used in the diagnosis and treatment of patients. As in traditional treatments such as medication, bypass surgery, and minimally invasive ways, laser treatment can also fail and present serious side effects. The true reason for laser treatment failure or the side effects thereof, remains unknown. From the literature review conducted, and experimental results generated we conclude that an optimal laser treatment for coronary artery disease (named heart disease) can be obtained if certain critical parameters are correctly measured and understood. These parameters include the laser power, the laser beam profile, the fluence rate, the treatment time, as well as the absorption and scattering coefficients of the target treatment tissue. Therefore, this paper proposes different, accurate methods for the measurement of these critical parameters to determine the optimal laser treatment of heart disease with a minimal risk of side effects. The results from the measurement of absorption and scattering properties can be used in a computer simulation package to predict the fluence rate. The computing technique is a program based on the random number (Monte Carlo) process and probability statistics to track the propagation of photons through a biological tissue.

Optimizing biological therapy in Crohn's disease.

PubMed

Gecse, Krisztina Barbara; Végh, Zsuzsanna; Lakatos, Péter László

2016-01-01

Anti-TNF therapy has revolutionized the treatment of inflammatory bowel diseases, including both Crohn's disease and ulcerative colitis. However, a significant proportion of patients does not respond to anti-TNF agents or lose response over time. Recently, therapeutic drug monitoring has gained a major role in identifying the mechanism and management of loss of response. The aim of this review article is to summarize the predictors of efficacy and outcomes, the different mechanisms of anti-TNF/biological failure in Crohn's disease and identify strategies to optimize biological treatment.

Treatment Optimization Using Computed Tomography-Delineated Targets Should be Used for Supraclavicular Irradiation for Breast Cancer

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

Liengsawangwong, Raweewan; Yu, T.-K.; Sun, T.-L.

2007-11-01

Background: The purpose of this study was to determine whether the use of optimized CT treatment planning offered better coverage of axillary level III (LIII)/supraclavicular (SC) targets than the empirically derived dose prescription that are commonly used. Materials/Methods: Thirty-two consecutive breast cancer patients who underwent CT treatment planning of a SC field were evaluated. Each patient was categorized according to body mass index (BMI) classes: normal, overweight, or obese. The SC and LIII nodal beds were contoured, and four treatment plans for each patient were generated. Three of the plans used empiric dose prescriptions, and these were compared with amore » CT-optimized plan. Each plan was evaluated by two criteria: whether 98% of target volume receive >90% of prescribed dose and whether < 5% of the irradiated volume received 105% of prescribed dose. Results: The mean depth of SC and LIII were 3.2 cm (range, 1.4-6.7 cm) and 3.1 (range, 1.7-5.8 cm). The depth of these targets varied according across BMI classes (p = 0.01). Among the four sets of plans, the CT-optimized plans were the most successful at achieving both of the dosimetry objectives for every BMI class (normal BMI, p = .003; overweight BMI, p < .0001; obese BMI, p < .001). Conclusions: Across all BMI classes, routine radiation prescriptions did not optimally cover intended targets for every patient. Optimized CT-based treatment planning generated the most successful plans; therefore, we recommend the use of routine CT simulation and treatment planning of SC fields in breast cancer.« less

Optimized alumina coagulants for water treatment

DOEpatents

Nyman, May D [Albuquerque, NM; Stewart, Thomas A [Albuquerque, NM

2012-02-21

Substitution of a single Ga-atom or single Ge-atom (GaAl.sub.12 and GeAl.sub.12 respectively) into the center of an aluminum Keggin polycation (Al.sub.13) produces an optimal water-treatment product for neutralization and coagulation of anionic contaminants in water. GaAl.sub.12 consistently shows .about.1 order of magnitude increase in pathogen reduction, compared to Al.sub.13. At a concentration of 2 ppm, GaAl.sub.12 performs equivalently to 40 ppm alum, removing .about.90% of the dissolved organic material. The substituted GaAl.sub.12 product also offers extended shelf-life and consistent performance. We also synthesized a related polyaluminum chloride compound made of pre-hydrolyzed dissolved alumina clusters of [GaO.sub.4Al.sub.12(OH).sub.24(H.sub.2O).sub.12].sup.7+.

A Simultaneous Approach to Optimizing Treatment Assignments with Mastery Scores. Research Report 89-5.

ERIC Educational Resources Information Center

Vos, Hans J.

An approach to simultaneous optimization of assignments of subjects to treatments followed by an end-of-mastery test is presented using the framework of Bayesian decision theory. Focus is on demonstrating how rules for the simultaneous optimization of sequences of decisions can be found. The main advantages of the simultaneous approach, compared…

Optimization of vascular-targeting drugs in a computational model of tumor growth

NASA Astrophysics Data System (ADS)

Gevertz, Jana

2012-04-01

A biophysical tool is introduced that seeks to provide a theoretical basis for helping drug design teams assess the most promising drug targets and design optimal treatment strategies. The tool is grounded in a previously validated computational model of the feedback that occurs between a growing tumor and the evolving vasculature. In this paper, the model is particularly used to explore the therapeutic effectiveness of two drugs that target the tumor vasculature: angiogenesis inhibitors (AIs) and vascular disrupting agents (VDAs). Using sensitivity analyses, the impact of VDA dosing parameters is explored, as is the effects of administering a VDA with an AI. Further, a stochastic optimization scheme is utilized to identify an optimal dosing schedule for treatment with an AI and a chemotherapeutic. The treatment regimen identified can successfully halt simulated tumor growth, even after the cessation of therapy.

Optimization and real-time control for laser treatment of heterogeneous soft tissues.

PubMed

Feng, Yusheng; Fuentes, David; Hawkins, Andrea; Bass, Jon M; Rylander, Marissa Nichole

2009-01-01

Predicting the outcome of thermotherapies in cancer treatment requires an accurate characterization of the bioheat transfer processes in soft tissues. Due to the biological and structural complexity of tumor (soft tissue) composition and vasculature, it is often very difficult to obtain reliable tissue properties that is one of the key factors for the accurate treatment outcome prediction. Efficient algorithms employing in vivo thermal measurements to determine heterogeneous thermal tissues properties in conjunction with a detailed sensitivity analysis can produce essential information for model development and optimal control. The goals of this paper are to present a general formulation of the bioheat transfer equation for heterogeneous soft tissues, review models and algorithms developed for cell damage, heat shock proteins, and soft tissues with nanoparticle inclusion, and demonstrate an overall computational strategy for developing a laser treatment framework with the ability to perform real-time robust calibrations and optimal control. This computational strategy can be applied to other thermotherapies using the heat source such as radio frequency or high intensity focused ultrasound.

Optimal control of vancomycin-resistant enterococci using preventive care and treatment of infections.

PubMed

Lowden, Jonathan; Miller Neilan, Rachael; Yahdi, Mohammed

2014-03-01

The rising prevalence of vancomycin-resistant enterococci (VRE) is a major health problem in intensive care units (ICU) because of its association with increased mortality and high health care costs. We present a mathematical framework for determining cost-effective strategies for prevention and treatment of VRE in the ICU. A system of five ordinary differential equations describes the movement of ICU patients in and out of five VRE-related states. Two control variables representing the prevention and treatment of VRE are incorporated into the system. The basic reproductive number is derived and calculated for different levels of the two controls. An optimal control problem is formulated to minimize VRE-related deaths and costs associated with prevention and treatment controls over a finite time period. Numerical solutions illustrate optimal single and dual allocations of the controls for various cost values. Results show that preventive care has the greatest impact in reducing the basic reproductive number, while treatment of VRE infections has the most impact on reducing VRE-related deaths. Copyright © 2014 Elsevier Inc. All rights reserved.

The association between substance use and sub-optimal HIV treatment engagement among HIV-infected female sex workers in Lilongwe, Malawi

PubMed Central

Lancaster, Kathryn E.; Lungu, Thandie; Mmodzi, Pearson; Hosseinipour, Mina C.; Chadwick, Katy; Powers, Kimberly A.; Pence, Brian W.; Go, Vivian F.; Hoffman, Irving F.; Miller, William C.

2016-01-01

Female sex workers (FSW) have a high prevalence of substance use and HIV, but the impact of substance use on HIV treatment engagement is not well established. We evaluated the association between alcohol and marijuana use and sub-optimal HIV treatment engagement outcomes among HIV-infected FSW in Lilongwe, Malawi. We enroled FSW using venue-based recruitment into a cross-sectional evaluation assessing substance use and HIV treatment engagement. Seropositive FSW, identified through HIV rapid testing, received rapid CD4 count and viral load testing. We used Poisson regression with robust variance estimates to ascertain associations of alcohol and marijuana use with sub-optimal HIV treatment outcomes: (1) lack of ART use among previously diagnosed, ART-eligible FSW and (2) viral nonsuppression among FSW on ART. Of previously diagnosed, ART-eligible FSW (n = 96), 29% were not using ART. Patterns of hazardous drinking were identified in 30%, harmful drinking in 10%, and alcohol dependence in 12%. ART-eligible FSW with harmful drinking or alcohol dependency were 1.9 (95% CI: 1.0, 3.8) times as likely to not use ART compared to FSW without harmful or dependent drinking. Among those on ART, 14% were virally nonsuppressed. The prevalence ratio for viral nonsuppression was 2.0 (95% CI: 0.6, 6.5) for harmful drinkers and alcohol-dependent FSW. Over 30% of ART-eligible FSW reported using marijuana. Marijuana-using FSW were 1.9 (95% CI: 0.8, 4.6) times as likely to not use ART compared to FSW who were not using marijuana. Given the high prevalence of alcohol use and its association with lack of ART use, ART uptake and alcohol reduction strategies should be tailored for alcohol-using FSW in Malawi. PMID:27442009

The association between substance use and sub-optimal HIV treatment engagement among HIV-infected female sex workers in Lilongwe, Malawi.

PubMed

Lancaster, Kathryn E; Lungu, Thandie; Mmodzi, Pearson; Hosseinipour, Mina C; Chadwick, Katy; Powers, Kimberly A; Pence, Brian W; Go, Vivian F; Hoffman, Irving F; Miller, William C

2017-02-01

Female sex workers (FSW) have a high prevalence of substance use and HIV, but the impact of substance use on HIV treatment engagement is not well established. We evaluated the association between alcohol and marijuana use and sub-optimal HIV treatment engagement outcomes among HIV-infected FSW in Lilongwe, Malawi. We enroled FSW using venue-based recruitment into a cross-sectional evaluation assessing substance use and HIV treatment engagement. Seropositive FSW, identified through HIV rapid testing, received rapid CD4 count and viral load testing. We used Poisson regression with robust variance estimates to ascertain associations of alcohol and marijuana use with sub-optimal HIV treatment outcomes: (1) lack of ART use among previously diagnosed, ART-eligible FSW and (2) viral nonsuppression among FSW on ART. Of previously diagnosed, ART-eligible FSW (n = 96), 29% were not using ART. Patterns of hazardous drinking were identified in 30%, harmful drinking in 10%, and alcohol dependence in 12%. ART-eligible FSW with harmful drinking or alcohol dependency were 1.9 (95% CI: 1.0, 3.8) times as likely to not use ART compared to FSW without harmful or dependent drinking. Among those on ART, 14% were virally nonsuppressed. The prevalence ratio for viral nonsuppression was 2.0 (95% CI: 0.6, 6.5) for harmful drinkers and alcohol-dependent FSW. Over 30% of ART-eligible FSW reported using marijuana. Marijuana-using FSW were 1.9 (95% CI: 0.8, 4.6) times as likely to not use ART compared to FSW who were not using marijuana. Given the high prevalence of alcohol use and its association with lack of ART use, ART uptake and alcohol reduction strategies should be tailored for alcohol-using FSW in Malawi.

Identifying the optimal spatially and temporally invariant root distribution for a semiarid environment

NASA Astrophysics Data System (ADS)

Sivandran, Gajan; Bras, Rafael L.

2012-12-01

In semiarid regions, the rooting strategies employed by vegetation can be critical to its survival. Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. Vegetation roots have strong control over this partitioning, and assuming a static root profile, predetermine the manner in which this partitioning is undertaken.A coupled, dynamic vegetation and hydrologic model, tRIBS + VEGGIE, was used to explore the role of vertical root distribution on hydrologic fluxes. Point-scale simulations were carried out using two spatially and temporally invariant rooting schemes: uniform: a one-parameter model and logistic: a two-parameter model. The simulations were forced with a stochastic climate generator calibrated to weather stations and rain gauges in the semiarid Walnut Gulch Experimental Watershed (WGEW) in Arizona. A series of simulations were undertaken exploring the parameter space of both rooting schemes and the optimal root distribution for the simulation, which was defined as the root distribution with the maximum mean transpiration over a 100-yr period, and this was identified. This optimal root profile was determined for five generic soil textures and two plant-functional types (PFTs) to illustrate the role of soil texture on the partitioning of moisture at the land surface. The simulation results illustrate the strong control soil texture has on the partitioning of rainfall and consequently the depth of the optimal rooting profile. High-conductivity soils resulted in the deepest optimal rooting profile with land surface moisture fluxes dominated by transpiration. As we move toward the lower conductivity end of the soil spectrum, a shallowing of the optimal rooting profile is observed and evaporation gradually becomes the dominate flux from the land surface. This study offers a methodology through which local plant, soil, and climate can be

Memo Addressing Lead and Copper Rule Requirements for Optimal Corrosion Control Treatment

EPA Pesticide Factsheets

EPA has recently published a memo to address the requirements pertaining to maintenance of optimal corrosion control treatment, in situations in which a large water system ceases to purchase treated water and switches to a new drinking water source.

Optimal transformations leading to normal distributions of positron emission tomography standardized uptake values.

PubMed

Scarpelli, Matthew; Eickhoff, Jens; Cuna, Enrique; Perlman, Scott; Jeraj, Robert

2018-01-30

The statistical analysis of positron emission tomography (PET) standardized uptake value (SUV) measurements is challenging due to the skewed nature of SUV distributions. This limits utilization of powerful parametric statistical models for analyzing SUV measurements. An ad-hoc approach, which is frequently used in practice, is to blindly use a log transformation, which may or may not result in normal SUV distributions. This study sought to identify optimal transformations leading to normally distributed PET SUVs extracted from tumors and assess the effects of therapy on the optimal transformations. The optimal transformation for producing normal distributions of tumor SUVs was identified by iterating the Box-Cox transformation parameter (λ) and selecting the parameter that maximized the Shapiro-Wilk P-value. Optimal transformations were identified for tumor SUV max distributions at both pre and post treatment. This study included 57 patients that underwent 18 F-fluorodeoxyglucose ( 18 F-FDG) PET scans (publically available dataset). In addition, to test the generality of our transformation methodology, we included analysis of 27 patients that underwent 18 F-Fluorothymidine ( 18 F-FLT) PET scans at our institution. After applying the optimal Box-Cox transformations, neither the pre nor the post treatment 18 F-FDG SUV distributions deviated significantly from normality (P  >  0.10). Similar results were found for 18 F-FLT PET SUV distributions (P  >  0.10). For both 18 F-FDG and 18 F-FLT SUV distributions, the skewness and kurtosis increased from pre to post treatment, leading to a decrease in the optimal Box-Cox transformation parameter from pre to post treatment. There were types of distributions encountered for both 18 F-FDG and 18 F-FLT where a log transformation was not optimal for providing normal SUV distributions. Optimization of the Box-Cox transformation, offers a solution for identifying normal SUV transformations for when the log

Optimal transformations leading to normal distributions of positron emission tomography standardized uptake values

NASA Astrophysics Data System (ADS)

Scarpelli, Matthew; Eickhoff, Jens; Cuna, Enrique; Perlman, Scott; Jeraj, Robert

2018-02-01

The statistical analysis of positron emission tomography (PET) standardized uptake value (SUV) measurements is challenging due to the skewed nature of SUV distributions. This limits utilization of powerful parametric statistical models for analyzing SUV measurements. An ad-hoc approach, which is frequently used in practice, is to blindly use a log transformation, which may or may not result in normal SUV distributions. This study sought to identify optimal transformations leading to normally distributed PET SUVs extracted from tumors and assess the effects of therapy on the optimal transformations. Methods. The optimal transformation for producing normal distributions of tumor SUVs was identified by iterating the Box-Cox transformation parameter (λ) and selecting the parameter that maximized the Shapiro-Wilk P-value. Optimal transformations were identified for tumor SUVmax distributions at both pre and post treatment. This study included 57 patients that underwent 18F-fluorodeoxyglucose (18F-FDG) PET scans (publically available dataset). In addition, to test the generality of our transformation methodology, we included analysis of 27 patients that underwent 18F-Fluorothymidine (18F-FLT) PET scans at our institution. Results. After applying the optimal Box-Cox transformations, neither the pre nor the post treatment 18F-FDG SUV distributions deviated significantly from normality (P  >  0.10). Similar results were found for 18F-FLT PET SUV distributions (P  >  0.10). For both 18F-FDG and 18F-FLT SUV distributions, the skewness and kurtosis increased from pre to post treatment, leading to a decrease in the optimal Box-Cox transformation parameter from pre to post treatment. There were types of distributions encountered for both 18F-FDG and 18F-FLT where a log transformation was not optimal for providing normal SUV distributions. Conclusion. Optimization of the Box-Cox transformation, offers a solution for identifying normal SUV transformations for when

An integrated prediction and optimization model of biogas production system at a wastewater treatment facility.

PubMed

Akbaş, Halil; Bilgen, Bilge; Turhan, Aykut Melih

2015-11-01

This study proposes an integrated prediction and optimization model by using multi-layer perceptron neural network and particle swarm optimization techniques. Three different objective functions are formulated. The first one is the maximization of methane percentage with single output. The second one is the maximization of biogas production with single output. The last one is the maximization of biogas quality and biogas production with two outputs. Methane percentage, carbon dioxide percentage, and other contents' percentage are used as the biogas quality criteria. Based on the formulated models and data from a wastewater treatment facility, optimal values of input variables and their corresponding maximum output values are found out for each model. It is expected that the application of the integrated prediction and optimization models increases the biogas production and biogas quality, and contributes to the quantity of electricity production at the wastewater treatment facility. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimal insecticide-treated bed-net coverage and malaria treatment in a malaria-HIV co-infection model.

PubMed

Mohammed-Awel, Jemal; Numfor, Eric

2017-03-01

We propose and study a mathematical model for malaria-HIV co-infection transmission and control, in which malaria treatment and insecticide-treated nets are incorporated. The existence of a backward bifurcation is established analytically, and the occurrence of such backward bifurcation is influenced by disease-induced mortality, insecticide-treated bed-net coverage and malaria treatment parameters. To further assess the impact of malaria treatment and insecticide-treated bed-net coverage, we formulate an optimal control problem with malaria treatment and insecticide-treated nets as control functions. Using reasonable parameter values, numerical simulations of the optimal control suggest the possibility of eliminating malaria and reducing HIV prevalence significantly, within a short time horizon.

Optimal Drug Synergy in Antimicrobial Treatments

PubMed Central

Torella, Joseph Peter; Chait, Remy; Kishony, Roy

2010-01-01

The rapid proliferation of antibiotic-resistant pathogens has spurred the use of drug combinations to maintain clinical efficacy and combat the evolution of resistance. Drug pairs can interact synergistically or antagonistically, yielding inhibitory effects larger or smaller than expected from the drugs' individual potencies. Clinical strategies often favor synergistic interactions because they maximize the rate at which the infection is cleared from an individual, but it is unclear how such interactions affect the evolution of multi-drug resistance. We used a mathematical model of in vivo infection dynamics to determine the optimal treatment strategy for preventing the evolution of multi-drug resistance. We found that synergy has two conflicting effects: it clears the infection faster and thereby decreases the time during which resistant mutants can arise, but increases the selective advantage of these mutants over wild-type cells. When competition for resources is weak, the former effect is dominant and greater synergy more effectively prevents multi-drug resistance. However, under conditions of strong resource competition, a tradeoff emerges in which greater synergy increases the rate of infection clearance, but also increases the risk of multi-drug resistance. This tradeoff breaks down at a critical level of drug interaction, above which greater synergy has no effect on infection clearance, but still increases the risk of multi-drug resistance. These results suggest that the optimal strategy for suppressing multi-drug resistance is not always to maximize synergy, and that in some cases drug antagonism, despite its weaker efficacy, may better suppress the evolution of multi-drug resistance. PMID:20532210

Constrained Optimization Methods in Health Services Research-An Introduction: Report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

PubMed

Crown, William; Buyukkaramikli, Nasuh; Thokala, Praveen; Morton, Alec; Sir, Mustafa Y; Marshall, Deborah A; Tosh, Jon; Padula, William V; Ijzerman, Maarten J; Wong, Peter K; Pasupathy, Kalyan S

2017-03-01

Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

A Study of Remitted and Treatment-Resistant Depression Using MMPI and Including Pessimism and Optimism Scales

PubMed Central

Suzuki, Masatoshi; Takahashi, Michio; Muneoka, Katsumasa; Sato, Koichi; Hashimoto, Kenji; Shirayama, Yukihiko

2014-01-01

Background The psychological aspects of treatment-resistant and remitted depression are not well documented. Methods We administered the Minnesota Multiphasic Personality Inventory (MMPI) to patients with treatment-resistant depression (n = 34), remitted depression (n = 25), acute depression (n = 21), and healthy controls (n = 64). Pessimism and optimism were also evaluated by MMPI. Results ANOVA and post-hoc tests demonstrated that patients with treatment-resistant and acute depression showed similarly high scores for frequent scale (F), hypochondriasis, depression, conversion hysteria, psychopathic device, paranoia, psychasthenia and schizophrenia on the MMPI compared with normal controls. Patients with treatment-resistant depression, but not acute depression registered high on the scale for cannot say answer. Using Student's t-test, patients with remitted depression registered higher on depression and social introversion scales, compared with normal controls. For pessimism and optimism, patients with treatment-resistant depression demonstrated similar changes to acutely depressed patients. Remitted depression patients showed lower optimism than normal controls by Student's t-test, even though these patients were deemed recovered from depression using HAM-D. Conclusions The patients with remitted depression and treatment-resistant depression showed subtle alterations on the MMPI, which may explain the hidden psychological features in these cohorts. PMID:25279466

Optimized postweld heat treatment procedures for 17-4 PH stainless steels

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

Bhaduri, A.K.; Sujith, S.; Srinivasan, G.

1995-05-01

The postweld heat treatment (PWHT) procedures for 17-4 PH stainless steel weldments of matching chemistry was optimized vis-a-vis its microstructure prior to welding based on microstructural studies and room-temperature mechanical properties. The 17-4 PH stainless steel was welded in two different prior microstructural conditions (condition A and condition H 1150) and then postweld heat treated to condition H900 or condition H1150, using different heat treatment procedures. Microstructural investigations and room-temperature tensile properties were determined to study the combined effects of prior microstructural and PWHT procedures.

Treatment of Infants Identified by Newborn Screening for Severe Combined Immunodeficiency

PubMed Central

Dorsey, Morna J.; Dvorak, Christopher C.; Cowan, Morton J.; Puck, Jennifer M.

2017-01-01

Background Severe combined immunodeficiency (SCID) is characterized by severely impaired T cell development and is fatal without treatment. Newborn screening (NBS) for SCID permits identification of affected infants before development of opportunistic infections and other complications. Substantial variation exists between treatment centers with regard to pre-transplant care and transplant protocols for NBS identified SCID infants, as well as for infants with other T lymphopenic disorders detected by NBS. Methods We developed approaches to management based on the study of infants identified by SCID NBS who received care at UCSF. Results From August 2010 through October 2016, 32 NBS SCID and leaky SCID cases from California and other states were treated and 42 NBS identified non-SCID T cell lymphopenia (TCL) cases were followed. Conclusions Our center’s approach supports successful outcomes; systematic review of our practice provides a framework for diagnosis and management, recognizing that more data will continue to shape best practices. PMID:28270365

Optimal strategy for controlling the spread of Plasmodium Knowlesi malaria: Treatment and culling

NASA Astrophysics Data System (ADS)

Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini

2015-05-01

Plasmodium Knowlesi malaria is a parasitic mosquito-borne disease caused by a eukaryotic protist of genus Plasmodium Knowlesi transmitted by mosquito, Anopheles leucosphyrus to human and macaques. We developed and analyzed a deterministic Mathematical model for the transmission of Plasmodium Knowlesi malaria in human and macaques. The optimal control theory is applied to investigate optimal strategies for controlling the spread of Plasmodium Knowlesi malaria using treatment and culling as control strategies. The conditions for optimal control of the Plasmodium Knowlesi malaria are derived using Pontryagin's Maximum Principle. Finally, numerical simulations suggested that the combination of the control strategies is the best way to control the disease in any community.

Access to an optimal treatment. Current situation.

PubMed

Ugarte-Gil, Manuel F; Silvestre, Adriana M R; Pons-Estel, Bernardo A

2015-03-01

Access to an optimal treatment is determined by several factors, like availability, pricing/funding, and acceptability. In Latin America (LA), one of the regions with more disparities particularly on healthcare in the world, access is affected by other factors, including socio-demographic factors like poverty, living in rural regions, and/or health coverage. Regarding rheumatoid arthritis (RA), an inadequate access to specialists leads to diagnosis and treatment delays diminishing the probability of remission or control. Unfortunately, in almost every LA country, there are cities with more than 100,000 inhabitants without rheumatologists; furthermore, a primary care reference system is present in only about half the countries. In the public health system, coverage of biologic disease-modifying antirheumatic drugs occurs for less than 10 % of the patients in about half of the countries. Also, as healthcare providers based their funding decisions mainly in direct costs instead of on patient-centered healthcare quality indicators, access to new drugs is more complicated in this region than in high-income countries. More accurate epidemiological data from LA need to be obtained in order to improve the management of patients with rheumatic diseases in general and RA in particular.

A qualitative analysis of aspects of treatment that adolescents with anorexia identify as helpful.

PubMed

Zaitsoff, Shannon; Pullmer, Rachelle; Menna, Rosanne; Geller, Josie

2016-04-30

This study aimed to identify aspects of treatment that adolescents with anorexia nervosa (AN) believe are helpful or unhelpful. Adolescent females receiving treatment for AN or subthreshold AN (n=21) were prompted during semi-structured interviews to generate responses to open-ended questions on what they felt would be most helpful or unhelpful in treating adolescents with eating disorders. Eight codes were developed and the two most frequently endorsed categories were (1) Alliance, where the therapist demonstrates clinical expertise and also expresses interest in the patient (n=21, 100.0%), and (2) Client Involvement in treatment (n=16, 76.2%). These top two categories were shared by participants with AN versus subthreshold AN and participants with high versus low readiness to change their dietary restriction behaviours. Development of the coding scheme and sample participant responses will be discussed. The integration of identified factors into empirically supported treatments for adolescent AN, such as Family-based Treatment, will be considered. This study provides initial information regarding aspects of treatment that adolescents identify as most helpful or unhelpful in their treatment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Multiple response optimization for high efficiency energy saving treatment of rhodamine B wastewater in a three-dimensional electrochemical reactor.

PubMed

Ji, Jing; Liu, Yang; Yang, Xue-Yuan; Xu, Juan; Li, Xiu-Yan

2018-07-15

The removal of high-concentration rhodamine B (RhB) wastewater was investigated in a three-dimensional electrochemical reactor (3DER) packed with granular activated carbon (GAC) particle electrodes. Response surface methodology (RSM) coupled with grey relational analysis (GRA) was used to evaluate the effects of voltage, initial pH, aeration rate and NaCl dosage on RhB removal and energy consumption of the 3DER. The optimal conditions were determined as voltage 7.25 V, pH 5.99, aeration rate 151.13 mL/min, and NaCl concentration 0.11 mol/L. After 30 min electrolysis, COD removal rate could arrive at 60.13% with an extremely low energy consumption of 6.22 kWh/kg COD. The voltage and NaCl were demonstrated to be the most significant factors affecting the COD removal and energy consumption of 3DER. The intermediates generated during the treatment process were identified and the possible degradation pathway of RhB was proposed. It is worth noting that 3DER also showed an excellent performance in total nitrogen (TN) removal under the optimal condition. The activated chlorine generated from chloride had great contributions to eliminate carbon and nitrogen of RhB wastewater. The treatment effluent had a good biodegradability, which was suitable for subsequent biological treatment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Robust optimization in lung treatment plans accounting for geometric uncertainty.

PubMed

Zhang, Xin; Rong, Yi; Morrill, Steven; Fang, Jian; Narayanasamy, Ganesh; Galhardo, Edvaldo; Maraboyina, Sanjay; Croft, Christopher; Xia, Fen; Penagaricano, Jose

2018-05-01

Robust optimization generates scenario-based plans by a minimax optimization method to find optimal scenario for the trade-off between target coverage robustness and organ-at-risk (OAR) sparing. In this study, 20 lung cancer patients with tumors located at various anatomical regions within the lungs were selected and robust optimization photon treatment plans including intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. The plan robustness was analyzed using perturbed doses with setup error boundary of ±3 mm in anterior/posterior (AP), ±3 mm in left/right (LR), and ±5 mm in inferior/superior (IS) directions from isocenter. Perturbed doses for D 99 , D 98 , and D 95 were computed from six shifted isocenter plans to evaluate plan robustness. Dosimetric study was performed to compare the internal target volume-based robust optimization plans (ITV-IMRT and ITV-VMAT) and conventional PTV margin-based plans (PTV-IMRT and PTV-VMAT). The dosimetric comparison parameters were: ITV target mean dose (D mean ), R 95 (D 95 /D prescription ), Paddick's conformity index (CI), homogeneity index (HI), monitor unit (MU), and OAR doses including lung (D mean , V 20 Gy and V 15 Gy ), chest wall, heart, esophagus, and maximum cord doses. A comparison of optimization results showed the robust optimization plan had better ITV dose coverage, better CI, worse HI, and lower OAR doses than conventional PTV margin-based plans. Plan robustness evaluation showed that the perturbed doses of D 99 , D 98 , and D 95 were all satisfied at least 99% of the ITV to received 95% of prescription doses. It was also observed that PTV margin-based plans had higher MU than robust optimization plans. The results also showed robust optimization can generate plans that offer increased OAR sparing, especially for normal lungs and OARs near or abutting the target. Weak correlation was found between normal lung dose and target size, and no other correlation

Patient-specific dosimetric endpoints based treatment plan quality control in radiotherapy.

PubMed

Song, Ting; Staub, David; Chen, Mingli; Lu, Weiguo; Tian, Zhen; Jia, Xun; Li, Yongbao; Zhou, Linghong; Jiang, Steve B; Gu, Xuejun

2015-11-07

In intensity modulated radiotherapy (IMRT), the optimal plan for each patient is specific due to unique patient anatomy. To achieve such a plan, patient-specific dosimetric goals reflecting each patient's unique anatomy should be defined and adopted in the treatment planning procedure for plan quality control. This study is to develop such a personalized treatment plan quality control tool by predicting patient-specific dosimetric endpoints (DEs). The incorporation of patient specific DEs is realized by a multi-OAR geometry-dosimetry model, capable of predicting optimal DEs based on the individual patient's geometry. The overall quality of a treatment plan is then judged with a numerical treatment plan quality indicator and characterized as optimal or suboptimal. Taking advantage of clinically available prostate volumetric modulated arc therapy (VMAT) treatment plans, we built and evaluated our proposed plan quality control tool. Using our developed tool, six of twenty evaluated plans were identified as sub-optimal plans. After plan re-optimization, these suboptimal plans achieved better OAR dose sparing without sacrificing the PTV coverage, and the dosimetric endpoints of the re-optimized plans agreed well with the model predicted values, which validate the predictability of the proposed tool. In conclusion, the developed tool is able to accurately predict optimally achievable DEs of multiple OARs, identify suboptimal plans, and guide plan optimization. It is a useful tool for achieving patient-specific treatment plan quality control.

Radiobiological Optimization of Combination Radiopharmaceutical Therapy Applied to Myeloablative Treatment of Non-Hodgkin’s Lymphoma

PubMed Central

Hobbs, Robert F; Wahl, Richard L; Frey, Eric C; Kasamon, Yvette; Song, Hong; Huang, Peng; Jones, Richard J; Sgouros, George

2014-01-01

Combination treatment is a hallmark of cancer therapy. Although the rationale for combination radiopharmaceutical therapy was described in the mid ‘90s, such treatment strategies have only been implemented clinically recently, and without a rigorous methodology for treatment optimization. Radiobiological and quantitative imaging-based dosimetry tools are now available that enable rational implementation of combined targeted radiopharmaceutical therapy. Optimal implementation should simultaneously account for radiobiological normal organ tolerance while optimizing the ratio of two different radiopharmaceuticals required to maximize tumor control. We have developed such a methodology and applied it to hypothetical myeloablative treatment of non-hodgkin’s lymphoma (NHL) patients using 131I-tositumomab and 90Y-ibritumomab tiuxetan. Methods The range of potential administered activities (AA) is limited by the normal organ maximum tolerated biologic effective doses (MTBEDs) arising from the combined radiopharmaceuticals. Dose limiting normal organs are expected to be the lungs for 131I-tositumomab and the liver for 90Y-ibritumomab tiuxetan in myeloablative NHL treatment regimens. By plotting the limiting normal organ constraints as a function of the AAs and calculating tumor biological effective dose (BED) along the normal organ MTBED limits, the optimal combination of activities is obtained. The model was tested using previously acquired patient normal organ and tumor kinetic data and MTBED values taken from the literature. Results The average AA values based solely on normal organ constraints was (19.0 ± 8.2) GBq with a range of 3.9 – 36.9 GBq for 131I-tositumomab, and (2.77 ± 1.64) GBq with a range of 0.42 – 7.54 GBq for 90Y-ibritumomab tiuxetan. Tumor BED optimization results were calculated and plotted as a function of AA for 5 different cases, established using patient normal organ kinetics for the two radiopharmaceuticals. Results included AA ranges

Implementation of evidence-based treatment for schizophrenic disorders: two-year outcome of an international field trial of optimal treatment

PubMed Central

Falloon, Ian RH; Montero, Isabel; Sungur, Mehmet; Mastroeni, Antonino; Malm, Ulf; Economou, Marina; Grawe, Rolf; Harangozo, Judit; Mizuno, Masafumi; Murakami, Masaaki; Hager, Bert; Held, Tilo; Veltro, Franco; Gedye, Robyn

2004-01-01

According to clinical trials literature, every person with a schizophrenic disorder should be provided with the combination of optimal dose antipsychotics, strategies to educate himself and his carers to cope more efficiently with environmental stresses, cognitive-behavioural strategies to enhance work and social goals and reducing residual symptoms, and assertive home-based management to help prevent and resolve major social needs and crises, including recurrent episodes of symptoms. Despite strong scientific support for the routine implementation of these 'evidence-based' strategies, few services provide more than the pharmacotherapy component, and even this is seldom applied in the manner associated with the best results in the clinical trials. An international collaborative group, the Optimal Treatment Project (OTP), has been developed to promote the routine use of evidence-based strategies for schizophrenic disorders. A field trial was started to evaluate the benefits and costs of applying evidence-based strategies over a 5-year period. Centres have been set up in 18 countries. This paper summarises the outcome after 24 months of 'optimal' treatment in 603 cases who had reached this stage in their treatment by the end of 2002. On all measures the evidence-based OTP approach achieved more than double the benefits associated with current best practices. One half of recent cases had achieved full recovery from clinical and social morbidity. These advantages were even more striking in centres where a random-control design was used. PMID:16633471

Implementation of evidence-based treatment for schizophrenic disorders: two-year outcome of an international field trial of optimal treatment.

PubMed

Falloon, Ian R H; Montero, Isabel; Sungur, Mehmet; Mastroeni, Antonino; Malm, Ulf; Economou, Marina; Grawe, Rolf; Harangozo, Judit; Mizuno, Masafumi; Murakami, Masaaki; Hager, Bert; Held, Tilo; Veltro, Franco; Gedye, Robyn

2004-06-01

According to clinical trials literature, every person with a schizophrenic disorder should be provided with the combination of optimal dose antipsychotics, strategies to educate himself and his carers to cope more efficiently with environmental stresses, cognitive-behavioural strategies to enhance work and social goals and reducing residual symptoms, and assertive home-based management to help prevent and resolve major social needs and crises, including recurrent episodes of symptoms. Despite strong scientific support for the routine implementation of these 'evidence-based' strategies, few services provide more than the pharmacotherapy component, and even this is seldom applied in the manner associated with the best results in the clinical trials. An international collaborative group, the Optimal Treatment Project (OTP), has been developed to promote the routine use of evidence-based strategies for schizophrenic disorders. A field trial was started to evaluate the benefits and costs of applying evidence-based strategies over a 5-year period. Centres have been set up in 18 countries. This paper summarises the outcome after 24 months of 'optimal' treatment in 603 cases who had reached this stage in their treatment by the end of 2002. On all measures the evidence-based OTP approach achieved more than double the benefits associated with current best practices. One half of recent cases had achieved full recovery from clinical and social morbidity. These advantages were even more striking in centres where a random-control design was used.

Speedup of lexicographic optimization by superiorization and its applications to cancer radiotherapy treatment

NASA Astrophysics Data System (ADS)

Bonacker, Esther; Gibali, Aviv; Küfer, Karl-Heinz; Süss, Philipp

2017-04-01

Multicriteria optimization problems occur in many real life applications, for example in cancer radiotherapy treatment and in particular in intensity modulated radiation therapy (IMRT). In this work we focus on optimization problems with multiple objectives that are ranked according to their importance. We solve these problems numerically by combining lexicographic optimization with our recently proposed level set scheme, which yields a sequence of auxiliary convex feasibility problems; solved here via projection methods. The projection enables us to combine the newly introduced superiorization methodology with multicriteria optimization methods to speed up computation while guaranteeing convergence of the optimization. We demonstrate our scheme with a simple 2D academic example (used in the literature) and also present results from calculations on four real head neck cases in IMRT (Radiation Oncology of the Ludwig-Maximilians University, Munich, Germany) for two different choices of superiorization parameter sets suited to yield fast convergence for each case individually or robust behavior for all four cases.

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm.

PubMed

Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

2016-01-01

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm

PubMed Central

Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

2016-01-01

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be

Optimization of (131)I doses for the treatment of hyperthyroidism.

PubMed

Araujo, F; Rebelo, A M O; Pereira, A C; Moura, M B; Lucena, E A; Dantas, A L A; Dantas, B M; Corbo, R

2009-11-15

Several methods can be used to determine the activity of (131)I in the treatment of hyperthyroidism. However, many of them do not consider all the parameters necessary for optimum dose calculation. The relationship between the dose absorbed by the thyroid and the activity administered depends basically on three parameters: organ mass, iodine uptake and effective half-life of iodine in the thyroid. Such parameters should be individually determined for each patient in order to optimize the administered activity. The objective of this work is to develop a methodology for individualized treatment with (131)I in patients with hyperthyroidism of the Grave's Disease. A neck-thyroid phantom developed at the IRD was used to calibrate a scintillation camera and a uptake probe SCT-13004 at the Nuclear Medicine Center of the University Hospital of Rio de Janeiro and a uptake probe SCT-13002, available at the Nuclear Medicine Institute in Goiânia. The biokinetic parameters were determined based on measurements performed in eight voluntary patients. It is concluded that the use of the equipment available at the hospital (scintillation camera and uptake probe) has shown to be a suitable and feasible procedure for dose optimization in terms of effectiveness, simplicity and cost.

Under What Assumptions Do Site-by-Treatment Instruments Identify Average Causal Effects?

ERIC Educational Resources Information Center

Reardon, Sean F.; Raudenbush, Stephen W.

2013-01-01

The increasing availability of data from multi-site randomized trials provides a potential opportunity to use instrumental variables methods to study the effects of multiple hypothesized mediators of the effect of a treatment. We derive nine assumptions needed to identify the effects of multiple mediators when using site-by-treatment interactions…

Clinical prediction model to identify vulnerable patients in ambulatory surgery: towards optimal medical decision-making.

PubMed

Mijderwijk, Herjan; Stolker, Robert Jan; Duivenvoorden, Hugo J; Klimek, Markus; Steyerberg, Ewout W

2016-09-01

Ambulatory surgery patients are at risk of adverse psychological outcomes such as anxiety, aggression, fatigue, and depression. We developed and validated a clinical prediction model to identify patients who were vulnerable to these psychological outcome parameters. We prospectively assessed 383 mixed ambulatory surgery patients for psychological vulnerability, defined as the presence of anxiety (state/trait), aggression (state/trait), fatigue, and depression seven days after surgery. Three psychological vulnerability categories were considered-i.e., none, one, or multiple poor scores, defined as a score exceeding one standard deviation above the mean for each single outcome according to normative data. The following determinants were assessed preoperatively: sociodemographic (age, sex, level of education, employment status, marital status, having children, religion, nationality), medical (heart rate and body mass index), and psychological variables (self-esteem and self-efficacy), in addition to anxiety, aggression, fatigue, and depression. A prediction model was constructed using ordinal polytomous logistic regression analysis, and bootstrapping was applied for internal validation. The ordinal c-index (ORC) quantified the discriminative ability of the model, in addition to measures for overall model performance (Nagelkerke's R (2) ). In this population, 137 (36%) patients were identified as being psychologically vulnerable after surgery for at least one of the psychological outcomes. The most parsimonious and optimal prediction model combined sociodemographic variables (level of education, having children, and nationality) with psychological variables (trait anxiety, state/trait aggression, fatigue, and depression). Model performance was promising: R (2)  = 30% and ORC = 0.76 after correction for optimism. This study identified a substantial group of vulnerable patients in ambulatory surgery. The proposed clinical prediction model could allow healthcare

Optimal Chemotherapy for Leukemia: A Model-Based Strategy for Individualized Treatment

PubMed Central

Jayachandran, Devaraj; Rundell, Ann E.; Hannemann, Robert E.; Vik, Terry A.; Ramkrishna, Doraiswami

2014-01-01

Acute Lymphoblastic Leukemia, commonly known as ALL, is a predominant form of cancer during childhood. With the advent of modern healthcare support, the 5-year survival rate has been impressive in the recent past. However, long-term ALL survivors embattle several treatment-related medical and socio-economic complications due to excessive and inordinate chemotherapy doses received during treatment. In this work, we present a model-based approach to personalize 6-Mercaptopurine (6-MP) treatment for childhood ALL with a provision for incorporating the pharmacogenomic variations among patients. Semi-mechanistic mathematical models were developed and validated for i) 6-MP metabolism, ii) red blood cell mean corpuscular volume (MCV) dynamics, a surrogate marker for treatment efficacy, and iii) leukopenia, a major side-effect. With the constraint of getting limited data from clinics, a global sensitivity analysis based model reduction technique was employed to reduce the parameter space arising from semi-mechanistic models. The reduced, sensitive parameters were used to individualize the average patient model to a specific patient so as to minimize the model uncertainty. Models fit the data well and mimic diverse behavior observed among patients with minimum parameters. The model was validated with real patient data obtained from literature and Riley Hospital for Children in Indianapolis. Patient models were used to optimize the dose for an individual patient through nonlinear model predictive control. The implementation of our approach in clinical practice is realizable with routinely measured complete blood counts (CBC) and a few additional metabolite measurements. The proposed approach promises to achieve model-based individualized treatment to a specific patient, as opposed to a standard-dose-for-all, and to prescribe an optimal dose for a desired outcome with minimum side-effects. PMID:25310465

Optimal medical treatment versus carotid endarterectomy: the rationale and design of the Aggressive Medical Treatment Evaluation for Asymptomatic Carotid Artery Stenosis (AMTEC) study.

PubMed

Kolos, Igor; Loukianov, Mikhail; Dupik, Nikolay; Boytsov, Sergey; Deev, Alexandr

2015-02-01

Carotid endarterectomy and medical therapy (aspirin) were shown superior to medical therapy alone for asymptomatic (≥ 60%) carotid stenosis. The role of modern medical therapy (statins, antihypertensive treatment, and aspirin) in the treatment of such patients is undefined. Establishing the safety, efficacy, and durability of optimal medical therapy and lifestyle modification requires rigorous comparison with carotid endarterectomy in asymptomatic patients. The objective is to compare the efficacy of carotid endarterectomy + optimal medical therapy versus optimal medical therapy alone in patients with asymptomatic (70-79%) extracranial carotid stenosis. The Aggressive Medical Treatment Evaluation for Asymptomatic Carotid Artery Stenosis study is a prospective, randomized, parallel, two-arm, multicenter trial. Primary end-points will be analyzed using standard time-to-event statistical modeling with adjustment for major baseline covariates. The primary analysis is on an intent-to-treat basis. The primary outcome is nonfatal stroke, nonfatal myocardial infarction, and death during follow-up of up to five-years, and the secondary outcome includes death from any cause and stroke. © 2013 The Authors. International Journal of Stroke © 2013 World Stroke Organization.

HIV epidemic control-a model for optimal allocation of prevention and treatment resources.

PubMed

Alistar, Sabina S; Long, Elisa F; Brandeau, Margaret L; Beck, Eduard J

2014-06-01

With 33 million people living with human immunodeficiency virus (HIV) worldwide and 2.7 million new infections occurring annually, additional HIV prevention and treatment efforts are urgently needed. However, available resources for HIV control are limited and must be used efficiently to minimize the future spread of the epidemic. We develop a model to determine the appropriate resource allocation between expanded HIV prevention and treatment services. We create an epidemic model that incorporates multiple key populations with different transmission modes, as well as production functions that relate investment in prevention and treatment programs to changes in transmission and treatment rates. The goal is to allocate resources to minimize R 0, the reproductive rate of infection. We first develop a single-population model and determine the optimal resource allocation between HIV prevention and treatment. We extend the analysis to multiple independent populations, with resource allocation among interventions and populations. We then include the effects of HIV transmission between key populations. We apply our model to examine HIV epidemic control in two different settings, Uganda and Russia. As part of these applications, we develop a novel approach for estimating empirical HIV program production functions. Our study provides insights into the important question of resource allocation for a country's optimal response to its HIV epidemic and provides a practical approach for decision makers. Better decisions about allocating limited HIV resources can improve response to the epidemic and increase access to HIV prevention and treatment services for millions of people worldwide.

Quality of mango nectar processed by high-pressure homogenization with optimized heat treatment.

PubMed

Tribst, Alline Artigiani Lima; Franchi, Mark Alexandrow; de Massaguer, Pilar Rodriguez; Cristianini, Marcelo

2011-03-01

This work aimed to evaluate the effect of high-pressure homogenization (HPH) with heat shock on Aspergillus niger, vitamin C, and color of mango nectar. The nectar was processed at 200 MPa followed by heat shock, which was optimized by response surface methodology by using mango nectar ratio (45 to 70), heat time (10 to 20), and temperature (60 to 85 °C) as variables. The color of mango nectar and vitamin C retention were evaluated at the optimized treatments, that is, 200 MPa + 61.5 °C/20 min or 73.5 °C/10 min. The mathematical model indicates that heat shock time and temperature showed a positive effect in the mould inactivation, whereas increasing ratio resulted in a protective effect on A. niger. The optimized treatments did not increase the retention of vitamin C, but had positive effect for the nectar color, in particular for samples treated at 200 MPa + 61.5 °C/20 min. The results obtained in this study show that the conidia can be inactivated by applying HPH with heat shock, particularly to apply HPH as an option to pasteurize fruit nectar for industries.

Guaranteed epsilon-optimal treatment plans with the minimum number of beams for stereotactic body radiation therapy

NASA Astrophysics Data System (ADS)

Yarmand, Hamed; Winey, Brian; Craft, David

2013-09-01

Stereotactic body radiation therapy (SBRT) is characterized by delivering a high amount of dose in a short period of time. In SBRT the dose is delivered using open fields (e.g., beam’s-eye-view) known as ‘apertures’. Mathematical methods can be used for optimizing treatment planning for delivery of sufficient dose to the cancerous cells while keeping the dose to surrounding organs at risk (OARs) minimal. Two important elements of a treatment plan are quality and delivery time. Quality of a plan is measured based on the target coverage and dose to OARs. Delivery time heavily depends on the number of beams used in the plan as the setup times for different beam directions constitute a large portion of the delivery time. Therefore the ideal plan, in which all potential beams can be used, will be associated with a long impractical delivery time. We use the dose to OARs in the ideal plan to find the plan with the minimum number of beams which is guaranteed to be epsilon-optimal (i.e., a predetermined maximum deviation from the ideal plan is guaranteed). Since the treatment plan optimization is inherently a multi-criteria-optimization problem, the planner can navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing epsilon-optimality. We use mixed integer programming (MIP) for optimization. To reduce the computation time for the resultant MIP, we use two heuristics: a beam elimination scheme and a family of heuristic cuts, known as ‘neighbor cuts’, based on the concept of ‘adjacent beams’. We show the effectiveness of the proposed technique on two clinical cases, a liver and a lung case. Based on our technique we propose an algorithm for fast generation of epsilon-optimal plans.

Comparison of the progressive resolution optimizer and photon optimizer in VMAT optimization for stereotactic treatments.

PubMed

Liu, Han; Sintay, Benjamin; Pearman, Keith; Shang, Qingyang; Hayes, Lane; Maurer, Jacqueline; Vanderstraeten, Caroline; Wiant, David

2018-05-20

The photon optimization (PO) algorithm was recently released by Varian Medical Systems to improve volumetric modulated arc therapy (VMAT) optimization within Eclipse (Version 13.5). The purpose of this study is to compare the PO algorithm with its predecessor, progressive resolution optimizer (PRO) for lung SBRT and brain SRS treatments. A total of 30 patients were selected retrospectively. Previously, all the plans were generated with the PRO algorithm within Eclipse Version 13.6. In the new version of PO algorithm (Version 15), dynamic conformal arcs (DCA) were first conformed to the target, then VMAT inverse planning was performed to achieve the desired dose distributions. PTV coverages were forced to be identical for the same patient for a fair comparison. SBRT plan quality was assessed based on selected dose-volume parameters, including the conformity index, V 20 for lung, V 30 Gy for chest wall, and D 0.035 cc for other critical organs. SRS plan quality was evaluated based on the conformity index and normal tissue volumes encompassed by the 12 and 6 Gy isodose lines (V 12 and V 6 ). The modulation complexity score (MCS) was used to compare plan complexity of two algorithms. No statistically significant differences between the PRO and PO algorithms were found for any of the dosimetric parameters studied, which indicates both algorithms produce comparable plan quality. Significant improvements in the gamma passing rate (increased from 97.0% to 99.2% for SBRT and 96.1% to 98.4% for SRS), MCS (average increase of 0.15 for SBRT and 0.10 for SRS), and delivery efficiency (MU reduction of 29.8% for SBRT and 28.3% for SRS) were found for the PO algorithm. MCS showed a strong correlation with the gamma passing rate, and an inverse correlation with total MUs used. The PO algorithm offers comparable plan quality to the PRO, while minimizing MLC complexity, thereby improving the delivery efficiency and accuracy. © 2018 The Authors. Journal of Applied Clinical Medical

Algorithms for optimizing the treatment of depression: making the right decision at the right time.

PubMed

Adli, M; Rush, A J; Möller, H-J; Bauer, M

2003-11-01

Medication algorithms for the treatment of depression are designed to optimize both treatment implementation and the appropriateness of treatment strategies. Thus, they are essential tools for treating and avoiding refractory depression. Treatment algorithms are explicit treatment protocols that provide specific therapeutic pathways and decision-making tools at critical decision points throughout the treatment process. The present article provides an overview of major projects of algorithm research in the field of antidepressant therapy. The Berlin Algorithm Project and the Texas Medication Algorithm Project (TMAP) compare algorithm-guided treatments with treatment as usual. The Sequenced Treatment Alternatives to Relieve Depression Project (STAR*D) compares different treatment strategies in treatment-resistant patients.

Optimization of a Plaque Neutralization Test (PNT) to identify the exposure history of Pacific Herring to viral hemorrhagic septicemia virus (VHSV)

USGS Publications Warehouse

Hart, Lucas; Mackenzie, Ashley; Purcell, Maureen; Thompson, Rachel L.; Hershberger, Paul

2017-01-01

Methods for a plaque neutralization test (PNT) were optimized for the detection and quantification of viral hemorrhagic septicemia virus (VHSV) neutralizing activity in the plasma of Pacific Herring Clupea pallasii. The PNT was complement dependent, as neutralizing activity was attenuated by heat inactivation; further, neutralizing activity was mostly restored by the addition of exogenous complement from specific-pathogen-free Pacific Herring. Optimal methods included the overnight incubation of VHSV aliquots in serial dilutions (starting at 1:16) of whole test plasma containing endogenous complement. The resulting viral titers were then enumerated using a viral plaque assay in 96-well microplates. Serum neutralizing activity was virus-specific as plasma from viral hemorrhagic septicemia (VHS) survivors demonstrated only negligible reactivity to infectious hematopoietic necrosis virus, a closely related rhabdovirus. Among Pacific Herring that survived VHSV exposure, neutralizing activity was detected in the plasma as early as 37 d postexposure and peaked at approximately 64 d postexposure. The onset of neutralizing activity was slightly delayed in fish reared at 7.4°C relative to those in warmer temperatures (9.9°C and 13.1°C); however, neutralizing activity persisted for at least 345 d postexposure in all temperature treatments. It is anticipated that this novel ability to assess VHSV neutralizing activity in Pacific Herring will enable retrospective comparisons between prior VHS infections and year-class recruitment failures. Additionally, the optimized PNT could be employed as a forecasting tool capable of identifying the potential for future VHS epizootics in wild Pacific Herring populations.

Towards an optimal treatment algorithm for metastatic pancreatic ductal adenocarcinoma (PDA)

PubMed Central

Uccello, M.; Moschetta, M.; Mak, G.; Alam, T.; Henriquez, C. Murias; Arkenau, H.-T.

2018-01-01

Chemotherapy remains the mainstay of treatment for advanced pancreatic ductal adenocarcinoma (pda). Two randomized trials have demonstrated superiority of the combination regimens folfirinox (5-fluorouracil, leucovorin, oxaliplatin, and irinotecan) and gemcitabine plus nab-paclitaxel over gemcitabine monotherapy as a first-line treatment in adequately fit subjects. Selected pda patients progressing to first-line therapy can receive secondline treatment with moderate clinical benefit. Nevertheless, the optimal algorithm and the role of combination therapy in second-line are still unclear. Published second-line pda clinical trials enrolled patients progressing to gemcitabine-based therapies in use before the approval of nab-paclitaxel and folfirinox. The evolving scenario in second-line may affect the choice of the first-line treatment. For example, nanoliposomal irinotecan plus 5-fluouracil and leucovorin is a novel second-line option which will be suitable only for patients progressing to gemcitabine-based therapy. Therefore, clinical judgement and appropriate patient selection remain key elements in treatment decision. In this review, we aim to illustrate currently available options and define a possible algorithm to guide treatment choice. Future clinical trials taking into account sequential treatment as a new paradigm in pda will help define a standard algorithm. PMID:29507500

Psychosocial issues in post-treatment cancer survivors: Desire for support and challenges in identifying individuals in need.

PubMed

Philip, Errol J; Merluzzi, Thomas V

2016-01-01

The ongoing and late effects of cancer treatment can interfere with quality of life and adoption of healthy behaviors, thus potentially impairing recovery and survival. Developing effective methods to identify individuals in need of support is crucial in providing comprehensive, ongoing care and ensuring optimal use of limited resources. The current study provides an examination of long-term survivors' reports of psychosocial issues, their desire for follow-up, and the role of widely used distress-screening measures for identifying survivors who desire help. 317 cancer survivors (M age = 62.98 years, female = 70%, Md years since treatment = 7.5 years, mixed diagnoses) completed measures of psychosocial adjustment and quality of life as well as a checklist of psychosocial issues on which they indicated whether they would like to speak with a health professional regarding each issue. Participants reported an average of 1.7 psychosocial issues. Only a minority desired to speak to a health professional; however, those desiring follow-up reported significant impairments in adjustment and quality of life. Though far from adequate as a stand-alone measure, area under the curve and regression analysis suggested a combination of the distress thermometer and number of psychosocial issues may be the best assessment of those desiring follow-up assistance. These results indicate that there is a need for a more sophisticated system of assisting survivors that takes into account issues, symptoms, and motivation for help. The present study is important in guiding the development of effective survivorship care and contributing to the growing literature describing the adjustment and care needs of survivors.

Simulation and optimization of an experimental membrane wastewater treatment plant using computational intelligence methods.

PubMed

Ludwig, T; Kern, P; Bongards, M; Wolf, C

2011-01-01

The optimization of relaxation and filtration times of submerged microfiltration flat modules in membrane bioreactors used for municipal wastewater treatment is essential for efficient plant operation. However, the optimization and control of such plants and their filtration processes is a challenging problem due to the underlying highly nonlinear and complex processes. This paper presents the use of genetic algorithms for this optimization problem in conjunction with a fully calibrated simulation model, as computational intelligence methods are perfectly suited to the nonconvex multi-objective nature of the optimization problems posed by these complex systems. The simulation model is developed and calibrated using membrane modules from the wastewater simulation software GPS-X based on the Activated Sludge Model No.1 (ASM1). Simulation results have been validated at a technical reference plant. They clearly show that filtration process costs for cleaning and energy can be reduced significantly by intelligent process optimization.

Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization

PubMed Central

Jayachandran, Devaraj; Laínez-Aguirre, José; Rundell, Ann; Vik, Terry; Hannemann, Robert; Reklaitis, Gintaras; Ramkrishna, Doraiswami

2015-01-01

6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP’s widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient’s ability to metabolize the drug instead of the traditional standard-dose-for-all approach. PMID:26226448

Identifying Treatment Effect Modifiers in the STarT Back Trial: A Secondary Analysis.

PubMed

Beneciuk, Jason M; Hill, Jonathan C; Campbell, Paul; Afolabi, Ebenezer; George, Steven Z; Dunn, Kate M; Foster, Nadine E

2017-01-01

Identification of patient characteristics influencing treatment outcomes is a top low back pain (LBP) research priority. Results from the STarT Back trial support the effectiveness of prognostic stratified care for LBP compared with current best care, however, patient characteristics associated with treatment response have not yet been explored. The purpose of this secondary analysis was to identify treatment effect modifiers within the STarT Back trial at 4-month follow-up (n = 688). Treatment response was dichotomized using back-specific physical disability measured using the Roland-Morris Disability Questionnaire (≥7). Candidate modifiers were identified using previous literature and evaluated using logistic regression with statistical interaction terms to provide preliminary evidence of treatment effect modification. Socioeconomic status (SES) was identified as an effect modifier for disability outcomes (odds ratio [OR] = 1.71, P = .028). High SES patients receiving prognostic stratified care were 2.5 times less likely to have a poor outcome compared with low SES patients receiving best current care (OR = .40, P = .006). Education level (OR = 1.33, P = .109) and number of pain medications (OR = .64, P = .140) met our criteria for effect modification with weaker evidence (.20 > P ≥ .05). These findings provide preliminary evidence for SES, education, and number of pain medications as treatment effect modifiers of prognostic stratified care delivered in the STarT Back Trial. This analysis provides preliminary exploratory findings about the characteristics of patients who might least likely benefit from targeted treatment using prognostic stratified care for LBP. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Identifying the Average Causal Mediation Effects with Multiple Mediators in the Presence of Treatment Non-Compliance

ERIC Educational Resources Information Center

Park, Soojin

2015-01-01

Identifying the causal mechanisms is becoming more essential in social and medical sciences. In the presence of treatment non-compliance, the Intent-To-Treated effect (hereafter, ITT effect) is identified as long as the treatment is randomized (Angrist et al., 1996). However, the mediated portion of effect is not identified without additional…

Treatment optimization in MS: Canadian MS Working Group updated recommendations.

PubMed

Freedman, Mark S; Selchen, Daniel; Arnold, Douglas L; Prat, Alexandre; Banwell, Brenda; Yeung, Michael; Morgenthau, David; Lapierre, Yves

2013-05-01

The Canadian Multiple Sclerosis Working Group (CMSWG) developed practical recommendations in 2004 to assist clinicians in optimizing the use of disease-modifying therapies (DMT) in patients with relapsing multiple sclerosis. The CMSWG convened to review how disease activity is assessed, propose a more current approach for assessing suboptimal response, and to suggest a scheme for switching or escalating treatment. Practical criteria for relapses, Expanded Disability Status Scale (EDSS) progression and MRI were developed to classify the clinical level of concern as Low, Medium and High. The group concluded that a change in treatment may be considered in any RRMS patient if there is a high level of concern in any one domain (relapses, progression or MRI), a medium level of concern in any two domains, or a low level of concern in all three domains. These recommendations for assessing treatment response should assist clinicians in making more rational choices in their management of relapsing MS patients.

Identifying MRI markers to evaluate early treatment-related changes post-laser ablation for cancer pain management

NASA Astrophysics Data System (ADS)

Tiwari, Pallavi; Danish, Shabbar; Madabhushi, Anant

2014-03-01

Laser interstitial thermal therapy (LITT) has recently emerged as a new treatment modality for cancer pain management that targets the cingulum (pain center in the brain), and has shown promise over radio-frequency (RF) based ablation which is reported to provide temporary relief. One of the major advantages enjoyed by LITT is its compatibility with magnetic resonance imaging (MRI), allowing for high resolution in vivo imaging to be used in LITT procedures. Since laser ablation for pain management is currently exploratory and is only performed at a few centers worldwide, its short-, and long-term effects on the cingulum are currently unknown. Traditionally treatment effects are evaluated by monitoring changes in volume of the ablation zone post-treatment. However, this is sub-optimal since it involves evaluating a single global parameter (volume) to detect changes pre-, and post-MRI. Additionally, the qualitative observations of LITT-related changes on multi-parametric MRI (MPMRI) do not specifically address differentiation between the appearance of treatment related changes (edema, necrosis) from recurrence of the disease (pain recurrence). In this work, we explore the utility of computer extracted texture descriptors on MP-MRI to capture early treatment related changes on a per-voxel basis by extracting quantitative relationships that may allow for an in-depth understanding of tissue response to LITT on MRI, subtle changes that may not be appreciable on original MR intensities. The second objective of this work is to investigate the efficacy of different MRI protocols in accurately capturing treatment related changes within and outside the ablation zone post-LITT. A retrospective cohort of studies comprising pre- and 24-hour post-LITT 3 Tesla T1-weighted (T1w), T2w, T2-GRE, and T2-FLAIR acquisitions was considered. Our scheme involved (1) inter-protocol as well as inter-acquisition affine registration of pre- and post-LITT MRI, (2) quantitation of MRI parameters

Treatment of chronic myeloid leukemia: assessing risk, monitoring response, and optimizing outcome.

PubMed

Shanmuganathan, Naranie; Hiwase, Devendra Keshaorao; Ross, David Morrall

2017-12-01

Over the past two decades, tyrosine kinase inhibitors have become the foundation of chronic myeloid leukemia (CML) treatment. The choice between imatinib and newer tyrosine kinase inhibitors (TKIs) needs to be balanced against the known toxicity and efficacy data for each drug, the therapeutic goal being to maximize molecular response assessed by BCR-ABL RQ-PCR assay. There is accumulating evidence that the early achievement of molecular targets is a strong predictor of superior long-term outcomes. Early response assessment provides the opportunity to intervene early with the aim of ensuring an optimal response. Failure to achieve milestones or loss of response can have diverse causes. We describe how clinical and laboratory monitoring can be used to ensure that each patient is achieving an optimal response and, in patients who do not reach optimal response milestones, how the monitoring results can be used to detect resistance and understand its origins.

Optimal Subdivision for Treatment and Management of Catastrophic Landslides in a Watershed Using Topographic Factors.

PubMed

Lin, Chao-Yuan; Fu, Kuei-Lin; Lin, Cheng-Yu

2016-11-01

Recent extreme rainfall events led to many landslides due to climate changes in Taiwan. How to effectively promote post-disaster treatment and/or management works in a watershed/drainage basin is a crucial issue. Regarding the processes of watershed treatment and/or management works, disaster hotspot scanning and treatment priority setup should be carried out in advance. A scanning method using landslide ratio to determine the appropriate outlet of an interested watershed, and an optimal subdivision system with better homogeneity and accuracy in landslide ratio estimation were developed to help efficient executions of treatment and/or management works. Topography is a key factor affecting watershed landslide ratio. Considering the complexity and uncertainty of the natural phenomenon, multivariate analysis was applied to understand the relationship between topographic factors and landslide ratio in the interested watershed. The concept of species-area curve, which is usually adopted at on-site vegetation investigation to determinate the suitable quadrate size, was used to derive the optimal threshold in subdivisions. Results show that three main component axes including factors of scale, network and shape extracted from Digital Terrain Model coupled with areas of landslide can effectively explain the characteristics of landslide ratio in the interested watershed, and a relation curve obtained from the accuracy of landslide ratio classification and number of subdivisions could be established to derive optimal subdivision of the watershed. The subdivision method promoted in this study could be further used for priority rank and benefit assessment of landslide treatment in a watershed.

Optimal Subdivision for Treatment and Management of Catastrophic Landslides in a Watershed Using Topographic Factors

NASA Astrophysics Data System (ADS)

Lin, Chao-Yuan; Fu, Kuei-Lin; Lin, Cheng-Yu

2016-11-01

Recent extreme rainfall events led to many landslides due to climate changes in Taiwan. How to effectively promote post-disaster treatment and/or management works in a watershed/drainage basin is a crucial issue. Regarding the processes of watershed treatment and/or management works, disaster hotspot scanning and treatment priority setup should be carried out in advance. A scanning method using landslide ratio to determine the appropriate outlet of an interested watershed, and an optimal subdivision system with better homogeneity and accuracy in landslide ratio estimation were developed to help efficient executions of treatment and/or management works. Topography is a key factor affecting watershed landslide ratio. Considering the complexity and uncertainty of the natural phenomenon, multivariate analysis was applied to understand the relationship between topographic factors and landslide ratio in the interested watershed. The concept of species-area curve, which is usually adopted at on-site vegetation investigation to determinate the suitable quadrate size, was used to derive the optimal threshold in subdivisions. Results show that three main component axes including factors of scale, network and shape extracted from Digital Terrain Model coupled with areas of landslide can effectively explain the characteristics of landslide ratio in the interested watershed, and a relation curve obtained from the accuracy of landslide ratio classification and number of subdivisions could be established to derive optimal subdivision of the watershed. The subdivision method promoted in this study could be further used for priority rank and benefit assessment of landslide treatment in a watershed.

Identifying models of HIV care and treatment service delivery in Tanzania, Uganda, and Zambia using cluster analysis and Delphi survey.

PubMed

Tsui, Sharon; Denison, Julie A; Kennedy, Caitlin E; Chang, Larry W; Koole, Olivier; Torpey, Kwasi; Van Praag, Eric; Farley, Jason; Ford, Nathan; Stuart, Leine; Wabwire-Mangen, Fred

2017-12-06

Organization of HIV care and treatment services, including clinic staffing and services, may shape clinical and financial outcomes, yet there has been little attempt to describe different models of HIV care in sub-Saharan Africa (SSA). Information about the relative benefits and drawbacks of different models could inform the scale-up of antiretroviral therapy (ART) and associated services in resource-limited settings (RLS), especially in light of expanded client populations with country adoption of WHO's test and treat recommendation. We characterized task-shifting/task-sharing practices in 19 diverse ART clinics in Tanzania, Uganda, and Zambia and used cluster analysis to identify unique models of service provision. We ran descriptive statistics to explore how the clusters varied by environmental factors and programmatic characteristics. Finally, we employed the Delphi Method to make systematic use of expert opinions to ensure that the cluster variables were meaningful in the context of actual task-shifting of ART services in SSA. The cluster analysis identified three task-shifting/task-sharing models. The main differences across models were the availability of medical doctors, the scope of clinical responsibility assigned to nurses, and the use of lay health care workers. Patterns of healthcare staffing in HIV service delivery were associated with different environmental factors (e.g., health facility levels, urban vs. rural settings) and programme characteristics (e.g., community ART distribution or integrated tuberculosis treatment on-site). Understanding the relative advantages and disadvantages of different models of care can help national programmes adapt to increased client load, select optimal adherence strategies within decentralized models of care, and identify differentiated models of care for clients to meet the growing needs of long-term ART patients who require more complicated treatment management.

Optimization of treatment with interferon beta in multiple sclerosis. Usefulness of automatic system application criteria

PubMed Central

Ruiz-Peña, Juan Luís; Duque, Pablo; Izquierdo, Guillermo

2008-01-01

Background A software based tool has been developed (Optem) to allow automatize the recommendations of the Canadian Multiple Sclerosis Working Group for optimizing MS treatment in order to avoid subjective interpretation. Methods Treatment Optimization Recommendations (TORs) were applied to our database of patients treated with IFN β1a IM. Patient data were assessed during year 1 for disease activity, and patients were assigned to 2 groups according to TOR: "change treatment" (CH) and "no change treatment" (NCH). These assessments were then compared to observed clinical outcomes for disease activity over the following years. Results We have data on 55 patients. The "change treatment" status was assigned to 22 patients, and "no change treatment" to 33 patients. The estimated sensitivity and specificity according to last visit status were 73.9% and 84.4%. During the following years, the Relapse Rate was always higher in the "change treatment" group than in the "no change treatment" group (5 y; CH: 0.7, NCH: 0.07; p < 0.001, 12 m – last visit; CH: 0.536, NCH: 0.34). We obtained the same results with the EDSS (4 y; CH: 3.53, NCH: 2.55, annual progression rate in 12 m – last visit; CH: 0.29, NCH: 0.13). Conclusion Applying TOR at the first year of therapy allowed accurate prediction of continued disease activity in relapses and disability progression. PMID:18325088

Optimal combination treatment and vascular outcomes in recent ischemic stroke patients by premorbid risk level.

PubMed

Park, Jong-Ho; Ovbiagele, Bruce

2015-08-15

Optimal combination of secondary stroke prevention treatment including antihypertensives, antithrombotic agents, and lipid modifiers is associated with reduced recurrent vascular risk including stroke. It is unclear whether optimal combination treatment has a differential impact on stroke patients based on level of vascular risk. We analyzed a clinical trial dataset comprising 3680 recent non-cardioembolic stroke patients aged ≥35 years and followed for 2 years. Patients were categorized by appropriateness levels 0 to III depending on the number of the drugs prescribed divided by the number of drugs potentially indicated for each patient (0=none of the indicated medications prescribed and III=all indicated medications prescribed [optimal combination treatment]). High-risk was defined as having a history of stroke or coronary heart disease (CHD) prior to the index stroke event. Independent associations of medication appropriateness level with a major vascular event (stroke, CHD, or vascular death), ischemic stroke, and all-cause death were analyzed. Compared with level 0, for major vascular events, the HR of level III in the low-risk group was 0.51 (95% CI: 0.20-1.28) and 0.32 (0.14-0.70) in the high-risk group; for stroke, the HR of level III in the low-risk group was 0.54 (0.16-1.77) and 0.25 (0.08-0.85) in the high-risk group; and for all-cause death, the HR of level III in the low-risk group was 0.66 (0.09-5.00) and 0.22 (0.06-0.78) in the high-risk group. Optimal combination treatment is related to a significantly lower risk of future vascular events and death among high-risk patients after a recent non-cardioembolic stroke. Copyright © 2015 Elsevier B.V. All rights reserved.

News of Biomedical Advances in HIV: Relationship to Treatment Optimism and Expected Risk Behavior in US MSM.

PubMed

Zimmerman, Rick S; Kirschbaum, Allison L

2018-02-01

HIV treatment optimism and the ways in which news of HIV biomedical advances in HIV is presented to the most at-risk communities interact in ways that affect risk behavior and the incidence of HIV. The goal of the current study was to understand the relationships among HIV treatment optimism, knowledge of HIV biomedical advances, and current and expected increased risk behavior as a result of reading hypothetical news stories of further advances. Most of an online-recruited sample of MSM were quite knowledgeable about current biomedical advances. After reading three hypothetical news stories, 15-24% of those not living with HIV and 26-52% of those living with HIV reported their condom use would decrease if the story they read were true. Results suggest the importance of more cautious reporting on HIV biomedical advances, and for targeting individuals with greater treatment optimism and those living with HIV via organizations where they are most likely to receive their information about HIV.

Optimization of the preparation conditions of ceramic products using drinking water treatment sludges.

PubMed

Zamora, R M Ramirez; Ayala, F Espesel; Garcia, L Chavez; Moreno, A Duran; Schouwenaars, R

2008-11-01

The aim of this work is to optimize, via Response Surface Methodology, the values of the main process parameters for the production of ceramic products using sludges obtained from drinking water treatment in order to valorise them. In the first experimental stage, sludges were collected from a drinking water treatment plant for characterization. In the second stage, trials were carried out to elaborate thin cross-section specimens and fired bricks following an orthogonal central composite design of experiments with three factors (sludge composition, grain size and firing temperature) and five levels. The optimization parameters (Y(1)=shrinking by firing (%), Y(2)=water absorption (%), Y(3)=density (g/cm(3)) and Y(4)=compressive strength (kg/cm(2))) were determined according to standardized analytical methods. Two distinct physicochemical processes were active during firing at different conditions in the experimental design, preventing the determination of a full response surface, which would allow direct optimization of production parameters. Nevertheless, the temperature range for the production of classical red brick was closely delimitated by the results; above this temperature, a lightweight ceramic with surprisingly high strength was produced, opening possibilities for the valorisation of a product with considerably higher added value than what was originally envisioned.

Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity modulated proton therapy treatment planning

PubMed Central

Cao, Wenhua; Lim, Gino; Li, Xiaoqiang; Li, Yupeng; Zhu, X. Ronald; Zhang, Xiaodong

2014-01-01

The purpose of this study is to investigate the feasibility and impact of incorporating deliverable monitor unit (MU) constraints into spot intensity optimization in intensity modulated proton therapy (IMPT) treatment planning. The current treatment planning system (TPS) for IMPT disregards deliverable MU constraints in the spot intensity optimization (SIO) routine. It performs a post-processing procedure on an optimized plan to enforce deliverable MU values that are required by the spot scanning proton delivery system. This procedure can create a significant dose distribution deviation between the optimized and post-processed deliverable plans, especially when small spot spacings are used. In this study, we introduce a two-stage linear programming (LP) approach to optimize spot intensities and constrain deliverable MU values simultaneously, i.e., a deliverable spot intensity optimization (DSIO) model. Thus, the post-processing procedure is eliminated and the associated optimized plan deterioration can be avoided. Four prostate cancer cases at our institution were selected for study and two parallel opposed beam angles were planned for all cases. A quadratic programming (QP) based model without MU constraints, i.e., a conventional spot intensity optimization (CSIO) model, was also implemented to emulate the commercial TPS. Plans optimized by both the DSIO and CSIO models were evaluated for five different settings of spot spacing from 3 mm to 7 mm. For all spot spacings, the DSIO-optimized plans yielded better uniformity for the target dose coverage and critical structure sparing than did the CSIO-optimized plans. With reduced spot spacings, more significant improvements in target dose uniformity and critical structure sparing were observed in the DSIO- than in the CSIO-optimized plans. Additionally, better sparing of the rectum and bladder was achieved when reduced spacings were used for the DSIO-optimized plans. The proposed DSIO approach ensures the

Dynamic analysis and optimal control for a model of hepatitis C with treatment

NASA Astrophysics Data System (ADS)

Zhang, Suxia; Xu, Xiaxia

2017-05-01

A model for hepatitis C is formulated to study the effects of treatment and public concern on HCV transmission dynamics. The stability of equilibria and persistence of the model are analyzed, and an optimal control measure is performed to prevent the spread of HCV with minimal infected individuals and cost. The dynamical analysis reveals that the disease-free equilibrium of the model is asymptotically stable if the basic reproductive number R0 is less than unity. On the other hand, if R0 > 1 , the disease is uniformly persistent. Numerical simulations are conducted to investigate the influence of different vital parameters on R0. For the corresponding optimality system, the optimal solution is discussed by Pontryagin Maximum Principle, and the comparisons of model-predicted consequences with control or not are presented.

Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

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

Ghomi, Pooyan Shirvani; Zinchenko, Yuriy

2014-08-15

Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization softwaremore » Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.« less

Accessibility of opioid analgesics and barriers to optimal chronic pain treatment in Poland in 2000-2015.

PubMed

Dzierżanowski, Tomasz; Ciałkowska-Rysz, Aleksandra

2017-03-01

Based on the international reports, consumption of opioid analgesics in Poland is relatively low. There is limited information on possible impediments to optimal opioid use. This study was aimed to identify possible barriers to access to opioid analgesics and causes of failure to comply with current clinical guidelines. Consumption data per capita in 2000-2015 were analyzed in terms of oral morphine equivalents in total, per prescription type, per reimbursement status, to identify the impact of regulations specific for Poland. The consumption of opioid analgesics has been consistently growing from 36.0 in 2000 to 103.4 mg oral morphine equivalents (OME) per capita in 2015, mainly thanks to strong opioid consumption growth. Tramadol is the most commonly used opioid in Poland. Fentanyl and buprenorphine transdermal formulations are the most frequently used strong opioid analgesics in terms of OME. The vast majority (92.8 %) of opioids were distributed upon for outpatient use in 2015, with a almost fourfold growth of consumption of strong opioids and almost threefold of weak opioids between 2000 and 2015. Strong opioids were 41 % of OME used upon prescription in 2015. Acceleration of consumption growth has been observed since 2013. The prescription pattern does not abide by the current clinical guidelines for pain treatment, and the most often used opioids in Poland are tramadol, buprenorphine, and fentanyl. The use of opioids in Poland grows fast, with acceleration since 2013. The most important legal impediments of optimal opioid analgesics use have been lack of reimbursement, special prescription forms, and complicated prescribing rules.

Accuracy of a Rationally Derived Method for Identifying Treatment Failure in Children and Adolescents

ERIC Educational Resources Information Center

Bishop, Matthew J.; Bybee, Taige S.; Lambert, Michael J.; Burlingame, Gary M.; Wells, M. Gawain; Poppleton, Landon E.

2005-01-01

Psychotherapy outcome can be enhanced by early identification of potential treatment failures before they leave treatment. In adults, compelling data are emerging that provide evidence that an early warning system that identifies potential treatment failures can be developed and applied to enhance outcome. The present study reports an analysis of…

Optimal Wastewater Loading under Conflicting Goals and Technology Limitations in a Riverine System.

PubMed

Rafiee, Mojtaba; Lyon, Steve W; Zahraie, Banafsheh; Destouni, Georgia; Jaafarzadeh, Nemat

2017-03-01

  This paper investigates a novel simulation-optimization (S-O) framework for identifying optimal treatment levels and treatment processes for multiple wastewater dischargers to rivers. A commonly used water quality simulation model, Qual2K, was linked to a Genetic Algorithm optimization model for exploration of relevant fuzzy objective-function formulations for addressing imprecision and conflicting goals of pollution control agencies and various dischargers. Results showed a dynamic flow dependence of optimal wastewater loading with good convergence to near global optimum. Explicit considerations of real-world technological limitations, which were developed here in a new S-O framework, led to better compromise solutions between conflicting goals than those identified within traditional S-O frameworks. The newly developed framework, in addition to being more technologically realistic, is also less complicated and converges on solutions more rapidly than traditional frameworks. This technique marks a significant step forward for development of holistic, riverscape-based approaches that balance the conflicting needs of the stakeholders.

Learning Optimal Individualized Treatment Rules from Electronic Health Record Data

PubMed Central

Wang, Yuanjia; Wu, Peng; Liu, Ying; Weng, Chunhua; Zeng, Donglin

2016-01-01

Medical research is experiencing a paradigm shift from “one-size-fits-all” strategy to a precision medicine approach where the right therapy, for the right patient, and at the right time, will be prescribed. We propose a statistical method to estimate the optimal individualized treatment rules (ITRs) that are tailored according to subject-specific features using electronic health records (EHR) data. Our approach merges statistical modeling and medical domain knowledge with machine learning algorithms to assist personalized medical decision making using EHR. We transform the estimation of optimal ITR into a classification problem and account for the non-experimental features of the EHR data and confounding by clinical indication. We create a broad range of feature variables that reflect both patient health status and healthcare data collection process. Using EHR data collected at Columbia University clinical data warehouse, we construct a decision tree for choosing the best second line therapy for treating type 2 diabetes patients. PMID:28503676

Treatment barriers identified by substance abusers assessed at a centralized intake unit.

PubMed

Rapp, Richard C; Xu, Jiangmin; Carr, Carey A; Lane, D Tim; Wang, Jichuan; Carlson, Robert

2006-04-01

The 59-item Barriers to Treatment Inventory (BTI) was administered to 312 substance abusers at a centralized intake unit following assessment but before treatment entry to assess their views on barriers to treatment. Factor analysis identified 25 items in 7 well-defined latent constructs: Absence of Problem, Negative Social Support, Fear of Treatment, Privacy Concerns, Time Conflict, Poor Treatment Availability, and Admission Difficulty. The factorial structure of the barriers is consistent with the findings of other studies that asked substance abusers about barriers to treatment and is conceptually compatible with Andersen's model of health care utilization. Factors were moderately to highly correlated, suggesting that they interact with one another. Selected characteristics were generally not predictive of barrier factors. Overall, results indicate that the BTI has good content validity and is a reliable instrument for assessing barriers to drug treatment. The potential utility of the BTI in assessment settings is discussed.

Optimization and management of materials in earthwork construction : tech transfer summary.

DOT National Transportation Integrated Search

2010-05-01

This research provides solutions to identified problems through better : management and optimization of the available pavement geotechnical : materials and through ground improvement, soil reinforcement, : and other soil treatment techniques. : Objec...

An optimized treatment for algorithmic differentiation of an important glaciological fixed-point problem

DOE PAGES

Goldberg, Daniel N.; Narayanan, Sri Hari Krishna; Hascoet, Laurent; ...

2016-05-20

We apply an optimized method to the adjoint generation of a time-evolving land ice model through algorithmic differentiation (AD). The optimization involves a special treatment of the fixed-point iteration required to solve the nonlinear stress balance, which differs from a straightforward application of AD software, and leads to smaller memory requirements and in some cases shorter computation times of the adjoint. The optimization is done via implementation of the algorithm of Christianson (1994) for reverse accumulation of fixed-point problems, with the AD tool OpenAD. For test problems, the optimized adjoint is shown to have far lower memory requirements, potentially enablingmore » larger problem sizes on memory-limited machines. In the case of the land ice model, implementation of the algorithm allows further optimization by having the adjoint model solve a sequence of linear systems with identical (as opposed to varying) matrices, greatly improving performance. Finally, the methods introduced here will be of value to other efforts applying AD tools to ice models, particularly ones which solve a hybrid shallow ice/shallow shelf approximation to the Stokes equations.« less

Numerical study and ex vivo assessment of HIFU treatment time reduction through optimization of focal point trajectory

NASA Astrophysics Data System (ADS)

Grisey, A.; Yon, S.; Pechoux, T.; Letort, V.; Lafitte, P.

2017-03-01

Treatment time reduction is a key issue to expand the use of high intensity focused ultrasound (HIFU) surgery, especially for benign pathologies. This study aims at quantitatively assessing the potential reduction of the treatment time arising from moving the focal point during long pulses. In this context, the optimization of the focal point trajectory is crucial to achieve a uniform thermal dose repartition and avoid boiling. At first, a numerical optimization algorithm was used to generate efficient trajectories. Thermal conduction was simulated in 3D with a finite difference code and damages to the tissue were modeled using the thermal dose formula. Given an initial trajectory, the thermal dose field was first computed, then, making use of Pontryagin's maximum principle, the trajectory was iteratively refined. Several initial trajectories were tested. Then, an ex vivo study was conducted in order to validate the efficicency of the resulting optimized strategies. Single pulses were performed at 3MHz on fresh veal liver samples with an Echopulse and the size of each unitary lesion was assessed by cutting each sample along three orthogonal planes and measuring the dimension of the whitened area based on photographs. We propose a promising approach to significantly shorten HIFU treatment time: the numerical optimization algorithm was shown to provide a reliable insight on trajectories that can improve treatment strategies. The model must now be improved in order to take in vivo conditions into account and extensively validated.

Intracranial aneurysms: optimized diagnostic tools call for thorough interdisciplinary treatment strategies.

PubMed

Mueller, Oliver M; Schlamann, Marc; Mueller, Daniela; Sandalcioglu, I Erol; Forsting, Michael; Sure, Ulrich

2011-09-01

Intracranial aneurysms (IAs) require deliberately selected treatment strategies as they are incrementally found prior to rupture and deleterious subarachnoid haemorrhage (SAH). Multiple and recurrent aneurysms necessitate both neurointerventionalists and neurosurgeons to optimize aneurysmal occlusion in an interdisciplinary effort. The present study was conducted to condense essential strategies from a single neurovascular centre with regard to the lessons learned. Medical charts of 321 consecutive patients treated for IAs at our centre from September 2008 until December 2010 were retrospectively analysed for clinical presentation of the aneurysms, multiplicity and treatment pathways. In addition, a selective Medline search was performed. A total of 321 patients with 492 aneurysms underwent occlusion of their symptomatic aneurysm: 132 (41.1%) individuals were treated surgically, 189 (58.2%) interventionally; 138 patients presented with a SAH, of these 44.2% were clipped and 55.8% were coiled. Aneurysms of the middle cerebral artery were primarily occluded surgically (88), whereas most of the aneurysms of the internal carotid artery and anterior communicating artery (114) were treated endovascularly. Multiple aneurysms (range 2-5 aneurysms/individual) were diagnosed in 98 patients (30.2%). During the study period 12 patients with recurrent aneurysms were allocated to another treatment modality (previously clip to coil and vice versa). Our data show that successful interdisciplinary occlusion of IAs is based on both neurosurgical and neurointerventional therapy. In particular, multiple and recurrent aneurysms require tailored individual approaches to aneurysmal occlusion. This is achieved by a consequent interdisciplinary pondering of the optimal strategy to occlude IAs in order to prevent SAH.

An integrated in vitro and in vivo high throughput screen identifies treatment leads for ependymoma

PubMed Central

Atkinson, Jennifer M.; Shelat, Anang A.; Carcaboso, Angel Montero; Kranenburg, Tanya A.; Arnold, Alexander; Boulos, Nidal; Wright, Karen; Johnson, Robert A.; Poppleton, Helen; Mohankumar, Kumarasamypet M.; Feau, Clementine; Phoenix, Timothy; Gibson, Paul; Zhu, Liqin; Tong, Yiai; Eden, Chris; Ellison, David W.; Priebe, Waldemar; Koul, Dimpy; Yung, W. K. Alfred; Gajjar, Amar; Stewart, Clinton F.; Guy, R. Kip; Gilbertson, Richard J.

2011-01-01

Summary Using a mouse model of ependymoma—a chemoresistant brain tumor—we combined multi-cell high-throughput screening (HTS), kinome-wide binding assays, and in vivo efficacy studies, to identify potential treatments with predicted toxicity against neural stem cells (NSC). We identified kinases within the insulin signaling pathway and centrosome cycle as regulators of ependymoma cell proliferation, and their corresponding inhibitors as potential therapies. FDA approved drugs not currently used to treat ependymoma were also identified that posses selective toxicity against ependymoma cells relative to normal NSCs both in vitro and in vivo e.g., 5-fluoruracil. Our comprehensive approach advances understanding of the biology and treatment of ependymoma including the discovery of several treatment leads for immediate clinical translation. PMID:21907928

Visualization of Global Disease Burden for the Optimization of Patient Management and Treatment.

PubMed

Schlee, Winfried; Hall, Deborah A; Edvall, Niklas K; Langguth, Berthold; Canlon, Barbara; Cederroth, Christopher R

2017-01-01

The assessment and treatment of complex disorders is challenged by the multiple domains and instruments used to evaluate clinical outcome. With the large number of assessment tools typically used in complex disorders comes the challenge of obtaining an integrative view of disease status to further evaluate treatment outcome both at the individual level and at the group level. Radar plots appear as an attractive visual tool to display multivariate data on a two-dimensional graphical illustration. Here, we describe the use of radar plots for the visualization of disease characteristics applied in the context of tinnitus, a complex and heterogeneous condition, the treatment of which has shown mixed success. Data from two different cohorts, the Swedish Tinnitus Outreach Project (STOP) and the Tinnitus Research Initiative (TRI) database, were used. STOP is a population-based cohort where cross-sectional data from 1,223 non-tinnitus and 933 tinnitus subjects were analyzed. By contrast, the TRI contained data from 571 patients who underwent various treatments and whose Clinical Global Impression (CGI) score was accessible to infer treatment outcome. In the latter, 34,560 permutations were tested to evaluate whether a particular ordering of the instruments could reflect better the treatment outcome measured with the CGI. Radar plots confirmed that tinnitus subtypes such as occasional and chronic tinnitus from the STOP cohort could be strikingly different, and helped appreciate a gender bias in tinnitus severity. Radar plots with greater surface areas were consistent with greater burden, and enabled a rapid appreciation of the global distress associated with tinnitus in patients categorized according to tinnitus severity. Permutations in the arrangement of instruments allowed to identify a configuration with minimal variance and maximized surface difference between CGI groups from the TRI database, thus affording a means of optimally evaluating the outcomes in individual

Energy self-sufficient sewage wastewater treatment plants: is optimized anaerobic sludge digestion the key?

PubMed

Jenicek, P; Kutil, J; Benes, O; Todt, V; Zabranska, J; Dohanyos, M

2013-01-01

The anaerobic digestion of primary and waste activated sludge generates biogas that can be converted into energy to power the operation of a sewage wastewater treatment plant (WWTP). But can the biogas generated by anaerobic sludge digestion ever completely satisfy the electricity requirements of a WWTP with 'standard' energy consumption (i.e. industrial pollution not treated, no external organic substrate added)? With this question in mind, we optimized biogas production at Prague's Central Wastewater Treatment Plant in the following ways: enhanced primary sludge separation; thickened waste activated sludge; implemented a lysate centrifuge; increased operational temperature; improved digester mixing. With these optimizations, biogas production increased significantly to 12.5 m(3) per population equivalent per year. In turn, this led to an equally significant increase in specific energy production from approximately 15 to 23.5 kWh per population equivalent per year. We compared these full-scale results with those obtained from WWTPs that are already energy self-sufficient, but have exceptionally low energy consumption. Both our results and our analysis suggest that, with the correct optimization of anaerobic digestion technology, even WWTPs with 'standard' energy consumption can either attain or come close to attaining energy self-sufficiency.

Individually prescribed diet is fundamental to optimize nutritional treatment in geriatric patients.

PubMed

Hedman, S; Nydahl, M; Faxén-Irving, G

2016-06-01

Malnutrition is a well-recognized problem in geriatric patients. Individually prescribed diet is fundamental to optimize nutritional treatment in geriatric patients. The objective of this study was to investigate routines regarding dietary prescriptions and monitoring of food intake in geriatric patients and to see how well the prescribed diet conforms to the patients' nutritional status and ability to eat. A further aim was to identify the most common reasons and factors interacting with patients not finishing a complete meal. This study combines two methods using both qualitative and quantitative analysis. Patients (n = 43; 82.5 ± 7.5 yrs; 60% females) at four geriatric wards performed a two-day dietary record, assisted by a dietician. Nurses and assistant nurses at each ward participated in a semi-structured interview regarding prescription of diets and portion size for the patients. The prescribed diet differed significantly (P < 0.01) from a diet based upon the patient's nutritional status and ability to eat. Only 30% of the patients were prescribed an energy-enriched diet in contrast to 60% that was in need of it. The most common reason for not finishing the meal was lack of appetite. Diet prescription for the patient was based upon information about eating difficulties identified in the Mini Nutritional Assessment-Short Form (MNA-SF) at admission and the type of diet that was prescribed on a previous ward. Monitoring of the patients' food intake was described as a continuous process discussed daily between the staff. Patients' nutritional status and to what extent they were able to eat a complete meal was not routinely considered when prescribing food and monitoring food intake in this study. By making use of this information the diet could be tailored to the patients' needs, thereby improving their nutritional treatment. Copyright © 2015 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

An automatic CFD-based flow diverter optimization principle for patient-specific intracranial aneurysms.

PubMed

Janiga, Gábor; Daróczy, László; Berg, Philipp; Thévenin, Dominique; Skalej, Martin; Beuing, Oliver

2015-11-05

The optimal treatment of intracranial aneurysms using flow diverting devices is a fundamental issue for neuroradiologists as well as neurosurgeons. Due to highly irregular manifold aneurysm shapes and locations, the choice of the stent and the patient-specific deployment strategy can be a very difficult decision. To support the therapy planning, a new method is introduced that combines a three-dimensional CFD-based optimization with a realistic deployment of a virtual flow diverting stent for a given aneurysm. To demonstrate the feasibility of this method, it was applied to a patient-specific intracranial giant aneurysm that was successfully treated using a commercial flow diverter. Eight treatment scenarios with different local compressions were considered in a fully automated simulation loop. The impact on the corresponding blood flow behavior was evaluated qualitatively as well as quantitatively, and the optimal configuration for this specific case was identified. The virtual deployment of an uncompressed flow diverter reduced the inflow into the aneurysm by 24.4% compared to the untreated case. Depending on the positioning of the local stent compression below the ostium, blood flow reduction could vary between 27.3% and 33.4%. Therefore, a broad range of potential treatment outcomes was identified, illustrating the variability of a given flow diverter deployment in general. This method represents a proof of concept to automatically identify the optimal treatment for a patient in a virtual study under certain assumptions. Hence, it contributes to the improvement of virtual stenting for intracranial aneurysms and can support physicians during therapy planning in the future. Copyright © 2015 Elsevier Ltd. All rights reserved.

A bottom-up robust optimization framework for identifying river basin development pathways under deep climate uncertainty

NASA Astrophysics Data System (ADS)

Taner, M. U.; Ray, P.; Brown, C.

2016-12-01

Hydroclimatic nonstationarity due to climate change poses challenges for long-term water infrastructure planning in river basin systems. While designing strategies that are flexible or adaptive hold intuitive appeal, development of well-performing strategies requires rigorous quantitative analysis that address uncertainties directly while making the best use of scientific information on the expected evolution of future climate. Multi-stage robust optimization (RO) offers a potentially effective and efficient technique for addressing the problem of staged basin-level planning under climate change, however the necessity of assigning probabilities to future climate states or scenarios is an obstacle to implementation, given that methods to reliably assign probabilities to future climate states are not well developed. We present a method that overcomes this challenge by creating a bottom-up RO-based framework that decreases the dependency on probability distributions of future climate and rather employs them after optimization to aid selection amongst competing alternatives. The iterative process yields a vector of `optimal' decision pathways each under the associated set of probabilistic assumptions. In the final phase, the vector of optimal decision pathways is evaluated to identify the solutions that are least sensitive to the scenario probabilities and are most-likely conditional on the climate information. The framework is illustrated for the planning of new dam and hydro-agricultural expansions projects in the Niger River Basin over a 45-year planning period from 2015 to 2060.

Optimal treatment sequence in COPD: Can a consensus be found?

PubMed

Ferreira, J; Drummond, M; Pires, N; Reis, G; Alves, C; Robalo-Cordeiro, C

2016-01-01

There is currently no consensus on the treatment sequence in chronic obstructive pulmonary disease (COPD), although it is recognized that early diagnosis is of paramount importance to start treatment in the early stages of the disease. Although it is fairly consensual that initial treatment should be with an inhaled short-acting beta agonist, a short-acting muscarinic antagonist, a long-acting beta-agonist or a long-acting muscarinic antagonist. As the disease progresses, several therapeutic options are available, and which to choose at each disease stage remains controversial. When and in which patients to use dual bronchodilation? When to use inhaled corticosteroids? And triple therapy? Are the existing non-inhaled therapies, such as mucolytic agents, antibiotics, phosphodiesterase-4 inhibitors, methylxanthines and immunostimulating agents, useful? If so, which patients would benefit? Should co-morbidities be taken into account when choosing COPD therapy for a patient? This paper reviews current guidelines and available evidence and proposes a therapeutic scheme for COPD patients. We also propose a treatment algorithm in the hope that it will help physicians to decide the best approach for their patients. The authors conclude that, at present, a full consensus on optimal treatment sequence in COPD cannot be found, mainly due to disease heterogeneity and lack of biomarkers to guide treatment. For the time being, and although some therapeutic approaches are consensual, treatment of COPD should be patient-oriented. Copyright © 2015 Sociedade Portuguesa de Pneumologia. Published by Elsevier España, S.L.U. All rights reserved.

Evidence-based medicine is affordable: the cost-effectiveness of current compared with optimal treatment in rheumatoid and osteoarthritis.

PubMed

Andrews, Gavin; Simonella, Leonardo; Lapsley, Helen; Sanderson, Kristy; March, Lyn

2006-04-01

To determine the cost-effectiveness of averting the burden of disease. We used secondary population data and metaanalyses of various government-funded services and interventions to investigate the costs and benefits of various levels of treatment for rheumatoid arthritis (RA) and osteoarthritis (OA) in adults using a burden of disease framework. Population burden was calculated for both diseases in the absence of any treatment as years lived with disability (YLD), ignoring the years of life lost. We then estimated the proportion of burden averted with current interventions, the proportion that could be averted with optimally implemented current evidence-based guidelines, and the direct treatment cost-effectiveness ratio in dollars per YLD averted for both treatment levels. The majority of people with arthritis sought medical treatment. Current treatment for RA averted 26% of the burden, with a cost-effectiveness ratio of dollar 19,000 per YLD averted. Optimal, evidence-based treatment would avert 48% of the burden, with a cost-effectiveness ratio of dollar 12,000 per YLD averted. Current treatment of OA in Australia averted 27% of the burden, with a cost-effectiveness ratio of dollar 25,000 per YLD averted. Optimal, evidence-based treatment would avert 39% of the burden, with an unchanged cost-effectiveness ratio of dollar 25,000 per YLD averted. While the precise dollar costs in each country will differ, the relativities at this level of coverage should remain the same. There is no evidence that closing the gap between evidence and practice would result in a drop in efficiency.

Exploring the optimal economic timing for crop tree release treatments in hardwoods: results from simulation

Treesearch

Chris B. LeDoux; Gary W. Miller

2008-01-01

In this study we used data from 16 Appalachian hardwood stands, a growth and yield computer simulation model, and stump-to-mill logging cost-estimating software to evaluate the optimal economic timing of crop tree release (CTR) treatments. The simulated CTR treatments consisted of one-time logging operations at stand age 11, 23, 31, or 36 years, with the residual...

TARGETED SEQUENTIAL DESIGN FOR TARGETED LEARNING INFERENCE OF THE OPTIMAL TREATMENT RULE AND ITS MEAN REWARD.

PubMed

Chambaz, Antoine; Zheng, Wenjing; van der Laan, Mark J

2017-01-01

This article studies the targeted sequential inference of an optimal treatment rule (TR) and its mean reward in the non-exceptional case, i.e. , assuming that there is no stratum of the baseline covariates where treatment is neither beneficial nor harmful, and under a companion margin assumption. Our pivotal estimator, whose definition hinges on the targeted minimum loss estimation (TMLE) principle, actually infers the mean reward under the current estimate of the optimal TR. This data-adaptive statistical parameter is worthy of interest on its own. Our main result is a central limit theorem which enables the construction of confidence intervals on both mean rewards under the current estimate of the optimal TR and under the optimal TR itself. The asymptotic variance of the estimator takes the form of the variance of an efficient influence curve at a limiting distribution, allowing to discuss the efficiency of inference. As a by product, we also derive confidence intervals on two cumulated pseudo-regrets, a key notion in the study of bandits problems. A simulation study illustrates the procedure. One of the corner-stones of the theoretical study is a new maximal inequality for martingales with respect to the uniform entropy integral.

All Might Have Won, But Not All Have the Prize: Optimal Treatment for Substance Abuse Among Adolescents with Conduct Problems

PubMed Central

Spas, Jayson; Ramsey, Susan; Paiva, Andrea L.; Stein, L.A.R.

2012-01-01

Considerable evidence from the literature on treatment outcomes indicates that substance abuse treatment among adolescents with conduct problems varies widely. Treatments commonly used among this population are cognitive-behavioral therapy (CBT), 12-step facilitation, multisystemic therapy (MST), psychoeducation (PE), and motivational interviewing (MI). This manuscript thoroughly and systematically reviews the available literature to determine which treatment is optimal for substance-abusing adolescents with conduct problems. Results suggest that although there are several evidence-based and empirically supported treatments, those that incorporate family-based intervention consistently provide the most positive treatment outcomes. In particular, this review further reveals that although many interventions have gained empirical support over the years, only one holds the prize as being the optimal treatment of choice for substance abuse treatment among adolescents with conduct problems. PMID:23170066

Identifying unproven cancer treatments on the health web: addressing accuracy, generalizability and scalability.

PubMed

Aphinyanaphongs, Yin; Fu, Lawrence D; Aliferis, Constantin F

2013-01-01

Building machine learning models that identify unproven cancer treatments on the Health Web is a promising approach for dealing with the dissemination of false and dangerous information to vulnerable health consumers. Aside from the obvious requirement of accuracy, two issues are of practical importance in deploying these models in real world applications. (a) Generalizability: The models must generalize to all treatments (not just the ones used in the training of the models). (b) Scalability: The models can be applied efficiently to billions of documents on the Health Web. First, we provide methods and related empirical data demonstrating strong accuracy and generalizability. Second, by combining the MapReduce distributed architecture and high dimensionality compression via Markov Boundary feature selection, we show how to scale the application of the models to WWW-scale corpora. The present work provides evidence that (a) a very small subset of unproven cancer treatments is sufficient to build a model to identify unproven treatments on the web; (b) unproven treatments use distinct language to market their claims and this language is learnable; (c) through distributed parallelization and state of the art feature selection, it is possible to prepare the corpora and build and apply models with large scalability.

Photo-Electrochemical Treatment of Reactive Dyes in Wastewater and Reuse of the Effluent: Method Optimization

PubMed Central

Sala, Mireia; López-Grimau, Víctor; Gutiérrez-Bouzán, Carmen

2014-01-01

In this work, the efficiency of a photo-electrochemical method to remove color in textile dyeing effluents is discussed. The decolorization of a synthetic effluent containing a bi-functional reactive dye was carried out by applying an electrochemical treatment at different intensities (2 A, 5 A and 10 A), followed by ultraviolet irradiation. The combination of both treatments was optimized. The final percentage of effluent decolorization, the reduction of halogenated organic volatile compound and the total organic carbon removal were the determinant factors in the selection of the best treatment conditions. The optimized method was applied to the treatment of nine simulated dyeing effluents prepared with different reactive dyes in order to compare the behavior of mono, bi, and tri-reactive dyes. Finally, the nine treated effluents were reused in new dyeing processes and the color differences (DECMC (2:1)) with respect to a reference were evaluated. The influence of the effluent organic matter removal on the color differences was also studied. The reuse of the treated effluents provides satisfactory dyeing results, and an important reduction in water consumption and salt discharge is achieved. PMID:28788251

Study on Power Ultrasound Optimization and Its Comparison with Conventional Thermal Processing for Treatment of Raw Honey

PubMed Central

2017-01-01

Summary The present study was done to optimize the power ultrasound processing for maximizing diastase activity of and minimizing hydroxymethylfurfural (HMF) content in honey using response surface methodology. Experimental design with treatment time (1-15 min), amplitude (20-100%) and volume (40-80 mL) as independent variables under controlled temperature conditions was studied and it was concluded that treatment time of 8 min, amplitude of 60% and volume of 60 mL give optimal diastase activity and HMF content, i.e. 32.07 Schade units and 30.14 mg/kg, respectively. Further thermal profile analyses were done with initial heating temperatures of 65, 75, 85 and 95 ºC until temperature of honey reached up to 65 ºC followed by holding time of 25 min at 65 ºC, and the results were compared with thermal profile of honey treated with optimized power ultrasound. The quality characteristics like moisture, pH, diastase activity, HMF content, colour parameters and total colour difference were least affected by optimized power ultrasound treatment. Microbiological analysis also showed lower counts of aerobic mesophilic bacteria and in ultrasonically treated honey than in thermally processed honey samples complete destruction of coliforms, yeasts and moulds. Thus, it was concluded that power ultrasound under suggested operating conditions is an alternative nonthermal processing technique for honey. PMID:29540991

A numerical identifiability test for state-space models--application to optimal experimental design.

PubMed

Hidalgo, M E; Ayesa, E

2001-01-01

This paper describes a mathematical tool for identifiability analysis, easily applicable to high order non-linear systems modelled in state-space and implementable in simulators with a time-discrete approach. This procedure also permits a rigorous analysis of the expected estimation errors (average and maximum) in calibration experiments. The methodology is based on the recursive numerical evaluation of the information matrix during the simulation of a calibration experiment and in the setting-up of a group of information parameters based on geometric interpretations of this matrix. As an example of the utility of the proposed test, the paper presents its application to an optimal experimental design of ASM Model No. 1 calibration, in order to estimate the maximum specific growth rate microH and the concentration of heterotrophic biomass XBH.

Optimizing SGLT inhibitor treatment for diabetes with chronic kidney diseases.

PubMed

Layton, Anita T

2018-06-28

Diabetes induces glomerular hyperfiltration, affects kidney function, and may lead to chronic kidney diseases. A novel therapeutic treatment for diabetic patients targets the sodium-glucose cotransporter isoform 2 (SGLT2) in the kidney. SGLT2 inhibitors enhance urinary glucose, [Formula: see text] and fluid excretion and lower hyperglycemia in diabetes by inhibiting [Formula: see text] and glucose reabsorption along the proximal convoluted tubule. A goal of this study is to predict the effects of SGLT2 inhibitors in diabetic patients with and without chronic kidney diseases. To that end, we applied computational rat kidney models to assess how SGLT2 inhibition affects renal solute transport and metabolism when nephron population are normal or reduced (the latter simulates chronic kidney disease). The model predicts that SGLT2 inhibition induces glucosuria and natriuresis, with those effects enhanced in a remnant kidney. The model also predicts that the [Formula: see text] transport load and thus oxygen consumption of the S3 segment are increased under SGLT2 inhibition, a consequence that may increase the risk of hypoxia for that segment. To protect the vulnerable S3 segment, we explore dual SGLT2/SGLT1 inhibition and seek to determine the optimal combination that would yield sufficient urinary glucose excretion while limiting the metabolic load on the S3 segment. The model predicts that the optimal combination of SGLT2/SGLT1 inhibition lowers the oxygen requirements of key tubular segments, but decreases urine flow and [Formula: see text] excretion; the latter effect may limit the cardiovascular protection of the treatment.

Recommendations for optimizing methotrexate treatment for patients with rheumatoid arthritis

PubMed Central

Bello, Alfonso E; Perkins, Elizabeth L; Jay, Randy; Efthimiou, Petros

2017-01-01

Methotrexate (MTX) remains the cornerstone therapy for patients with rheumatoid arthritis (RA), with well-established safety and efficacy profiles and support in international guidelines. Clinical and radiologic results indicate benefits of MTX monotherapy and combination with other agents, yet patients may not receive optimal dosing, duration, or route of administration to maximize their response to this drug. This review highlights best practices for MTX use in RA patients. First, to improve the response to oral MTX, a high initial dose should be administered followed by rapid titration. Importantly, this approach does not appear to compromise safety or tolerability for patients. Treatment with oral MTX, with appropriate dose titration, then should be continued for at least 6 months (as long as the patient experiences some response to treatment within 3 months) to achieve an accurate assessment of treatment efficacy. If oral MTX treatment fails due to intolerability or inadequate response, the patient may be “rescued” by switching to subcutaneous delivery of MTX. Consideration should also be given to starting with subcutaneous MTX given its favorable bioavailability and pharmacodynamic profile over oral delivery. Either initiation of subcutaneous MTX therapy or switching from oral to subcutaneous administration improves persistence with treatment. Upon transition from oral to subcutaneous delivery, MTX dosage should be maintained, rather than increased, and titration should be performed as needed. Similarly, if another RA treatment is necessary to control the disease, the MTX dosage and route of administration should be maintained, with titration as needed. PMID:28435338

Optimizing Requirements Decisions with KEYS

NASA Technical Reports Server (NTRS)

Jalali, Omid; Menzies, Tim; Feather, Martin

2008-01-01

Recent work with NASA's Jet Propulsion Laboratory has allowed for external access to five of JPL's real-world requirements models, anonymized to conceal proprietary information, but retaining their computational nature. Experimentation with these models, reported herein, demonstrates a dramatic speedup in the computations performed on them. These models have a well defined goal: select mitigations that retire risks which, in turn, increases the number of attainable requirements. Such a non-linear optimization is a well-studied problem. However identification of not only (a) the optimal solution(s) but also (b) the key factors leading to them is less well studied. Our technique, called KEYS, shows a rapid way of simultaneously identifying the solutions and their key factors. KEYS improves on prior work by several orders of magnitude. Prior experiments with simulated annealing or treatment learning took tens of minutes to hours to terminate. KEYS runs much faster than that; e.g for one model, KEYS ran 13,000 times faster than treatment learning (40 minutes versus 0.18 seconds). Processing these JPL models is a non-linear optimization problem: the fewest mitigations must be selected while achieving the most requirements. Non-linear optimization is a well studied problem. With this paper, we challenge other members of the PROMISE community to improve on our results with other techniques.

Optimized evaporation technique for leachate treatment: Small scale implementation.

PubMed

Benyoucef, Fatima; Makan, Abdelhadi; El Ghmari, Abderrahman; Ouatmane, Aziz

2016-04-01

This paper introduces an optimized evaporation technique for leachate treatment. For this purpose and in order to study the feasibility and measure the effectiveness of the forced evaporation, three cuboidal steel tubs were designed and implemented. The first control-tub was installed at the ground level to monitor natural evaporation. Similarly, the second and the third tub, models under investigation, were installed respectively at the ground level (equipped-tub 1) and out of the ground level (equipped-tub 2), and provided with special equipment to accelerate the evaporation process. The obtained results showed that the evaporation rate at the equipped-tubs was much accelerated with respect to the control-tub. It was accelerated five times in the winter period, where the evaporation rate was increased from a value of 0.37 mm/day to reach a value of 1.50 mm/day. In the summer period, the evaporation rate was accelerated more than three times and it increased from a value of 3.06 mm/day to reach a value of 10.25 mm/day. Overall, the optimized evaporation technique can be applied effectively either under electric or solar energy supply, and will accelerate the evaporation rate from three to five times whatever the season temperature. Copyright © 2016. Published by Elsevier Ltd.

Pharmacodynamically optimized erythropoietin treatment combined with phlebotomy reduction predicted to eliminate blood transfusions in selected preterm infants.

PubMed

Rosebraugh, Matthew R; Widness, John A; Nalbant, Demet; Cress, Gretchen; Veng-Pedersen, Peter

2014-02-01

Preterm very-low-birth-weight (VLBW) infants weighing <1.5 kg at birth develop anemia, often requiring multiple red blood cell transfusions (RBCTx). Because laboratory blood loss is a primary cause of anemia leading to RBCTx in VLBW infants, our purpose was to simulate the extent to which RBCTx can be reduced or eliminated by reducing laboratory blood loss in combination with pharmacodynamically optimized erythropoietin (Epo) treatment. Twenty-six VLBW ventilated infants receiving RBCTx were studied during the first month of life. RBCTx simulations were based on previously published RBCTx criteria and data-driven Epo pharmacodynamic optimization of literature-derived RBC life span and blood volume data corrected for phlebotomy loss. Simulated pharmacodynamic optimization of Epo administration and reduction in phlebotomy by ≥ 55% predicted a complete elimination of RBCTx in 1.0-1.5 kg infants. In infants <1.0 kg with 100% reduction in simulated phlebotomy and optimized Epo administration, a 45% reduction in RBCTx was predicted. The mean blood volume drawn from all infants was 63 ml/kg: 33% required for analysis and 67% discarded. When reduced laboratory blood loss and optimized Epo treatment are combined, marked reductions in RBCTx in ventilated VLBW infants were predicted, particularly among those with birth weights >1.0 kg.

Cherenkov imaging method for rapid optimization of clinical treatment geometry in total skin electron beam therapy

PubMed Central

Zhang, Rongxiao; Gladstone, David J.; Williams, Benjamin B.; Glaser, Adam K.; Pogue, Brian W.; Jarvis, Lesley A.

2016-01-01

Purpose: A method was developed utilizing Cherenkov imaging for rapid and thorough determination of the two gantry angles that produce the most uniform treatment plane during dual-field total skin electron beam therapy (TSET). Methods: Cherenkov imaging was implemented to gather 2D measurements of relative surface dose from 6 MeV electron beams on a white polyethylene sheet. An intensified charge-coupled device camera time-gated to the Linac was used for Cherenkov emission imaging at sixty-two different gantry angles (1° increments, from 239.5° to 300.5°). Following a modified Stanford TSET technique, which uses two fields per patient position for full body coverage, composite images were created as the sum of two beam images on the sheet; each angle pair was evaluated for minimum variation across the patient region of interest. Cherenkov versus dose correlation was verified with ionization chamber measurements. The process was repeated at source to surface distance (SSD) = 441, 370.5, and 300 cm to determine optimal angle spread for varying room geometries. In addition, three patients receiving TSET using a modified Stanford six-dual field technique with 6 MeV electron beams at SSD = 441 cm were imaged during treatment. Results: As in previous studies, Cherenkov intensity was shown to directly correlate with dose for homogenous flat phantoms (R2 = 0.93), making Cherenkov imaging an appropriate candidate to assess and optimize TSET setup geometry. This method provided dense 2D images allowing 1891 possible treatment geometries to be comprehensively analyzed from one data set of 62 single images. Gantry angles historically used for TSET at their institution were 255.5° and 284.5° at SSD = 441 cm; however, the angles optimized for maximum homogeneity were found to be 252.5° and 287.5° (+6° increase in angle spread). Ionization chamber measurements confirmed improvement in dose homogeneity across the treatment field from a range of 24.4% at the initial angles

Double-blind optimization of subcallosal cingulate deep brain stimulation for treatment-resistant depression: a pilot study.

PubMed

Ramasubbu, Rajamannar; Anderson, Susan; Haffenden, Angela; Chavda, Swati; Kiss, Zelma H T

2013-09-01

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is reported to be a safe and effective new treatment for treatment-resistant depression (TRD). However, the optimal electrical stimulation parameters are unknown and generally selected by trial and error. This pilot study investigated the relationship between stimulus parameters and clinical effects in SCC-DBS treatment for TRD. Four patients with TRD underwent SCC-DBS surgery. In a double-blind stimulus optimization phase, frequency and pulse widths were randomly altered weekly, and corresponding changes in mood and depression were evaluated using a visual analogue scale (VAS) and the 17-item Hamilton Rating Scale for Depression (HAM-D-17). In the open-label postoptimization phase, depressive symptoms were evaluated biweekly for 6 months to determine long-term clinical outcomes. Longer pulse widths (270-450 μs) were associated with reductions in HAM-D-17 scores in 3 patients and maximal happy mood VAS responses in all 4 patients. Only 1 patient showed acute clinical or mood effects from changing the stimulation frequency. After 6 months of open-label therapy, 2 patients responded and 1 patient partially responded. Limitations include small sample size, weekly changes in stimulus parameters, and fixed-order and carry-forward effects. Longer pulse width stimulation may have a role in stimulus optimization for SCC-DBS in TRD. Longer pulse durations produce larger apparent current spread, suggesting that we do not yet know the optimal target or stimulus parameters for this therapy. Investigations using different stimulus parameters are required before embarking on large-scale randomized sham-controlled trials.

Optimization of Treatment Geometry to Reduce Normal Brain Dose in Radiosurgery of Multiple Brain Metastases with Single-Isocenter Volumetric Modulated Arc Therapy.

PubMed

Wu, Qixue; Snyder, Karen Chin; Liu, Chang; Huang, Yimei; Zhao, Bo; Chetty, Indrin J; Wen, Ning

2016-09-30

Treatment of patients with multiple brain metastases using a single-isocenter volumetric modulated arc therapy (VMAT) has been shown to decrease treatment time with the tradeoff of larger low dose to the normal brain tissue. We have developed an efficient Projection Summing Optimization Algorithm to optimize the treatment geometry in order to reduce dose to normal brain tissue for radiosurgery of multiple metastases with single-isocenter VMAT. The algorithm: (a) measures coordinates of outer boundary points of each lesion to be treated using the Eclipse Scripting Application Programming Interface, (b) determines the rotations of couch, collimator, and gantry using three matrices about the cardinal axes, (c) projects the outer boundary points of the lesion on to Beam Eye View projection plane, (d) optimizes couch and collimator angles by selecting the least total unblocked area for each specific treatment arc, and (e) generates a treatment plan with the optimized angles. The results showed significant reduction in the mean dose and low dose volume to normal brain, while maintaining the similar treatment plan qualities on the thirteen patients treated previously. The algorithm has the flexibility with regard to the beam arrangements and can be integrated in the treatment planning system for clinical application directly.

Optimization of conventional water treatment plant using dynamic programming.

PubMed

Mostafa, Khezri Seyed; Bahareh, Ghafari; Elahe, Dadvar; Pegah, Dadras

2015-12-01

In this research, the mathematical models, indicating the capability of various units, such as rapid mixing, coagulation and flocculation, sedimentation, and the rapid sand filtration are used. Moreover, cost functions were used for the formulation of conventional water and wastewater treatment plant by applying Clark's formula (Clark, 1982). Also, by applying dynamic programming algorithm, it is easy to design a conventional treatment system with minimal cost. The application of the model for a case reduced the annual cost. This reduction was approximately in the range of 4.5-9.5% considering variable limitations. Sensitivity analysis and prediction of system's feedbacks were performed for different alterations in proportion from parameters optimized amounts. The results indicated (1) that the objective function is more sensitive to design flow rate (Q), (2) the variations in the alum dosage (A), and (3) the sand filter head loss (H). Increasing the inflow by 20%, the total annual cost would increase to about 12.6%, while 20% reduction in inflow leads to 15.2% decrease in the total annual cost. Similarly, 20% increase in alum dosage causes 7.1% increase in the total annual cost, while 20% decrease results in 7.9% decrease in the total annual cost. Furthermore, the pressure decrease causes 2.95 and 3.39% increase and decrease in total annual cost of treatment plants. © The Author(s) 2013.

MO-B-BRB-03: Systems Engineering Tools for Treatment Planning Process Optimization in Radiation Medicine

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

Kapur, A.

The radiotherapy treatment planning process has evolved over the years with innovations in treatment planning, treatment delivery and imaging systems. Treatment modality and simulation technologies are also rapidly improving and affecting the planning process. For example, Image-guided-radiation-therapy has been widely adopted for patient setup, leading to margin reduction and isocenter repositioning after simulation. Stereotactic Body radiation therapy (SBRT) and Radiosurgery (SRS) have gradually become the standard of care for many treatment sites, which demand a higher throughput for the treatment plans even if the number of treatments per day remains the same. Finally, simulation, planning and treatment are traditionally sequentialmore » events. However, with emerging adaptive radiotherapy, they are becoming more tightly intertwined, leading to iterative processes. Enhanced efficiency of planning is therefore becoming more critical and poses serious challenge to the treatment planning process; Lean Six Sigma approaches are being utilized increasingly to balance the competing needs for speed and quality. In this symposium we will discuss the treatment planning process and illustrate effective techniques for managing workflow. Topics will include: Planning techniques: (a) beam placement, (b) dose optimization, (c) plan evaluation (d) export to RVS. Planning workflow: (a) import images, (b) Image fusion, (c) contouring, (d) plan approval (e) plan check (f) chart check, (g) sequential and iterative process Influence of upstream and downstream operations: (a) simulation, (b) immobilization, (c) motion management, (d) QA, (e) IGRT, (f) Treatment delivery, (g) SBRT/SRS (h) adaptive planning Reduction of delay between planning steps with Lean systems due to (a) communication, (b) limited resource, (b) contour, (c) plan approval, (d) treatment. Optimizing planning processes: (a) contour validation (b) consistent planning protocol, (c) protocol/template sharing, (d

Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs.

PubMed

Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Graves, Yan Jiang; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

2013-12-21

Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using

Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs

NASA Astrophysics Data System (ADS)

Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Jiang Graves, Yan; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

2013-12-01

Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using

A Longitudinal Analysis of Treatment Optimism and HIV Acquisition and Transmission Risk Behaviors Among Black Men Who Have Sex with Men in HPTN 061.

PubMed

Levy, Matthew E; Phillips, Gregory; Magnus, Manya; Kuo, Irene; Beauchamp, Geetha; Emel, Lynda; Hucks-Ortiz, Christopher; Hamilton, Erica L; Wilton, Leo; Chen, Iris; Mannheimer, Sharon; Tieu, Hong-Van; Scott, Hyman; Fields, Sheldon D; Del Rio, Carlos; Shoptaw, Steven; Mayer, Kenneth

2017-10-01

Little is known about HIV treatment optimism and risk behaviors among Black men who have sex with men (BMSM). Using longitudinal data from BMSM in the HPTN 061 study, we examined participants' self-reported comfort with having condomless sex due to optimistic beliefs regarding HIV treatment. We assessed correlates of treatment optimism and its association with subsequent risk behaviors for HIV acquisition or transmission using multivariable logistic regression with generalized estimating equations. Independent correlates of treatment optimism included age ≥35 years, annual household income <$20,000, depressive symptoms, high HIV conspiracy beliefs, problematic alcohol use, and previous HIV diagnosis. Treatment optimism was independently associated with subsequent condomless anal sex with a male partner of serodiscordant/unknown HIV status among HIV-infected men, but this association was not statistically significant among HIV-uninfected men. HIV providers should engage men in counseling conversations to assess and minimize willingness to have condomless sex that is rooted in optimistic treatment beliefs without knowledge of viral suppression.

Optimization of antitumor treatment conditions for transcutaneous CO2 application: An in vivo study.

PubMed

Ueha, Takeshi; Kawamoto, Teruya; Onishi, Yasuo; Harada, Risa; Minoda, Masaya; Toda, Mitsunori; Hara, Hitomi; Fukase, Naomasa; Kurosaka, Masahiro; Kuroda, Ryosuke; Akisue, Toshihiro; Sakai, Yoshitada

2017-06-01

Carbon dioxide (CO2) therapy can be applied to treat a variety of disorders. We previously found that transcutaneous application of CO2 with a hydrogel decreased the tumor volume of several types of tumors and induced apoptosis via the mitochondrial pathway. However, only one condition of treatment intensity has been tested. For widespread application in clinical antitumor therapy, the conditions must be optimized. In the present study, we investigated the relationship between the duration, frequency, and treatment interval of transcutaneous CO2 application and antitumor effects in murine xenograft models. Murine xenograft models of three types of human tumors (breast cancer, osteosarcoma, and malignant fibrous histiocytoma/undifferentiated pleomorphic sarcoma) were used to assess the antitumor effects of transcutaneous CO2 application of varying durations, frequencies, and treatment intervals. In all human tumor xenografts, apoptosis was significantly induced by CO2 treatment for ≥10 min, and a significant decrease in tumor volume was observed with CO2 treatments of >5 min. The effect on tumor volume was not dependent on the frequency of CO2 application, i.e., twice or five times per week. However, treatment using 3- and 4-day intervals was more effective at decreasing tumor volume than treatment using 2- and 5-day intervals. The optimal conditions of transcutaneous CO2 application to obtain the best antitumor effect in various tumors were as follows: greater than 10 min per application, twice per week, with 3- and 4-day intervals, and application to the site of the tumor. The results suggest that this novel transcutaneous CO2 application might be useful to treat primary tumors, while mitigating some side effects, and therefore could be safe for clinical trials.

SU-F-J-06: Optimized Patient Inclusion for NaF PET Response-Based Biopsies

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

Roth, A; Harmon, S; Perk, T

Purpose: A method to guide mid-treatment biopsies using quantitative [F-18]NaF PET/CT response is being investigated in a clinical trial. This study aims to develop methodology to identify patients amenable to mid-treatment biopsy based on pre-treatment imaging characteristics. Methods: 35 metastatic prostate cancer patients had NaF PET/CT scans taken prior to the start of treatment and 9–12 weeks into treatment. For mid-treatment biopsy targeting, lesions must be at least 1.5 cm{sup 3} and located in a clinically feasible region (lumbar/sacral spine, pelvis, humerus, or femur). Three methods were developed based on number of lesions present prior to treatment: a feasibility-restricted method,more » a location-restricted method, and an unrestricted method. The feasibility restricted method only utilizes information from lesions meeting biopsy requirements in the pre-treatment scan. The unrestricted method accounts for all lesions present in the pre-treatment scan. For each method, optimized classification cutoffs for candidate patients were determined. Results: 13 of the 35 patients had enough lesions at the mid-treatment for biopsy candidacy. Of 1749 lesions identified in all 35 patients at mid-treatment, only 9.8% were amenable to biopsy. Optimizing the feasibility-restricted method required 4 lesions at pre-treatment meeting volume and region requirements for biopsy, resulting patient identification sensitivity of 0.8 and specificity of 0.7. Of 6 false positive patients, only one patient lacked lesions for biopsy. Restricting for location alone showed poor results (sensitivity 0.2 and specificity 0.3). The optimized unrestricted method required patients have at least 37 lesions in pretreatment scan, resulting in a sensitivity of 0.8 and specificity of 0.8. There were 5 false positives, only one lacked lesions for biopsy. Conclusion: Incorporating the overall pre-treatment number of NaF PET/CT identified lesions provided best prediction for identifying

Optimization of electrocoagulation process for the treatment of landfill leachate

NASA Astrophysics Data System (ADS)

Huda, N.; Raman, A. A.; Ramesh, S.

2017-06-01

The main problem of landfill leachate is its diverse composition comprising of persistent organic pollutants (POPs) which must be removed before being discharge into the environment. In this study, the treatment of leachate using electrocoagulation (EC) was investigated. Iron was used as both the anode and cathode. Response surface methodology was used for experimental design and to study the effects of operational parameters. Central Composite Design was used to study the effects of initial pH, inter-electrode distance, and electrolyte concentration on color, and COD removals. The process could remove up to 84 % color and 49.5 % COD. The experimental data was fitted onto second order polynomial equations. All three factors were found to be significantly affect the color removal. On the other hand, electrolyte concentration was the most significant parameter affecting the COD removal. Numerical optimization was conducted to obtain the optimum process performance. Further work will be conducted towards integrating EC with other wastewater treatment processes such as electro-Fenton.

Optimizing molluscicide treatment strategies in different control stages of schistosomiasis in the People's Republic of China.

PubMed

Yang, Guo-Jing; Sun, Le-Ping; Hong, Qing-Biao; Zhu, Hong-Ru; Yang, Kun; Gao, Qi; Zhou, Xiao-Nong

2012-11-14

The application of chemical molluscicides is still one of the most effective measures for schistosomiasis control in P. R. China. By applying diverse molluscicide treatment scenarios on different snail densities in the field, we attempted to understand the cost-effectiveness of molluscicide application so as to prescribe an optimal management approach to control intermediate host snail Oncomelania hupensis under acceptable thresholds based on the goal of the National Schistosomiasis Control Programme. The molluscicidal field trial was carried out in the marshland of an island along the Yangtze River, Jiangsu province, P.R. China in October 2010. Three plots in the island representing low-density, medium-density and high-density groups were identified after the baseline survey on snail density. Each snail density plot was divided into four experimental units in which molluscicide (50% niclosamide ethanolamine salt wettable powder) was applied once, twice, trice and four times, respectively. The logistic regression model to correlate snail mortality rate with the covariates of number of molluscicidal treatment and snail density, and a linear regression model to investigate the relationship between cost-effectiveness and number of molluscicidal treatment as well as snail density were established. The study revealed that increase in the number of molluscicide treatments led to increased snail mortality across all three population density groups. The most cost-effective regimen was seen in the high snail density group with a single molluscicide treatment. For both high and low density groups, the more times molluscicide were applied, the less cost-effectiveness was. However, for the median density group, the level of cost-effectiveness for two applications was slightly higher than that in one time. We concluded that different stages of the national schistosomiasis control/elimination programme, namely morbidity control, transmission control and transmission interruption

Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit.

PubMed

Qin, Nan; Shen, Chenyang; Tsai, Min-Yu; Pinto, Marco; Tian, Zhen; Dedes, Georgios; Pompos, Arnold; Jiang, Steve B; Parodi, Katia; Jia, Xun

2018-01-01

One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC. The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases. Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation. We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. Copyright © 2017 Elsevier Inc. All rights reserved.

Identifying Effective Treatments from a Brief Experimental Analysis: Using a Single-Case Design Elements To Aid Decision Making.

ERIC Educational Resources Information Center

Martens, Brian K.; Eckert, Tanya L.; Bradley, Tracy A.; Ardoin, Scott P.

1999-01-01

Discusses the benefits of using brief experimental analysis to aid in treatment selection, identifies the forms of treatment that are most appropriate for this type of analysis, and describes key design elements for comparing treatments. Presents a study demonstrating the use of these design elements to identify an effective intervention for two…

Identifying treatment responders and predictors of improvement after cognitive-behavioral therapy for juvenile fibromyalgia.

PubMed

Sil, Soumitri; Arnold, Lesley M; Lynch-Jordan, Anne; Ting, Tracy V; Peugh, James; Cunningham, Natoshia; Powers, Scott W; Lovell, Daniel J; Hashkes, Philip J; Passo, Murray; Schikler, Kenneth N; Kashikar-Zuck, Susmita

2014-07-01

The primary objective of this study was to estimate a clinically significant and quantifiable change in functional disability to identify treatment responders in a clinical trial of cognitive-behavioral therapy (CBT) for youth with juvenile fibromyalgia (JFM). The second objective was to examine whether baseline functional disability (Functional Disability Inventory), pain intensity, depressive symptoms (Children's Depression Inventory), coping self-efficacy (Pain Coping Questionnaire), and parental pain history predicted treatment response in disability at 6-month follow-up. Participants were 100 adolescents (11-18 years of age) with JFM enrolled in a recently published clinical trial comparing CBT to a fibromyalgia education (FE) intervention. Patients were identified as achieving a clinically significant change in disability (i.e., were considered treatment responders) if they achieved both a reliable magnitude of change (estimated as a > or = 7.8-point reduction on the FDI) using the Reliable Change Index, and a reduction in FDI disability grade based on established clinical reference points. Using this rigorous standard, 40% of patients who received CBT (20 of 50) were identified as treatment responders, compared to 28% who received FE (14 of 50). For CBT, patients with greater initial disability and higher coping efficacy were significantly more likely to achieve a clinically significant improvement in functioning. Pain intensity, depressive symptoms, and parent pain history did not significantly predict treatment response. Estimating clinically significant change for outcome measures in behavioral trials sets a high bar but is a potentially valuable approach to improve the quality of clinical trials, to enhance interpretability of treatment effects, and to challenge researchers to develop more potent and tailored interventions. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

In what ways do communities support optimal antiretroviral treatment in Zimbabwe?

PubMed

Scott, K; Campbell, C; Madanhire, C; Skovdal, M; Nyamukapa, C; Gregson, S

2014-12-01

Little research has been conducted on how pre-existing indigenous community resources, especially social networks, affect the success of externally imposed HIV interventions. Antiretroviral treatment (ART), an externally initiated biomedical intervention, is being rolled out across sub-Saharan Africa. Understanding the ways in which community networks are working to facilitate optimal ART access and adherence will enable policymakers to better engage with and bolster these pre-existing resources. We conducted 67 interviews and eight focus group discussions with 127 people from three key population groups in Manicaland, eastern Zimbabwe: healthcare workers, adults on ART and carers of children on ART. We also observed over 100 h of HIV treatment sites at local clinics and hospitals. Our research sought to determine how indigenous resources were enabling people to achieve optimal ART access and adherence. We analysed data transcripts using thematic network technique, coding references to supportive community networks that enable local people to achieve ART access and adherence. People on ART or carers of children on ART in Zimbabwe report drawing support from a variety of social networks that enable them to overcome many obstacles to adherence. Key support networks include: HIV groups; food and income support networks; home-based care, church and women's groups; family networks; and relationships with healthcare providers. More attention to the community context in which HIV initiatives occur will help ensure that interventions work with and benefit from pre-existing social capital. © The Author (2013). Published by Oxford University Press.

In what ways do communities support optimal antiretroviral treatment in Zimbabwe?

PubMed Central

Scott, K.; Campbell, C.; Madanhire, C.; Skovdal, M.; Nyamukapa, C.; Gregson, S.

2014-01-01

Little research has been conducted on how pre-existing indigenous community resources, especially social networks, affect the success of externally imposed HIV interventions. Antiretroviral treatment (ART), an externally initiated biomedical intervention, is being rolled out across sub-Saharan Africa. Understanding the ways in which community networks are working to facilitate optimal ART access and adherence will enable policymakers to better engage with and bolster these pre-existing resources. We conducted 67 interviews and eight focus group discussions with 127 people from three key population groups in Manicaland, eastern Zimbabwe: healthcare workers, adults on ART and carers of children on ART. We also observed over 100 h of HIV treatment sites at local clinics and hospitals. Our research sought to determine how indigenous resources were enabling people to achieve optimal ART access and adherence. We analysed data transcripts using thematic network technique, coding references to supportive community networks that enable local people to achieve ART access and adherence. People on ART or carers of children on ART in Zimbabwe report drawing support from a variety of social networks that enable them to overcome many obstacles to adherence. Key support networks include: HIV groups; food and income support networks; home-based care, church and women's groups; family networks; and relationships with healthcare providers. More attention to the community context in which HIV initiatives occur will help ensure that interventions work with and benefit from pre-existing social capital. PMID:23503291

Sample treatment optimization for fish stool metabolomics.

PubMed

Hano, Takeshi; Ito, Mana; Ito, Katsutoshi; Uchida, Motoharu

2018-06-07

Gut microbiota play an essential role in an organism's health. The fecal metabolite profiling content reflects these microbiota-mediated physiological changes in various organisms, including fish. Therefore, metabolomics analysis of fish feces should provide insight into the dynamics linking physiology and gut microbiota. However, metabolites are often unstable in aquatic environments, making fecal metabolites difficult to examine in fish. In this study, a novel method using gas chromatography-mass spectrometry (GC-MS) was developed and optimized for the preparation of metabolomics samples from the feces of the marine fish, red sea bream (Pagrus major). The preparation methodology was optimized, focusing on rinsing frequency and rinsing solvent. Feces (collected within 4 h of excretion) were rinsed three times with sterilized 2.5% NaCl solution or 3.0% artificial seawater (ASW). Among the 86 metabolites identified in the NaCl-rinsed samples, 57 showed superior recovery to that in ASW-rinsed samples, indicating that NaCl is a better rinsing solvent, particularly for amino acids, organic acids, and fatty acids. To evaluate rinsing frequency, fecal samples were rinsed with NaCl solution 0, 1, 3, or 5 times. The results indicate that three or more rinses enabled robust and stable detection of metabolites encapsulated within the solid fecal residue. Furthermore, these data suggest that rinsing is unnecessary when studying sugars, amino acids, and sterols, again highlighting the need for appropriate rinsing solvent and frequency. This study provides further insight into the use of fecal samples to evaluate and promote fish health during farming and supports the application of this and similar analyses to study the effects of environmental fluctuations and/or contamination. Copyright © 2018 Elsevier B.V. All rights reserved.

Improved Outcomes for Transscleral Cyclophotocoagulation Through Optimized Treatment Parameters.

PubMed

Quigley, Harry A

2018-06-18

To compare outcomes of transscleral diode cyclophotocoagulation with the treatment parameters used. This was a retrospective chart review of a random, 50% sample of diode procedures using the G-probe over 10 years for uncontrolled glaucoma. The main outcome measure was intraocular pressure reduction by 20% and final IOP ≤21▒mm Hg. In 236 eyes (persons) treated by 5 glaucoma specialists, most eyes had severe glaucoma, with 75% having <20/200 acuity. Median follow-up was 2.7 years. In eyes receiving only one treatment, IOP success criterion was met in 72% (129/180). Success was significantly related to power per delivery and median total joules per treatment (successes=135 joules, failures=98 joules; P=0.0009), but not to number of deliveries, nor to extent of circumference treated. Greater success was associated with 3 or 4 second duration/delivery, power level based on audible cues, and firm pressure on the sclera. Using a standard 2000 milliwatt, 2 second, 20 deliveries in each eye had the lowest success (49%). Of those with no preoperative pain, 40 persons (57%) had no postoperative pain, while 20 reported pain of 1-3/10 (29%). Phthisis occurred in 7 eyes (3%), 5 of which had severe secondary eye disease. Nine eyes had no light perception (NLP) preoperatively, while 50 eyes were NLP at last followup, many after additional surgeries for other conditions. Diode cyclophotocoaguation achieved reasonable IOP lowering, often without severe postoperative pain or complication. Greater success was achieved when audible effects were used to tailor the power settings to individual responses. Diode treatments with no intraoperative effect adjustment or using standardized protocols may not achieve optimal success.

Cherenkov imaging method for rapid optimization of clinical treatment geometry in total skin electron beam therapy

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

Andreozzi, Jacqueline M., E-mail: Jacqueline.M.Andreozzi.th@dartmouth.edu, E-mail: Lesley.A.Jarvis@hitchcock.org; Glaser, Adam K.; Zhang, Rongxiao

2016-02-15

Purpose: A method was developed utilizing Cherenkov imaging for rapid and thorough determination of the two gantry angles that produce the most uniform treatment plane during dual-field total skin electron beam therapy (TSET). Methods: Cherenkov imaging was implemented to gather 2D measurements of relative surface dose from 6 MeV electron beams on a white polyethylene sheet. An intensified charge-coupled device camera time-gated to the Linac was used for Cherenkov emission imaging at sixty-two different gantry angles (1° increments, from 239.5° to 300.5°). Following a modified Stanford TSET technique, which uses two fields per patient position for full body coverage, compositemore » images were created as the sum of two beam images on the sheet; each angle pair was evaluated for minimum variation across the patient region of interest. Cherenkov versus dose correlation was verified with ionization chamber measurements. The process was repeated at source to surface distance (SSD) = 441, 370.5, and 300 cm to determine optimal angle spread for varying room geometries. In addition, three patients receiving TSET using a modified Stanford six-dual field technique with 6 MeV electron beams at SSD = 441 cm were imaged during treatment. Results: As in previous studies, Cherenkov intensity was shown to directly correlate with dose for homogenous flat phantoms (R{sup 2} = 0.93), making Cherenkov imaging an appropriate candidate to assess and optimize TSET setup geometry. This method provided dense 2D images allowing 1891 possible treatment geometries to be comprehensively analyzed from one data set of 62 single images. Gantry angles historically used for TSET at their institution were 255.5° and 284.5° at SSD = 441 cm; however, the angles optimized for maximum homogeneity were found to be 252.5° and 287.5° (+6° increase in angle spread). Ionization chamber measurements confirmed improvement in dose homogeneity across the treatment field from a range of 24.4% at the

Process optimization via response surface methodology in the treatment of metal working industry wastewater with electrocoagulation.

PubMed

Guvenc, Senem Yazici; Okut, Yusuf; Ozak, Mert; Haktanir, Birsu; Bilgili, Mehmet Sinan

2017-02-01

In this study, process parameters in chemical oxygen demand (COD) and turbidity removal from metal working industry (MWI) wastewater were optimized by electrocoagulation (EC) using aluminum, iron and steel electrodes. The effects of process variables on COD and turbidity were investigated by developing a mathematical model using central composite design method, which is one of the response surface methodologies. Variance analysis was conducted to identify the interaction between process variables and model responses and the optimum conditions for the COD and turbidity removal. Second-order regression models were developed via the Statgraphics Centurion XVI.I software program to predict COD and turbidity removal efficiencies. Under the optimum conditions, removal efficiencies obtained from aluminum electrodes were found to be 76.72% for COD and 99.97% for turbidity, while the removal efficiencies obtained from iron electrodes were found to be 76.55% for COD and 99.9% for turbidity and the removal efficiencies obtained from steel electrodes were found to be 65.75% for COD and 99.25% for turbidity. Operational costs at optimum conditions were found to be 4.83, 1.91 and 2.91 €/m 3 for aluminum, iron and steel electrodes, respectively. Iron electrode was found to be more suitable for MWI wastewater treatment in terms of operational cost and treatment efficiency.

Optimal anthropometric measures and thresholds to identify undiagnosed type 2 diabetes in three major Asian ethnic groups.

PubMed

Alperet, Derrick Johnston; Lim, Wei-Yen; Mok-Kwee Heng, Derrick; Ma, Stefan; van Dam, Rob M

2016-10-01

To identify optimal anthropometric measures and cutoffs to identify undiagnosed diabetes mellitus (UDM) in three major Asian ethnic groups (Chinese, Malays, and Asian-Indians). Cross-sectional data were analyzed from 14,815 ethnic Chinese, Malay, and Asian-Indian participants of the Singapore National Health Surveys, which included anthropometric measures and an oral glucose tolerance test. Receiver operating characteristic curve analyses were used with calculation of the area under the curve (AUC) to evaluate the performance of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHTR) for the identification of UDM. BMI performed significantly worse (AUCMEN  = 0.70; AUCWOMEN  = 0.75) than abdominal measures, whereas WHTR (AUCMEN  = 0.76; AUCWOMEN  = 0.79) was among the best performing measures in both sexes and all ethnic groups. Anthropometric measures performed better in Chinese than in Asian-Indian participants for the identification of UDM. A WHTR cutoff of 0.52 appeared optimal with a sensitivity of 76% in men and 73% in women and a specificity of 63% in men and 70% in women. Although ethnic differences were observed in the performance of anthropometric measures for the identification of UDM, abdominal adiposity measures generally performed better than BMI, and WHTR performed best in all Asian ethnic groups. © 2016 The Obesity Society.

A systematic approach of removal mechanisms, control and optimization of silver nanoparticle in wastewater treatment plants.

PubMed

Vilela, Paulina; Liu, Hongbin; Lee, SeungChul; Hwangbo, Soonho; Nam, KiJeon; Yoo, ChangKyoo

2018-08-15

The release of silver nanoparticles (AgNPs) to wastewater caused by over-generation and poor treatment of the remaining nanomaterial has raised the interest of researchers. AgNPs can have a negative impact on watersheds and generate degradation of the effluent quality of wastewater treatment plants (WWTPs). The aim of this research is to design and analyze an integrated model system for the removal of AgNPs with high effluent quality in WWTPs using a systematic approach of removal mechanisms modeling, optimization, and control of the removal of silver nanoparticles. The activated sludge model 1 was modified with the inclusion of AgNPs removal mechanisms, such as adsorption/desorption, dissolution, and inhibition of microbial organisms. Response surface methodology was performed to minimize the AgNPs and total nitrogen concentrations in the effluent by optimizing operating conditions of the system. Then, the optimal operating conditions were utilized for the implementation of control strategies into the system for further analysis of enhancement of AgNPs removal efficiency. Thus, the overall AgNP removal efficiency was found to be slightly higher than 80%, which was an improvement of almost 7% compared to the BSM1 reference value. This study provides a systematic approach to find an optimal solution for enhancing AgNP removal efficiency in WWTPs and thereby to prevent pollution in the environment. Copyright © 2018 Elsevier B.V. All rights reserved.

Cancer treatment as a game: integrating evolutionary game theory into the optimal control of chemotherapy

NASA Astrophysics Data System (ADS)

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2012-12-01

Chemotherapy for metastatic cancer commonly fails due to evolution of drug resistance in tumor cells. Here, we view cancer treatment as a game in which the oncologists choose a therapy and tumors ‘choose’ an adaptive strategy. We propose the oncologist can gain an upper hand in the game by choosing treatment strategies that anticipate the adaptations of the tumor. In particular, we examine the potential benefit of exploiting evolutionary tradeoffs in tumor adaptations to therapy. We analyze a math model where cancer cells face tradeoffs in allocation of resistance to two drugs. The tumor ‘chooses’ its strategy by natural selection and the oncologist chooses her strategy by solving a control problem. We find that when tumor cells perform best by investing resources to maximize response to one drug the optimal therapy is a time-invariant delivery of both drugs simultaneously. However, if cancer cells perform better using a generalist strategy allowing resistance to both drugs simultaneously, then the optimal protocol is a time varying solution in which the two drug concentrations negatively covary. However, drug interactions can significantly alter these results. We conclude that knowledge of both evolutionary tradeoffs and drug interactions is crucial in planning optimal chemotherapy schedules for individual patients.

Triage and optimization: A new paradigm in the treatment of massive pulmonary embolism.

PubMed

Pasrija, Chetan; Shah, Aakash; George, Praveen; Kronfli, Anthony; Raithel, Maxwell; Boulos, Francesca; Ghoreishi, Mehrdad; Bittle, Gregory J; Mazzeffi, Michael A; Rubinson, Lewis; Gammie, James S; Griffith, Bartley P; Kon, Zachary N

2018-04-07

Massive pulmonary embolism (PE) remains a highly fatal condition. Although venoarterial extracorporeal membrane oxygenation (VA-ECMO) and surgical pulmonary embolectomy in the management of massive PE have been reported previously, the outcomes remain less than ideal. We hypothesized that the institution of a protocolized approach of triage and optimization using VA-ECMO would result in improved outcomes compared with historical surgical management. All patients with a massive PE referred to the cardiac surgery service between 2010 and 2017 were retrospectively reviewed. Patients were stratified by treatment strategy: historical control versus the protocolized approach. In the historical control group, the primary intervention was surgical pulmonary embolectomy. In the protocol approach group, patients were treated based on an algorithmic approach using VA-ECMO. The primary outcome was 1-year survival. A total of 56 patients (control, n = 27; protocol, n = 29) were identified. All 27 patients in the historical control group underwent surgical pulmonary embolectomy, whereas 2 of 29 patients in the protocol approach group were deemed appropriate for direct surgical pulmonary embolectomy. The remaining 27 patients were placed on VA-ECMO. In the protocol approach group, 15 of 29 patients were treated with anticoagulation alone and 14 patients ultimately required surgical pulmonary embolectomy. One-year survival was significantly lower in the historical control group compared with the protocol approach group (73% vs 96%; P = .02), with no deaths occurring after surgical pulmonary embolectomy in the protocol approach group. A protocolized strategy involving the aggressive institution of VA-ECMO appears to be an effective method to triage and optimize patients with massive PE to recovery or intervention. Implementation of this strategy rather than an aggressive surgical approach may reduce the mortality associated with massive PE. Copyright © 2018 The American

Aptitude x Treatment Interactions: Implications for Patient Education Research.

ERIC Educational Resources Information Center

Holloway, Richard L.; And Others

1988-01-01

Aptitude treatment interaction (ATI) identifies patient characteristics and optimal instructional treatments, is compatible with psychological theories and clinical approaches, and offers a specific methodology for approaching existing problems in a new way. This article presents studies in which ATI has illuminated patient needs and treatments…

Optimized Reduction of Unsteady Radial Forces in a Singlechannel Pump for Wastewater Treatment

NASA Astrophysics Data System (ADS)

Kim, Jin-Hyuk; Cho, Bo-Min; Choi, Young-Seok; Lee, Kyoung-Yong; Peck, Jong-Hyeon; Kim, Seon-Chang

2016-11-01

A single-channel pump for wastewater treatment was optimized to reduce unsteady radial force sources caused by impeller-volute interactions. The steady and unsteady Reynolds- averaged Navier-Stokes equations using the shear-stress transport turbulence model were discretized by finite volume approximations and solved on tetrahedral grids to analyze the flow in the single-channel pump. The sweep area of radial force during one revolution and the distance of the sweep-area center of mass from the origin were selected as the objective functions; the two design variables were related to the internal flow cross-sectional area of the volute. These objective functions were integrated into one objective function by applying the weighting factor for optimization. Latin hypercube sampling was employed to generate twelve design points within the design space. A response-surface approximation model was constructed as a surrogate model for the objectives, based on the objective function values at the generated design points. The optimized results showed considerable reduction in the unsteady radial force sources in the optimum design, relative to those of the reference design.

Obesity and skin and soft tissue infections: how to optimize antimicrobial usage for prevention and treatment?

PubMed

Grupper, Mordechai; Nicolau, David P

2017-04-01

Skin and soft tissue infections (SSTIs) are prevalent in the obese population, with rising trend expected. Although numerous antibiotics are available for the prevention and treatment of SSTIs, their characterization in obese patients is not a regulatory mandate. Consequently, information that carries importance for optimizing the dosing regimen in the obese population may not be readily available. This review focuses on the most recent pharmacokinetic and pharmacodynamic data on this topic with attention to cefazolin for surgical prophylaxis as well as antibiotics that are active against methicillin-resistant Staphylococcus aureus (MRSA). Moreover, the implications for optimizing SSTIs prevention and treatment in the obese population will also be discussed. On the basis of pharmacokinetic/pharmacodynamic considerations, most studies found a perioperative prophylactic cefazolin regimen of 2 g to be reasonable in the case of obese patients undergoing cesarean delivery or bariatric surgery. There is general paucity of data regarding the pharmacokinetic/pharmacodynamic characteristics of antimicrobials active against MRSA in obese patients, especially for the target tissue. Therapeutic drug monitoring has been correlated with pharmacokinetic/pharmacodynamic optimization for vancomycin and teicoplanin, and should be used in these cases. There is more supportive evidence for the use of oxazolidinones (linezolid and tedizolid), daptomycin and lipoglycopeptides (telavancin, dalbavancin and oritavancin) in the management of SSTIs in this population. The pharmacokinetic/pharmacodynamic approach, which can be used as a basis or supplement to clinical trials, provides valuable data and decision-making tools for optimizing regimens used for both prevention and treatment of SSTIs in the obese population. Important pharmacokinetic/pharmacodynamic characteristics of antibiotics, such as the penetration into the subcutaneous tissue and the probability of reaching the

Identifying patients with depression who require a change in treatment and implementing that change.

PubMed

Papakostas, George I

2016-02-01

Creating an effective treatment regimen for patients diagnosed with major depressive disorder (MDD) can be a challenge for clinicians. With each treatment trial, only 20% to 30% of patients achieve remission, and many of those who do reach remission experience residual symptoms. Patients with treatment-resistant depression or with residual symptoms are candidates for a change in treatment. Other patients requiring treatment changes are those who experience intolerable adverse effects and those who experience an illness recurrence. Because early detection can lead to improved outcomes, clinicians must be vigilant about assessing patients to identify when one or more of these situations occur. Clinicians must also communicate effectively with their patients to ensure that they understand the treatment strategies, goals, and potential adverse effects; have realistic expectations of treatment; and express their treatment preferences. Timely and appropriate treatment adjustment is necessary to help patients with MDD achieve recovery. © Copyright 2016 Physicians Postgraduate Press, Inc.

Optimizing Anti-VEGF Treatment Outcomes for Patients with Neovascular Age-Related Macular Degeneration.

PubMed

Wykoff, Charles C; Clark, W Lloyd; Nielsen, Jared S; Brill, Joel V; Greene, Laurence S; Heggen, Cherilyn L

2018-02-01

The introduction of anti-vascular endothelial growth factor (anti-VEGF) drugs to ophthalmology has revolutionized the treatment of neovascular age-related macular degeneration (nAMD). Despite this significant progress, gaps and challenges persist in the diagnosis of nAMD, initiation of treatment, and management of frequent intravitreal injections. Thus, nAMD remains a leading cause of blindness in the United States. To present current knowledge, evidence, and expert perspectives on anti-VEGF therapies in nAMD to support managed care professionals and providers in decision making and collaborative strategies to overcome barriers to optimize anti-VEGF treatment outcomes among nAMD patients. Three anti-VEGF therapies currently form the mainstay of treatment for nAMD, including 2 therapies approved by the FDA for treatment of nAMD (aflibercept and ranibizumab) and 1 therapy approved by the FDA for oncology indications and used off-label for treatment of nAMD (bevacizumab). In clinical trials, each of the 3 agents maintained visual acuity (VA) in approximately 90% or more of nAMD patients over 2 years. However, in long-term and real-world settings, significant gaps and challenges in diagnosis, treatment, and management pose barriers to achieving optimal outcomes for patients with nAMD. Many considerations, including individual patient characteristics, on-label versus off-label treatment, repackaging, and financial considerations, add to the complexity of nAMD decision making and management. Many factors may contribute to additional challenges leading to suboptimal long-term outcomes among nAMD patients, such as delays in diagnosis and/or treatment approval and initiation, individual patient response to different anti-VEGF therapies, lapses in physician regimentation of anti-VEGF injection and monitoring, and inadequate patient adherence to treatment and monitoring. These latter factors highlight the considerable logistical, emotional, and financial burdens of long

WE-B-304-02: Treatment Planning Evaluation and Optimization Should Be Biologically and Not Dose/volume Based

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

Deasy, J.

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning bymore » the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.« less

WE-B-304-01: Treatment Planning Evaluation and Optimization Should Be Dose/volume and Not Biologically Based

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

Mayo, C.

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning bymore » the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.« less

Third degree waiting time discrimination: optimal allocation of a public sector healthcare treatment under rationing by waiting.

PubMed

Gravelle, Hugh; Siciliani, Luigi

2009-08-01

In many public healthcare systems treatments are rationed by waiting time. We examine the optimal allocation of a fixed supply of a given treatment between different groups of patients. Even in the absence of any distributional aims, welfare is increased by third degree waiting time discrimination: setting different waiting times for different groups waiting for the same treatment. Because waiting time imposes dead weight losses on patients, lower waiting times should be offered to groups with higher marginal waiting time costs and with less elastic demand for the treatment.

Estimating the optimal dynamic antipsychotic treatment regime: Evidence from the sequential multiple assignment randomized CATIE Schizophrenia Study

PubMed Central

Shortreed, Susan M.; Moodie, Erica E. M.

2012-01-01

Summary Treatment of schizophrenia is notoriously difficult and typically requires personalized adaption of treatment due to lack of efficacy of treatment, poor adherence, or intolerable side effects. The Clinical Antipsychotic Trials in Intervention Effectiveness (CATIE) Schizophrenia Study is a sequential multiple assignment randomized trial comparing the typical antipsychotic medication, perphenazine, to several newer atypical antipsychotics. This paper describes the marginal structural modeling method for estimating optimal dynamic treatment regimes and applies the approach to the CATIE Schizophrenia Study. Missing data and valid estimation of confidence intervals are also addressed. PMID:23087488

Dimensions of design space: a decision-theoretic approach to optimal research design.

PubMed

Conti, Stefano; Claxton, Karl

2009-01-01

Bayesian decision theory can be used not only to establish the optimal sample size and its allocation in a single clinical study but also to identify an optimal portfolio of research combining different types of study design. Within a single study, the highest societal payoff to proposed research is achieved when its sample sizes and allocation between available treatment options are chosen to maximize the expected net benefit of sampling (ENBS). Where a number of different types of study informing different parameters in the decision problem could be conducted, the simultaneous estimation of ENBS across all dimensions of the design space is required to identify the optimal sample sizes and allocations within such a research portfolio. This is illustrated through a simple example of a decision model of zanamivir for the treatment of influenza. The possible study designs include: 1) a single trial of all the parameters, 2) a clinical trial providing evidence only on clinical endpoints, 3) an epidemiological study of natural history of disease, and 4) a survey of quality of life. The possible combinations, samples sizes, and allocation between trial arms are evaluated over a range of cost-effectiveness thresholds. The computational challenges are addressed by implementing optimization algorithms to search the ENBS surface more efficiently over such large dimensions.

Accumulating Data to Optimally Predict Obesity Treatment (ADOPT): Recommendations from the Biological Domain.

PubMed

Rosenbaum, Michael; Agurs-Collins, Tanya; Bray, Molly S; Hall, Kevin D; Hopkins, Mark; Laughlin, Maren; MacLean, Paul S; Maruvada, Padma; Savage, Cary R; Small, Dana M; Stoeckel, Luke

2018-04-01

The responses to behavioral, pharmacological, or surgical obesity treatments are highly individualized. The Accumulating Data to Optimally Predict obesity Treatment (ADOPT) project provides a framework for how obesity researchers, working collectively, can generate the evidence base needed to guide the development of tailored, and potentially more effective, strategies for obesity treatment. The objective of the ADOPT biological domain subgroup is to create a list of high-priority biological measures for weight-loss studies that will advance the understanding of individual variability in response to adult obesity treatments. This list includes measures of body composition, energy homeostasis (energy intake and output), brain structure and function, and biomarkers, as well as biobanking procedures, which could feasibly be included in most, if not all, studies of obesity treatment. The recommended high-priority measures are selected to balance needs for sensitivity, specificity, and/or comprehensiveness with feasibility to achieve a commonality of usage and increase the breadth and impact of obesity research. The accumulation of data on key biological factors, along with behavioral, psychosocial, and environmental factors, can generate a more precise description of the interplay and synergy among them and their impact on treatment responses, which can ultimately inform the design and delivery of effective, tailored obesity treatments. © 2018 The Obesity Society.

SU-E-T-175: Clinical Evaluations of Monte Carlo-Based Inverse Treatment Plan Optimization for Intensity Modulated Radiotherapy

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

Chi, Y; Li, Y; Tian, Z

2015-06-15

Purpose: Pencil-beam or superposition-convolution type dose calculation algorithms are routinely used in inverse plan optimization for intensity modulated radiation therapy (IMRT). However, due to their limited accuracy in some challenging cases, e.g. lung, the resulting dose may lose its optimality after being recomputed using an accurate algorithm, e.g. Monte Carlo (MC). It is the objective of this study to evaluate the feasibility and advantages of a new method to include MC in the treatment planning process. Methods: We developed a scheme to iteratively perform MC-based beamlet dose calculations and plan optimization. In the MC stage, a GPU-based dose engine wasmore » used and the particle number sampled from a beamlet was proportional to its optimized fluence from the previous step. We tested this scheme in four lung cancer IMRT cases. For each case, the original plan dose, plan dose re-computed by MC, and dose optimized by our scheme were obtained. Clinically relevant dosimetric quantities in these three plans were compared. Results: Although the original plan achieved a satisfactory PDV dose coverage, after re-computing doses using MC method, it was found that the PTV D95% were reduced by 4.60%–6.67%. After re-optimizing these cases with our scheme, the PTV coverage was improved to the same level as in the original plan, while the critical OAR coverages were maintained to clinically acceptable levels. Regarding the computation time, it took on average 144 sec per case using only one GPU card, including both MC-based beamlet dose calculation and treatment plan optimization. Conclusion: The achieved dosimetric gains and high computational efficiency indicate the feasibility and advantages of the proposed MC-based IMRT optimization method. Comprehensive validations in more patient cases are in progress.« less

Metabolomic approach to optimizing and evaluating antibiotic treatment in the axenic culture of cyanobacterium Nostoc flagelliforme.

PubMed

Han, Pei-pei; Jia, Shi-ru; Sun, Ying; Tan, Zhi-lei; Zhong, Cheng; Dai, Yu-jie; Tan, Ning; Shen, Shi-gang

2014-09-01

The application of antibiotic treatment with assistance of metabolomic approach in axenic isolation of cyanobacterium Nostoc flagelliforme was investigated. Seven antibiotics were tested at 1-100 mg L(-1), and order of tolerance of N. flagelliforme cells was obtained as kanamycin > ampicillin, tetracycline > chloromycetin, gentamicin > spectinomycin > streptomycin. Four antibiotics were selected based on differences in antibiotic sensitivity of N. flagelliforme and associated bacteria, and their effects on N. flagelliforme cells including the changes of metabolic activity with antibiotics and the metabolic recovery after removal were assessed by a metabolomic approach based on gas chromatography-mass spectrometry combined with multivariate analysis. The results showed that antibiotic treatment had affected cell metabolism as antibiotics treated cells were metabolically distinct from control cells, but the metabolic activity would be recovered via eliminating antibiotics and the sequence of metabolic recovery time needed was spectinomycin, gentamicin > ampicillin > kanamycin. The procedures of antibiotic treatment have been accordingly optimized as a consecutive treatment starting with spectinomycin, then gentamicin, ampicillin and lastly kanamycin, and proved to be highly effective in eliminating the bacteria as examined by agar plating method and light microscope examination. Our work presented a strategy to obtain axenic culture of N. flagelliforme and provided a method for evaluating and optimizing cyanobacteria purification process through diagnosing target species cellular state.

A new Monte Carlo-based treatment plan optimization approach for intensity modulated radiation therapy.

PubMed

Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun

2015-04-07

Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation

Identifying the optimal depth for mussel suspended culture in shallow and turbid environments

NASA Astrophysics Data System (ADS)

Filgueira, Ramón; Grant, Jon; Petersen, Jens Kjerulf

2018-02-01

Bivalve aquaculture is commonly carried out in shallow water systems, which are susceptible to resuspension of benthic particulate matter by natural processes such as tidal currents, winds and wave action, as well as human activity. The resuspended material can alter the availability of food particles for cultured bivalves. The effect of resuspended material on bivalve bioenergetics and growth is a function of the quality and concentration of resuspended particles and background diet in the water column. Given the potential for positive or negative impacts on bivalve growth and consequently on farm productivity, farmers must position the cultured biomass at the appropriate depth to benefit from or mitigate the impact of this resuspended material. A combination of field measurements, a 1-D vertical resuspension model and a bioenergetic model for mussels based on Dynamic Energy Budget (DEB) theory has been carried out for a mussel farm in Skive Fjord, a shallow Danish fjord, with the aim of identifying the optimal depth for culture. Observations at the farm location revealed that horizontal advection is more important than vertical resuspension during periods with predominant Eastern winds. In addition, high background seston in the water column reduces the impact of resuspension on the available food for mussels. The simulation of different scenarios in terms of food availability suggested minimal effects of resuspension on mussel growth. Based on this finding and the fact that phytoplankton concentration, the main food source for mussels, is usually higher in the upper part of the water column, suspended culture in the top 3 m of the water column seems to be the optimal practice to produce mussels in Skive Fjord.

MO-F-CAMPUS-T-01: Radiosurgery of Multiple Brain Metastases with Single-Isocenter VMAT: Optimizing Treatment Geometry to Reduce Normal Brain Dose

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

Wu, Q; Snyder, K; Liu, C

Purpose: To develop an optimization algorithm to reduce normal brain dose by optimizing couch and collimator angles for single isocenter multiple targets treatment of stereotactic radiosurgery. Methods: Three metastatic brain lesions were retrospectively planned using single-isocenter volumetric modulated arc therapy (VMAT). Three matrices were developed to calculate the projection of each lesion on Beam’s Eye View (BEV) by the rotating couch, collimator and gantry respectively. The island blocking problem was addressed by computing the total area of open space between any two lesions with shared MLC leaf pairs. The couch and collimator angles resulting in the smallest open areas weremore » the optimized angles for each treatment arc. Two treatment plans with and without couch and collimator angle optimization were developed using the same objective functions and to achieve 99% of each target volume receiving full prescription dose of 18Gy. Plan quality was evaluated by calculating each target’s Conformity Index (CI), Gradient Index (GI), and Homogeneity index (HI), and absolute volume of normal brain V8Gy, V10Gy, V12Gy, and V14Gy. Results: Using the new couch/collimator optimization strategy, dose to normal brain tissue was reduced substantially. V8, V10, V12, and V14 decreased by 2.3%, 3.6%, 3.5%, and 6%, respectively. There were no significant differences in the conformity index, gradient index, and homogeneity index between two treatment plans with and without the new optimization algorithm. Conclusion: We have developed a solution to the island blocking problem in delivering radiation to multiple brain metastases with shared isocenter. Significant reduction in dose to normal brain was achieved by using optimal couch and collimator angles that minimize total area of open space between any of the two lesions with shared MLC leaf pairs. This technique has been integrated into Eclipse treatment system using scripting API.« less

Case Example of Dose Optimization Using Data From Bortezomib Dose-Finding Clinical Trials

PubMed Central

Backenroth, Daniel; Cheung, Ying Kuen Ken; Hershman, Dawn L.; Vulih, Diana; Anderson, Barry; Ivy, Percy; Minasian, Lori

2016-01-01

Purpose The current dose-finding methodology for estimating the maximum tolerated dose of investigational anticancer agents is based on the cytotoxic chemotherapy paradigm. Molecularly targeted agents (MTAs) have different toxicity profiles, which may lead to more long-lasting mild or moderate toxicities as well as to late-onset and cumulative toxicities. Several approved MTAs have been poorly tolerated during long-term administration, leading to postmarketing dose optimization studies to re-evaluate the optimal treatment dose. Using data from completed bortezomib dose-finding trials, we explore its toxicity profile, optimize its dose, and examine the appropriateness of current designs for identifying an optimal dose. Patients and Methods We classified the toxicities captured from 481 patients in 14 bortezomib dose-finding studies conducted through the National Cancer Institute Cancer Therapy Evaluation Program, computed the incidence of late-onset toxicities, and compared the incidence of dose-limiting toxicities (DLTs) among groups of patients receiving different doses of bortezomib. Results A total of 13,008 toxicities were captured: 46% of patients’ first DLTs and 88% of dose reductions or discontinuations of treatment because of toxicity were observed after the first cycle. Moreover, for the approved dose of 1.3 mg/m2, the estimated cumulative incidence of DLT was > 50%, and the estimated cumulative incidence of dose reduction or treatment discontinuation because of toxicity was nearly 40%. Conclusions When considering the entire course of treatment, the approved bortezomib dose exceeds the conventional ceiling DLT rate of 20% to 33%. Retrospective analysis of trial data provides an opportunity for dose optimization of MTAs. Future dose-finding studies of MTAs should take into account late-onset toxicities to ensure that a tolerable dose is identified for future efficacy and comparative trials. PMID:26926682

Case Example of Dose Optimization Using Data From Bortezomib Dose-Finding Clinical Trials.

PubMed

Lee, Shing M; Backenroth, Daniel; Cheung, Ying Kuen Ken; Hershman, Dawn L; Vulih, Diana; Anderson, Barry; Ivy, Percy; Minasian, Lori

2016-04-20

The current dose-finding methodology for estimating the maximum tolerated dose of investigational anticancer agents is based on the cytotoxic chemotherapy paradigm. Molecularly targeted agents (MTAs) have different toxicity profiles, which may lead to more long-lasting mild or moderate toxicities as well as to late-onset and cumulative toxicities. Several approved MTAs have been poorly tolerated during long-term administration, leading to postmarketing dose optimization studies to re-evaluate the optimal treatment dose. Using data from completed bortezomib dose-finding trials, we explore its toxicity profile, optimize its dose, and examine the appropriateness of current designs for identifying an optimal dose. We classified the toxicities captured from 481 patients in 14 bortezomib dose-finding studies conducted through the National Cancer Institute Cancer Therapy Evaluation Program, computed the incidence of late-onset toxicities, and compared the incidence of dose-limiting toxicities (DLTs) among groups of patients receiving different doses of bortezomib. A total of 13,008 toxicities were captured: 46% of patients' first DLTs and 88% of dose reductions or discontinuations of treatment because of toxicity were observed after the first cycle. Moreover, for the approved dose of 1.3 mg/m(2), the estimated cumulative incidence of DLT was > 50%, and the estimated cumulative incidence of dose reduction or treatment discontinuation because of toxicity was nearly 40%. When considering the entire course of treatment, the approved bortezomib dose exceeds the conventional ceiling DLT rate of 20% to 33%. Retrospective analysis of trial data provides an opportunity for dose optimization of MTAs. Future dose-finding studies of MTAs should take into account late-onset toxicities to ensure that a tolerable dose is identified for future efficacy and comparative trials. © 2016 by American Society of Clinical Oncology.

Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis*

PubMed Central

León, Ileana R.; Schwämmle, Veit; Jensen, Ole N.; Sprenger, Richard R.

2013-01-01

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods. PMID:23792921

Optimization of low energy sonication treatment for granular activated carbon colonizing biomass assessment.

PubMed

Saccani, G; Bernasconi, M; Antonelli, M

2014-01-01

This study is aimed at optimizing a low energy sonication (LES) treatment for granular activated carbon (GAC)-colonizing biomass detachment and determination, evaluating detachment efficiency and the effects of ultrasound exposure on bacterial cell viability. GAC samples were collected from two filters fed with groundwater. Conventional heterotrophic plate count (HPC) and fluorescence microscopy with a double staining method were used to evaluate cell viability, comparing two LES procedures, without and with periodical bulk substitution. A 20 min LES treatment, with bulk substitution after cycles of 5 min as maximum treatment time, allowed to recover 87%/100% of attached biomass, protecting detached bacteria from ultrasound damaging effects. Observed viable cell inactivation rate was 6.5/7.9% cell/min, with membrane-compromised cell damage appearing to be even higher (11.5%/13.1% cell/min). Assessing bacterial detachment and damaging ultrasound effects, fluorescence microscopy turned out to be more sensitive compared to conventional HPC. The optimized method revealed a GAC-colonizing biomass of 9.9 x 10(7) cell/gGAC for plant 1 and 8.8 x 10(7) cell/gGAC for plant 2, 2 log lower than reported in literature. The difference between the two GAC-colonizing biomasses is higher in terms of viable cells (46.3% of total cells in plant 1 GAC-colonizing biomass compared to the 33.3% in plant 2). Studying influent water contamination through multivariate statistical analyses, apossible combined toxic and genotoxic effect of chromium VI and trichloroethylene was suggested as a reason for the lower viable cell fraction observed in plant 2 GAC-colonizing population.

Optimization of epilepsy treatment with vagus nerve stimulation

NASA Astrophysics Data System (ADS)

Uthman, Basim; Bewernitz, Michael; Liu, Chang-Chia; Ghacibeh, Georges

2007-11-01

Epilepsy is one of the most common chronic neurological disorders that affects close to 50 million people worldwide. Antiepilepsy drugs (AEDs), the main stay of epilepsy treatment, control seizures in two thirds of patients only. Other therapies include the ketogenic diet, ablative surgery, hormonal treatments and neurostimulation. While other approaches to stimulation of the brain are currently in the experimental phase vagus nerve stimulation (VNS) has been approved by the FDA since July 1997 for the adjunctive treatment of intractable partial onset epilepsy with and without secondary generalization in patients twelve years of age or older. The safety and efficacy of VNS have been proven and duplicated in two subsequent double-blinded controlled studies after two pilot studies demonstrated the feasibility of VNS in man. Long term observational studies confirmed the safety of VNS and that its effectiveness is sustained over time. While AEDs influence seizure thresholds via blockade or modulation of ionic channels, inhibit excitatory neurotransmitters or enhance inhibitory neurotransmitters the exact mechanism of action of VNS is not known. Neuroimaging studies revealed that VNS increases blood flow in certain regions of the brain such as the thalamus. Chemical lesions in the rat brains showed that norepinephrine is an important link in the anticonvulsant effect of VNS. Analysis of cerebrospinal fluid obtained from patients before and after treatment with VNS showed modest decreases in excitatory neurotransmitters. Although Hammond et al. reported no effect of VNS on scalp EEG by visual analysis and Salinsky et al. found no effect of VNS on scalp EEG by spectral analysis, Kuba et al. suggested that VNS reduces interictal epileptiform activity. Further, nonlinear dynamical analysis of the electroencephalogram in the rat and man have reportedly shown predictable changes (decrease in the short term Lyapunov exponent STLmax and T-index) more than an hour prior to the

Pregnancy Research on Osteopathic Manipulation Optimizing Treatment Effects: the PROMOTE study.

PubMed

Hensel, Kendi L; Buchanan, Steve; Brown, Sarah K; Rodriguez, Mayra; Cruser, des Anges

2015-01-01

The purpose of this study was to evaluate the efficacy of osteopathic manipulative treatment (OMT) to reduce low back pain and improve functioning during the third trimester in pregnancy and to improve selected outcomes of labor and delivery. Pregnancy research on osteopathic manipulation optimizing treatment effects was a randomized, placebo-controlled trial of 400 women in their third trimester. Women were assigned randomly to usual care only (UCO), usual care plus OMT (OMT), or usual care plus placebo ultrasound treatment (PUT). The study included 7 treatments over 9 weeks. The OMT protocol included specific techniques that were administered by board-certified OMT specialists. Outcomes were assessed with the use of self-report measures for pain and back-related functioning and medical records for delivery outcomes. There were 136 women in the OMT group: 131 women in the PUT group and 133 women in the UCO group. Characteristics at baseline were similar across groups. Findings indicate significant treatment effects for pain and back-related functioning (P < .001 for both groups), with outcomes for the OMT group similar to that of the PUT group; however, both groups were significantly improved compared with the UCO group. For secondary outcome of meconium-stained amniotic fluid, there were no differences among the groups. OMT was effective for mitigating pain and functional deterioration compared with UCO; however, OMT did not differ significantly from PUT. This may be attributed to PUT being a more active treatment than intended. There was no higher likelihood of conversion to high-risk status based on treatment group. Therefore, OMT is a safe, effective adjunctive modality to improve pain and functioning during the third trimester. Copyright © 2015 Elsevier Inc. All rights reserved.

[Optimism, family cohesion and treatment as predictors of quality of life in blood cancer diseases].

PubMed

Lavielle-Sotomayor, Pilar; Rozen-Fuller, Etta; Bustamante-Rojano, Juan; Martínez-Murillo, Carlos

2017-01-01

Quality of life must be a part of the goals of care given to blood cancer patients and it must be used to assess the effectiveness of their treatment. The objective was to evaluate the quality of life of patients with leukemia and its relationship with psychological, familial and disease-related aspects. An analytic cross-sectional study was carried out in patients with acute leukemia at different stages of treatment. We used SF-36, Optimism and Family Cohesion scales. Quality of life was affected physically and mentally in the treatment phases aimed to mitigate the active, and the advanced stage of this disease (50.6 ± 25.6, 62 ± 14.3; 46 ± 23.2, 53.8 ± 23.4, respectively), regardless of gender, age, level of optimism and family cohesion. Patients could carry out basic functions of self-care (bathing, feeding, etcetera), but not activities of daily living (shopping, household chores, etcetera), which require a greater effort. Although the patients perceived having been affected in the emotional health area-by the presence of anxiety and depression-they did not consider that these alterations limited their ability to carry out work and everyday activities. Quality of life was most affected at mental dimension and physical dimension, mainly in patients at induction and palliative treatment. The results showed that the objectives of care aimed to reduce symptoms and maintain patient comfort are not achieved.

The Emerging Role for rTMS in Optimizing the Treatment of Adolescent Depression

PubMed Central

Croarkin, Paul E.; Wall, Christopher A.; McClintock, Shawn M.; Kozel, F. Andrew; Husain, Mustafa M.; Sampson, Shirlene M.

2010-01-01

Major depressive disorder (MDD) in adolescents is a common illness and significant public health problem. Treatment is challenging due to recurrences and limited modalities. Selective serotonin reuptake inhibitors (SSRIs) and Cognitive Behavioral Therapy (CBT) are considered the standard of care in severe or treatment resistant MDD in this age group. However, responses to these interventions are often suboptimal. A growing body of research supports the efficacy of repetitive transcranial magnetic stimulation for the treatment of MDD in adults. Induced seizures are a primary safety concern, although this is rare with appropriate precautions. There is, however, limited experience with rTMS as a therapeutic intervention for adolescent psychiatric disturbances. This review will summarize the rTMS efficacy and safety data in adults and describe all published experience with adolescent MDD. Applications in other adolescent psychiatric illnesses such as schizophrenia and attention-deficit/hyperactivity disorder (ADHD) are reviewed. Safety and ethical issues are paramount with investigational treatments in adolescent psychiatric illnesses. However, further research with rTMS in adolescent MDD is imperative to establish standards for optimal stimulation site, treatment parameters, and its role in treatment algorithms. These may diverge from adult data. Early intervention with neuromodulation could also hold the promise of addressing the developmental course of dysfunctional neurocircuitry. PMID:20418774

The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans.

PubMed

Siebers, Jeffrey V

2008-04-04

Monte Carlo (MC) is rarely used for IMRT plan optimization outside of research centres due to the extensive computational resources or long computation times required to complete the process. Time can be reduced by degrading the statistical precision of the MC dose calculation used within the optimization loop. However, this eventually introduces optimization convergence errors (OCEs). This study determines the statistical noise levels tolerated during MC-IMRT optimization under the condition that the optimized plan has OCEs <100 cGy (1.5% of the prescription dose) for MC-optimized IMRT treatment plans.Seven-field prostate IMRT treatment plans for 10 prostate patients are used in this study. Pre-optimization is performed for deliverable beams with a pencil-beam (PB) dose algorithm. Further deliverable-based optimization proceeds using: (1) MC-based optimization, where dose is recomputed with MC after each intensity update or (2) a once-corrected (OC) MC-hybrid optimization, where a MC dose computation defines beam-by-beam dose correction matrices that are used during a PB-based optimization. Optimizations are performed with nominal per beam MC statistical precisions of 2, 5, 8, 10, 15, and 20%. Following optimizer convergence, beams are re-computed with MC using 2% per beam nominal statistical precision and the 2 PTV and 10 OAR dose indices used in the optimization objective function are tallied. For both the MC-optimization and OC-optimization methods, statistical equivalence tests found that OCEs are less than 1.5% of the prescription dose for plans optimized with nominal statistical uncertainties of up to 10% per beam. The achieved statistical uncertainty in the patient for the 10% per beam simulations from the combination of the 7 beams is ~3% with respect to maximum dose for voxels with D>0.5D(max). The MC dose computation time for the OC-optimization is only 6.2 minutes on a single 3 Ghz processor with results clinically equivalent to high precision MC

Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements

PubMed Central

Whitaker, May

2016-01-01

Purpose Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. Material and methods This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. Results The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. Conclusions The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected. PMID:27504129

Robustness of IPSA optimized high-dose-rate prostate brachytherapy treatment plans to catheter displacements.

PubMed

Poder, Joel; Whitaker, May

2016-06-01

Inverse planning simulated annealing (IPSA) optimized brachytherapy treatment plans are characterized with large isolated dwell times at the first or last dwell position of each catheter. The potential of catheter shifts relative to the target and organs at risk in these plans may lead to a more significant change in delivered dose to the volumes of interest relative to plans with more uniform dwell times. This study aims to determine if the Nucletron Oncentra dwell time deviation constraint (DTDC) parameter can be optimized to improve the robustness of high-dose-rate (HDR) prostate brachytherapy plans to catheter displacements. A set of 10 clinically acceptable prostate plans were re-optimized with a DTDC parameter of 0 and 0.4. For each plan, catheter displacements of 3, 7, and 14 mm were retrospectively applied and the change in dose volume histogram (DVH) indices and conformity indices analyzed. The robustness of clinically acceptable prostate plans to catheter displacements in the caudal direction was found to be dependent on the DTDC parameter. A DTDC value of 0 improves the robustness of planning target volume (PTV) coverage to catheter displacements, whereas a DTDC value of 0.4 improves the robustness of the plans to changes in hotspots. The results indicate that if used in conjunction with a pre-treatment catheter displacement correction protocol and a tolerance of 3 mm, a DTDC value of 0.4 may produce clinically superior plans. However, the effect of the DTDC parameter in plan robustness was not observed to be as strong as initially suspected.

Selected chemical composition changes in microwave-convective dried parsley leaves affected by ultrasound and steaming pre-treatments - An optimization approach.

PubMed

Dadan, Magdalena; Rybak, Katarzyna; Wiktor, Artur; Nowacka, Malgorzata; Zubernik, Joanna; Witrowa-Rajchert, Dorota

2018-01-15

Parsley leaves contain a high amount of bioactive components (especially lutein), therefore it is crucial to select the most appropriate pre-treatment and drying conditions, in order to obtain high quality of dried leaves, which was the aim of this study. The optimization was done using response surface methodology (RSM) for the following factors: microwave power (100, 200, 300W), air temperature (20, 30, 40°C) and pre-treatment variant (ultrasound, steaming and dipping as a control). Total phenolic content (TPC), antioxidant activity, chlorophyll and lutein contents (using UPLC-PDA) were determined in dried leaves. The analysed responses were dependent on the applied drying parameters and the pre-treatment type. The possibility of ultrasound and steam treatment application was proven and the optimal processing conditions were selected. Copyright © 2017 Elsevier Ltd. All rights reserved.

Technoeconomic Optimization of Waste Heat Driven Forward Osmosis for Flue Gas Desulfurization Wastewater Treatment

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

Gingerich, Daniel B; Bartholomew, Timothy V; Mauter, Meagan S

With the Environmental Protection Agency’s recent Effluent Limitation Guidelines for Steam Electric Generators, power plants are having to install and operate new wastewater technologies. Many plants are evaluating desalination technologies as possible compliance options. However, the desalination technologies under review that can reduce wastewater volume or treat to a zero-liquid discharges standard have a significant energy penalty to the plant. Waste heat, available from the exhaust gas or cooling water from coal-fired power plants, offers an opportunity to drive wastewater treatment using thermal desalination technologies. One such technology is forward osmosis (FO). Forward osmosis utilizes an osmotic pressure gradient tomore » passively pull water from a saline or wastewater stream across a semi-permeable membrane and into a more concentrated draw solution. This diluted draw solution is then fed into a distillation column, where the addition of low temperature waste heat can drive the separation to produce a reconcentrated draw solution and treated water for internal plant reuse. The use of low-temperature waste heat decouples water treatment from electricity production and eliminates the link between reducing water pollution and increasing air emissions from auxiliary electricity generation. In order to evaluate the feasibility of waste heat driven FO, we first build a model of an FO system for flue gas desulfurization (FGD) wastewater treatment at coal-fired power plants. This model includes the FO membrane module, the distillation column for draw solution recovery, and waste heat recovery from the exhaust gas. We then add a costing model to account for capital and operating costs of the forward osmosis system. We use this techno-economic model to optimize waste heat driven FO for the treatment of FGD wastewater. We apply this model to three case studies: the National Energy Technology Laboratory (NETL) 550 MW model coal fired power plant without

Text categorization models for identifying unproven cancer treatments on the web.

PubMed

Aphinyanaphongs, Yin; Aliferis, Constantin

2007-01-01

The nature of the internet as a non-peer-reviewed (and largely unregulated) publication medium has allowed wide-spread promotion of inaccurate and unproven medical claims in unprecedented scale. Patients with conditions that are not currently fully treatable are particularly susceptible to unproven and dangerous promises about miracle treatments. In extreme cases, fatal adverse outcomes have been documented. Most commonly, the cost is financial, psychological, and delayed application of imperfect but proven scientific modalities. To help protect patients, who may be desperately ill and thus prone to exploitation, we explored the use of machine learning techniques to identify web pages that make unproven claims. This feasibility study shows that the resulting models can identify web pages that make unproven claims in a fully automatic manner, and substantially better than previous web tools and state-of-the-art search engine technology.

Optimal Treatment of Symptomatic Hemorrhoids

PubMed Central

Kim, Soung-Ho

2011-01-01

Hemorrhoids are the most common anorectal complaint, and approximately 10 to 20 percent of patients with symptomatic hemorrhoids require surgery. Symptoms of hemorrhoids, such as painless rectal bleeding, tissue protrusion and mucous discharge, vary. The traditional therapeutic strategies of medicine include surgical, as well as non-surgical, treatment. To alleviate symptoms caused by hemorrhoids, oral treatments, such as fiber, suppositories and Sitz baths have been applied to patients. Other non-surgical treatments, such as infrared photocoagulation, injection sclerotherapy and rubber band ligation have been used to fixate the hemorrhoid's cushion. If non-surgical treatment has no effect, surgical treatments, such as a hemorrhoidectomy, procedure for prolapsed hemorrhoids, and transanal hemorrhoidal dearterialization are used. PMID:22259741

Optimal combinations of broadly neutralizing antibodies for prevention and treatments of HIV-1 clade C infection

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

Wagh, Kshitij; Bhattacharya, Tanmoy; Williamson, Carolyn

In this study, the identification of a new generation of potent broadly neutralizing HIV-1 antibodies (bnAbs) has generated substantial interest in their potential use for the prevention and/or treatment of HIV-1 infection. While combinations of bnAbs targeting distinct epitopes on the viral envelope (Env) will likely be required to overcome the extraordinary diversity of HIV-1, a key outstanding question is which bnAbs, and how many, will be needed to achieve optimal clinical benefit. We assessed the neutralizing activity of 15 bnAbs targeting four distinct epitopes of Env, including the CD4-binding site (CD4bs), the V1/V2-glycan region, the V3-glycan region, and themore » gp41 membrane proximal external region (MPER), against a panel of 200 acute/early clade C HIV-1 Env pseudoviruses. A mathematical model was developed that predicted neutralization by a subset of experimentally evaluated bnAb combinations with high accuracy. Using this model, we performed a comprehensive and systematic comparison of the predicted neutralizing activity of over 1,600 possible double, triple, and quadruple bnAb combinations. The most promising bnAb combinations were identified based not only on breadth and potency of neutralization, but also other relevant measures, such as the extent of complete neutralization and instantaneous inhibitory potential (IIP). By this set of criteria, triple and quadruple combinations of bnAbs were identified that were significantly more effective than the best double combinations, and further improved the probability of having multiple bnAbs simultaneously active against a given virus, a requirement that may be critical for countering escape in vivo. These results provide a rationale for advancing bnAb combinations with the best in vitro predictors of success into clinical trials for both the prevention and treatment of HIV-1 infection.« less

Optimal combinations of broadly neutralizing antibodies for prevention and treatments of HIV-1 clade C infection

DOE PAGES

Wagh, Kshitij; Bhattacharya, Tanmoy; Williamson, Carolyn; ...

2016-03-30

In this study, the identification of a new generation of potent broadly neutralizing HIV-1 antibodies (bnAbs) has generated substantial interest in their potential use for the prevention and/or treatment of HIV-1 infection. While combinations of bnAbs targeting distinct epitopes on the viral envelope (Env) will likely be required to overcome the extraordinary diversity of HIV-1, a key outstanding question is which bnAbs, and how many, will be needed to achieve optimal clinical benefit. We assessed the neutralizing activity of 15 bnAbs targeting four distinct epitopes of Env, including the CD4-binding site (CD4bs), the V1/V2-glycan region, the V3-glycan region, and themore » gp41 membrane proximal external region (MPER), against a panel of 200 acute/early clade C HIV-1 Env pseudoviruses. A mathematical model was developed that predicted neutralization by a subset of experimentally evaluated bnAb combinations with high accuracy. Using this model, we performed a comprehensive and systematic comparison of the predicted neutralizing activity of over 1,600 possible double, triple, and quadruple bnAb combinations. The most promising bnAb combinations were identified based not only on breadth and potency of neutralization, but also other relevant measures, such as the extent of complete neutralization and instantaneous inhibitory potential (IIP). By this set of criteria, triple and quadruple combinations of bnAbs were identified that were significantly more effective than the best double combinations, and further improved the probability of having multiple bnAbs simultaneously active against a given virus, a requirement that may be critical for countering escape in vivo. These results provide a rationale for advancing bnAb combinations with the best in vitro predictors of success into clinical trials for both the prevention and treatment of HIV-1 infection.« less

Endovascular abdominal aortic stenosis treatment with the OptiMed self-expandable nitinol stent.

PubMed

Ghazi, Payam; Haji-Zeinali, Ali-Mohammad; Shafiee, Nahid; Qureshi, Shakeel A

2009-10-01

To evaluate the safety and feasibility of self-expandable stents (OptiMed) for treatment of abdominal aortic stenosis in the situations in which the aortic stenosis locates near the origin of celiac, superior mesenteric, renal and inferior mesenteric arteries. Five consecutive patients scheduled for endovascular treatment of abdominal aortic stenosis by self-expandable nitinol stent (Sinus-Aorta/OptiMed) implantation. The diameter of the stent was chosen as 10-30% more than that of the normal portion of the aorta above the stenosis. Long stents of 60 mm or longer were chosen. After stent deployment, balloon postdilation was performed with a balloon in patients with residual gradient > 5 mm Hg. All patients were successfully treated with the OptiMed stents. The balloon predilation was performed in one patient due to severe stenosis. The mean diameter and length of the stents deployed were 20.4 +/- 2.9 (range, 16-24 mm) and 64 +/- 8.9 (range, 60-80 mm), respectively. The balloon postdilation was performed in all cases. The mean diameter of the balloons was 13.6 +/- 1.5 (range, 12-15 mm). The mean diameter of stenosis increased from 4.8 +/- 1.9 to 14.4 +/- 1.8 mm after stent placement. The mean peak systolic gradient decreased from 46.8 +/- 31.5 mm Hg to 0.8 +/- 1.8 mm Hg. During follow-up (22.8 +/- 14.3 months), none of the patients had restenosis within the stent, occlusion of any branches of the aorta, or other related complications. In our small series, we observed that abdominal aortic stenosis can be successfully and effectively treated with OptiMed stents in the situations in which the stenotic segment is located next to the origins of the main visceral branches of abdominal aorta.

Technical and economical optimization of a full-scale poultry manure treatment process: total ammonia nitrogen balance.

PubMed

Alejo-Alvarez, Luz; Guzmán-Fierro, Víctor; Fernández, Katherina; Roeckel, Marlene

2016-11-01

A full-scale process for the treatment of 80 tons per day of poultry manure was designed and optimized. A total ammonia nitrogen (TAN) balance was performed at steady state, considering the stoichiometry and the kinetic data from the anaerobic digestion and the anaerobic ammonia oxidation. The equipment, reactor design, investment costs, and operational costs were considered. The volume and cost objective functions optimized the process in terms of three variables: the water recycle ratio, the protein conversion during AD, and the TAN conversion in the process. The processes were compared with and without water recycle; savings of 70% and 43% in the annual fresh water consumption and the heating costs, respectively, were achieved. The optimal process complies with the Chilean environmental legislation limit of 0.05 g total nitrogen/L.

Resistant hypertension optimal treatment trial: a randomized controlled trial.

PubMed

Krieger, Eduardo M; Drager, Luciano F; Giorgi, Dante Marcelo Artigas; Krieger, Jose Eduardo; Pereira, Alexandre Costa; Barreto-Filho, José Augusto Soares; da Rocha Nogueira, Armando; Mill, José Geraldo

2014-01-01

The prevalence of resistant hypertension (ReHy) is not well established. Furthermore, diuretics, angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers, and calcium channel blockers are largely used as the first 3-drug combinations for treating ReHy. However, the fourth drug to be added to the triple regimen is still controversial and guided by empirical choices. We sought (1) to determine the prevalence of ReHy in patients with stage II hypertension; (2) to compare the effects of spironolactone vs clonidine, when added to the triple regimen; and (3) to evaluate the role of measuring sympathetic and renin-angiotensin-aldosterone activities in predicting blood pressure response to spironolactone or clonidine. The Resistant Hypertension Optimal Treatment (ReHOT) study (ClinicalTrials.gov NCT01643434) is a prospective, multicenter, randomized trial comprising 26 sites in Brazil. In step 1, 2000 patients will be treated according to hypertension guidelines for 12 weeks, to detect the prevalence of ReHy. Medical therapy adherence will be checked by pill count monitoring. In step 2, patients with confirmed ReHy will be randomized to an open label 3-month treatment with spironolactone (titrating dose, 12.5-50 mg once daily) or clonidine (titrating dose, 0.1-0.3 mg twice daily). The primary endpoint is the effective control of blood pressure after a 12-week randomized period of treatment. The ReHOT study will disseminate results about the prevalence of ReHy in stage II hypertension and the comparison of spironolactone vs clonidine for blood pressure control in patients with ReHy under 3-drug standard regimen. © 2013 Wiley Periodicals, Inc.

Optimal management of lower pole stones: the direction of future travel

PubMed Central

Moore, Sacha L.; Bres-Niewada, Ewa; Cook, Paul; Wells, Hannah

2016-01-01

Introduction Kidney stone disease is increasing worldwide with its most common location being in the lower pole. A clear strategy for effective management of these stones is essential in the light of ever increasing choice, effectiveness, and complications of different treatment options. Material and methods This review identifies the latest and clinically relevant publications focused on optimal management of lower pole stones. Results We present an up-to-date European Association of Urology and American Urological Association algorithm for lower pole stones, risks and benefits of different treatments, and changing landscape with the miniaturization of percutaneous stone treatments. Conclusions Available literature seems to be deficient on quality of life, patient centered decision making, and cost analysis of optimal management with no defined standard of ‘stone free rate’, all of which are critical in any surgical consultation and outcome analysis. PMID:27729994

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.

Complaint-adaptive power density optimization as a tool for HTP-guided steering in deep hyperthermia treatment of pelvic tumors

NASA Astrophysics Data System (ADS)

Canters, R. A. M.; Franckena, M.; van der Zee, J.; Van Rhoon, G. C.

2008-12-01

For an efficient clinical use of HTP (hyperthermia treatment planning), optimization methods are needed. In this study, a complaint-adaptive PD (power density) optimization as a tool for HTP-guided steering in deep hyperthermia of pelvic tumors is developed and tested. PD distribution in patients is predicted using FE-models. Two goal functions, Opt1 and Opt2, are applied to optimize PD distributions. Optimization consists of three steps: initial optimization, adaptive optimization after a first complaint and increasing the weight of a region after recurring complaints. Opt1 initially considers only target PD whereas Opt2 also takes into account hot spots. After patient complaints though, both limit PD in a region. Opt1 and Opt2 are evaluated in a phantom test, using patient models and during hyperthermia treatment. The phantom test and a sensitivity study in ten patient models, show that HTP-guided steering is most effective in peripheral complaint regions. Clinical evaluation in two groups of five patients shows that time between complaints is longer using Opt2 (p = 0.007). However, this does not lead to significantly different temperatures (T50s of 40.3 (Opt1) versus 40.1 °C (Opt2) (p = 0.898)). HTP-guided steering is feasible in terms of PD reduction in complaint regions and in time consumption. Opt2 is preferable in future use, because of better complaint reduction and control.

Multi-objective Optimization for the Robust Performance of Drinking Water Treatment Plants under Climate Change and Climate Extremes

NASA Astrophysics Data System (ADS)

Raseman, W. J.; Kasprzyk, J. R.; Rosario-Ortiz, F.; Summers, R. S.; Stewart, J.; Livneh, B.

2016-12-01

To promote public health, the United States Environmental Protection Agency (US EPA), and similar entities around the world enact strict laws to regulate drinking water quality. These laws, such as the Stage 1 and 2 Disinfectants and Disinfection Byproducts (D/DBP) Rules, come at a cost to water treatment plants (WTPs) which must alter their operations and designs to meet more stringent standards and the regulation of new contaminants of concern. Moreover, external factors such as changing influent water quality due to climate extremes and climate change, may force WTPs to adapt their treatment methods. To grapple with these issues, decision support systems (DSSs) have been developed to aid WTP operation and planning. However, there is a critical need to better address long-term decision making for WTPs. In this poster, we propose a DSS framework for WTPs for long-term planning, which improves upon the current treatment of deep uncertainties within the overall potable water system including the impact of climate on influent water quality and uncertainties in treatment process efficiencies. We present preliminary results exploring how a multi-objective evolutionary algorithm (MOEA) search can be coupled with models of WTP processes to identify high-performing plans for their design and operation. This coupled simulation-optimization technique uses Borg MOEA, an auto-adaptive algorithm, and the Water Treatment Plant Model, a simulation model developed by the US EPA to assist in creating the D/DBP Rules. Additionally, Monte Carlo sampling methods were used to study the impact of uncertainty of influent water quality on WTP decision-making and generate plans for robust WTP performance.

Simulation and optimization of a coking wastewater biological treatment process by activated sludge models (ASM).

PubMed

Wu, Xiaohui; Yang, Yang; Wu, Gaoming; Mao, Juan; Zhou, Tao

2016-01-01

Applications of activated sludge models (ASM) in simulating industrial biological wastewater treatment plants (WWTPs) are still difficult due to refractory and complex components in influents as well as diversity in activated sludges. In this study, an ASM3 modeling study was conducted to simulate and optimize a practical coking wastewater treatment plant (CWTP). First, respirometric characterizations of the coking wastewater and CWTP biomasses were conducted to determine the specific kinetic and stoichiometric model parameters for the consecutive aeration-anoxic-aeration (O-A/O) biological process. All ASM3 parameters have been further estimated and calibrated, through cross validation by the model dynamic simulation procedure. Consequently, an ASM3 model was successfully established to accurately simulate the CWTP performances in removing COD and NH4-N. An optimized CWTP operation condition could be proposed reducing the operation cost from 6.2 to 5.5 €/m(3) wastewater. This study is expected to provide a useful reference for mathematic simulations of practical industrial WWTPs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy.

PubMed

Laber, Eric B; Zhao, Ying-Qi; Regh, Todd; Davidian, Marie; Tsiatis, Anastasios; Stanford, Joseph B; Zeng, Donglin; Song, Rui; Kosorok, Michael R

2016-04-15

A personalized treatment strategy formalizes evidence-based treatment selection by mapping patient information to a recommended treatment. Personalized treatment strategies can produce better patient outcomes while reducing cost and treatment burden. Thus, among clinical and intervention scientists, there is a growing interest in conducting randomized clinical trials when one of the primary aims is estimation of a personalized treatment strategy. However, at present, there are no appropriate sample size formulae to assist in the design of such a trial. Furthermore, because the sampling distribution of the estimated outcome under an estimated optimal treatment strategy can be highly sensitive to small perturbations in the underlying generative model, sample size calculations based on standard (uncorrected) asymptotic approximations or computer simulations may not be reliable. We offer a simple and robust method for powering a single stage, two-armed randomized clinical trial when the primary aim is estimating the optimal single stage personalized treatment strategy. The proposed method is based on inverting a plugin projection confidence interval and is thereby regular and robust to small perturbations of the underlying generative model. The proposed method requires elicitation of two clinically meaningful parameters from clinical scientists and uses data from a small pilot study to estimate nuisance parameters, which are not easily elicited. The method performs well in simulated experiments and is illustrated using data from a pilot study of time to conception and fertility awareness. Copyright © 2015 John Wiley & Sons, Ltd.

Patients' understanding of treatment goals and disease course and their relationship with optimism, hope, and quality of life: a preliminary study among advanced breast cancer outpatients before receiving palliative treatment.

PubMed

Soylu, Cem; Babacan, Taner; Sever, Ali R; Altundag, Kadri

2016-08-01

The aims of this study were to explore advanced breast cancer patients' knowledge of treatment intent and expectation of illness course and to evaluate their relationship with optimism, hope, and quality of life (QoL). Patients with advanced breast cancer (n = 55) who were treated in the ambulatory clinic of the University of Hacettepe were included in the study. They completed Life Orientation Scale, The Hope Scale, and the European Organization for Research and Treatment of Cancer Quality of Life questionnaires. The data regarding the knowledge of illness progression and the perceptions of therapy intent were assessed using self-administered open-ended questionnaires that were answered by the patients. The data revealed that 58.2 % of the patients had an inaccurate perception of treatment intent, believing the aim of treatment was cure, whereas only 38.2 % of the patients had a realistic expectation that their disease may remain stable or may progress over a year. In addition, the awareness of disease progression and perception of goals of treatment was significantly related to hope and optimism scores but not to QoL. A large proportion of patients diagnosed with advanced breast cancer believed that their treatment was "curative", and they would improve within a year. Findings of our study suggest that patients with inaccurate perception of treatment intent and unrealistic expectation of prognosis have higher hope and optimism scores than those who do not, but there were no significant differences in terms of global health status.

Developing Optimized Treatment Plans for Patients with Dyslipidemia in the Era of Proprotein Convertase Subtilisin/Kexin Type 9 Inhibitor Therapeutics.

PubMed

Underberg, James A; Blaha, Michael J; Jackson, Elizabeth J; Jones, Peter H

2017-10-01

This educational content was derived from a live satellite symposium at the American College of Physicians Internal Medicine Meeting 2017 in San Diego, California (online at http://courses.elseviercme.com/acp/702e). This activity will focus on optimized treatment plans for patients with dyslipidemia in the era of proprotein convertase subtilisin/kexin type 9 inhibitor therapeutics. Low-density lipoprotein cholesterol has been identified as an important therapeutic target to prevent the progression of atherosclerotic disease; however, only 1 of every 3 adults with high low-density lipoprotein cholesterol has the condition under control. Expert faculty on this panel will discuss the science of proprotein convertase subtilisin/kexin type 9 inhibitors and aid physicians in the best practices to achieve low-density lipoprotein cholesterol target in their patients. Copyright © 2017. Published by Elsevier Inc.

Strategy for Identifying Repurposed Drugs for the Treatment of Cerebral Cavernous Malformation

PubMed Central

Gibson, Christopher C.; Zhu, Weiquan; Davis, Chadwick T.; Bowman-Kirigin, Jay A.; Chan, Aubrey C.; Ling, Jing; Walker, Ashley E.; Goitre, Luca; Monache, Simona Delle; Retta, Saverio Francesco; Shiu, Yan-Ting E.; Grossmann, Allie H.; Thomas, Kirk R.; Donato, Anthony J.; Lesniewski, Lisa A.; Whitehead, Kevin J.; Li, Dean Y.

2014-01-01

Background Cerebral cavernous malformation (CCM) is a hemorrhagic stroke disease affecting up to 0.5% of North Americans with no approved non-surgical treatment. A subset of patients have a hereditary form of the disease due primarily to loss-of-function mutations in KRIT1, CCM2, or PDCD10. We sought to identify known drugs that could be repurposed to treat CCM. Methods and Results We developed an unbiased screening platform based on both cellular and animal models of loss-of-function of CCM2. Our discovery strategy consisted of four steps: an automated immunofluorescence and machine-learning-based primary screen of structural phenotypes in human endothelial cells deficient in CCM2; a secondary screen of functional changes in endothelial stability in these same cells; a rapid in vivo tertiary screen of dermal microvascular leak in mice lacking endothelial Ccm2; and finally a quaternary screen of CCM lesion burden in these same mice. We screened 2,100 known drugs and bioactive compounds, and identified two candidates for further study, cholecalciferol (Vitamin D3) and tempol (a scavenger of superoxide). Each drug decreased lesion burden in a mouse model of CCM vascular disease by approximately 50%. Conclusions By identifying known drugs as potential therapeutics for CCM, we have decreased the time, cost, and risk of bringing treatments to patients. Each drug also prompts additional exploration of biomarkers of CCM disease. We further suggest that the structure-function screening platform presented here may be adapted and scaled to facilitate drug discovery for diverse loss-of-function genetic vascular disease. PMID:25486933

Optimization of photo-Fenton process for the treatment of prednisolone.

PubMed

Díez, Aida María; Ribeiro, Ana Sofia; Sanromán, Maria Angeles; Pazos, Marta

2018-03-29

Prednisolone is a widely prescribed synthetic glucocorticoid and stated to be toxic to a number of non-target aquatic organisms. Its extensive consumption generates environmental concern due to its detection in wastewater samples at concentrations ranged from ng/L to μg/L that requests the application of suitable degradation processes. Regarding the actual treatment options, advanced oxidation processes (AOPs) are presented as a viable alternative. In this work, the comparison in terms of pollutant removal and energetic efficiencies, between different AOPs such as Fenton (F), photo-Fenton (UV/F), photolysis (UV), and hydrogen peroxide/photolysis (UV/H 2 O 2 ), was carried out. Light diode emission (LED) was the selected source to provide the UV radiation. The UV/F process revealed the best performance, reaching high levels of both degradation and mineralization with low energy consumption. Its optimization was conducted and the operational parameters were iron and H 2 O 2 concentrations and the working volume. Using the response surface methodology with the Box-Behnken design, the effect of independent variables and their interactions on the process response were effectively evaluated. Different responses were analyzed taking into account the prednisolone removal (TOC and drug abatements) and the energy consumptions associated. The obtained model showed an improvement of the UV/F process when treating smaller volumes and when adding high concentrations of H 2 O 2 and Fe 2+ . The validation of this model was successfully carried out, having only 5% of discrepancy between the model and the experimental results. Finally, the performance of the process when having a real wastewater matrix was also tested, achieving complete mineralization and detoxification after 8 h. In addition, prednisolone degradation products were identified. Finally, the obtained low energy permitted to confirm the viability of the process.

Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy

PubMed Central

Barish, Syndi; Ochs, Michael F.; Sontag, Eduardo D.; Gevertz, Jana L.

2017-01-01

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, mathematical modeling, and statistical analyses for identifying robust optimal treatment protocols. VEPART begins with time course experimental data for a sample population, and a mathematical model fit to aggregate data from that sample population. Using nonparametric statistics, the sample population is amplified and used to create a large number of virtual populations. At the final step of VEPART, robustness is assessed by identifying and analyzing the optimal therapy (perhaps restricted to a set of clinically realizable protocols) across each virtual population. As proof of concept, we have applied the VEPART method to study the robustness of treatment response in a mouse model of melanoma subject to treatment with immunostimulatory oncolytic viruses and dendritic cell vaccines. Our analysis (i) showed that every scheduling variant of the experimentally used treatment protocol is fragile (nonrobust) and (ii) discovered an alternative region of dosing space (lower oncolytic virus dose, higher dendritic cell dose) for which a robust optimal protocol exists. PMID:28716945

Hydraulic optimization and modeling of hydro-cyclone-systems for treatment and purification of any kind of waters

NASA Astrophysics Data System (ADS)

Spangemacher, Lars; Fröhlich, Siegmund; Buse, Hauke

2017-11-01

Water is an indispensable resource for many purposes and good drinking water quality is essential for mankind. This article is supposed to show the need for mobile water treatment systems and therefore to give an overview of different mobile drinking water systems and the technologies available for obtaining good water quality. The aim is to develop a simple to operate water treatment system with few processing stages such as multi-cyclone-cartridge and reverse osmosis with energy recuperation, while the focus is set on modeling and optimizing of hydrocyclone systems as the first treatment stage.

Identifying optimal postmarket surveillance strategies for medical and surgical devices: implications for policy, practice and research.

PubMed

Gagliardi, Anna R; Umoquit, Muriah; Lehoux, Pascale; Ross, Sue; Ducey, Ariel; Urbach, David R

2013-03-01

Non-drug technologies offer many benefits, but have been associated with adverse events, prompting calls for improved postmarket surveillance. There is little empirical research to guide the development of such a system. The purpose of this study was to identify optimal postmarket surveillance strategies for medical and surgical devices. Qualitative methods were used for sampling, data collection and analysis. Stakeholders from Canada and the USA representing different roles and perspectives were first interviewed to identify examples and characteristics of different surveillance strategies. These stakeholders and others they recommended were then assembled at a 1-day nominal group meeting to discuss and prioritise the components of a postmarket device surveillance system, and research needed to achieve such a system. Consultations were held with 37 participants, and 47 participants attended the 1-day meeting. They recommended a multicomponent system including reporting by facilities, clinicians and patients, supported with some external surveillance for validation and real-time trials for high-risk devices. Many considerations were identified that constitute desirable characteristics of, and means by which to implement such a system. An overarching network was envisioned to broker linkages, establish a shared minimum dataset, and support communication and decision making. Numerous research questions were identified, which could be pursued in tandem with phased implementation of the system. These findings provide unique guidance for establishing a device safety network that is based on existing initiatives, and could be expanded and evaluated in a prospective, phased fashion as it was developed.

Identifying perceived barriers to monitoring service quality among substance abuse treatment providers in South Africa

PubMed Central

2014-01-01

Background A performance measurement system is planned for South African substance abuse treatment services. Provider-level barriers to implementing these systems have been identified in the United States, but little is known about the nature of these barriers in South Africa. This study explored the willingness of South African substance abuse treatment providers’ to adopt a performance measurement system and perceived barriers to monitoring service quality that would need to be addressed during system development. Methods Three focus group discussions were held with treatment providers from two of the nine provinces in South Africa. These providers represented the diverse spread of substance abuse treatment services available in the country. The final sample comprised 21 representatives from 12 treatment facilities: eight treatment centres in the Western Cape and four in KwaZulu-Natal. Content analysis was used to extract core themes from these discussions. Results Participants identified barriers to the monitoring of service quality that included outdated modes of collecting data, personnel who were already burdened by paperwork, lack of time to collect data, and limited skills to analyse and interpret data. Participants recommended that developers engage with service providers in a participatory manner to ensure that service providers are invested in the proposed performance measurement system. Conclusion Findings show that substance abuse treatment providers are willing to adopt a performance measurement system and highlight several barriers that need to be addressed during system development in order to enhance the likelihood that this system will be successfully implemented. PMID:24499037

Can we use genetic and genomic approaches to identify candidate animals for targeted selective treatment.

PubMed

Laurenson, Yan C S M; Kyriazakis, Ilias; Bishop, Stephen C

2013-10-18

Estimated breeding values (EBV) for faecal egg count (FEC) and genetic markers for host resistance to nematodes may be used to identify resistant animals for selective breeding programmes. Similarly, targeted selective treatment (TST) requires the ability to identify the animals that will benefit most from anthelmintic treatment. A mathematical model was used to combine the concepts and evaluate the potential of using genetic-based methods to identify animals for a TST regime. EBVs obtained by genomic prediction were predicted to be the best determinant criterion for TST in terms of the impact on average empty body weight and average FEC, whereas pedigree-based EBVs for FEC were predicted to be marginally worse than using phenotypic FEC as a determinant criterion. Whilst each method has financial implications, if the identification of host resistance is incorporated into a wider genomic selection indices or selective breeding programmes, then genetic or genomic information may be plausibly included in TST regimes. Copyright © 2013 Elsevier B.V. All rights reserved.

Optimization of direct anti-viral agent treatment schedule: Focus on HCV genotype 3.

PubMed

Morisco, Filomena; Granata, Rocco; Camera, Silvia; Ippolito, Antonio; Milella, Michele; Conti, Fabio; Masetti, Chiara; Smedile, Antonella; Tundo, Paolo; Santantonio, Teresa; Valvano, Maria Rosa; Termite, Antonio; Gatti, Pietro; Messina, Vincenzo; Iacobellis, Angelo; Librandi, Marta; Caporaso, Nicola; Andriulli, Angelo

2018-03-01

Direct antiviral agents (DAAs) have led to high sustained virological responses (SVR) in hepatitis C virus (HCV) patients. However, genotype 3 patients respond to treatment in a suboptimal way. This study aims to identify which of the several treatment schedules recommended for genotype 3 would constitute the best option. Twenty-four Italian centers were involved in this real-life study of HCV genotype 3 patients treated with DAAs. To expand the number of cases, we conducted a systematic review of the literature on the outcome of genotype 3 patients treated with DAAs. A total of 233 patients with HCV genotype 3 were enrolled. Cirrhotic patients accounted for 83.7%. Overall, the SVR12 rate was achieved by 205 patients (88.0%); the SVR rates were 78.8% after sofosbuvir/ribavirin, 92.5% after sofosbuvir/daclatasvir ± ribavirin, and 100% after sofosbuvir/ledipasvir (seven patients). No difference in rate of SVR was observed in cirrhotic and non-cirrhotic patients (92.2 vs 94.4) using a combination regimen of NS5A and NS5B inhibitors.The systematic review of the literature provided data of 3311 patients: The mean weighted SVR12 rate was 84.4% (CI: 80.4-87.8); the rates varied from 79.0% (CI: 70.9-85.3) with sofosbuvir/ribavirin, to 83.7% (CI: 66.2-93.1) with sofosbuvir/ledispavir, and to 88.2% (CI: 83.3-91.7) with sofosbuvir/daclatasvir. Our results reinforce the concept that patients with HCV genotype 3 should no longer be considered difficult-to-treat individuals. The optimal therapeutic regimen for these patients appears to be the combination sofosbuvir/daclatasvir, administered for 12 weeks without the use of RBV in non-cirrhotic patients. In cirrhotics the meta-analytic approach suggests extending therapy to 24 weeks.

Identifying the substance abuse treatment needs of caregivers involved with child welfare.

PubMed

Chuang, Emmeline; Wells, Rebecca; Bellettiere, John; Cross, Theodore P

2013-07-01

Parental substance use significantly increases risk of child maltreatment, but is often under-identified by child protective services. This study examined how agency use of standardized substance use assessments and child welfare investigative caseworker education, experience, and caseload affected caseworkers' identification of parental substance abuse treatment needs. Data are from a national probability sample of permanent, primary caregivers involved with child protective services whose children initially remained at home and whose confidential responses on two validated instruments indicated harmful substance use or dependence. Investigative caseworkers reported use of a formal assessment in over two thirds of cases in which substance use was accurately identified. However, weighted logistic regression indicated that agency provision of standardized assessment instruments was not associated with caseworker identification of caregiver needs. Caseworkers were also less likely to identify substance abuse when their caseloads were high and when caregivers were fathers. Implications for agency practice are discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

Identifying the Substance Abuse Treatment Needs of Caregivers Involved with Child Welfare

PubMed Central

Wells, Rebecca; Bellettiere, John; Cross, Theodore P.

2013-01-01

Parental substance use significantly increases risk of child maltreatment, but is often under-identified by child protective services. This study examined how agency use of standardized substance use assessments and child welfare investigative caseworker education, experience, and caseload affected caseworkers’ identification of parental substance abuse treatment needs. Data are from a national probability sample of permanent, primary caregivers involved with child protective services whose children initially remained at home and whose confidential responses on two validated instruments indicated harmful substance use or dependence. Investigative caseworkers reported use of a formal assessment in over two thirds of cases in which substance use was accurately identified. However, weighted logistic regression indicated that agency provision of standardized assessment instruments was not associated with caseworker identification of caregiver needs. Caseworkers were also less likely to identify substance abuse when their caseloads were high and when caregivers were fathers. Implications for agency practice are discussed. PMID:23453481

Output-driven feedback system control platform optimizes combinatorial therapy of tuberculosis using a macrophage cell culture model.

PubMed

Silva, Aleidy; Lee, Bai-Yu; Clemens, Daniel L; Kee, Theodore; Ding, Xianting; Ho, Chih-Ming; Horwitz, Marcus A

2016-04-12

Tuberculosis (TB) remains a major global public health problem, and improved treatments are needed to shorten duration of therapy, decrease disease burden, improve compliance, and combat emergence of drug resistance. Ideally, the most effective regimen would be identified by a systematic and comprehensive combinatorial search of large numbers of TB drugs. However, optimization of regimens by standard methods is challenging, especially as the number of drugs increases, because of the extremely large number of drug-dose combinations requiring testing. Herein, we used an optimization platform, feedback system control (FSC) methodology, to identify improved drug-dose combinations for TB treatment using a fluorescence-based human macrophage cell culture model of TB, in which macrophages are infected with isopropyl β-D-1-thiogalactopyranoside (IPTG)-inducible green fluorescent protein (GFP)-expressing Mycobacterium tuberculosis (Mtb). On the basis of only a single screening test and three iterations, we identified highly efficacious three- and four-drug combinations. To verify the efficacy of these combinations, we further evaluated them using a methodologically independent assay for intramacrophage killing of Mtb; the optimized combinations showed greater efficacy than the current standard TB drug regimen. Surprisingly, all top three- and four-drug optimized regimens included the third-line drug clofazimine, and none included the first-line drugs isoniazid and rifampin, which had insignificant or antagonistic impacts on efficacy. Because top regimens also did not include a fluoroquinolone or aminoglycoside, they are potentially of use for treating many cases of multidrug- and extensively drug-resistant TB. Our study shows the power of an FSC platform to identify promising previously unidentified drug-dose combinations for treatment of TB.

Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands

USGS Publications Warehouse

Poitras, Travis; Villarreal, Miguel; Waller, Eric K.; Nauman, Travis; Miller, Mark E.; Duniway, Michael C.

2018-01-01

Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.

MO-AB-BRA-08: Rapid Treatment Field Uniformity Optimization for Total Skin Electron Beam Therapy Using Cherenkov Imaging

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

Andreozzi, J; Zhang, R; Glaser, A

Purpose: To evaluate treatment field heterogeneity resulting from gantry angle choice in total skin electron beam therapy (TSEBT) following a modified Stanford dual-field technique, and determine a relationship between source to surface distance (SSD) and optimized gantry angle spread. Methods: Cherenkov imaging was used to image 62 treatment fields on a sheet of 1.2m x 2.2m x 1.2cm polyethylene following standard TSEBT setup at our institution (6 MeV, 888 MU/min, no spoiler, SSD=441cm), where gantry angles spanned from 239.5° to 300.5° at 1° increments. Average Cherenkov intensity and coefficient of variation in the region of interest were compared for themore » set of composite Cherenkov images created by summing all unique combinations of angle pairs to simulate dual-field treatment. The angle pair which produced the lowest coefficient of variation was further studied using an ionization chamber. The experiment was repeated at SSD=300cm, and SSD=370.5cm. Cherenkov imaging was also implemented during TSEBT of three patients. Results: The most uniform treatment region from a symmetric angle spread was achieved using gantry angles +/−17.5° about the horizontal axis at SSD=441cm, +/−18.5° at SSD=370.5cm, and +/−19.5° at SSD=300cm. Ionization chamber measurements comparing the original treatment spread (+/−14.5°) and the optimized angle pair (+/−17.5°) at SSD=441cm showed no significant deviation (r=0.999) in percent depth dose curves, and chamber measurements from nine locations within the field showed an improvement in dose uniformity from 24.41% to 9.75%. Ionization chamber measurements correlated strongly (r=0.981) with Cherenkov intensity measured concurrently on the flat Plastic Water phantom. Patient images and TLD results also showed modest uniformity improvements. Conclusion: A decreasing linear relationship between optimal angle spread and SSD was observed. Cherenkov imaging offers a new method of rapidly analyzing and optimizing TSEBT

Dynamic regime marginal structural mean models for estimation of optimal dynamic treatment regimes, Part II: proofs of results.

PubMed

Orellana, Liliana; Rotnitzky, Andrea; Robins, James M

2010-03-03

In this companion article to "Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part I: Main Content" [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the optimal index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption.

A sensitivity-based approach to optimize the surface treatment of a low-height tramway noise barrier

NASA Astrophysics Data System (ADS)

Jolibois, Alexandre

Transportation noise has become a main nuisance in urban areas, in the industrialized world and across the world, to the point that according to the World Health Organization 65% of the European population is exposed to excessive noise and 20% to night-time levels that may harm their health. There is therefore a need to find new ways to mitigate transportation noise in urban areas. In this work, a possible device to achieve this goal is studied: a low-height noise barrier. It consists of a barrier typically less than one meter high placed close to the source, designed to decrease significantly the noise level for nearby pedestrians and cyclists. A numerical method which optimizes the surface treatment of a low-height barrier in order to increase its insertion loss is presented. Tramway noise barriers are especially studied since the noise sources are in this case close to the ground and would be attenuated more by the barrier. The acoustic behavior of the surface treatment is modeled via its admittance. It can be itself described by a few parameters (flow resistivity, geometrical dimensions...), which can then be optimized. It is proposed to couple porous layers and micro-perforated panel (MPP) resonators in order to take advantage of their different acoustic properties. Moreover, the optimization is achieved using a sensitivity-based method, since in this framework the gradient of the attenuation can be evaluated accurately and efficiently. Several shapes are considered: half-cylinder, quarter-cylinder, straight wall, T-shape and square shape. In the case of a half-cylindrical geometry, a semi-analytical solution for the sound field in terms of a series of cylindrical waves is derived, which simplifies the sensitivity calculation and optimization process. The boundary element method (BEM) is used to evaluate the attenuation for the remaining shapes, and in this case the sensitivity is evaluated using the adjoint state approach. For all considered geometries, it is

Optimal blood glucose control in diabetes mellitus treatment using dynamic programming based on Ackerman’s linear model

NASA Astrophysics Data System (ADS)

Pradanti, Paskalia; Hartono

2018-03-01

Determination of insulin injection dose in diabetes mellitus treatment can be considered as an optimal control problem. This article is aimed to simulate optimal blood glucose control for patient with diabetes mellitus. The blood glucose regulation of diabetic patient is represented by Ackerman’s Linear Model. This problem is then solved using dynamic programming method. The desired blood glucose level is obtained by minimizing the performance index in Lagrange form. The results show that dynamic programming based on Ackerman’s Linear Model is quite good to solve the problem.

Optimizing prophylactic treatment of migraine: Subtypes and patient matching

PubMed Central

Dib, Michel

2008-01-01

Advances in our understanding of the pathophysiology of migraine have resulted in important breakthroughs in treatment. For example, understanding of the role of serotonin in the cerebrovascular circulation has led to the development of triptans for the acute relief of migraine headaches, and the identification of cortical spreading depression as an early central event associated wih migraine has brought renewed interest in antiepileptic drugs for migraine prophylaxis. However, migraine still remains inadequately treated. Indeed, it is apparent that migraine is not a single disease but rather a syndrome that can manifest itself in a variety of pathological conditions. The consequences of this may be that treatment needs to be matched to particular patients. Clinical research needs to be devoted to identifying which sort of patients benefit best from which treatments, particularly in the field of prophylaxis. We propose four patterns of precipitating factors (adrenergic, serotoninergic, menstrual, and muscular) which may be used to structure migraine prophylaxis. Finally, little is known about long-term outcome in treated migraine. It is possible that appropriate early prophylaxis may modify the long-term course of the disease and avoid late complications. PMID:19209286

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

PubMed

Guthier, Christian V; Damato, Antonio L; Hesser, Juergen W; Viswanathan, Akila N; Cormack, Robert A

2017-12-01

Interstitial high-dose rate (HDR) brachytherapy is an important therapeutic strategy for the treatment of locally advanced gynecologic (GYN) cancers. The outcome of this therapy is determined by the quality of dose distribution achieved. This paper focuses on a novel yet simple heuristic for catheter selection for GYN HDR brachytherapy and their comparison against state of the art optimization strategies. The proposed technique is intended to act as a decision-supporting tool to select a favorable needle configuration. The presented heuristic for catheter optimization is based on a shrinkage-type algorithm (SACO). It is compared against state of the art planning in a retrospective study of 20 patients who previously received image-guided interstitial HDR brachytherapy using a Syed Neblett template. From those plans, template orientation and position are estimated via a rigid registration of the template with the actual catheter trajectories. All potential straight trajectories intersecting the contoured clinical target volume (CTV) are considered for catheter optimization. Retrospectively generated plans and clinical plans are compared with respect to dosimetric performance and optimization time. All plans were generated with one single run of the optimizer lasting 0.6-97.4 s. Compared to manual optimization, SACO yields a statistically significant (P ≤ 0.05) improved target coverage while at the same time fulfilling all dosimetric constraints for organs at risk (OARs). Comparing inverse planning strategies, dosimetric evaluation for SACO and "hybrid inverse planning and optimization" (HIPO), as gold standard, shows no statistically significant difference (P > 0.05). However, SACO provides the potential to reduce the number of used catheters without compromising plan quality. The proposed heuristic for needle selection provides fast catheter selection with optimization times suited for intraoperative treatment planning. Compared to manual optimization, the

Pregnancy Research on Osteopathic Manipulation Optimizing Treatment Effects: The PROMOTE Study Protocol.

PubMed

Hensel, Kendi L; Carnes, Michael S; Stoll, Scott T

2016-11-01

The structural and physiologic changes in a woman's body during pregnancy can predispose pregnant women to low back pain and its associated disability, as well as to complications of pregnancy, labor, and delivery. Anecdotal and empirical evidence has indicated that osteopathic manipulative treatment (OMT) may be efficacious in improving pain and functionality in women who are pregnant. Based on that premise, the Pregnancy Research on Osteopathic Manipulation Optimizing Treatment Effects (PROMOTE) study was designed as a prospective, randomized, placebo-controlled, and blinded clinical trial to evaluate the efficacy of an OMT protocol for pain during third-trimester pregnancy. The OMT protocol developed for the PROMOTE study was based on physiologic theory and the concept of the interrelationship of structure and function. The 12 well-defined, standardized OMT techniques used in the protocol are commonly taught at osteopathic medical schools in the United States. These techniques can be easily replicated as a 20-minute protocol applied in conjunction with usual prenatal care, thus making it feasible to implement into clinical practice. This article presents an overview of the study design and treatment protocols used in the PROMOTE study.

NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

PubMed

Zou, Meng; Liu, Zhaoqi; Zhang, Xiang-Sun; Wang, Yong

2015-10-15

In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. In summary, NCC-AUC provides a rigorous optimization framework to

A Randomized Clinical Trial to Determine Optimal Infertility Treatment in Older Couples: The Forty and Over Treatment Trial (FORT-T)

PubMed Central

Goldman, Marlene B.; Thornton, Kim L.; Ryley, David; Alper, Michael M.; Fung, June L.; Hornstein, Mark D.; Reindollar, Richard H.

2014-01-01

Objective To determine optimal infertility therapy in women at the end of their reproductive potential. Design Randomized clinical trial. Setting Academic medical centers and private infertility center in a state with mandated insurance coverage. Patients Couples with ≥ 6 months of unexplained infertility; female partner aged 38–42. Interventions Randomized to treatment with 2 cycles of clomiphene citrate (CC) and intrauterine insemination (IUI), follicle stimulating hormone (FSH)/IUI, or immediate IVF, followed by IVF if not pregnant. Main Outcome Measures Proportion with a clinically recognized pregnancy, number of treatment cycles, and time to conception after 2 treatment cycles and at the end of treatment. Results 154 couples were randomized to receive CC/IUI (N=51), FSH/IUI (N=52), or immediate IVF (N=51); 140 (90.9%) couples initiated treatment. Cumulative clinical pregnancy rates per couple after the first 2 cycles of CC/IUI, FSH/IUI, or immediate IVF were 21.6%, 17.3%, and 49.0%, respectively. After all treatment, 71.4% (110/154) of couples conceived a clinically recognized pregnancy and 46.1% delivered at least one live-born baby. 84.2% of all live born infants resulting from treatment were achieved from IVF. There were 36% fewer treatment cycles in the IVF arm compared to either COH/IUI arm and couples conceived a pregnancy leading to a live birth after fewer treatment cycles. Conclusions An RCT to compare treatment initiated with 2 cycles of COH/IUI to immediate IVF in older women with unexplained infertility demonstrated superior pregnancy rates with fewer treatment cycles in the immediate IVF group. PMID:24796764

Brachytherapy optimization using radiobiological-based planning for high dose rate and permanent implants for prostate cancer treatment

NASA Astrophysics Data System (ADS)

Seeley, Kaelyn; Cunha, J. Adam; Hong, Tae Min

2017-01-01

We discuss an improvement in brachytherapy--a prostate cancer treatment method that directly places radioactive seeds inside target cancerous regions--by optimizing the current standard for delivering dose. Currently, the seeds' spatiotemporal placement is determined by optimizing the dose based on a set of physical, user-defined constraints. One particular approach is the ``inverse planning'' algorithms that allow for tightly fit isodose lines around the target volumes in order to reduce dose to the patient's organs at risk. However, these dose distributions are typically computed assuming the same biological response to radiation for different types of tissues. In our work, we consider radiobiological parameters to account for the differences in the individual sensitivities and responses to radiation for tissues surrounding the target. Among the benefits are a more accurate toxicity rate and more coverage to target regions for planning high-dose-rate treatments as well as permanent implants.

Optimized interface and recrystallized grains by CsBr treatment for enhanced photovoltaic performance of perovskite solar cells

NASA Astrophysics Data System (ADS)

Liu, Li; Su, Pengyu; Yao, Huizhen; Wang, Jun; Fu, Wuyou; Liu, Xizhe; Yang, Haibin

2018-06-01

Doping, interface optimization and recrystallization are effective approaches for fabricating high performance perovskite solar cells (PSCs). In our work, simple CsBr treatment is introduced to improve the performance of TiO2 nanorods-based PSCs. Both Cs+ and Br- are doped into CH3NH3PbI3 simultaneously, as well as optimizes the interface between perovskite and hole-transporting material (HTM). In addition, the perovskite grains are recrystallized through this method. Finally, a power conversion efficiency (PCE) of 16.02% with 0.72 in fill factor (FF) and 1.08 in open circuit voltage (VOC) is obtained through CsBr treatment, which is 19.91% higher than that of untreated devices (13.36% with 0.65 in FF and 1.02 in VOC). Furthermore, the power output maintains ∼14% after 3500 h under the humidity within 15% at room temperature.

Global Aesthetics Consensus: Hyaluronic Acid Fillers and Botulinum Toxin Type A—Recommendations for Combined Treatment and Optimizing Outcomes in Diverse Patient Populations

PubMed Central

Liew, Steven; Signorini, Massimo; Vieira Braz, André; Fagien, Steven; Swift, Arthur; De Boulle, Koenraad L.; Raspaldo, Hervé; Trindade de Almeida, Ada R.; Monheit, Gary

2016-01-01

Background: Combination of fillers and botulinum toxin for aesthetic applications is increasingly popular. Patient demographics continue to diversify, and include an expanding population receiving maintenance treatments over decades. Methods: A multinational panel of plastic surgeons and dermatologists convened the Global Aesthetics Consensus Group to develop updated guidelines with a worldwide perspective for hyaluronic acid fillers and botulinum toxin. This publication considers strategies for combined treatments, and how patient diversity influences treatment planning and outcomes. Results: Global Aesthetics Consensus Group recommendations reflect increased use of combined treatments in the lower and upper face, and some midface regions. A fully patient-tailored approach considers physiologic and chronologic age, ethnically associated facial morphotypes, and aesthetic ideals based on sex and culture. Lower toxin dosing, to modulate rather than paralyze muscles, is indicated where volume deficits influence muscular activity. Combination of toxin with fillers is appropriate for several indications addressed previously with toxin alone. New scientific data regarding hyaluronic acid fillers foster an evidence-based approach to selection of products and injection techniques. Focus on aesthetic units, rather than isolated rhytides, optimizes results from toxin and fillers. It also informs longitudinal treatment planning, and analysis of toxin nonresponders. Conclusions: The emerging objective of injectable treatment is facial harmonization rather than rejuvenation. Combined treatment is now a standard of care. Its use will increase further as we refine the concept that aspects of aging are intimately related, and that successful treatment entails identifying and addressing the primary causes of each. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, V. PMID:27119917

Youth Top Problems: using idiographic, consumer-guided assessment to identify treatment needs and to track change during psychotherapy.

PubMed

Weisz, John R; Chorpita, Bruce F; Frye, Alice; Ng, Mei Yi; Lau, Nancy; Bearman, Sarah Kate; Ugueto, Ana M; Langer, David A; Hoagwood, Kimberly E

2011-06-01

To complement standardized measurement of symptoms, we developed and tested an efficient strategy for identifying (before treatment) and repeatedly assessing (during treatment) the problems identified as most important by caregivers and youths in psychotherapy. A total of 178 outpatient-referred youths, 7-13 years of age, and their caregivers separately identified the 3 problems of greatest concern to them at pretreatment and then rated the severity of those problems weekly during treatment. The Top Problems measure thus formed was evaluated for (a) whether it added to the information obtained through empirically derived standardized measures (e.g., the Child Behavior Checklist [CBCL; Achenbach & Rescorla, 2001] and the Youth Self-Report [YSR; Achenbach & Rescorla, 2001]) and (b) whether it met conventional psychometric standards. The problems identified were significant and clinically relevant; most matched CBCL/YSR items while adding specificity. The top problems also complemented the information yield of the CBCL/YSR; for example, for 41% of caregivers and 79% of youths, the identified top problems did not correspond to any items of any narrowband scales in the clinical range. Evidence on test-retest reliability, convergent and discriminant validity, sensitivity to change, slope reliability, and the association of Top Problems slopes with standardized measure slopes supported the psychometric strength of the measure. The Top Problems measure appears to be a psychometrically sound, client-guided approach that complements empirically derived standardized assessment; the approach can help focus attention and treatment planning on the problems that youths and caregivers consider most important and can generate evidence on trajectories of change in those problems during treatment. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

Isolation, Identification, and Optimization of Culture Conditions of a Bioflocculant-Producing Bacterium Bacillus megaterium SP1 and Its Application in Aquaculture Wastewater Treatment

PubMed Central

Luo, Liang; Huang, Xiaoli; Du, Xue; Wang, Chang'an; Li, Jinnan; Wang, Liansheng

2016-01-01

A bioflocculant-producing bacterium, Bacillus megaterium SP1, was isolated from biofloc in pond water and identified by using both 16S rDNA sequencing analysis and a Biolog GEN III MicroStation System. The optimal carbon and nitrogen sources for Bacillus megaterium SP1 were 20 g L−1 of glucose and 0.5 g L−1 of beef extract at 30°C and pH 7. The bioflocculant produced by strain SP1 under optimal culture conditions was applied into aquaculture wastewater treatment. The removal rates of chemical oxygen demand (COD), total ammonia nitrogen (TAN), and suspended solids (SS) in aquaculture wastewater reached 64, 63.61, and 83.8%, respectively. The volume of biofloc (FV) increased from 4.93 to 25.97 mL L−1. The addition of Bacillus megaterium SP1 in aquaculture wastewater could effectively improve aquaculture water quality, promote the formation of biofloc, and then form an efficient and healthy aquaculture model based on biofloc technology. PMID:27840823

SU-E-T-593: Clinical Evaluation of Direct Aperture Optimization in Head/Neck and Prostate IMRT Treatment

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

Hosini, M; GALAL, M; Emam, I

2014-06-01

Purpose: To investigate the planning and dosimetric advantages of direct aperture optimization (DAO) over beam-let optimization in IMRT treatment of head and neck (H/N) and prostate cancers. Methods: Five Head and Neck as well as five prostate patients were planned using the beamlet optimizer in Elekta-Xio ver 4.6 IMRT treatment planning system. Based on our experience in beamlet IMRT optimization, PTVs in H/N plans were prescribed to 70 Gy delivered by 7 fields. While prostate PTVs were prescribed to 76 Gy with 9 fields. In all plans, fields were set to be equally spaced. All cases were re-planed using Directmore » Aperture optimizer in Prowess Panther ver 5.01 IMRT planning system at same configurations and dose constraints. Plans were evaluated according to ICRU criteria, number of segments, number of monitor units and planning time. Results: For H/N plans, the near maximum dose (D2) and the dose that covers 95% D95 of PTV has improved by 4% in DAO. For organs at risk (OAR), DAO reduced the volume covered by 30% (V30) in spinal cord, right parotid, and left parotid by 60%, 54%, and 53% respectively. This considerable dosimetric quality improvement achieved using 25% less planning time and lower number of segments and monitor units by 46% and 51% respectively. In DAO prostate plans, Both D2 and D95 for the PTV were improved by only 2%. The V30 of the right femur, left femur and bladder were improved by 35%, 15% and 3% respectively. On the contrary, the rectum V30 got even worse by 9%. However, number of monitor units, and number of segments decreased by 20% and 25% respectively. Moreover the planning time reduced significantly too. Conclusion: DAO introduces considerable advantages over the beamlet optimization in regards to organs at risk sparing. However, no significant improvement occurred in most studied PTVs.« less

Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part II: Proofs of Results*

PubMed Central

Orellana, Liliana; Rotnitzky, Andrea; Robins, James M.

2010-01-01

In this companion article to “Dynamic Regime Marginal Structural Mean Models for Estimation of Optimal Dynamic Treatment Regimes, Part I: Main Content” [Orellana, Rotnitzky and Robins (2010), IJB, Vol. 6, Iss. 2, Art. 7] we present (i) proofs of the claims in that paper, (ii) a proposal for the computation of a confidence set for the optimal index when this lies in a finite set, and (iii) an example to aid the interpretation of the positivity assumption. PMID:20405047

A multi-factor GIS method to identify optimal geographic locations for electric vehicle (EV) charging stations

NASA Astrophysics Data System (ADS)

Zhang, Yongqin; Iman, Kory

2018-05-01

Fuel-based transportation is one of the major contributors to poor air quality in the United States. Electric Vehicle (EV) is potentially the cleanest transportation technology to our environment. This research developed a spatial suitability model to identify optimal geographic locations for installing EV charging stations for travelling public. The model takes into account a variety of positive and negative factors to identify prime locations for installing EV charging stations in Wasatch Front, Utah, where automobile emission causes severe air pollution due to atmospheric inversion condition near the valley floor. A walkable factor grid was created to store index scores from input factor layers to determine prime locations. 27 input factors including land use, demographics, employment centers etc. were analyzed. Each factor layer was analyzed to produce a summary statistic table to determine the site suitability. Potential locations that exhibit high EV charging usage were identified and scored. A hot spot map was created to demonstrate high, moderate, and low suitability areas for installing EV charging stations. A spatially well distributed EV charging system was then developed, aiming to reduce "range anxiety" from traveling public. This spatial methodology addresses the complex problem of locating and establishing a robust EV charging station infrastructure for decision makers to build a clean transportation infrastructure, and eventually improve environment pollution.

Thromboxane Formation Assay to Identify High On-Treatment Platelet Reactivity to Aspirin.

PubMed

Mohring, Annemarie; Piayda, Kerstin; Dannenberg, Lisa; Zako, Saif; Schneider, Theresa; Bartkowski, Kirsten; Levkau, Bodo; Zeus, Tobias; Kelm, Malte; Hohlfeld, Thomas; Polzin, Amin

2017-01-01

Platelet inhibition by aspirin is indispensable in the secondary prevention of cardiovascular events. Nevertheless, impaired aspirin antiplatelet effects (high on-treatment platelet reactivity [HTPR]) are frequent. This is associated with an enhanced risk of cardiovascular events. The current gold standard to evaluate platelet hyper-reactivity despite aspirin intake is the light-transmittance aggregometry (LTA). However, pharmacologically, the most specific test is the measurement of arachidonic acid (AA)-induced thromboxane (TX) B2 formation. Currently, the optimal cut-off to define HTPR to aspirin by inhibition of TX formation is not known. Therefore, in this pilot study, we aimed to calculate a TX formation cut-off value to detect HTPR defined by the current gold standard LTA. We measured platelet function in 2,507 samples. AA-induced TX formation by ELISA and AA-induced LTA were used to measure aspirin antiplatelet effects. TX formation correlated nonlinearly with the maximum of aggregation in the AA-induced LTA (Spearman's rho R = 0.7396; 95% CI 0.7208-0.7573, p < 0.0001). Receiver operating characteristic analysis and Youden's J statistics revealed 209.8 ng/mL as the optimal cut-off value to detect HTPR to aspirin with the TX ELISA (area under the curve: 0.92, p < 0.0001, sensitivity of 82.7%, specificity of 90.3%). In summary, TX formation ELISA is reliable in detecting HTPR to aspirin. The calculated cut-off level needs to be tested in trials with clinical end points. © 2017 S. Karger AG, Basel.

Optimization of the anaerobic treatment of a waste stream from an enhanced oil recovery process.

PubMed

Alimahmoodi, Mahmood; Mulligan, Catherine N

2011-01-01

The aim of this work was to optimize the anaerobic treatment of a waste stream from an enhanced oil recovery (EOR) process. The treatment of a simulated waste water containing about 150 mg chemical oxygen demand (COD)/L of total petroleum hydrocarbons (TPH) and the saturation level of CO2 was evaluated. A two-step anaerobic system was undertaken in the mesophilic temperature range (30-40°C). The method of evolutionary operation EVOP factorial design was used to optimize pH, temperature and organic loading rate with the target parameters of CO2 reduction and CH4 production in the first reactor and TPH removal in the second reactor. The results showed 98% methanogenic removal of CO2 and CH4 yield of 0.38 L/gCOD in the first reactor and 83% TPH removal in the second reactor. In addition to enhancing CO2 and TPH removal and CH4 production, application of this method showed the degree of importance of the operational variables and their interactive effects for the two reactors in series. Copyright © 2010 Elsevier Ltd. All rights reserved.

Dosing strategies to optimize currently available anti-MRSA treatment options (Part 1: IV options).

PubMed

Hall, Ronald G; Thatcher, Michael; Wei, Wei; Varghese, Shibin; Varughese, Lincy; Ndiulor, Michelle; Payne, Kenna D

2017-05-01

Methicillin-resistant Staphylococcus aureus (MRSA) continues to be a predominant pathogen resulting in significant morbidity and mortality. Optimal dosing of anti-MRSA agents is needed to help prevent the development of antimicrobial resistance and to increase the likelihood of a favorable clinical outcome. Areas covered: This review summarizes the available data for antimicrobials routinely used for MRSA infections that are not administered orally or topically. We make recommendations and highlight the current gaps in the literature. A PubMed (1966 - Present) search was performed to identify relevant literature for this review. Expert commentary: Improvements in MIC determination and therapeutic drug monitoring are needed to fully implement individualized dosing that optimizes antimicrobial pharmacodynamics.Additional data will become available for these agents in regards to effectiveness for severe MRSA infections and pharmacokinetic data for special patient populations.

Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy

NASA Astrophysics Data System (ADS)

Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

2013-11-01

To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (∼1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust

Robust plan optimization for electromagnetic transponder guided hypo-fractionated prostate treatment using volumetric modulated arc therapy.

PubMed

Zhang, Pengpeng; Hunt, Margie; Happersett, Laura; Yang, Jie; Zelefsky, Michael; Mageras, Gig

2013-11-07

To develop an optimization algorithm for volumetric modulated arc therapy which incorporates an electromagnetic tracking (EMT) guided gating strategy and is robust to residual intra-fractional motion uncertainties. In a computer simulation, intra-fractional motion traces from prior treatments with EMT were converted to a probability distribution function (PDF), truncated using a patient specific action volume that encloses allowed deviations from the planned position, and renormalized to yield a new PDF with EMT-gated interventions. In lieu of a conventional planning target volume (PTV), multiple instances of clinical target volume (CTV) and organs at risk (OARs) were replicated and displaced to extreme positions inside the action volume representing possible delivery scenarios. When optimizing the volumetric modulated arc therapy plan, doses to the CTV and OARs were calculated as a sum of doses to the replicas weighted by the PDF to account for motion. A treatment plan meeting the clinical constraints was produced and compared to the counterpart conventional margin (PTV) plan. EMT traces from a separate testing database served to simulate motion during gated delivery. Dosimetric end points extracted from dose accumulations for each motion trace were utilized to evaluate potential clinical benefit. Five prostate cases from a hypofractionated protocol (42.5 Gy in 5 fractions) were retrospectively investigated. The patient specific gating window resulted in tight anterior and inferior action levels (~1 mm) to protect rectal wall and bladder wall, and resulted in an average of four beam interruptions per fraction in the simulation. The robust-optimized plans achieved the same average CTV D95 coverage of 40.5 Gy as the PTV-optimized plans, but with reduced patient-averaged rectum wall D1cc by 2.2 Gy (range 0.7 to 4.7 Gy) and bladder wall mean dose by 2.9 Gy (range 2.0 to 3.4 Gy). Integration of an intra-fractional motion management strategy into the robust optimization

SU-F-BRD-07: Fast Monte Carlo-Based Biological Optimization of Proton Therapy Treatment Plans for Thyroid Tumors

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

Wan Chan Tseung, H; Ma, J; Ma, D

2015-06-15

Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) based biological planning for the treatment of thyroid tumors in spot-scanning proton therapy. Methods: Recently, we developed a fast and accurate GPU-based MC simulation of proton transport that was benchmarked against Geant4.9.6 and used as the dose calculation engine in a clinically-applicable GPU-accelerated IMPT optimizer. Besides dose, it can simultaneously score the dose-averaged LET (LETd), which makes fast biological dose (BD) estimates possible. To convert from LETd to BD, we used a linear relation based on cellular irradiation data. Given a thyroid patient with a 93cc tumor volume, we createdmore » a 2-field IMPT plan in Eclipse (Varian Medical Systems). This plan was re-calculated with our MC to obtain the BD distribution. A second 5-field plan was made with our in-house optimizer, using pre-generated MC dose and LETd maps. Constraints were placed to maintain the target dose to within 25% of the prescription, while maximizing the BD. The plan optimization and calculation of dose and LETd maps were performed on a GPU cluster. The conventional IMPT and biologically-optimized plans were compared. Results: The mean target physical and biological doses from our biologically-optimized plan were, respectively, 5% and 14% higher than those from the MC re-calculation of the IMPT plan. Dose sparing to critical structures in our plan was also improved. The biological optimization, including the initial dose and LETd map calculations, can be completed in a clinically viable time (∼30 minutes) on a cluster of 25 GPUs. Conclusion: Taking advantage of GPU acceleration, we created a MC-based, biologically optimized treatment plan for a thyroid patient. Compared to a standard IMPT plan, a 5% increase in the target’s physical dose resulted in ∼3 times as much increase in the BD. Biological planning was thus effective in escalating the target BD.« less

Economic comparison of common treatment protocols and J5 vaccination for clinical mastitis in dairy herds using optimized culling decisions.

PubMed

Kessels, J A; Cha, E; Johnson, S K; Welcome, F L; Kristensen, A R; Gröhn, Y T

2016-05-01

This study used an existing dynamic optimization model to compare costs of common treatment protocols and J5 vaccination for clinical mastitis in US dairy herds. Clinical mastitis is an infection of the mammary gland causing major economic losses in dairy herds due to reduced milk production, reduced conception, and increased risk of mortality and culling for infected cows. Treatment protocols were developed to reflect common practices in dairy herds. These included targeted therapy following pathogen identification, and therapy without pathogen identification using a broad-spectrum antimicrobial or treating with the cheapest treatment option. The cost-benefit of J5 vaccination was also estimated. Effects of treatment were accounted for as changes in treatment costs, milk loss due to mastitis, milk discarded due to treatment, and mortality. Following ineffective treatments, secondary decisions included extending the current treatment, alternative treatment, discontinuing treatment, and pathogen identification followed by recommended treatment. Average net returns for treatment protocols and vaccination were generated using an existing dynamic programming model. This model incorporates cow and pathogen characteristics to optimize management decisions to treat, inseminate, or cull cows. Of the treatment protocols where 100% of cows received recommended treatment, pathogen-specific identification followed by recommended therapy yielded the highest average net returns per cow per year. Out of all treatment scenarios, the highest net returns were achieved with selecting the cheapest treatment option and discontinuing treatment, or alternate treatment with a similar spectrum therapy; however, this may not account for the full consequences of giving nonrecommended therapies to cows with clinical mastitis. Vaccination increased average net returns in all scenarios. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Structure-Guided Lead Optimization of Triazolopyrimidine-Ring Substituents Identifies Potent Plasmodium falciparum Dihydroorotate Dehydrogenase Inhibitors with Clinical Candidate Potential

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

Coteron, Jose M.; Marco, Maria; Esquivias, Jorge

2012-02-27

Drug therapy is the mainstay of antimalarial therapy, yet current drugs are threatened by the development of resistance. In an effort to identify new potential antimalarials, we have undertaken a lead optimization program around our previously identified triazolopyrimidine-based series of Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors. The X-ray structure of PfDHODH was used to inform the medicinal chemistry program allowing the identification of a potent and selective inhibitor (DSM265) that acts through DHODH inhibition to kill both sensitive and drug resistant strains of the parasite. This compound has similar potency to chloroquine in the humanized SCID mouse P. falciparum model,more » can be synthesized by a simple route, and rodent pharmacokinetic studies demonstrated it has excellent oral bioavailability, a long half-life and low clearance. These studies have identified the first candidate in the triazolopyrimidine series to meet previously established progression criteria for efficacy and ADME properties, justifying further development of this compound toward clinical candidate status.« less

Potential annealing treatments for tailoring the starting microstructure of low-enriched U-Mo dispersion fuels to optimize performance during irradiation

NASA Astrophysics Data System (ADS)

Keiser, Dennis D.; Jue, Jan-Fong; Woolstenhulme, Nicolas E.; Ewh, Ashley

2011-12-01

Low-enriched uranium-molybdenum (U-Mo) alloy particles dispersed in aluminum alloy (e.g., dispersion fuels) are being developed for application in research and test reactors. To achieve the best performance of these fuels during irradiation, optimization of the starting microstructure may be required by utilizing a heat treatment that results in the formation of uniform, Si-rich interaction layers between the U-Mo particles and Al-Si matrix. These layers behave in a stable manner under certain irradiation conditions. To identify the optimum heat treatment for producing these kinds of layers in a dispersion fuel plate, a systematic annealing study has been performed using actual dispersion fuel samples, which were fabricated at relatively low temperatures to limit the growth of any interaction layers in the samples prior to controlled heat treatment. These samples had different Al matrices with varying Si contents and were annealed between 450 and 525 °C for up to 4 h. The samples were then characterized using scanning electron microscopy (SEM) to examine the thickness, composition, and uniformity of the interaction layers. Image analysis was performed to quantify various attributes of the dispersion fuel microstructures that related to the development of the interaction layers. The most uniform layers were observed to form in fuel samples that had an Al matrix with at least 4 wt.% Si and a heat treatment temperature of at least 475 °C.

Whole Genome Re-Sequencing Identifies a Quantitative Trait Locus Repressing Carbon Reserve Accumulation during Optimal Growth in Chlamydomonas reinhardtii

PubMed Central

Goold, Hugh Douglas; Nguyen, Hoa Mai; Kong, Fantao; Beyly-Adriano, Audrey; Légeret, Bertrand; Billon, Emmanuelle; Cuiné, Stéphan; Beisson, Fred; Peltier, Gilles; Li-Beisson, Yonghua

2016-01-01

Microalgae have emerged as a promising source for biofuel production. Massive oil and starch accumulation in microalgae is possible, but occurs mostly when biomass growth is impaired. The molecular networks underlying the negative correlation between growth and reserve formation are not known. Thus isolation of strains capable of accumulating carbon reserves during optimal growth would be highly desirable. To this end, we screened an insertional mutant library of Chlamydomonas reinhardtii for alterations in oil content. A mutant accumulating five times more oil and twice more starch than wild-type during optimal growth was isolated and named constitutive oil accumulator 1 (coa1). Growth in photobioreactors under highly controlled conditions revealed that the increase in oil and starch content in coa1 was dependent on light intensity. Genetic analysis and DNA hybridization pointed to a single insertional event responsible for the phenotype. Whole genome re-sequencing identified in coa1 a >200 kb deletion on chromosome 14 containing 41 genes. This study demonstrates that, 1), the generation of algal strains accumulating higher reserve amount without compromising biomass accumulation is feasible; 2), light is an important parameter in phenotypic analysis; and 3), a chromosomal region (Quantitative Trait Locus) acts as suppressor of carbon reserve accumulation during optimal growth. PMID:27141848

Optimization of a Nanomedicine-based Pc 4-PDT Strategy for Targeted Treatment of EGFR-Overexpressing Cancers

PubMed Central

Master, Alyssa M.; Livingston, Megan; Oleinick, Nancy L.; Gupta, Anirban Sen

2012-01-01

The current clinical mainstays for cancer treatment, namely, surgical resection, chemotherapy and radiotherapy, can cause significant trauma, systemic toxicity, and functional/cosmetic debilitation of tissue, especially if repetitive treatment becomes necessary due to tumor recurrence. Hence there is significant clinical interest in alternate treatment strategies like photodynamic therapy (PDT) which can effectively and selectively eradicate tumors and can be safely repeated if needed. We have previously demonstrated that the second-generation photosensitizer Pc 4 can be formulated within polymeric micelles, and these micelles can be specifically targeted to EGFR-overexpressing cancer cells using GE11 peptide ligands, to enhance cell-specific Pc 4 delivery and internalization. In the current study, we report on the in vitro optimization of the EGFR-targeting, Pc 4 loading of the micellar nanoformulation, along with optimization of the corresponding photoirradiation conditions to maximize Pc 4 delivery, internalization and subsequent PDT-induced cytotoxicity in EGFR-overexpressing cells in vitro. In our studies, absorption and fluorescence spectroscopy were used to monitor the cell-specific uptake of the GE11-decorated Pc 4-loaded micelles and the cytotoxic singlet oxygen production from the micelle-encapsulated Pc 4, to determine the optimum ligand density and Pc 4 loading. It was found that the micelle formulations bearing 10 mole% of GE11-modified polymer component resulted in the highest cellular uptake in EGFR-overexpressing A431 cells within the shortest incubation periods. Also, the loading of ~50 μg Pc 4 per mg of polymer in these micellar formulations resulted in the highest levels of singlet oxygen production. When formulations bearing these optimized parameters were tested in vitro on A431 cells for PDT effect, a formulation dose containing 400 nM Pc 4 and photoirradiation duration of 400 seconds at a fluence of 200 mJ/cm2 yielded close to 100% cell

Using benchmarking to identify inter-centre differences in persistent ductus arteriosus treatment: can we improve outcome?

PubMed

Jansen, Esther J S; Dijkman, Koen P; van Lingen, Richard A; de Vries, Willem B; Vijlbrief, Daniel C; de Boode, Willem P; Andriessen, Peter

2017-10-01

The aim of this study was to identify inter-centre differences in persistent ductus arteriosus treatment and their related outcomes. Materials and methods We carried out a retrospective, multicentre study including infants between 24+0 and 27+6 weeks of gestation in the period between 2010 and 2011. In all centres, echocardiography was used as the standard procedure to diagnose a patent ductus arteriosus and to document ductal closure. In total, 367 preterm infants were included. All four participating neonatal ICU had a comparable number of preterm infants; however, differences were observed in the incidence of treatment (33-63%), choice and dosing of medication (ibuprofen or indomethacin), number of pharmacological courses (1-4), and the need for surgical ligation after failure of pharmacological treatment (8-52%). Despite the differences in treatment, we found no difference in short-term morbidity between the centres. Adjusted mortality showed independent risk contribution of gestational age, birth weight, ductal ligation, and perinatal centre. Using benchmarking as a tool identified inter-centre differences. In these four perinatal centres, the factors that explained the differences in patent ductus arteriosus treatment are quite complex. Timing, choice of medication, and dosing are probably important determinants for successful patent ductus arteriosus closure.

Optimization of rotational speed and hydraulic retention time of a rotational sponge reactor for sewage treatment.

PubMed

Hewawasam, Choolaka; Matsuura, Norihisa; Takimoto, Yuya; Hatamoto, Masashi; Yamaguchi, Takashi

2018-05-26

A rotational sponge (RS) reactor was proposed as an alternative sewage treatment process. Prior to the application of an RS reactor for sewage treatment, this study evaluated reactor performance with regard to organic removal, nitrification, and nitrogen removal and sought to optimize the rotational speed and hydraulic retention time (HRT) of the system. RS reactor obtained highest COD removal, nitrification, and nitrogen removal efficiencies of 91%, 97%, and 65%, respectively. For the optimization, response surface methodology (RSM) was employed and optimum conditions of rotational speed and HRT were 18 rounds per hour and 4.8 h, respectively. COD removal, nitrification, and nitrogen removal efficiencies at the optimum conditions were 85%, 85%, and 65%, respectively. Corresponding removal rates at optimum conditions were 1.6 kg-COD m -3 d -1 , 0.3 kg-NH 4 + -N m -3 d -1 , and 0.12 kg-N m -3 d -1 . Microbial community analysis revealed an abundance of nitrifying and denitrifying bacteria in the reactor, which contributed to nitrification and nitrogen removal. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling the role of information and limited optimal treatment on disease prevalence.

PubMed

Kumar, Anuj; Srivastava, Prashant K; Takeuchi, Yasuhiro

2017-02-07

Disease outbreaks induce behavioural changes in healthy individuals to avoid contracting infection. We first propose a compartmental model which accounts for the effect of individual's behavioural response due to information of the disease prevalence. It is assumed that the information is growing as a function of infective population density that saturates at higher density of infective population and depends on active educational and social programmes. Model analysis has been performed and the global stability of equilibrium points is established. Further, choosing the treatment (a pharmaceutical intervention) and the effect of information (a non-pharmaceutical intervention) as controls, an optimal control problem is formulated to minimize the cost and disease fatality. In the cost functional, the nonlinear effect of controls is accounted. Analytical characterization of optimal control paths is done with the help of Pontryagin's Maximum Principle. Numerical findings suggest that if only control via information is used, it is effective and economical for early phase of disease spread whereas treatment works well for long term control except for initial phase. Furthermore, we observe that the effect of information induced behavioural response plays a crucial role in the absence of pharmaceutical control. Moreover, comprehensive use of both the control interventions is more effective than any single applied control policy and it reduces the number of infective individuals and minimizes the economic cost generated from disease burden and applied controls. Thus, the combined effect of both the control policies is found more economical during the entire epidemic period whereas the implementation of a single policy is not found economically viable. Copyright © 2016 Elsevier Ltd. All rights reserved.

Factor Analysis of Therapist-Identified Treatment Targets in Community-Based Children's Mental Health.

PubMed

Love, Allison R; Okado, Izumi; Orimoto, Trina E; Mueller, Charles W

2018-01-01

The present study used exploratory and confirmatory factor analyses to identify underlying latent factors affecting variation in community therapists' endorsement of treatment targets. As part of a statewide practice management program, therapist completed monthly reports of treatment targets (up to 10 per month) for a sample of youth (n = 790) receiving intensive in-home therapy. Nearly 75 % of youth were diagnosed with multiple co-occurring disorders. Five factors emerged: Disinhibition, Societal Rules Evasion, Social Engagement Deficits, Emotional Distress, and Management of Biodevelopmental Outcomes. Using logistic regression, primary diagnosis predicted therapist selection of Disinhibition and Emotional Distress targets. Client age predicted endorsement of Societal Rules Evasion targets. Practice-to-research implications are discussed.

The Voice of the Patient Methodology: A Novel Mixed-Methods Approach to Identifying Treatment Goals for Men with Prostate Cancer.

PubMed

Saigal, Christopher S; Lambrechts, Sylvia I; Seenu Srinivasan, V; Dahan, Ely

2017-06-01

Many guidelines advocate the use of shared decision making for men with newly diagnosed prostate cancer. Decision aids can facilitate the process of shared decision making. Implicit in this approach is the idea that physicians understand which elements of treatment matter to patients. Little formal work exists to guide physicians or developers of decision aids in identifying these attributes. We use a mixed-methods technique adapted from marketing science, the 'Voice of the Patient', to describe and identify treatment elements of value for men with localized prostate cancer. We conducted semi-structured interviews with 30 men treated for prostate cancer in the urology clinic of the West Los Angeles Veteran Affairs Medical Center. We used a qualitative analysis to generate themes in patient narratives, and a quantitative approach, agglomerative hierarchical clustering, to identify attributes of treatment that were most relevant to patients making decisions about prostate cancer. We identified five 'traditional' prostate cancer treatment attributes: sexual dysfunction, bowel problems, urinary problems, lifespan, and others' opinions. We further identified two novel treatment attributes: a treatment's ability to validate a sense of proactivity and the need for an incision (separate from risks of surgery). Application of a successful marketing technique, the 'Voice of the Customer', in a clinical setting elicits non-obvious attributes that highlight unique patient decision-making concerns. Use of this method in the development of decision aids may result in more effective decision support.

How cognitive assessment through clinical neurophysiology may help optimize chronic alcoholism treatment.

PubMed

Campanella, S; Petit, G; Verbanck, P; Kornreich, C; Noel, X

2011-07-01

Alcohol dependence constitutes a serious worldwide public health problem. The last few decades have seen many pharmacological studies devoted to the improvement of alcoholism treatment. Although psychosocial treatments (e.g. individual or group therapy) have historically been the mainstay of alcoholism treatment, a successful approach for alcohol dependence consists in associating pharmacologic medications with therapy, as 40-70% of patients following only psychosocial therapy typically resume alcohol use within a year of post-detoxification treatment. Nowadays, two main pharmacological options, naltrexone and acomprosate, both approved by the US Food and Drug Administration, are available and seemingly improve on the results yielded by standard techniques employed in the management of alcoholism. However, insufficient data exist to confirm the superiority of one drug over the other, and research is ongoing to determine what type of alcohol-dependent individual benefits the most from using either medication. Available data on the application of both drugs clearly suggest different practical applications. Thus, a fundamental question remains as to how we can identify which alcoholic patients are likely to benefit from the use of naltrexone, acamprosate or both, and which are not. The aim of the present manuscript is to suggest the use of cognitive event-related potentials as an interesting way to identify subgroups of alcoholic patients displaying specific clinical symptoms and cognitive disturbances. We propose that this may help clinicians improve their treatment of alcoholic patients by focusing therapy on individual cognitive disturbances, and by adapting the pharmaceutical approach to the specific needs of the patient. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

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

Kim, Minsun, E-mail: mk688@uw.edu; Stewart, Robert D.; Phillips, Mark H.

2015-11-15

proliferating tumors with T{sub d} less than 10 days, there was no significant increase in tumor BED but the treatment course could be shortened without a loss in tumor BED. The improvement in the tumor mean BED was more pronounced with smaller tumors (p-value = 0.08). Conclusions: Spatiotemporal optimization of patient plans has the potential to significantly improve local tumor control (larger BED/EUD) of patients with a favorable geometry, such as smaller tumors with larger distances between the tumor target and nearby OAR. In patients with a less favorable geometry and for fast growing tumors, plans optimized using spatiotemporal optimization and conventional (spatial-only) optimization are equivalent (negligible differences in tumor BED/EUD). However, spatiotemporal optimization yields shorter treatment courses than conventional spatial-only optimization. Personalized, spatiotemporal optimization of treatment schedules can increase patient convenience and help with the efficient allocation of clinical resources. Spatiotemporal optimization can also help identify a subset of patients that might benefit from nonconventional (large dose per fraction) treatments that are ineligible for the current practice of stereotactic body radiation therapy.« less

Using Cotton Model Simulations to Estimate Optimally Profitable Irrigation Strategies

NASA Astrophysics Data System (ADS)

Mauget, S. A.; Leiker, G.; Sapkota, P.; Johnson, J.; Maas, S.

2011-12-01

In recent decades irrigation pumping from the Ogallala Aquifer has led to declines in saturated thickness that have not been compensated for by natural recharge, which has led to questions about the long-term viability of agriculture in the cotton producing areas of west Texas. Adopting irrigation management strategies that optimize profitability while reducing irrigation waste is one way of conserving the aquifer's water resource. Here, a database of modeled cotton yields generated under drip and center pivot irrigated and dryland production scenarios is used in a stochastic dominance analysis that identifies such strategies under varying commodity price and pumping cost conditions. This database and analysis approach will serve as the foundation for a web-based decision support tool that will help producers identify optimal irrigation treatments under specified cotton price, electricity cost, and depth to water table conditions.

A Screening Tool to Identify Spasticity in Need of Treatment

PubMed Central

Zorowitz, Richard D.; Wein, Theodore H.; Dunning, Kari; Deltombe, Thierry; Olver, John H.; Davé, Shashank J.; Dimyan, Michael A.; Kelemen, John; Pagan, Fernando L.; Evans, Christopher J.; Gillard, Patrick J.; Kissela, Brett M.

2017-01-01

Objective To develop a clinically useful patient-reported screening tool for health care providers to identify patients with spasticity in need of treatment regardless of etiology. Design Eleven spasticity experts participated in a modified Delphi panel and reviewed and revised 2 iterations of a screening tool designed to identify spasticity symptoms and impact on daily function and sleep. Spasticity expert panelists evaluated items pooled from existing questionnaires to gain consensus on the screening tool content. The study also included cognitive interviews of 20 patients with varying spasticity etiologies to determine if the draft screening tool was understandable and relevant to patients with spasticity. Results The Delphi panel reached an initial consensus on 21 of 47 items for the screening tool and determined that the tool should have no more than 11 to 15 items and a 1-month recall period for symptom and impact items. After 2 rounds of review, 13 items were selected and modified by the expert panelists. Most patients (n = 16 [80%]) completed the cognitive interview and interpreted the items as intended. Conclusions Through the use of a Delphi panel and patient interviews, a 13-item spasticity screening tool was developed that will be practical and easy to use in routine clinical practice. PMID:27552355

Patterns of co-occurring addictions, posttraumatic stress disorder, and major depressive disorder in detoxification treatment seekers: Implications for improving detoxification treatment outcomes.

PubMed

Anderson, RaeAnn E; Hruska, Bryce; Boros, Alec P; Richardson, Christopher J; Delahanty, Douglas L

2018-03-01

Poly-substance use and psychiatric comorbidity are common among individuals receiving substance detoxification services. Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are the most common co-occurring psychiatric disorders with substance use disorder (SUD). Current treatment favors a one-size-fits-all approach to treating addiction focusing on one substance or one comorbidity. Research examining patterns of substance use and comorbidities can inform efforts to effectively identify and differentially treat individuals with co-occurring conditions. Using latent class analysis, the current study identified four patterns of PTSD, MDD, and substance use among 375 addiction treatment seekers receiving medically supervised detoxification. The four identified classes were: 1) a PTSD-MDD-Poly SUD class characterized by PTSD and MDD occurring in the context of opioid, cannabis, and tobacco use disorders; 2) an MDD-Poly SUD class characterized by MDD and alcohol, opioid, tobacco, and cannabis use disorders; 3) an alcohol-tobacco class characterized by alcohol and tobacco use disorders; and 4) an opioid-tobacco use disorder class characterized by opioid and tobacco use disorders. The observed classes differed on gender and clinical characteristics including addiction severity, trauma history, and PTSD/MDD symptom severity. The observed classes likely require differing treatment approaches. For example, people in the PTSD-MDD-Poly SUD class would likely benefit from treatment approaches targeting anxiety sensitivity and distress tolerance, while the opioid-tobacco class would benefit from treatments that incorporate motivational interviewing. Appropriate matching of treatment to class could optimize treatment outcomes for polysubstance and comorbid psychiatric treatment seekers. These findings also underscore the importance of well-developed referral networks to optimize outpatient psychotherapy for detoxification treatment-seekers to enhance long

MO-FG-202-05: Identifying Treatment Planning System Errors in IROC-H Phantom Irradiations

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

Kerns, J; Followill, D; Howell, R

Purpose: Treatment Planning System (TPS) errors can affect large numbers of cancer patients receiving radiation therapy. Using an independent recalculation system, the Imaging and Radiation Oncology Core-Houston (IROC-H) can identify institutions that have not sufficiently modelled their linear accelerators in their TPS model. Methods: Linear accelerator point measurement data from IROC-H’s site visits was aggregated and analyzed from over 30 linear accelerator models. Dosimetrically similar models were combined to create “classes”. The class data was used to construct customized beam models in an independent treatment dose verification system (TVS). Approximately 200 head and neck phantom plans from 2012 to 2015more » were recalculated using this TVS. Comparison of plan accuracy was evaluated by comparing the measured dose to the institution’s TPS dose as well as the TVS dose. In cases where the TVS was more accurate than the institution by an average of >2%, the institution was identified as having a non-negligible TPS error. Results: Of the ∼200 recalculated plans, the average improvement using the TVS was ∼0.1%; i.e. the recalculation, on average, slightly outperformed the institution’s TPS. Of all the recalculated phantoms, 20% were identified as having a non-negligible TPS error. Fourteen plans failed current IROC-H criteria; the average TVS improvement of the failing plans was ∼3% and 57% were found to have non-negligible TPS errors. Conclusion: IROC-H has developed an independent recalculation system to identify institutions that have considerable TPS errors. A large number of institutions were found to have non-negligible TPS errors. Even institutions that passed IROC-H criteria could be identified as having a TPS error. Resolution of such errors would improve dose delivery for a large number of IROC-H phantoms and ultimately, patients.« less

Optimizing the management of depression: primary care experience.

PubMed

Cameron, Catherine; Habert, Jeff; Anand, Leena; Furtado, Melissa

2014-12-01

This article is intended to identify some of the most important challenges faced by family physicians when treating MDD and to provide practical solutions. Key issues, reviewed from a primary care view point will include: treating to remission (and not just response), identification of high-risk groups, diagnosis, acute treatment approaches (including pharmacotherapy and the management of related side effects), the use of psychotherapy and somatic therapies, assessment of the adequacy of treatment including the assessment of remission, response measurement, optimal follow-up care throughout the phase of treatment, the key components of patient education and strategies for partial/limited response to the first-line antidepressant (switching, augmentation and combination strategies), how to provide support for improved treatment adherence, and approaches to prevent the recurrence of depressive episodes. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

OptFuels: Fuel treatment optimization

Treesearch

Greg Jones

2011-01-01

Scientists at the USDA Forest Service, Rocky Mountain Research Station, in Missoula, MT, in collaboration with scientists at the University of Montana, are developing a tool to help forest managers prioritize forest fuel reduction treatments. Although several computer models analyze fuels and fire behavior, stand-level effects of fuel treatments, and priority planning...

An optimization model for collection, haul, transfer, treatment and disposal of infectious medical waste: Application to a Greek region.

PubMed

Mantzaras, Gerasimos; Voudrias, Evangelos A

2017-11-01

The objective of this work was to develop an optimization model to minimize the cost of a collection, haul, transfer, treatment and disposal system for infectious medical waste (IMW). The model calculates the optimum locations of the treatment facilities and transfer stations, their design capacities (t/d), the number and capacities of all waste collection, transport and transfer vehicles and their optimum transport path and the minimum IMW management system cost. Waste production nodes (hospitals, healthcare centers, peripheral health offices, private clinics and physicians in private practice) and their IMW production rates were specified and used as model inputs. The candidate locations of the treatment facilities, transfer stations and sanitary landfills were designated, using a GIS-based methodology. Specifically, Mapinfo software with exclusion criteria for non-appropriate areas was used for siting candidate locations for the construction of the treatment plant and calculating the distance and travel time of all possible vehicle routes. The objective function was a non-linear equation, which minimized the total collection, transport, treatment and disposal cost. Total cost comprised capital and operation costs for: (1) treatment plant, (2) waste transfer stations, (3) waste transport and transfer vehicles and (4) waste collection bins and hospital boxes. Binary variables were used to decide whether a treatment plant and/or a transfer station should be constructed and whether a collection route between two or more nodes should be followed. Microsoft excel software was used as installation platform of the optimization model. For the execution of the optimization routine, two completely different software were used and the results were compared, thus, resulting in higher reliability and validity of the results. The first software was Evolver, which is based on the use of genetic algorithms. The second one was Crystal Ball, which is based on Monte Carlo

An Integrated Human/Murine Transcriptome and Pathway Approach To Identify Prenatal Treatments For Down Syndrome.

PubMed

Guedj, Faycal; Pennings, Jeroen LA; Massingham, Lauren J; Wick, Heather C; Siegel, Ashley E; Tantravahi, Umadevi; Bianchi, Diana W

2016-09-02

Anatomical and functional brain abnormalities begin during fetal life in Down syndrome (DS). We hypothesize that novel prenatal treatments can be identified by targeting signaling pathways that are consistently perturbed in cell types/tissues obtained from human fetuses with DS and mouse embryos. We analyzed transcriptome data from fetuses with trisomy 21, age and sex-matched euploid controls, and embryonic day 15.5 forebrains from Ts1Cje, Ts65Dn, and Dp16 mice. The new datasets were compared to other publicly available datasets from humans with DS. We used the human Connectivity Map (CMap) database and created a murine adaptation to identify FDA-approved drugs that can rescue affected pathways. USP16 and TTC3 were dysregulated in all affected human cells and two mouse models. DS-associated pathway abnormalities were either the result of gene dosage specific effects or the consequence of a global cell stress response with activation of compensatory mechanisms. CMap analyses identified 56 molecules with high predictive scores to rescue abnormal gene expression in both species. Our novel integrated human/murine systems biology approach identified commonly dysregulated genes and pathways. This can help to prioritize therapeutic molecules on which to further test safety and efficacy. Additional studies in human cells are ongoing prior to pre-clinical prenatal treatment in mice.

Multi objective genetic algorithm to optimize the local heat treatment of a hardenable aluminum alloy

NASA Astrophysics Data System (ADS)

Piccininni, A.; Palumbo, G.; Franco, A. Lo; Sorgente, D.; Tricarico, L.; Russello, G.

2018-05-01

The continuous research for lightweight components for transport applications to reduce the harmful emissions drives the attention to the light alloys as in the case of Aluminium (Al) alloys, capable to combine low density with high values of the strength-to-weight ratio. Such advantages are partially counterbalanced by the poor formability at room temperature. A viable solution is to adopt a localized heat treatment by laser of the blank before the forming process to obtain a tailored distribution of material properties so that the blank can be formed at room temperature by means of conventional press machines. Such an approach has been extensively investigated for age hardenable alloys, but in the present work the attention is focused on the 5000 series; in particular, the optimization of the deep drawing process of the alloy AA5754 H32 is proposed through a numerical/experimental approach. A preliminary investigation was necessary to correctly tune the laser parameters (focus length, spot dimension) to effectively obtain the annealed state. Optimal process parameters were then obtained coupling a 2D FE model with an optimization platform managed by a multi-objective genetic algorithm. The optimal solution (i.e. able to maximize the LDR) in terms of blankholder force and extent of the annealed region was thus evaluated and validated through experimental trials. A good matching between experimental and numerical results was found. The optimal solution allowed to obtain an LDR of the locally heat treated blank larger than the one of the material either in the wrought condition (H32) either in the annealed condition (H111).

Process optimization of ultrasound-assisted alcoholic-alkaline treatment for granular cold water swelling starches.

PubMed

Zhu, Bo; Liu, Jianli; Gao, Weidong

2017-09-01

This paper reports on the process optimization of ultrasonic assisted alcoholic-alkaline treatment to prepare granular cold water swelling (GCWS) starches. In this work, three statistical approaches such as Plackett-Burman, steepest ascent path analysis and Box-Behnken design were successfully combined to investigate the effects of major treatment process variables including starch concentration, ethanol volume fraction, sodium hydroxide dosage, ultrasonic power and treatment time, and drying operation, that is, vacuum degree and drying time on cold-water solubility. Results revealed that ethanol volume fraction, sodium hydroxide dosage, applied power and ultrasonic treatment time were significant factors that affected the cold-water solubility of GCWS starches. The maximum cold-water solubility was obtained when treated at 400W of applied power for 27.38min. Optimum volume fraction of ethanol and sodium hydroxide dosage were 66.85% and 53.76mL, respectively. The theoretical values (93.87%) and the observed values (93.87%) were in reasonably good agreement and the deviation was less than 1%. Verification and repeated trial results indicated that the ultrasound-assisted alcoholic-alkaline treatment could be successfully used for the preparation of granular cold water swelling starches at room temperatures and had excellent improvement on the cold-water solubility of GCWS starches. Copyright © 2016. Published by Elsevier B.V.

MO-FG-CAMPUS-TeP2-05: Optimizing Stereotactic Radiosurgery Treatment of Multiple Brain Metastasis Lesions with Individualized Rotational Arc Trajectories

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

Dong, P; Xing, L; Ma, L

Purpose: Radiosurgery of multiple (n>4) brain metastasis lesions requires 3–4 noncoplanar VMAT arcs with excessively high monitor units and long delivery time. We investigated whether an improved optimization technique would decrease the needed arc numbers and increase the delivery efficiency, while improving or maintaining the plan quality. Methods: The proposed 4pi arc space optimization algorithm consists of two steps: automatic couch angle selection followed by aperture generation for each arc with optimized control points distribution. We use a greedy algorithm to select the couch angles. Starting from a single coplanar arc plan we search through the candidate noncoplanar arcs tomore » pick a single noncoplanar arc that will bring the best plan quality when added into the existing treatment plan. Each time, only one additional noncoplanar arc is considered making the calculation time tractable. This process repeats itself until desired number of arc is reached. The technique is first evaluated in coplanar arc delivery scheme with testing cases and then applied to noncoplanar treatments of a case with 12 brain metastasis lesions. Results: Clinically acceptable plans are created within minutes. For the coplanar testing cases the algorithm yields singlearc plans with better dose distributions than that of two-arc VMAT, simultaneously with a 12–17% reduction in the delivery time and a 14–21% reduction in MUs. For the treatment of 12 brain mets while Paddick conformity indexes of the two plans were comparable the SCG-optimization with 2 arcs (1 noncoplanar and 1 coplanar) significantly improved the conventional VMAT with 3 arcs (2 noncoplanar and 1 coplanar). Specifically V16 V10 and V5 of the brain were reduced by 11%, 11% and 12% respectively. The beam delivery time was shortened by approximately 30%. Conclusion: The proposed 4pi arc space optimization technique promises to significantly reduce the brain toxicity while greatly improving the treatment

Selective robust optimization: A new intensity-modulated proton therapy optimization strategy

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

Li, Yupeng; Niemela, Perttu; Siljamaki, Sami

2015-08-15

Purpose: To develop a new robust optimization strategy for intensity-modulated proton therapy as an important step in translating robust proton treatment planning from research to clinical applications. Methods: In selective robust optimization, a worst-case-based robust optimization algorithm is extended, and terms of the objective function are selectively computed from either the worst-case dose or the nominal dose. Two lung cancer cases and one head and neck cancer case were used to demonstrate the practical significance of the proposed robust planning strategy. The lung cancer cases had minimal tumor motion less than 5 mm, and, for the demonstration of the methodology,more » are assumed to be static. Results: Selective robust optimization achieved robust clinical target volume (CTV) coverage and at the same time increased nominal planning target volume coverage to 95.8%, compared to the 84.6% coverage achieved with CTV-based robust optimization in one of the lung cases. In the other lung case, the maximum dose in selective robust optimization was lowered from a dose of 131.3% in the CTV-based robust optimization to 113.6%. Selective robust optimization provided robust CTV coverage in the head and neck case, and at the same time improved controls over isodose distribution so that clinical requirements may be readily met. Conclusions: Selective robust optimization may provide the flexibility and capability necessary for meeting various clinical requirements in addition to achieving the required plan robustness in practical proton treatment planning settings.« less

Three-Dimensional Microwave Hyperthermia for Breast Cancer Treatment in a Realistic Environment Using Particle Swarm Optimization.

PubMed

Nguyen, Phong Thanh; Abbosh, Amin; Crozier, Stuart

2017-06-01

In this paper, a technique for noninvasive microwave hyperthermia treatment for breast cancer is presented. In the proposed technique, microwave hyperthermia of patient-specific breast models is implemented using a three-dimensional (3-D) antenna array based on differential beam-steering subarrays to locally raise the temperature of the tumor to therapeutic values while keeping healthy tissue at normal body temperature. This approach is realized by optimizing the excitations (phases and amplitudes) of the antenna elements using the global optimization method particle swarm optimization. The antennae excitation phases are optimized to maximize the power at the tumor, whereas the amplitudes are optimized to accomplish the required temperature at the tumor. During the optimization, the technique ensures that no hotspots exist in healthy tissue. To implement the technique, a combination of linked electromagnetic and thermal analyses using MATLAB and the full-wave electromagnetic simulator is conducted. The technique is tested at 4.2 GHz, which is a compromise between the required power penetration and focusing, in a realistic simulation environment, which is built using a 3-D antenna array of 4 × 6 unidirectional antenna elements. The presented results on very dense 3-D breast models, which have the realistic dielectric and thermal properties, validate the capability of the proposed technique in focusing power at the exact location and volume of tumor even in the challenging cases where tumors are embedded in glands. Moreover, the models indicate the capability of the technique in dealing with tumors at different on- and off-axis locations within the breast with high efficiency in using the microwave power.

SU-F-T-387: A Novel Optimization Technique for Field in Field (FIF) Chestwall Radiation Therapy Using a Single Plan to Improve Delivery Safety and Treatment Planning Efficiency

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

Tabibian, A; Kim, A; Rose, J

Purpose: A novel optimization technique was developed for field-in-field (FIF) chestwall radiotherapy using bolus every other day. The dosimetry was compared to currently used optimization. Methods: The prior five patients treated at our clinic to the chestwall and supraclavicular nodes with a mono-isocentric four-field arrangement were selected for this study. The prescription was 5040 cGy in 28 fractions, 5 mm bolus every other day on the tangent fields, 6 and/or 10 MV x-rays, and multileaf collimation.Novelly, tangents FIF segments were forward planned optimized based on the composite bolus and non-bolus dose distribution simultaneously. The prescription was spilt into 14 fractionsmore » for both bolus and non-bolus tangents. The same segments and monitor units were used for the bolus and non-bolus treatment. The plan was optimized until the desired coverage was achieved, minimized 105% hotspots, and a maximum dose of less than 108%. Each tangential field had less than 5 segments.Comparison plans were generated using FIF optimization with the same dosimetric goals, but using only the non-bolus calculation for FIF optimization. The non-bolus fields were then copied and bolus was applied. The same segments and monitor units were used for the bolus and non-bolus segments. Results: The prescription coverage of the chestwall, as defined by RTOG guidelines, was on average 51.8% for the plans that optimized bolus and non-bolus treatments simultaneous (SB) and 43.8% for the plans optimized to the non-bolus treatments (NB). Chestwall coverage of 90% prescription averaged to 80.4% for SB and 79.6% for NB plans. The volume receiving 105% of the prescription was 1.9% for SB and 0.8% for NB plans on average. Conclusion: Simultaneously optimizing for bolus and non-bolus treatments noticeably improves prescription coverage of the chestwall while maintaining similar hotspots and 90% prescription coverage in comparison to optimizing only to non-bolus treatments.« less

SU-E-T-549: A Combinatorial Optimization Approach to Treatment Planning with Non-Uniform Fractions in Intensity Modulated Proton Therapy

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

Papp, D; Unkelbach, J

2014-06-01

Purpose: Non-uniform fractionation, i.e. delivering distinct dose distributions in two subsequent fractions, can potentially improve outcomes by increasing biological dose to the target without increasing dose to healthy tissues. This is possible if both fractions deliver a similar dose to normal tissues (exploit the fractionation effect) but high single fraction doses to subvolumes of the target (hypofractionation). Optimization of such treatment plans can be formulated using biological equivalent dose (BED), but leads to intractable nonconvex optimization problems. We introduce a novel optimization approach to address this challenge. Methods: We first optimize a reference IMPT plan using standard techniques that deliversmore » a homogeneous target dose in both fractions. The method then divides the pencil beams into two sets, which are assigned to either fraction one or fraction two. The total intensity of each pencil beam, and therefore the physical dose, remains unchanged compared to the reference plan. The objectives are to maximize the mean BED in the target and to minimize the mean BED in normal tissues, which is a quadratic function of the pencil beam weights. The optimal reassignment of pencil beams to one of the two fractions is formulated as a binary quadratic optimization problem. A near-optimal solution to this problem can be obtained by convex relaxation and randomized rounding. Results: The method is demonstrated for a large arteriovenous malformation (AVM) case treated in two fractions. The algorithm yields a treatment plan, which delivers a high dose to parts of the AVM in one of the fractions, but similar doses in both fractions to the normal brain tissue adjacent to the AVM. Using the approach, the mean BED in the target was increased by approximately 10% compared to what would have been possible with a uniform reference plan for the same normal tissue mean BED.« less

High-risk populations identified in Childhood Cancer Survivor Study investigations: implications for risk-based surveillance.

PubMed

Hudson, Melissa M; Mulrooney, Daniel A; Bowers, Daniel C; Sklar, Charles A; Green, Daniel M; Donaldson, Sarah S; Oeffinger, Kevin C; Neglia, Joseph P; Meadows, Anna T; Robison, Leslie L

2009-05-10

Childhood cancer survivors often experience complications related to cancer and its treatment that may adversely affect quality of life and increase the risk of premature death. The purpose of this manuscript is to review how data derived from Childhood Cancer Survivor Study (CCSS) investigations have facilitated identification of childhood cancer survivor populations at high risk for specific organ toxicity and secondary carcinogenesis and how this has informed clinical screening practices. Articles previously published that used the resource of the CCSS to identify risk factors for specific organ toxicity and subsequent cancers were reviewed and results summarized. CCSS investigations have characterized specific groups to be at highest risk of morbidity related to endocrine and reproductive dysfunction, pulmonary toxicity, cerebrovascular injury, neurologic and neurosensory sequelae, and subsequent neoplasms. Factors influencing risk for specific outcomes related to the individual survivor (eg, sex, race/ethnicity, age at diagnosis, attained age), sociodemographic status (eg, education, household income, health insurance) and cancer history (eg, diagnosis, treatment, time from diagnosis) have been consistently identified. These CCSS investigations that clarify risk for treatment complications related to specific treatment modalities, cumulative dose exposures, and sociodemographic factors identify profiles of survivors at high risk for cancer-related morbidity who deserve heightened surveillance to optimize outcomes after treatment for childhood cancer.

Dental treatment for people with cystic fibrosis.

PubMed

Harrington, N; Barry, P J; Barry, S M

2016-06-01

To describe the nature and consequences of the multi-system genetic condition cystic fibrosis with a view to ensuring optimal dental treatment planning for these patients. A literature search was conducted to identify the key medical and dental manifestations of cystic fibrosis. These findings are discussed and utilised to create recommendations for treatment planning in patients with cystic fibrosis for the practising dental practitioner. Cystic fibrosis is a complex, lethal, multisystem autosomal recessive disorder resulting from mutations on chromosome 7 which result in dysfunction of an ion channel that sits on epithelial surfaces. Respiratory disease remains the leading cause of mortality. Survival has greatly increased in recent decades secondary to improved treatment and specialist care. Specific dental manifestations of the disease may result from the condition itself or complications of treatment. Modification of patient management may be necessary to provide optimum patient care. The pathophysiology and clinical manifestations are relevant to practicing dental practitioners and inform recommendations to be utilised to ensure optimal treatment planning for these patients.

Exploiting a new electrochemical sensor for biofilm monitoring and water treatment optimization.

PubMed

Pavanello, Giovanni; Faimali, Marco; Pittore, Massimiliano; Mollica, Angelo; Mollica, Alessandro; Mollica, Alfonso

2011-02-01

Bacterial biofilm development is a serious problem in many fields, and the existing biofilm monitoring sensors often turn out to be inadequate. In this perspective, a new sensor (ALVIM) has been developed, exploiting the natural marine and freshwater biofilms electrochemical activity, proportional to surface covering. The results presented in this work, obtained testing the ALVIM system both in laboratory and in an industrial environment, show that the sensor gives a fast and accurate response to biofilm growth, and that this response can be used to optimize cleaning treatments inside pipelines. Compared to the existing biofilm sensors, the proposed system show significant technological innovations, higher sensitivity and precision. © 2010 Elsevier Ltd. All rights reserved.

Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms

NASA Astrophysics Data System (ADS)

Babier, Aaron; Boutilier, Justin J.; Sharpe, Michael B.; McNiven, Andrea L.; Chan, Timothy C. Y.

2018-05-01

We developed and evaluated a novel inverse optimization (IO) model to estimate objective function weights from clinical dose-volume histograms (DVHs). These weights were used to solve a treatment planning problem to generate ‘inverse plans’ that had similar DVHs to the original clinical DVHs. Our methodology was applied to 217 clinical head and neck cancer treatment plans that were previously delivered at Princess Margaret Cancer Centre in Canada. Inverse plan DVHs were compared to the clinical DVHs using objective function values, dose-volume differences, and frequency of clinical planning criteria satisfaction. Median differences between the clinical and inverse DVHs were within 1.1 Gy. For most structures, the difference in clinical planning criteria satisfaction between the clinical and inverse plans was at most 1.4%. For structures where the two plans differed by more than 1.4% in planning criteria satisfaction, the difference in average criterion violation was less than 0.5 Gy. Overall, the inverse plans were very similar to the clinical plans. Compared with a previous inverse optimization method from the literature, our new inverse plans typically satisfied the same or more clinical criteria, and had consistently lower fluence heterogeneity. Overall, this paper demonstrates that DVHs, which are essentially summary statistics, provide sufficient information to estimate objective function weights that result in high quality treatment plans. However, as with any summary statistic that compresses three-dimensional dose information, care must be taken to avoid generating plans with undesirable features such as hotspots; our computational results suggest that such undesirable spatial features were uncommon. Our IO-based approach can be integrated into the current clinical planning paradigm to better initialize the planning process and improve planning efficiency. It could also be embedded in a knowledge-based planning or adaptive radiation therapy framework to

Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms.

PubMed

Babier, Aaron; Boutilier, Justin J; Sharpe, Michael B; McNiven, Andrea L; Chan, Timothy C Y

2018-05-10

We developed and evaluated a novel inverse optimization (IO) model to estimate objective function weights from clinical dose-volume histograms (DVHs). These weights were used to solve a treatment planning problem to generate 'inverse plans' that had similar DVHs to the original clinical DVHs. Our methodology was applied to 217 clinical head and neck cancer treatment plans that were previously delivered at Princess Margaret Cancer Centre in Canada. Inverse plan DVHs were compared to the clinical DVHs using objective function values, dose-volume differences, and frequency of clinical planning criteria satisfaction. Median differences between the clinical and inverse DVHs were within 1.1 Gy. For most structures, the difference in clinical planning criteria satisfaction between the clinical and inverse plans was at most 1.4%. For structures where the two plans differed by more than 1.4% in planning criteria satisfaction, the difference in average criterion violation was less than 0.5 Gy. Overall, the inverse plans were very similar to the clinical plans. Compared with a previous inverse optimization method from the literature, our new inverse plans typically satisfied the same or more clinical criteria, and had consistently lower fluence heterogeneity. Overall, this paper demonstrates that DVHs, which are essentially summary statistics, provide sufficient information to estimate objective function weights that result in high quality treatment plans. However, as with any summary statistic that compresses three-dimensional dose information, care must be taken to avoid generating plans with undesirable features such as hotspots; our computational results suggest that such undesirable spatial features were uncommon. Our IO-based approach can be integrated into the current clinical planning paradigm to better initialize the planning process and improve planning efficiency. It could also be embedded in a knowledge-based planning or adaptive radiation therapy framework to

EUD-based biological optimization for carbon ion therapy

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

Brüningk, Sarah C., E-mail: sarah.brueningk@icr.ac.uk; Kamp, Florian; Wilkens, Jan J.

2015-11-15

Purpose: Treatment planning for carbon ion therapy requires an accurate modeling of the biological response of each tissue to estimate the clinical outcome of a treatment. The relative biological effectiveness (RBE) accounts for this biological response on a cellular level but does not refer to the actual impact on the organ as a whole. For photon therapy, the concept of equivalent uniform dose (EUD) represents a simple model to take the organ response into account, yet so far no formulation of EUD has been reported that is suitable to carbon ion therapy. The authors introduce the concept of an equivalentmore » uniform effect (EUE) that is directly applicable to both ion and photon therapies and exemplarily implemented it as a basis for biological treatment plan optimization for carbon ion therapy. Methods: In addition to a classical EUD concept, which calculates a generalized mean over the RBE-weighted dose distribution, the authors propose the EUE to simplify the optimization process of carbon ion therapy plans. The EUE is defined as the biologically equivalent uniform effect that yields the same probability of injury as the inhomogeneous effect distribution in an organ. Its mathematical formulation is based on the generalized mean effect using an effect-volume parameter to account for different organ architectures and is thus independent of a reference radiation. For both EUD concepts, quadratic and logistic objective functions are implemented into a research treatment planning system. A flexible implementation allows choosing for each structure between biological effect constraints per voxel and EUD constraints per structure. Exemplary treatment plans are calculated for a head-and-neck patient for multiple combinations of objective functions and optimization parameters. Results: Treatment plans optimized using an EUE-based objective function were comparable to those optimized with an RBE-weighted EUD-based approach. In agreement with previous results from

Enhancing the Effectiveness of Smoking Treatment Research: Conceptual Bases and Progress

PubMed Central

Baker, Timothy B.; Collins, Linda M.; Mermelstein, Robin; Piper, Megan E.; Schlam, Tanya R.; Cook, Jessica W.; Bolt, Daniel M.; Smith, Stevens S.; Jorenby, Douglas E.; Fraser, David; Loh, Wei-Yin; Theobald, Wendy E.; Fiore, Michael C.

2015-01-01

Background and aims A chronic care strategy could potentially enhance the reach and effectiveness of smoking treatment by providing effective interventions for all smokers, including those who are initially unwilling to quit. This paper describes the conceptual bases of a National Cancer Institute-funded research program designed to develop an optimized, comprehensive, chronic care smoking treatment. Methods This research is grounded in three methodological approaches: 1) the Phase-Based Model, which guides the selection of intervention components to be experimentally evaluated for the different phases of smoking treatment (motivation, preparation, cessation, and maintenance); 2) the Multiphase Optimization Strategy (MOST), which guides the screening of intervention components via efficient experimental designs and, ultimately, the assembly of promising components into an optimized treatment package; and 3) pragmatic research methods, such as electronic health record recruitment, that facilitate the efficient translation of research findings into clinical practice. Using this foundation and working in primary care clinics, we conducted three factorial experiments (reported in three accompanying articles) to screen 15 motivation, preparation, cessation, and maintenance phase intervention components for possible inclusion in a chronic care smoking treatment program. Results This research identified intervention components with relatively strong evidence of effectiveness at particular phases of smoking treatment and it demonstrated the efficiency of the MOST approach in terms both of the number of intervention components tested and of the richness of the information yielded. Conclusions A new, synthesized research approach efficiently evaluates multiple intervention components to identify promising components for every phase of smoking treatment. Many intervention components interact with one another, supporting the use of factorial experiments in smoking treatment

A treatment-oriented typology of self-identified hypersexuality referrals.

PubMed

Cantor, James M; Klein, Carolin; Lykins, Amy; Rullo, Jordan E; Thaler, Lea; Walling, Bobbi R

2013-07-01

Men and women have been seeking professional assistance to help control hypersexual urges and behaviors since the nineteenth century. Despite that the literature emphasizes that cases of hypersexuality are highly diverse with regard to clinical presentation and comorbid features, the major models for understanding and treating hypersexuality employ a "one size fits all" approach. That is, rather than identify which problematic behaviors might respond best to which interventions, existing approaches presume or assert without evidence that all cases of hypersexuality (however termed or defined) represent the same underlying problem and merit the same approach to intervention. The present article instead provides a typology of hypersexuality referrals that links individual clinical profiles or symptom clusters to individual treatment suggestions. Case vignettes are provided to illustrate the most common profiles of hypersexuality referral that presented to a large, hospital-based sexual behaviors clinic, including: (1) Paraphilic Hypersexuality, (2) Avoidant Masturbation, (3) Chronic Adultery, (4) Sexual Guilt, (5) the Designated Patient, and (6) better accounted for as a symptom of another condition.

Investigating multi-objective fluence and beam orientation IMRT optimization

NASA Astrophysics Data System (ADS)

Potrebko, Peter S.; Fiege, Jason; Biagioli, Matthew; Poleszczuk, Jan

2017-07-01

Radiation Oncology treatment planning requires compromises to be made between clinical objectives that are invariably in conflict. It would be beneficial to have a ‘bird’s-eye-view’ perspective of the full spectrum of treatment plans that represent the possible trade-offs between delivering the intended dose to the planning target volume (PTV) while optimally sparing the organs-at-risk (OARs). In this work, the authors demonstrate Pareto-aware radiotherapy evolutionary treatment optimization (PARETO), a multi-objective tool featuring such bird’s-eye-view functionality, which optimizes fluence patterns and beam angles for intensity-modulated radiation therapy (IMRT) treatment planning. The problem of IMRT treatment plan optimization is managed as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. To achieve this, PARETO is built around a powerful multi-objective evolutionary algorithm, called Ferret, which simultaneously optimizes multiple fitness functions that encode the attributes of the desired dose distribution for the PTV and OARs. The graphical interfaces within PARETO provide useful information such as: the convergence behavior during optimization, trade-off plots between the competing objectives, and a graphical representation of the optimal solution database allowing for the rapid exploration of treatment plan quality through the evaluation of dose-volume histograms and isodose distributions. PARETO was evaluated for two relatively complex clinical cases, a paranasal sinus and a pancreas case. The end result of each PARETO run was a database of optimal (non-dominated) treatment plans that demonstrated trade-offs between the OAR and PTV fitness functions, which were all equally good in the Pareto-optimal sense (where no one objective can be improved without worsening at least one other). Ferret was able to produce high quality solutions even though a large number of parameters

Coverage-based constraints for IMRT optimization

NASA Astrophysics Data System (ADS)

Mescher, H.; Ulrich, S.; Bangert, M.

2017-09-01

Radiation therapy treatment planning requires an incorporation of uncertainties in order to guarantee an adequate irradiation of the tumor volumes. In current clinical practice, uncertainties are accounted for implicitly with an expansion of the target volume according to generic margin recipes. Alternatively, it is possible to account for uncertainties by explicit minimization of objectives that describe worst-case treatment scenarios, the expectation value of the treatment or the coverage probability of the target volumes during treatment planning. In this note we show that approaches relying on objectives to induce a specific coverage of the clinical target volumes are inevitably sensitive to variation of the relative weighting of the objectives. To address this issue, we introduce coverage-based constraints for intensity-modulated radiation therapy (IMRT) treatment planning. Our implementation follows the concept of coverage-optimized planning that considers explicit error scenarios to calculate and optimize patient-specific probabilities q(\\hat{d}, \\hat{v}) of covering a specific target volume fraction \\hat{v} with a certain dose \\hat{d} . Using a constraint-based reformulation of coverage-based objectives we eliminate the trade-off between coverage and competing objectives during treatment planning. In-depth convergence tests including 324 treatment plan optimizations demonstrate the reliability of coverage-based constraints for varying levels of probability, dose and volume. General clinical applicability of coverage-based constraints is demonstrated for two cases. A sensitivity analysis regarding penalty variations within this planing study based on IMRT treatment planning using (1) coverage-based constraints, (2) coverage-based objectives, (3) probabilistic optimization, (4) robust optimization and (5) conventional margins illustrates the potential benefit of coverage-based constraints that do not require tedious adjustment of target volume objectives.

Identification and Treatment of Pathophysiological Comorbidities of Autism Spectrum Disorder to Achieve Optimal Outcomes

PubMed Central

Frye, Richard E.; Rossignol, Daniel A.

2016-01-01

the optimal treatments for these abnormalities. PMID:27330338

Identifying treatment effect heterogeneity in clinical trials using subpopulations of events: STEPP.

PubMed

Lazar, Ann A; Bonetti, Marco; Cole, Bernard F; Yip, Wai-Ki; Gelber, Richard D

2016-04-01

Investigators conducting randomized clinical trials often explore treatment effect heterogeneity to assess whether treatment efficacy varies according to patient characteristics. Identifying heterogeneity is central to making informed personalized healthcare decisions. Treatment effect heterogeneity can be investigated using subpopulation treatment effect pattern plot (STEPP), a non-parametric graphical approach that constructs overlapping patient subpopulations with varying values of a characteristic. Procedures for statistical testing using subpopulation treatment effect pattern plot when the endpoint of interest is survival remain an area of active investigation. A STEPP analysis was used to explore patterns of absolute and relative treatment effects for varying levels of a breast cancer biomarker, Ki-67, in the phase III Breast International Group 1-98 randomized clinical trial, comparing letrozole to tamoxifen as adjuvant therapy for postmenopausal women with hormone receptor-positive breast cancer. Absolute treatment effects were measured by differences in 4-year cumulative incidence of breast cancer recurrence, while relative effects were measured by the subdistribution hazard ratio in the presence of competing risks using O-E (observed-minus-expected) methodology, an intuitive non-parametric method. While estimation of hazard ratio values based on O-E methodology has been shown, a similar development for the subdistribution hazard ratio has not. Furthermore, we observed that the subpopulation treatment effect pattern plot analysis may not produce results, even with 100 patients within each subpopulation. After further investigation through simulation studies, we observed inflation of the type I error rate of the traditional test statistic and sometimes singular variance-covariance matrix estimates that may lead to results not being produced. This is due to the lack of sufficient number of events within the subpopulations, which we refer to as instability of

SU-E-T-222: Computational Optimization of Monte Carlo Simulation On 4D Treatment Planning Using the Cloud Computing Technology

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

Chow, J

Purpose: This study evaluated the efficiency of 4D lung radiation treatment planning using Monte Carlo simulation on the cloud. The EGSnrc Monte Carlo code was used in dose calculation on the 4D-CT image set. Methods: 4D lung radiation treatment plan was created by the DOSCTP linked to the cloud, based on the Amazon elastic compute cloud platform. Dose calculation was carried out by Monte Carlo simulation on the 4D-CT image set on the cloud, and results were sent to the FFD4D image deformation program for dose reconstruction. The dependence of computing time for treatment plan on the number of computemore » node was optimized with variations of the number of CT image set in the breathing cycle and dose reconstruction time of the FFD4D. Results: It is found that the dependence of computing time on the number of compute node was affected by the diminishing return of the number of node used in Monte Carlo simulation. Moreover, the performance of the 4D treatment planning could be optimized by using smaller than 10 compute nodes on the cloud. The effects of the number of image set and dose reconstruction time on the dependence of computing time on the number of node were not significant, as more than 15 compute nodes were used in Monte Carlo simulations. Conclusion: The issue of long computing time in 4D treatment plan, requiring Monte Carlo dose calculations in all CT image sets in the breathing cycle, can be solved using the cloud computing technology. It is concluded that the optimized number of compute node selected in simulation should be between 5 and 15, as the dependence of computing time on the number of node is significant.« less

Optimization of a Tube Hydroforming Process

NASA Astrophysics Data System (ADS)

Abedrabbo, Nader; Zafar, Naeem; Averill, Ron; Pourboghrat, Farhang; Sidhu, Ranny

2004-06-01

An approach is presented to optimize a tube hydroforming process using a Genetic Algorithm (GA) search method. The goal of the study is to maximize formability by identifying the optimal internal hydraulic pressure and feed rate while satisfying the forming limit diagram (FLD). The optimization software HEEDS is used in combination with the nonlinear structural finite element code LS-DYNA to carry out the investigation. In particular, a sub-region of a circular tube blank is formed into a square die. Compared to the best results of a manual optimization procedure, a 55% increase in expansion was achieved when using the pressure and feed profiles identified by the automated optimization procedure.

Establishment of the Pediatric Obesity Weight Evaluation Registry: A National Research Collaborative for Identifying the Optimal Assessment and Treatment of Pediatric Obesity.

PubMed

Kirk, Shelley; Armstrong, Sarah; King, Eileen; Trapp, Christine; Grow, Mollie; Tucker, Jared; Joseph, Madeline; Liu, Lenna; Weedn, Ashley; Sweeney, Brooke; Fox, Claudia; Fathima, Samreen; Williams, Ronald; Kim, Roy; Stratbucker, William

2017-02-01

Prospective patient registries have been successfully utilized in several disease states with a goal of improving treatment approaches through multi-institutional collaboration. The prevalence of youth with severe obesity is at a historic high in the United States, yet evidence to guide effective weight management is limited. The Pediatric Obesity Weight Evaluation Registry (POWER) was established in 2013 to identify and promote effective intervention strategies for pediatric obesity. Sites in POWER provide multicomponent pediatric weight management (PWM) care for youth with obesity and collect a defined set of demographic and clinical parameters, which they regularly submit to the POWER Data Coordinating Center. A program profile survey was completed by sites to describe characteristics of the respective PWM programs. From January 2014 through December 2015, 26 US sites were enrolled in POWER and had submitted data on 3643 youth with obesity. Ninety-five percent were 6-18 years of age, 54% female, 32% nonwhite, 32% Hispanic, and 59% publicly insured. Over two-thirds had severe obesity. All sites included a medical provider and used weight status in their referral criteria. Other program characteristics varied widely between sites. POWER is an established national registry representing a diverse sample of youth with obesity participating in multicomponent PWM programs across the United States. Using high-quality data collection and a collaborative research infrastructure, POWER aims to contribute to the development of evidence-based guidelines for multicomponent PWM programs.

Optimizing adherence to antiretroviral therapy

PubMed Central

Sahay, Seema; Reddy, K. Srikanth; Dhayarkar, Sampada

2011-01-01

HIV has now become a manageable chronic disease. However, the treatment outcomes may get hampered by suboptimal adherence to ART. Adherence optimization is a concrete reality in the wake of ‘universal access’ and it is imperative to learn lessons from various studies and programmes. This review examines current literature on ART scale up, treatment outcomes of the large scale programmes and the role of adherence therein. Social, behavioural, biological and programme related factors arise in the context of ART adherence optimization. While emphasis is laid on adherence, retention of patients under the care umbrella emerges as a major challenge. An in-depth understanding of patients’ health seeking behaviour and health care delivery system may be useful in improving adherence and retention of patients in care continuum and programme. A theoretical framework to address the barriers and facilitators has been articulated to identify problematic areas in order to intervene with specific strategies. Empirically tested objective adherence measurement tools and approaches to assess adherence in clinical/ programme settings are required. Strengthening of ART programmes would include appropriate policies for manpower and task sharing, integrating traditional health sector, innovations in counselling and community support. Implications for the use of theoretical model to guide research, clinical practice, community involvement and policy as part of a human rights approach to HIV disease is suggested. PMID:22310817

Pain-Coping Traits of Nontraditional Women Athletes: Relevance to Optimal Treatment and Rehabilitation

PubMed Central

Meyers, Michael C.; Higgs, Robert; LeUnes, Arnold D.; Bourgeois, Anthony E.; Laurent, C. Matthew

2015-01-01

Context The primary goal of traditional treatment and rehabilitation programs is to safely return athletes to full functional capacity. Nontraditional activities such as rock climbing or rodeo are typically less training structured and coach structured; individualism, self-determination, and autonomy are more prevalent than observed in athletes in National Collegiate Athletic Association (NCAA)-sponsored sports. The limited research available on nontraditional athletes has provided the athletic trainer little insight into the coping skills and adaptations to stressors that these athletes may bring into the clinical setting, especially among the growing number of women participating in these types of activities. A better understanding of the pain-coping traits of nontraditional competitors would enhance insight and triage procedures while heading off potential athlete-related risk factors in the clinical setting. Objective To quantify and compare pain-coping traits among individual-sport women athletes participating in nontraditional versus traditional NCAA-structured competition, with relevance to optimal treatment and rehabilitation. Design Cross-sectional study. Setting Data collected during each participant's respective group meeting before seasonal activity. Participants or Other Participants A total of 298 athletes involved in either nontraditional, non-NCAA individual sports (n = 152; mean age = 20.2 ± 1.3 years; downhill skiing, martial arts, rock climbing, rodeo, skydiving, telemark skiing) or traditional NCAA sports (n = 146; mean age = 20.3 ± 1.4 years; equestrian, golf, swimming/diving, tennis, track). Main Outcome Measure(s) All participants completed the Sports Inventory for Pain, a sport-specific, self-report instrument that measures pain-coping traits relevant to competition, treatment, and rehabilitation. Trait measures were direct coping, cognitive, catastrophizing, avoidance, body awareness, and total coping response. Data were grouped for

Study Identifies New Lymphoma Treatment Target

Cancer.gov

NCI researchers have identified new therapeutic targets for diffuse large B-cell lymphoma. Drugs that hit these targets are under clinical development and the researchers hope to begin testing them in clinical trials of patients with DLBCL.

Role of functional imaging in treatment plan optimization of stereotactic body radiation therapy for liver cancer.

PubMed

De Bari, Berardino; Jumeau, Raphael; Deantonio, Letizia; Adib, Salim; Godin, Sarah; Zeverino, Michele; Moeckli, Raphael; Bourhis, Jean; Prior, John O; Ozsahin, Mahmut

2016-10-13

We report the first known instance of the clinical use of 99mTc-mebrofenin hepatobiliary scintigraphy (HBS) for the optimization of radiotherapy treatment planning and for the follow-up of acute toxicity in a patient undergoing stereotactic body radiation therapy for hepatocellular carcinoma. In our experience, HBS allowed the identification and the sparing of more functioning liver areas, thus potentially reducing the risk of radiation-induced liver toxicity.

Intensity modulated neutron radiotherapy optimization by photon proxy

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

Snyder, Michael; Hammoud, Ahmad; Bossenberger, Todd

2012-08-15

Purpose: Introducing intensity modulation into neutron radiotherapy (IMNRT) planning has the potential to mitigate some normal tissue complications seen in past neutron trials. While the hardware to deliver IMNRT plans has been in use for several years, until recently the IMNRT planning process has been cumbersome and of lower fidelity than conventional photon plans. Our in-house planning system used to calculate neutron therapy plans allows beam weight optimization of forward planned segments, but does not provide inverse optimization capabilities. Commercial treatment planning systems provide inverse optimization capabilities, but currently cannot model our neutron beam. Methods: We have developed a methodologymore » and software suite to make use of the robust optimization in our commercial planning system while still using our in-house planning system to calculate final neutron dose distributions. Optimized multileaf collimator (MLC) leaf positions for segments designed in the commercial system using a 4 MV photon proxy beam are translated into static neutron ports that can be represented within our in-house treatment planning system. The true neutron dose distribution is calculated in the in-house system and then exported back through the MATLAB software into the commercial treatment planning system for evaluation. Results: The planning process produces optimized IMNRT plans that reduce dose to normal tissue structures as compared to 3D conformal plans using static MLC apertures. The process involves standard planning techniques using a commercially available treatment planning system, and is not significantly more complex than conventional IMRT planning. Using a photon proxy in a commercial optimization algorithm produces IMNRT plans that are more conformal than those previously designed at our center and take much less time to create. Conclusions: The planning process presented here allows for the optimization of IMNRT plans by a commercial treatment

A robust two-stage design identifying the optimal biological dose for phase I/II clinical trials.

PubMed

Zang, Yong; Lee, J Jack

2017-01-15

We propose a robust two-stage design to identify the optimal biological dose for phase I/II clinical trials evaluating both toxicity and efficacy outcomes. In the first stage of dose finding, we use the Bayesian model averaging continual reassessment method to monitor the toxicity outcomes and adopt an isotonic regression method based on the efficacy outcomes to guide dose escalation. When the first stage ends, we use the Dirichlet-multinomial distribution to jointly model the toxicity and efficacy outcomes and pick the candidate doses based on a three-dimensional volume ratio. The selected candidate doses are then seamlessly advanced to the second stage for dose validation. Both toxicity and efficacy outcomes are continuously monitored so that any overly toxic and/or less efficacious dose can be dropped from the study as the trial continues. When the phase I/II trial ends, we select the optimal biological dose as the dose obtaining the minimal value of the volume ratio within the candidate set. An advantage of the proposed design is that it does not impose a monotonically increasing assumption on the shape of the dose-efficacy curve. We conduct extensive simulation studies to examine the operating characteristics of the proposed design. The simulation results show that the proposed design has desirable operating characteristics across different shapes of the underlying true dose-toxicity and dose-efficacy curves. The software to implement the proposed design is available upon request. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Optimal designs for prediction studies of whiplash.

PubMed

Kamper, Steven J; Hancock, Mark J; Maher, Christopher G

2011-12-01

Commentary. To provide guidance for the design and interpretation of predictive studies of whiplash associated disorders (WAD). Numerous studies have sought to define and explain the clinical course and response to treatment of people with WAD. Design of these studies is often suboptimal, which can lead to biased findings and issues with interpreting the results. Literature review and commentary. Predictive studies can be grouped into four broad categories; studies of symptomatic course, studies that aim to identify factors that predict outcome, studies that aim to isolate variables that are causally responsible for outcome, and studies that aim to identify patients who respond best to particular treatments. Although the specific research question will determine the optimal methods, there are a number of generic features that should be incorporated into design of such studies. The aim of these features is to minimize bias, generate adequately precise prognostic estimates, and ensure generalizability of the findings. This paper provides a summary of important considerations in the design, conduct, and reporting of prediction studies in the field of whiplash.

Biological effective dose evaluation in gynaecological brachytherapy: LDR and HDR treatments, dependence on radiobiological parameters, and treatment optimisation.

PubMed

Bianchi, C; Botta, F; Conte, L; Vanoli, P; Cerizza, L

2008-10-01

This study was undertaken to compare the biological efficacy of different high-dose-rate (HDR) and low-dose-rate (LDR) treatments of gynaecological lesions, to identify the causes of possible nonuniformity and to optimise treatment through customised calculation. The study considered 110 patients treated between 2001 and 2006 with external beam radiation therapy and/or brachytherapy with either LDR (afterloader Selectron, (137)Cs) or HDR (afterloader microSelectron Classic, (192)Ir). The treatments were compared in terms of biologically effective dose (BED) to the tumour and to the rectum (linear-quadratic model) by using statistical tests for comparisons between independent samples. The difference between the two treatments was statistically significant in one case only. However, within each technique, we identified considerable nonuniformity in therapeutic efficacy due to differences in fractionation schemes and overall treatment time. To solve this problem, we created a Microsoft Excel spreadsheet allowing calculation of the optimal treatment for each patient: best efficacy (BED(tumour)) without exceeding toxicity threshold (BED(rectum)). The efficacy of a treatment may vary as a result of several factors. Customised radiobiological evaluation is a useful adjunct to clinical evaluation in planning equivalent treatments that satisfy all dosimetric constraints.

Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content

NASA Astrophysics Data System (ADS)

Liao, Kaihua; Zhou, Zhiwen; Lai, Xiaoming; Zhu, Qing; Feng, Huihui

2017-04-01

The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0-20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m-3) than that based on the smallest SDRD (RMSE = 0.034 m3 m-3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE <0.020 m3 m-3) than these based on EFs (-PCA) and Theta (-PCA). The sampling design stratified by the land use was more efficient than the global random method. Forty and 60 sampling sites are needed for stratified sampling and global sampling respectively to make their performances comparable to the best K

Singularities in Optimal Structural Design

NASA Technical Reports Server (NTRS)

Patnaik, S. N.; Guptill, J. D.; Berke, L.

1992-01-01

Singularity conditions that arise during structural optimization can seriously degrade the performance of the optimizer. The singularities are intrinsic to the formulation of the structural optimization problem and are not associated with the method of analysis. Certain conditions that give rise to singularities have been identified in earlier papers, encompassing the entire structure. Further examination revealed more complex sets of conditions in which singularities occur. Some of these singularities are local in nature, being associated with only a segment of the structure. Moreover, the likelihood that one of these local singularities may arise during an optimization procedure can be much greater than that of the global singularity identified earlier. Examples are provided of these additional forms of singularities. A framework is also given in which these singularities can be recognized. In particular, the singularities can be identified by examination of the stress displacement relations along with the compatibility conditions and/or the displacement stress relations derived in the integrated force method of structural analysis.

Singularities in optimal structural design

NASA Technical Reports Server (NTRS)

Patnaik, S. N.; Guptill, J. D.; Berke, L.

1992-01-01

Singularity conditions that arise during structural optimization can seriously degrade the performance of the optimizer. The singularities are intrinsic to the formulation of the structural optimization problem and are not associated with the method of analysis. Certain conditions that give rise to singularities have been identified in earlier papers, encompassing the entire structure. Further examination revealed more complex sets of conditions in which singularities occur. Some of these singularities are local in nature, being associated with only a segment of the structure. Moreover, the likelihood that one of these local singularities may arise during an optimization procedure can be much greater than that of the global singularity identified earlier. Examples are provided of these additional forms of singularities. A framework is also given in which these singularities can be recognized. In particular, the singularities can be identified by examination of the stress displacement relations along with the compatibility conditions and/or the displacement stress relations derived in the integrated force method of structural analysis.

Online total organic carbon (TOC) monitoring for water and wastewater treatment plants processes and operations optimization

NASA Astrophysics Data System (ADS)

Assmann, Céline; Scott, Amanda; Biller, Dondra

2017-08-01

Organic measurements, such as biological oxygen demand (BOD) and chemical oxygen demand (COD) were developed decades ago in order to measure organics in water. Today, these time-consuming measurements are still used as parameters to check the water treatment quality; however, the time required to generate a result, ranging from hours to days, does not allow COD or BOD to be useful process control parameters - see (1) Standard Method 5210 B; 5-day BOD Test, 1997, and (2) ASTM D1252; COD Test, 2012. Online organic carbon monitoring allows for effective process control because results are generated every few minutes. Though it does not replace BOD or COD measurements still required for compliance reporting, it allows for smart, data-driven and rapid decision-making to improve process control and optimization or meet compliances. Thanks to the smart interpretation of generated data and the capability to now take real-time actions, municipal drinking water and wastewater treatment facility operators can positively impact their OPEX (operational expenditure) efficiencies and their capabilities to meet regulatory requirements. This paper describes how three municipal wastewater and drinking water plants gained process insights, and determined optimization opportunities thanks to the implementation of online total organic carbon (TOC) monitoring.

A high-throughput phenotypic screen identifies clofazimine as a potential treatment for cryptosporidiosis

PubMed Central

Jumani, Rajiv S.; Wright, Timothy M.; Chatterjee, Arnab K.; Huston, Christopher D.; Schultz, Peter G.; McNamara, Case W.

2017-01-01

Cryptosporidiosis has emerged as a leading cause of non-viral diarrhea in children under five years of age in the developing world, yet the current standard of care to treat Cryptosporidium infections, nitazoxanide, demonstrates limited and immune-dependent efficacy. Given the lack of treatments with universal efficacy, drug discovery efforts against cryptosporidiosis are necessary to find therapeutics more efficacious than the standard of care. To date, cryptosporidiosis drug discovery efforts have been limited to a few targeted mechanisms in the parasite and whole cell phenotypic screens against small, focused collections of compounds. Using a previous screen as a basis, we initiated the largest known drug discovery effort to identify novel anticryptosporidial agents. A high-content imaging assay for inhibitors of Cryptosporidium parvum proliferation within a human intestinal epithelial cell line was miniaturized and automated to enable high-throughput phenotypic screening against a large, diverse library of small molecules. A screen of 78,942 compounds identified 12 anticryptosporidial hits with sub-micromolar activity, including clofazimine, an FDA-approved drug for the treatment of leprosy, which demonstrated potent and selective in vitro activity (EC50 = 15 nM) against C. parvum. Clofazimine also displayed activity against C. hominis–the other most clinically-relevant species of Cryptosporidium. Importantly, clofazimine is known to accumulate within epithelial cells of the small intestine, the primary site of Cryptosporidium infection. In a mouse model of acute cryptosporidiosis, a once daily dosage regimen for three consecutive days or a single high dose resulted in reduction of oocyst shedding below the limit detectable by flow cytometry. Recently, a target product profile (TPP) for an anticryptosporidial compound was proposed by Huston et al. and highlights the need for a short dosing regimen (< 7 days) and formulations for children < 2 years

Simultaneous delivery time and aperture shape optimization for the volumetric-modulated arc therapy (VMAT) treatment planning problem

NASA Astrophysics Data System (ADS)

Mahnam, Mehdi; Gendreau, Michel; Lahrichi, Nadia; Rousseau, Louis-Martin

2017-07-01

In this paper, we propose a novel heuristic algorithm for the volumetric-modulated arc therapy treatment planning problem, optimizing the trade-off between delivery time and treatment quality. We present a new mixed integer programming model in which the multi-leaf collimator leaf positions, gantry speed, and dose rate are determined simultaneously. Our heuristic is based on column generation; the aperture configuration is modeled in the columns and the dose distribution and time restriction in the rows. To reduce the number of voxels and increase the efficiency of the master model, we aggregate similar voxels using a clustering technique. The efficiency of the algorithm and the treatment quality are evaluated on a benchmark clinical prostate cancer case. The computational results show that a high-quality treatment is achievable using a four-thread CPU. Finally, we analyze the effects of the various parameters and two leaf-motion strategies.

Optimal Duration of Conservative Management Prior to Surgery for Cervical and Lumbar Radiculopathy: A Literature Review

PubMed Central

Alentado, Vincent J.; Lubelski, Daniel; Steinmetz, Michael P.; Benzel, Edward C.; Mroz, Thomas E.

2014-01-01

Study Design Literature review. Objective Since the 1970s, spine surgeons have commonly required 6 weeks of failed conservative treatment prior to considering surgical intervention for various spinal pathologies. It is unclear, however, if this standard has been validated in the literature. The authors review the natural history, outcomes, and cost-effectiveness studies relating to the current standard of 6 weeks of nonoperative care prior to surgery for patients with spinal pathologies. Methods A systematic Medline search from 1953 to 2013 was performed to identify natural history, outcomes, and cost-effectiveness studies relating to the optimal period of conservative management prior to surgical intervention for both cervical and lumbar radiculopathy. Demographic information, operative indications, and clinical outcomes are reviewed for each study. Results A total of 5,719 studies were identified; of these, 13 studies were selected for inclusion. Natural history studies demonstrated that 88% of patients with cervical radiculopathy and 70% of patients with lumbar radiculopathy showed improvement within 4 weeks following onset of symptoms. Outcomes and cost-effectiveness studies supported surgical intervention within 8 weeks of symptom onset for both cervical and lumbar radiculopathy. Conclusions There are limited studies supporting any optimal duration of conservative treatment prior to surgery for cervical and lumbar radiculopathy. Therefore, evidence-based conclusions cannot be made. Based on the available literature, we suggest that an optimal timing for surgery following cervical radiculopathy is within 8 weeks of onset of symptoms. A shorter period of 4 weeks may be appropriate based on natural history studies. Additionally, we found that optimal timing for surgery following lumbar radiculopathy is between 4 and 8 weeks. A prospective study is needed to explicitly identify the optimal duration of conservative therapy prior to surgery so that costs

[Optimization of acupoint application scheme in the treatment of bronchial asthma based on the orthogonal design method].

PubMed

Shi, Kuan; Wu, Wenzhong; Liu, Lanying; Wang, Hesheng; Chen, Dong; Liu, Chengyong; Zhang, Cong

2017-06-12

To study the primary and secondary factors of the allergic history, the frequency of acupoint application and the time of acupoint application in the treatment of bronchial asthma and optimize its scheme. Eighty patients of bronchial asthma were selected as the subjects in the orthogonal trial. The herbal medicines were the empirical formula of acupoint application (prepared at the ratio as 2:2:1:1:1:1:1:1:1 of semen brassicae , rhizome corydalis , unprocessed radix kansui , asarum sieboldii , ephedra , semen lepidii , syzygium aromaticum , cortex cinnamomi and fructus gleditsiae ) and used on bilateral Feishu (BL 13), Xinshu (BL 15), Geshu (BL 17) and Shenshu (BL 23). Firstly, two groups were divided according to allergic history (40 cases with allergic history and 40 cases without allergic history), and then four subgroups were divided on the basis of the two main groups, 10 cases in each one. Through studying three factors and two levels, i.e. allergic history (Factor A:A Ⅰ :with allergic history; A Ⅱ :without allergic history), the frequency of acupoint application (Factor B:B Ⅰ :4 times; B Ⅱ :10 times, in which, in the group of 4-time applications, the application was given once every 10 days; in the group of 10-time applications, the application was given once every 4 days); and the time of application (Factor C:C Ⅰ :4 h; C Ⅱ :8 h), the optimal scheme was screened on the basis of the attack frequency before and after treatment and the score of the asthma quality life questionnaire (AQLQ) before treatment and 6 months after treatment in the patients of each group. ① The orthogonal trial indicated that the best optimal scheme was A Ⅰ B Ⅱ C Ⅰ , meaning the patients with allergic history were treated with acupoint application for 10 times, remained for 4 h. ②Factor B (frequency of acupoint application) and C (time of acpoint application) were the significant influential factors of AQLQ scores (both P <0.05). ③The comparison of the attack

A randomized phase 3 study on the optimization of the combination of bevacizumab with FOLFOX/OXXEL in the treatment of patients with metastatic colorectal cancer-OBELICS (Optimization of BEvacizumab scheduLIng within Chemotherapy Scheme).

PubMed

Avallone, Antonio; Piccirillo, Maria Carmela; Aloj, Luigi; Nasti, Guglielmo; Delrio, Paolo; Izzo, Francesco; Di Gennaro, Elena; Tatangelo, Fabiana; Granata, Vincenza; Cavalcanti, Ernesta; Maiolino, Piera; Bianco, Francesco; Aprea, Pasquale; De Bellis, Mario; Pecori, Biagio; Rosati, Gerardo; Carlomagno, Chiara; Bertolini, Alessandro; Gallo, Ciro; Romano, Carmela; Leone, Alessandra; Caracò, Corradina; de Lutio di Castelguidone, Elisabetta; Daniele, Gennaro; Catalano, Orlando; Botti, Gerardo; Petrillo, Antonella; Romano, Giovanni M; Iaffaioli, Vincenzo R; Lastoria, Secondo; Perrone, Francesco; Budillon, Alfredo

2016-02-08

Despite the improvements in diagnosis and treatment, colorectal cancer (CRC) is the second cause of cancer deaths in both sexes. Therefore, research in this field remains of great interest. The approval of bevacizumab, a humanized anti-vascular endothelial growth factor (VEGF) monoclonal antibody, in combination with a fluoropyrimidine-based chemotherapy in the treatment of metastatic CRC has changed the oncology practice in this disease. However, the efficacy of bevacizumab-based treatment, has thus far been rather modest. Efforts are ongoing to understand the better way to combine bevacizumab and chemotherapy, and to identify valid predictive biomarkers of benefit to avoid unnecessary and costly therapy to nonresponder patients. The BRANCH study in high-risk locally advanced rectal cancer patients showed that varying bevacizumab schedule may impact on the feasibility and efficacy of chemo-radiotherapy. OBELICS is a multicentre, open-label, randomised phase 3 trial comparing in mCRC patients two treatment arms (1:1): standard concomitant administration of bevacizumab with chemotherapy (mFOLFOX/OXXEL regimen) vs experimental sequential bevacizumab given 4 days before chemotherapy, as first or second treatment line. Primary end point is the objective response rate (ORR) measured according to RECIST criteria. A sample size of 230 patients was calculated allowing reliable assessment in all plausible first-second line case-mix conditions, with a 80% statistical power and 2-sided alpha error of 0.05. Secondary endpoints are progression free-survival (PFS), overall survival (OS), toxicity and quality of life. The evaluation of the potential predictive role of several circulating biomarkers (circulating endothelial cells and progenitors, VEGF and VEGF-R SNPs, cytokines, microRNAs, free circulating DNA) as well as the value of the early [(18)F]-Fluorodeoxyglucose positron emission tomography (FDG-PET) response, are the objectives of the traslational project. Overall this

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Optimization of Multicomponent Behavioral and Biobehavioral Interventions for the Prevention and Treatment of HIV/AIDS

PubMed Central

Collins, Linda M.; Kugler, Kari C.; Gwadz, Marya Viorst

2015-01-01

To move society toward an AIDS-free generation, behavioral interventions for prevention and treatment of HIV/AIDS must be not only effective, but also cost-effective, efficient, and readily scalable. The purpose of this article is to introduce to the HIV/AIDS research community the multiphase optimization strategy (MOST), a new methodological framework inspired by engineering principles and designed to develop behavioral interventions that have these important characteristics. Many behavioral interventions comprise multiple components. In MOST, randomized experimentation is conducted to assess the individual performance of each intervention component, and whether its presence/absence/setting has an impact on the performance of other components. This information is used to engineer an intervention that meets a specific optimization criterion, defined a priori in terms of effectiveness, cost, cost-effectiveness, and/or scalability. MOST will enable intervention science to develop a coherent knowledge base about what works and does not work. Ultimately this will improve behavioral interventions systematically and incrementally. PMID:26238037

Optimization of Multicomponent Behavioral and Biobehavioral Interventions for the Prevention and Treatment of HIV/AIDS.

PubMed

Collins, Linda M; Kugler, Kari C; Gwadz, Marya Viorst

2016-01-01

To move society toward an AIDS-free generation, behavioral interventions for prevention and treatment of HIV/AIDS must be not only effective, but also cost-effective, efficient, and readily scalable. The purpose of this article is to introduce to the HIV/AIDS research community the multiphase optimization strategy (MOST), a new methodological framework inspired by engineering principles and designed to develop behavioral interventions that have these important characteristics. Many behavioral interventions comprise multiple components. In MOST, randomized experimentation is conducted to assess the individual performance of each intervention component, and whether its presence/absence/setting has an impact on the performance of other components. This information is used to engineer an intervention that meets a specific optimization criterion, defined a priori in terms of effectiveness, cost, cost-effectiveness, and/or scalability. MOST will enable intervention science to develop a coherent knowledge base about what works and does not work. Ultimately this will improve behavioral interventions systematically and incrementally.

Development, optimization and evaluation of curcumin loaded biodegradable crosslinked gelatin film for the effective treatment of periodontitis.

PubMed

Chauhan, Sheetal; Bansal, Monika; Khan, Gayasuddin; Yadav, Sarita K; Singh, Ashish K; Prakash, Pradyot; Mishra, Brahmeshwar

2018-07-01

Aim of the present study was to prepare curcumin (CUR) loaded biodegradable crosslinked gelatin (GE) film to alleviate the existing shortcomings in the treatment of periodontitis. Gelatin film was optimized to provide anticipated mucoadhesive strength, mechanical properties, folding endurance, and prolonged drug release over treatment duration, for successful application in the periodontitis. The film was developed by using solvent casting technique and "Design of Experiments" approach was employed for evaluating the influence of independent variables on dependent response variables. Solid-state characterization of the film was performed by FTIR, XRD, and SEM. Further, prepared formulations were evaluated for drug content uniformity, surface pH, folding endurance, swelling index, mechanical strength, mucoadhesive strength, in vitro biodegradation, and in vitro drug release behavior. Solid state characterization of the formulation showed that CUR is physico-chemically compatible with other excipients and CUR was entrapped in an amorphous form inside the smooth and uniform film. The optimized film showed degree of crosslinking 51.04 ± 2.4, swelling index 138.10 ± 1.25, and folding endurance 270 ± 3 with surface pH around 7.0. Crosslinker concentrations positively affected swelling index and biodegradation of film due to altered matrix density of the polymer. Results of in vitro drug release demonstrated the capability of the developed film for efficiently delivering CUR in a sustained manner up to 7 days. The developed optimized film could be considered as a promising delivery strategy to administer medicament locally into the periodontal pockets for the safe and efficient management of periodontitis.

Online stochastic optimization of radiotherapy patient scheduling.

PubMed

Legrain, Antoine; Fortin, Marie-Andrée; Lahrichi, Nadia; Rousseau, Louis-Martin

2015-06-01

The effective management of a cancer treatment facility for radiation therapy depends mainly on optimizing the use of the linear accelerators. In this project, we schedule patients on these machines taking into account their priority for treatment, the maximum waiting time before the first treatment, and the treatment duration. We collaborate with the Centre Intégré de Cancérologie de Laval to determine the best scheduling policy. Furthermore, we integrate the uncertainty related to the arrival of patients at the center. We develop a hybrid method combining stochastic optimization and online optimization to better meet the needs of central planning. We use information on the future arrivals of patients to provide an accurate picture of the expected utilization of resources. Results based on real data show that our method outperforms the policies typically used in treatment centers.

Using Geographical Information Systems to Identify Populations in Need of Improved Accessibility to Antivenom Treatment for Snakebite Envenoming in Costa Rica

PubMed Central

Hansson, Erik; Sasa, Mahmood; Mattisson, Kristoffer; Robles, Arodys; Gutiérrez, José María

2013-01-01

Introduction Snakebite accidents are an important health problem in rural areas of tropical countries worldwide, including Costa Rica, where most bites are caused by the pit-viper Bothrops asper. The treatment of these potentially fatal accidents is based on the timely administration of specific antivenom. In many regions of the world, insufficient health care systems and lack of antivenom in remote and poor areas where snakebites are common, means that efficient treatment is unavailable for many snakebite victims, leading to unnecessary mortality and morbidity. In this study, geographical information systems (GIS) were used to identify populations in Costa Rica with a need of improved access to antivenom treatment: those living in areas with a high risk of snakebites and long time to reach antivenom treatment. Method/Principal Findings Populations living in areas with high risk of snakebites were identified using two approaches: one based on the district-level reported incidence, and another based on mapping environmental factors favoring B. asper presence. Time to reach treatment using ambulance was estimated using cost surface analysis, thereby enabling adjustment of transportation speed by road availability and quality, topography and land use. By mapping populations in high risk of snakebites and the estimated time to treatment, populations with need of improved treatment access were identified. Conclusion/Significance This study demonstrates the usefulness of GIS for improving treatment of snakebites. By mapping reported incidence, risk factors, location of existing treatment resources, and the time estimated to reach these for at-risk populations, rational allocation of treatment resources is facilitated. PMID:23383352

Using geographical information systems to identify populations in need of improved accessibility to antivenom treatment for snakebite envenoming in Costa Rica.

PubMed

Hansson, Erik; Sasa, Mahmood; Mattisson, Kristoffer; Robles, Arodys; Gutiérrez, José María

2013-01-01

Snakebite accidents are an important health problem in rural areas of tropical countries worldwide, including Costa Rica, where most bites are caused by the pit-viper Bothrops asper. The treatment of these potentially fatal accidents is based on the timely administration of specific antivenom. In many regions of the world, insufficient health care systems and lack of antivenom in remote and poor areas where snakebites are common, means that efficient treatment is unavailable for many snakebite victims, leading to unnecessary mortality and morbidity. In this study, geographical information systems (GIS) were used to identify populations in Costa Rica with a need of improved access to antivenom treatment: those living in areas with a high risk of snakebites and long time to reach antivenom treatment. Populations living in areas with high risk of snakebites were identified using two approaches: one based on the district-level reported incidence, and another based on mapping environmental factors favoring B. asper presence. Time to reach treatment using ambulance was estimated using cost surface analysis, thereby enabling adjustment of transportation speed by road availability and quality, topography and land use. By mapping populations in high risk of snakebites and the estimated time to treatment, populations with need of improved treatment access were identified. This study demonstrates the usefulness of GIS for improving treatment of snakebites. By mapping reported incidence, risk factors, location of existing treatment resources, and the time estimated to reach these for at-risk populations, rational allocation of treatment resources is facilitated.

SU-F-J-105: Towards a Novel Treatment Planning Pipeline Delivering Pareto- Optimal Plans While Enabling Inter- and Intrafraction Plan Adaptation

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

Kontaxis, C; Bol, G; Lagendijk, J

2016-06-15

Purpose: To develop a new IMRT treatment planning methodology suitable for the new generation of MR-linear accelerator machines. The pipeline is able to deliver Pareto-optimal plans and can be utilized for conventional treatments as well as for inter- and intrafraction plan adaptation based on real-time MR-data. Methods: A Pareto-optimal plan is generated using the automated multicriterial optimization approach Erasmus-iCycle. The resulting dose distribution is used as input to the second part of the pipeline, an iterative process which generates deliverable segments that target the latest anatomical state and gradually converges to the prescribed dose. This process continues until a certainmore » percentage of the dose has been delivered. Under a conventional treatment, a Segment Weight Optimization (SWO) is then performed to ensure convergence to the prescribed dose. In the case of inter- and intrafraction adaptation, post-processing steps like SWO cannot be employed due to the changing anatomy. This is instead addressed by transferring the missing/excess dose to the input of the subsequent fraction. In this work, the resulting plans were delivered on a Delta4 phantom as a final Quality Assurance test. Results: A conventional static SWO IMRT plan was generated for two prostate cases. The sequencer faithfully reproduced the input dose for all volumes of interest. For the two cases the mean relative dose difference of the PTV between the ideal input and sequenced dose was 0.1% and −0.02% respectively. Both plans were delivered on a Delta4 phantom and passed the clinical Quality Assurance procedures by achieving 100% pass rate at a 3%/3mm gamma analysis. Conclusion: We have developed a new sequencing methodology capable of online plan adaptation. In this work, we extended the pipeline to support Pareto-optimal input and clinically validated that it can accurately achieve these ideal distributions, while its flexible design enables inter- and intrafraction plan

A Requirements-Driven Optimization Method for Acoustic Treatment Design

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.

2016-01-01

Acoustic treatment designers have long been able to target specific noise sources inside turbofan engines. Facesheet porosity and cavity depth are key design variables of perforate-over-honeycomb liners that determine levels of noise suppression as well as the frequencies at which suppression occurs. Layers of these structures can be combined to create a robust attenuation spectrum that covers a wide range of frequencies. Looking to the future, rapidly-emerging additive manufacturing technologies are enabling new liners with multiple degrees of freedom, and new adaptive liners with variable impedance are showing promise. More than ever, there is greater flexibility and freedom in liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. The subject of this paper is an analytical method that derives the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground.

Patient-derived multicellular tumor spheroids towards optimized treatment for patients with hepatocellular carcinoma.

PubMed

Song, Yeonhwa; Kim, Jin-Sun; Kim, Se-Hyuk; Park, Yoon Kyung; Yu, Eunsil; Kim, Ki-Hun; Seo, Eul-Ju; Oh, Heung-Bum; Lee, Han Chu; Kim, Kang Mo; Seo, Haeng Ran

2018-05-25

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and has poor prognosis. Specially, patients with HCC usually have poor tolerance of systemic chemotherapy, because HCCs develop from chronically damaged tissue that contains considerable inflammation, fibrosis, and cirrhosis. Since HCC exhibits highly heterogeneous molecular characteristics, a proper in vitro system is required for the study of HCC pathogenesis. To this end, we have established two new hepatitis B virus (HBV) DNA-secreting HCC cell lines from infected patients. Based on these two new HCC cell lines, we have developed chemosensitivity assays for patient-derived multicellular tumor spheroids (MCTSs) in order to select optimized anti-cancer drugs to provide more informative data for clinical drug application. To monitor the effect of the interaction of cancer cells and stromal cells in MCTS, we used a 3D co-culture model with patient-derived HCC cells and stromal cells from human hepatic stellate cells, human fibroblasts, and human umbilical vein endothelial cells to facilitate screening for optimized cancer therapy. To validate our system, we performed a comparison of chemosensitivity of the three culture systems, which are monolayer culture system, tumor spheroids, and MCTSs of patient-derived cells, to sorafenib, 5-fluorouracil, and cisplatin, as these compounds are typically standard therapy for advanced HCC in South Korea. In summary, these findings suggest that the MCTS culture system is the best methodology for screening for optimized treatment for each patients with HCC, because tumor spheroids not only mirror the 3D cellular context of the tumors but also exhibit therapeutically relevant pathophysiological gradients and heterogeneity of in vivo tumors.

Identifying factors for optimal development of health-related websites: a delphi study among experts and potential future users.

PubMed

Schneider, Francine; van Osch, Liesbeth; de Vries, Hein

2012-02-14

The Internet has become a popular medium for offering tailored and targeted health promotion programs to the general public. However, suboptimal levels of program use in the target population limit the public health impact of these programs. Optimizing program development is considered as one of the main processes to increase usage rates. To distinguish factors potentially related to optimal development of health-related websites by involving both experts and potential users. By considering and incorporating the opinions of experts and potential users in the development process, involvement in the program is expected to increase, consequently resulting in increased appreciation, lower levels of attrition, and higher levels of sustained use. We conducted a systematic three-round Delphi study through the Internet. Both national and international experts (from the fields of health promotion, health psychology, e-communication, and technical Web design) and potential users were invited via email to participate. During this study an extensive list of factors potentially related to optimal development of health-related websites was identified, by focusing on factors related to layout, general and risk information provision, questionnaire use, additional services, and ease of use. Furthermore, we assessed the extent to which experts and potential users agreed on the importance of these factors. Differences as well as similarities among experts and potentials users were deduced. In total, 20 of 62 contacted experts participated in the first round (32% response rate); 60 of 200 contacted experts (30% response rate) and 210 potential users (95% response rate) completed the second-round questionnaire, and 32 of 60 contacted experts completed the third round (53% response rate). Results revealed important factors consented upon by experts and potential users (eg, ease of use, clear structure, and detailed health information provision), as well as differences regarding

Treatment of an actual slaughterhouse wastewater by integration of biological and advanced oxidation processes: Modeling, optimization, and cost-effectiveness analysis.

PubMed

Bustillo-Lecompte, Ciro Fernando; Mehrvar, Mehrab

2016-11-01

Biological and advanced oxidation processes are combined to treat an actual slaughterhouse wastewater (SWW) by a sequence of an anaerobic baffled reactor, an aerobic activated sludge reactor, and a UV/H2O2 photoreactor with recycle in continuous mode at laboratory scale. In the first part of this study, quadratic modeling along with response surface methodology are used for the statistical analysis and optimization of the combined process. The effects of the influent total organic carbon (TOC) concentration, the flow rate, the pH, the inlet H2O2 concentration, and their interaction on the overall treatment efficiency, CH4 yield, and H2O2 residual in the effluent of the photoreactor are investigated. The models are validated at different operating conditions using experimental data. Maximum TOC and total nitrogen (TN) removals of 91.29 and 86.05%, respectively, maximum CH4 yield of 55.72%, and minimum H2O2 residual of 1.45% in the photoreactor effluent were found at optimal operating conditions. In the second part of this study, continuous distribution kinetics is applied to establish a mathematical model for the degradation of SWW as a function of time. The agreement between model predictions and experimental values indicates that the proposed model could describe the performance of the combined anaerobic-aerobic-UV/H2O2 processes for the treatment of SWW. In the final part of the study, the optimized combined anaerobic-aerobic-UV/H2O2 processes with recycle were evaluated using a cost-effectiveness analysis to minimize the retention time, the electrical energy consumption, and the overall incurred treatment costs required for the efficient treatment of slaughterhouse wastewater effluents. Copyright © 2016 Elsevier Ltd. All rights reserved.

Heat Treatment Optimization and Properties Correlation for H11-Type Hot-Work Tool Steel

NASA Astrophysics Data System (ADS)

Podgornik, B.; Puš, G.; Žužek, B.; Leskovšek, V.; Godec, M.

2018-02-01

The aim of this research was to determine the effect of vacuum-heat-treatment process parameters on the material properties and their correlations for low-Si-content AISI H11-type hot-work tool steel using a single Circumferentially Notched and fatigue Pre-cracked Tensile Bar (CNPTB) test specimen. The work was also focused on the potential of the proposed approach for designing advanced tempering diagrams and optimizing the vacuum heat treatment and design of forming tools. The results show that the CNPTB specimen allows a simultaneous determination and correlation of multiple properties for hot-work tool steels, with the compression and bending strength both increasing with hardness, and the strain-hardening exponent and bending strain increasing with the fracture toughness. On the other hand, the best machinability and surface quality of the hardened hot-work tool steel are obtained for hardness values between 46 and 50 HRC and a fracture toughness below 60 MPa√m.

Heat Treatment Optimization and Properties Correlation for H11-Type Hot-Work Tool Steel

NASA Astrophysics Data System (ADS)

Podgornik, B.; Puš, G.; Žužek, B.; Leskovšek, V.; Godec, M.

2017-12-01

The aim of this research was to determine the effect of vacuum-heat-treatment process parameters on the material properties and their correlations for low-Si-content AISI H11-type hot-work tool steel using a single Circumferentially Notched and fatigue Pre-cracked Tensile Bar (CNPTB) test specimen. The work was also focused on the potential of the proposed approach for designing advanced tempering diagrams and optimizing the vacuum heat treatment and design of forming tools. The results show that the CNPTB specimen allows a simultaneous determination and correlation of multiple properties for hot-work tool steels, with the compression and bending strength both increasing with hardness, and the strain-hardening exponent and bending strain increasing with the fracture toughness. On the other hand, the best machinability and surface quality of the hardened hot-work tool steel are obtained for hardness values between 46 and 50 HRC and a fracture toughness below 60 MPa√m.

[Possibilities of treatment optimization in children and adolescents with epilepsy and disturbances of emotion and volition (disphoria)].

PubMed

Popov, Yu V; Yakovleva, Yu A; Semenova, S V

To optimize the treatment of dysphoriain children and adolescents in regard to sex and disease severity. Seventy children and adolescents (boys - 45, girls - 25), aged from 6 to 18 years, with different forms of epilepsy and emotion and dysphoric disturbances were studied using CPRS andGCIscales Depending on dysphoria severity, patients were stratified into three groups: mild (n=19 (27.1%), moderate (n=27 (38.6%)) and severe (n=24 (34.3%)). Dysphoric disorders were significantly more prevalent in boys, hostility and aggression were characteristic of boys as well. These facts impactedtreatment options. Neuroleptics were more frequently used in boys (35.5%) compared to girls(16%).Mild dysphoria didn't require additional treatment besides AED in 78,4%. In 75% cases of moderate dysphoria,systemic treatment with neuroleptics for 6 months was necessary. One-time recommendations for neuroleptic treatment were made in all three groups with the prevalence in a groupof children with severe and moderate dysphoria.

Optimal Cut-Off Points on the Health Anxiety Inventory, Illness Attitude Scales and Whiteley Index to Identify Severe Health Anxiety

PubMed Central

Hedman, Erik; Lekander, Mats; Ljótsson, Brjánn; Lindefors, Nils; Rück, Christian; Andersson, Gerhard; Andersson, Erik

2015-01-01

Background Health anxiety can be viewed as a dimensional phenomenon where severe health anxiety in form of DSM-IV hypochondriasis represents a cut-off where the health anxiety becomes clinically significant. Three of the most reliable and used self-report measures of health anxiety are the Health Anxiety Inventory (HAI), the Illness Attitude Scales (IAS) and the Whiteley Index (WI). Identifying the optimal cut-offs for classification of presence of a diagnosis of severe health anxiety on these measures has several advantages in clinical and research settings. The aim of this study was therefore to investigate the HAI, IAS and WI as proximal diagnostic instruments for severe health anxiety defined as DSM-IV hypochondriasis. Methods We investigated sensitivity, specificity and predictive value on the HAI, IAS and WI using a total of 347 adult participants of whom 158 had a diagnosis of severe health anxiety, 97 had obsessive-compulsive disorder and 92 were healthy non-clinical controls. Diagnostic assessments were conducted using the Anxiety Disorder Interview Schedule. Results Optimal cut-offs for identifying a diagnosis of severe health anxiety was 67 on the HAI, 47 on the IAS, and 5 on the WI. Sensitivity and specificity were high, ranging from 92.6 to 99.4%. Positive and negative predictive values ranged from 91.6 to 99.4% using unadjusted prevalence rates. Conclusions The HAI, IAS and WI have very good properties as diagnostic indicators of severe health anxiety and can be used as cost-efficient proximal estimates of the diagnosis. PMID:25849477

Optimal management of immune-related adverse events resulting from treatment with immune checkpoint inhibitors: a review and update.

PubMed

Nagai, Hiroki; Muto, Manabu

2018-06-01

Over the last two decades, molecular-targeted agents have become mainstream treatment for many types of malignancies and have improved the overall survival of patients. However, most patients eventually develop resistance to these targeted therapies. Recently, immunotherapies such as immune checkpoint inhibitors have revolutionized the treatment paradigm for many types of malignancies. Immune checkpoint inhibitors have been approved for treatment of melanoma, non-small cell lung cancer, renal cell carcinoma, head and neck squamous cell carcinoma, Hodgkin's lymphoma, bladder cancer and gastric cancer. However, oncologists have been faced with immune-related adverse events caused by immune checkpoint inhibitors; these are generally mild but can be fatal in some cases. Because immune checkpoint inhibitors have distinct toxicity profiles from those of chemotherapy or targeted therapy, many oncologists are not familiar with the principles for optimal management of immune-related adverse events, which require early recognition and appropriate treatment without delay. To achieve this, oncologists must educate patients and health-care workers, develop checklists of appropriate tests for immune-related adverse events and collaborate closely with organ specialists. Clinical questions that remain include whether immune checkpoint inhibitors should be administered to patients with autoimmune disease and whether patients for whom immune-related adverse events lead to delays in immunotherapy should be retreated. In addition, the predicted use of combination immunotherapies in the near future means that oncologists will face a higher incidence and severity of immune-related adverse events. This review provides an overview of the optimal management of immune-related adverse events attributed to immune checkpoint inhibitors.