Delayed gadolinium-enhanced MRI of the fibrocartilage disc of the temporomandibular joint – a feasibility study

PubMed Central

Pittschieler, Elisabeth; Szomolanyi, Pavol; Schmid-Schwap, Martina; Weber, Michael; Egerbacher, Monika; Traxler, Hannes; Trattnig, Siegfried

2014-01-01

Objective To 1) test the feasibility of delayed Gadolinium-Enhanced Magnetic Resonance Imaging of Cartilage (dGEMRIC) at 3 T in the temporomandibular joint (TMJ) and 2) to determine the optimal delay for measurements of the TMJ disc after i.v. contrast agent (CA) administration. Design MRI of the right and left TMJ of six asymptomatic volunteers was performed at 3 T using a dedicated coil. 2D inversion recovery (2D-IR) sequences were performed at 4 time points covering 120 minutes and 3D gradient-echo (3D GRE) dual flip-angle sequences were performed at 14 time points covering 130 minutes after the administration of 0.2 mmol/kg of Gd-diethylenetriamine pentaacetic acid ion (Gd-DTPA)2-, i.e., 0.4 mL of Magnevist™ per kg body weight. Pair-wise tests were used to assess differences between pre-and post-contrast T1 values. Results 2D-IR sequences showed a statistically significant drop (p < 0.001) in T1 values after i.v. CA administration. The T1 drop of 50% was reached 60 minutes after bolus injection in the TMJ disc. The 3D GRE dual flip-angle sequences confirmed these results and show plateau of T1 after 60 minutes. Conclusions T1(Gd) maps calculated from dGEMRIC data allow in vivo assessment of the fibrocartilage disc of the TMJ. The recommended measurement time for dGEMRIC in the TMJ after i.v. CA administration is from 60 to 120 minutes. PMID:25131629

Direct comparison of intra-articular versus intravenous delayed gadolinium-enhanced MRI of hip joint cartilage.

PubMed

Zilkens, Christoph; Miese, Falk; Kim, Young-Jo; Jäger, Marcus; Mamisch, Tallal C; Hosalkar, Harish; Antoch, Gerald; Krauspe, Rüdiger; Bittersohl, Bernd

2014-01-01

To investigate the potential of delayed gadolinium-enhanced magnetic resonance imaging in cartilage (dGEMRIC) after intra-articular (ia) contrast agent administration at 3 Tesla (T), a paired study comparing intravenous (iv) dGEMRIC (standard) with ia-dGEMRIC was performed. Thirty-five symptomatic patients with suspected cartilage damage underwent ia- and iv-dGEMRIC. MRI was performed with a 3T system wherein the interval between both measurements was 2 weeks. For iv-dGEMRIC, FDA approved Gd-DOTA(-) was injected intravenously 45 min before the MRI scan. For ia-dGEMRIC, 10-20 mL of a 2 mM solution of Gd- DOTA(-) was injected under fluoroscopic guidance 30 min before the MRI scan. Both ia- and iv-dGEMRIC demonstrated the typical T1Gd pattern in hip joint cartilage with increasing values toward the superior regions in acetabular cartilage reflecting the higher glycosaminoglycan (GAG) content in the main weight-bearing area. Correlation analysis revealed a moderate correlation between both techniques (r = 0.439, P-value < 0.001), whereas the T1Gd values for iv-dGEMRIC were significantly higher than those for ia-dGEMRIC. This corresponds with the Bland-Altman plot analysis, which revealed a systemic bias (higher T1Gd values after iv gadolinium application) of ∼70 ms. Ia-dGEMRIC was able to reveal the characteristic T1Gd pattern in hip joint cartilage confirming the sensitivity of ia-dGEMRIC for GAG. In addition, there was a significant correlation between iv-dGEMRIC and ia-dGEMRIC. However, the T1Gd values after ia contrast media application were significantly lower than those after iv application that has to be considered for future studies. Copyright © 2013 Wiley Periodicals, Inc.

Delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) of cadaveric shoulders: comparison of contrast dynamics in hyaline and fibrous cartilage after intraarticular gadolinium injection.

PubMed

Wiener, E; Hodler, J; Pfirrmann, C W A

2009-01-01

Delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) is a novel method to investigate cartilaginous and fibrocartilaginous structures. To investigate the contrast dynamics in hyaline and fibrous cartilage of the glenohumeral joint after intraarticular injection of gadopentetate dimeglumine. Transverse T(1) maps were acquired on a 1.5T scanner before and after intraarticular injection of 2.0 mmol/l gadopentetate dimeglumine in five cadaveric shoulders using a dual flip angle three-dimensional gradient echo (3D-GRE) sequence. The acquisition time for the T(1) maps was 5 min 5 s for the whole shoulder. Measurements were repeated every 15 min over 2.5 hours. Regions of interest (ROIs) covering the glenoid cartilage and the labrum were drawn to assess the temporal evolution of the relaxation parameters. T(1) of unenhanced hyaline cartilage of the glenoid was 568+/-34 ms. T(1) of unenhanced fibrous cartilage of the labrum was 552+/-38 ms. Significant differences (P=0.002 and 0.03) in the relaxation parameters were already measurable after 15 min. After 2 to 2.5 hours, hyaline and fibrous cartilage still demonstrated decreasing relaxation parameters, with a larger range of the T(1)(Gd) values in fibrous cartilage. T(1) and triangle Delta R(1) values of hyaline and fibrous cartilage after 2.5 hours were 351+/-16 ms and 1.1+/-0.09 s(-1), and 332+/-31 ms and 1.2+/-0.1 s(-1), respectively. A significant decrease in T(1)(Gd) was found 15 min after intraarticular contrast injection. Contrast accumulation was faster in hyaline than in fibrous cartilage. After 2.5 hours, contrast accumulation showed a higher rate of decrease in hyaline cartilage, but neither hyaline nor fibrous cartilage had reached equilibrium.

Low Field Squid MRI Devices, Components and Methods

NASA Technical Reports Server (NTRS)

Hahn, Inseob (Inventor); Penanen, Konstantin I. (Inventor); Eom, Byeong H. (Inventor)

2013-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

Low Field Squid MRI Devices, Components and Methods

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor); Eom, Byeong H. (Inventor); Hahn, Inseob (Inventor)

2014-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

Low field SQUID MRI devices, components and methods

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor); Eom, Byeong H. (Inventor); Hahn, Inseob (Inventor)

2011-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

Low field SQUID MRI devices, components and methods

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor); Eom, Byeong H (Inventor); Hahn, Inseob (Inventor)

2010-01-01

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

In vitro determination of biomechanical properties of human articular cartilage in osteoarthritis using multi-parametric MRI

NASA Astrophysics Data System (ADS)

Juras, Vladimir; Bittsansky, Michal; Majdisova, Zuzana; Szomolanyi, Pavol; Sulzbacher, Irene; Gäbler, Stefan; Stampfl, Jürgen; Schüller, Georg; Trattnig, Siegfried

2009-03-01

The objective of this study was to evaluate the correlations between MR parameters and the biomechanical properties of naturally degenerated human articular cartilage. Human cartilage explants from the femoral condyles of patients who underwent total knee replacement were evaluated on a micro-imaging system at 3 T. To quantify glycosaminoglycan (GAG) content, delayed gadolinium-enhanced MRI of the cartilage (dGEMRIC) was used. T2 maps were created by using multi-echo, multi-slice spin echo sequences with six echoes: 15, 30, 45, 60, 75, and 90 ms. Data for apparent diffusion constant (ADC) maps were obtained from pulsed gradient spin echo (PGSE) sequences with five b-values: 10.472, 220.0, 627.0, 452.8, 724.5, and 957.7. MR parameters were correlated with mechanical parameters (instantaneous ( I) and equilibrium ( Eq) modulus and relaxation time ( τ)), and the OA stage of each cartilage specimen was determined by histological evaluation of hematoxylin-eosin stained slices. For some parameters, a high correlation was found: the correlation of T1Gd vs Eq ( r = 0.8095), T1Gd vs I/ Eq ( r = -0.8441) and T1Gd vs τ ( r = 0.8469). The correlation of T2 and ADC with selected biomechanical parameters was not statistically significant. In conclusion, GAG content measured by dGEMRIC is highly related to the selected biomechanical properties of naturally degenerated articular cartilage. In contrast, T2 and ADC were unable to estimate these properties. The results of the study imply that some MR parameters can non-invasively predict the biomechanical properties of degenerated articular cartilage.

Quantitative rotating frame relaxometry methods in MRI.

PubMed

Gilani, Irtiza Ali; Sepponen, Raimo

2016-06-01

Macromolecular degeneration and biochemical changes in tissue can be quantified using rotating frame relaxometry in MRI. It has been shown in several studies that the rotating frame longitudinal relaxation rate constant (R1ρ ) and the rotating frame transverse relaxation rate constant (R2ρ ) are sensitive biomarkers of phenomena at the cellular level. In this comprehensive review, existing MRI methods for probing the biophysical mechanisms that affect the rotating frame relaxation rates of the tissue (i.e. R1ρ and R2ρ ) are presented. Long acquisition times and high radiofrequency (RF) energy deposition into tissue during the process of spin-locking in rotating frame relaxometry are the major barriers to the establishment of these relaxation contrasts at high magnetic fields. Therefore, clinical applications of R1ρ and R2ρ MRI using on- or off-resonance RF excitation methods remain challenging. Accordingly, this review describes the theoretical and experimental approaches to the design of hard RF pulse cluster- and adiabatic RF pulse-based excitation schemes for accurate and precise measurements of R1ρ and R2ρ . The merits and drawbacks of different MRI acquisition strategies for quantitative relaxation rate measurement in the rotating frame regime are reviewed. In addition, this review summarizes current clinical applications of rotating frame MRI sequences. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Advanced MRI Methods for Assessment of Chronic Liver Disease

PubMed Central

Taouli, Bachir; Ehman, Richard L.; Reeder, Scott B.

2010-01-01

MRI plays an increasingly important role for assessment of patients with chronic liver disease. MRI has numerous advantages, including lack of ionizing radiation and the possibility of performing multiparametric imaging. With recent advances in technology, advanced MRI methods such as diffusion-, perfusion-weighted MRI, MR elastography, chemical shift based fat-water separation and MR spectroscopy can now be applied to liver imaging. We will review the respective roles of these techniques for assessment of chronic liver disease. PMID:19542391

A Novel Marker Based Method to Teeth Alignment in MRI

NASA Astrophysics Data System (ADS)

Luukinen, Jean-Marc; Aalto, Daniel; Malinen, Jarmo; Niikuni, Naoko; Saunavaara, Jani; Jääsaari, Päivi; Ojalammi, Antti; Parkkola, Riitta; Soukka, Tero; Happonen, Risto-Pekka

2018-04-01

Magnetic resonance imaging (MRI) can precisely capture the anatomy of the vocal tract. However, the crowns of teeth are not visible in standard MRI scans. In this study, a marker-based teeth alignment method is presented and evaluated. Ten patients undergoing orthognathic surgery were enrolled. Supraglottal airways were imaged preoperatively using structural MRI. MRI visible markers were developed, and they were attached to maxillary teeth and corresponding locations on the dental casts. Repeated measurements of intermarker distances in MRI and in a replica model was compared using linear regression analysis. Dental cast MRI and corresponding caliper measurements did not differ significantly. In contrast, the marker locations in vivo differed somewhat from the dental cast measurements likely due to marker placement inaccuracies. The markers were clearly visible in MRI and allowed for dental models to be aligned to head and neck MRI scans.

The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI Methods

PubMed Central

Jack, Clifford R.; Bernstein, Matt A.; Fox, Nick C.; Thompson, Paul; Alexander, Gene; Harvey, Danielle; Borowski, Bret; Britson, Paula J.; Whitwell, Jennifer L.; Ward, Chadwick; Dale, Anders M.; Felmlee, Joel P.; Gunter, Jeffrey L.; Hill, Derek L.G.; Killiany, Ron; Schuff, Norbert; Fox-Bosetti, Sabrina; Lin, Chen; Studholme, Colin; DeCarli, Charles S.; Krueger, Gunnar; Ward, Heidi A.; Metzger, Gregory J.; Scott, Katherine T.; Mallozzi, Richard; Blezek, Daniel; Levy, Joshua; Debbins, Josef P.; Fleisher, Adam S.; Albert, Marilyn; Green, Robert; Bartzokis, George; Glover, Gary; Mugler, John; Weiner, Michael W.

2008-01-01

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimer's disease. Magnetic resonance imaging (MRI), (18F)-fluorode-oxyglucose positron emission tomography (FDG PET), urine serum, and cerebrospinal fluid (CSF) biomarkers, as well as clinical/psychometric assessments are acquiredat multiple time points. All data will be cross-linked and made available to the general scientific community. The purpose of this report is to describe the MRI methods employed in ADNI. The ADNI MRI core established specifications thatguided protocol development. A major effort was devoted toevaluating 3D T1-weighted sequences for morphometric analyses. Several options for this sequence were optimized for the relevant manufacturer platforms and then compared in a reduced-scale clinical trial. The protocol selected for the ADNI study includes: back-to-back 3D magnetization prepared rapid gradient echo (MP-RAGE) scans; B1-calibration scans when applicable; and an axial proton density-T2 dual contrast (i.e., echo) fast spin echo/turbo spin echo (FSE/TSE) for pathology detection. ADNI MRI methods seek to maximize scientific utility while minimizing the burden placed on participants. The approach taken in ADNI to standardization across sites and platforms of the MRI protocol, postacquisition corrections, and phantom-based monitoring of all scanners could be used as a model for other multisite trials. PMID:18302232

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

PubMed Central

Despotović, Ivana

2015-01-01

Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation. PMID:25945121

EEG-Informed fMRI: A Review of Data Analysis Methods

PubMed Central

Abreu, Rodolfo; Leal, Alberto; Figueiredo, Patrícia

2018-01-01

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest. PMID:29467634

[4D-MRI using the synchronized sampling method (SSM)].

PubMed

Shimada, Yasuhiro; Fujimoto, Ichirou; Takemoto, Hironori; Takano, Sayoko; Masaki, Shinobu; Honda, Kiyoshi; Takeo, Kazuhiro

2002-12-01

A synchronized sampling method (SSM) was developed for the study of voluntary movements by combining the electrocardiographic (ECG) gating method with an external triggering device, and four-dimensional magnetic resonance imaging (4D-MRI) at a rate of 30 frames per second was accomplished by volumetric imaging with the SSM. This method was first applied to the motion imaging of articulatory organs during repetitions of a Japanese five-vowel sequence, and the dynamic change in vocal tract area function was demonstrated with sufficient temporal resolution. This paper describes the methodology, applicability, and limitations of 4D-MRI with the SSM.

Sodium MRI: Methods and applications

PubMed Central

Madelin, Guillaume; Lee, Jae-Seung; Regatte, Ravinder R.; Jerschow, Alexej

2014-01-01

Sodium NMR spectroscopy and MRI have become popular in recent years through the increased availability of high-field MRI scanners, advanced scanner hardware and improved methodology. Sodium MRI is being evaluated for stroke and tumor detection, for breast cancer studies, and for the assessment of osteoarthritis and muscle and kidney functions, to name just a few. In this article, we aim to present an up-to-date review of the theoretical background, the methodology, the challenges and limitations, and current and potential new applications of sodium MRI. PMID:24815363

MRI-based methods for quantification of the cerebral metabolic rate of oxygen

PubMed Central

Rodgers, Zachary B; Detre, John A

2016-01-01

The brain depends almost entirely on oxidative metabolism to meet its significant energy requirements. As such, the cerebral metabolic rate of oxygen (CMRO2) represents a key measure of brain function. Quantification of CMRO2 has helped elucidate brain functional physiology and holds potential as a clinical tool for evaluating neurological disorders including stroke, brain tumors, Alzheimer’s disease, and obstructive sleep apnea. In recent years, a variety of magnetic resonance imaging (MRI)-based CMRO2 quantification methods have emerged. Unlike positron emission tomography – the current “gold standard” for measurement and mapping of CMRO2 – MRI is non-invasive, relatively inexpensive, and ubiquitously available in modern medical centers. All MRI-based CMRO2 methods are based on modeling the effect of paramagnetic deoxyhemoglobin on the magnetic resonance signal. The various methods can be classified in terms of the MRI contrast mechanism used to quantify CMRO2: T2*, T2′, T2, or magnetic susceptibility. This review article provides an overview of MRI-based CMRO2 quantification techniques. After a brief historical discussion motivating the need for improved CMRO2 methodology, current state-of-the-art MRI-based methods are critically appraised in terms of their respective tradeoffs between spatial resolution, temporal resolution, and robustness, all of critical importance given the spatially heterogeneous and temporally dynamic nature of brain energy requirements. PMID:27089912

A new method in accelerating PROPELLER MRI.

PubMed

Li, Bing Keong; D'Arcy, Michael; Weber, Ewald; Crozier, Stuart

2008-01-01

In this work, a new method has been proposed to accelerate the PROPELLER MRI operation. The proposed method uses a rotary phased array coil and a new method in acquiring the k-space strips and preparing the complete k-space trajectories data set. It is numerically shown that for a 12 strips PROPELLER MR brain imaging sequence, the operation time can be reduced by four folds, with no apparent loss in the image quality.

The Effect of Intra-articular Injection of Autologous Microfragmented Fat Tissue on Proteoglycan Synthesis in Patients with Knee Osteoarthritis

PubMed Central

Borić, Igor; Rod, Eduard; Jeleč, Željko; Radić, Andrej; Vrdoljak, Trpimir; Skelin, Andrea; Trbojević-Akmačić, Irena; Plečko, Mihovil; Primorac, Dragan

2017-01-01

Osteoarthritis (OA) is one of the leading musculoskeletal disorders in the adult population. It is associated with cartilage damage triggered by the deterioration of the extracellular matrix tissue. The present study explores the effect of intra-articular injection of autologous microfragmented adipose tissue to host chondrocytes and cartilage proteoglycans in patients with knee OA. A prospective, non-randomized, interventional, single-center, open-label clinical trial was conducted from January 2016 to April 2017. A total of 17 patients were enrolled in the study, and 32 knees with osteoarthritis were assessed. Surgical intervention (lipoaspiration) followed by tissue processing and intra-articular injection of the final microfragmented adipose tissue product into the affected knee(s) was performed in all patients. Patients were assessed for visual analogue scale (VAS), delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and immunoglobulin G (IgG) glycans at the baseline, three, six and 12 months after the treatment. Magnetic resonance sequence in dGEMRIC due to infiltration of the anionic, negatively charged contrast gadopentetate dimeglumine (Gd-DTPA2−) into the cartilage indicated that the contents of cartilage glycosaminoglycans significantly increased in specific areas of the treated knee joint. In addition, dGEMRIC consequently reflected subsequent changes in the mechanical axis of the lower extremities. The results of our study indicate that the use of autologous and microfragmented adipose tissue in patients with knee OA (measured by dGEMRIC MRI) increased glycosaminoglycan (GAG) content in hyaline cartilage, which is in line with observed VAS and clinical results. PMID:29027984

A hybrid method for classifying cognitive states from fMRI data.

PubMed

Parida, S; Dehuri, S; Cho, S-B; Cacha, L A; Poznanski, R R

2015-09-01

Functional magnetic resonance imaging (fMRI) makes it possible to detect brain activities in order to elucidate cognitive-states. The complex nature of fMRI data requires under-standing of the analyses applied to produce possible avenues for developing models of cognitive state classification and improving brain activity prediction. While many models of classification task of fMRI data analysis have been developed, in this paper, we present a novel hybrid technique through combining the best attributes of genetic algorithms (GAs) and ensemble decision tree technique that consistently outperforms all other methods which are being used for cognitive-state classification. Specifically, this paper illustrates the combined effort of decision-trees ensemble and GAs for feature selection through an extensive simulation study and discusses the classification performance with respect to fMRI data. We have shown that our proposed method exhibits significant reduction of the number of features with clear edge classification accuracy over ensemble of decision-trees.

fMRI capture of auditory hallucinations: Validation of the two-steps method.

PubMed

Leroy, Arnaud; Foucher, Jack R; Pins, Delphine; Delmaire, Christine; Thomas, Pierre; Roser, Mathilde M; Lefebvre, Stéphanie; Amad, Ali; Fovet, Thomas; Jaafari, Nemat; Jardri, Renaud

2017-10-01

Our purpose was to validate a reliable method to capture brain activity concomitant with hallucinatory events, which constitute frequent and disabling experiences in schizophrenia. Capturing hallucinations using functional magnetic resonance imaging (fMRI) remains very challenging. We previously developed a method based on a two-steps strategy including (1) multivariate data-driven analysis of per-hallucinatory fMRI recording and (2) selection of the components of interest based on a post-fMRI interview. However, two tests still need to be conducted to rule out critical pitfalls of conventional fMRI capture methods before this two-steps strategy can be adopted in hallucination research: replication of these findings on an independent sample and assessment of the reliability of the hallucination-related patterns at the subject level. To do so, we recruited a sample of 45 schizophrenia patients suffering from frequent hallucinations, 20 schizophrenia patients without hallucinations and 20 matched healthy volunteers; all participants underwent four different experiments. The main findings are (1) high accuracy in reporting unexpected sensory stimuli in an MRI setting; (2) good detection concordance between hypothesis-driven and data-driven analysis methods (as used in the two-steps strategy) when controlled unexpected sensory stimuli are presented; (3) good agreement of the two-steps method with the online button-press approach to capture hallucinatory events; (4) high spatial consistency of hallucinatory-related networks detected using the two-steps method on two independent samples. By validating the two-steps method, we advance toward the possible transfer of such technology to new image-based therapies for hallucinations. Hum Brain Mapp 38:4966-4979, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

An Automated Method for Identifying Artifact in Independent Component Analysis of Resting-State fMRI

PubMed Central

Bhaganagarapu, Kaushik; Jackson, Graeme D.; Abbott, David F.

2013-01-01

An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available. PMID:23847511

Methods and utility of EEG-fMRI in epilepsy

PubMed Central

Lemieux, Louis; Chaudhary, Umair Javaid

2015-01-01

Brain activity data in general and more specifically in epilepsy can be represented as a matrix that includes measures of electrophysiology, anatomy and behaviour. Each of these sub-matrices has a complex interaction depending upon the brain state i.e., rest, cognition, seizures and interictal periods. This interaction presents significant challenges for interpretation but also potential for developing further insights into individual event types. Successful treatments in epilepsy hinge on unravelling these complexities, and also on the sensitivity and specificity of methods that characterize the nature and localization of underlying physiological and pathological networks. Limitations of pharmacological and surgical treatments call for refinement and elaboration of methods to improve our capability to localise the generators of seizure activity and our understanding of the neurobiology of epilepsy. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI), by potentially circumventing some of the limitations of EEG in terms of sensitivity, can allow the mapping of haemodynamic networks over the entire brain related to specific spontaneous and triggered epileptic events in humans, and thereby provide new localising information. In this work we review the published literature, and discuss the methods and utility of EEG-fMRI in localising the generators of epileptic activity. We draw on our experience and that of other groups, to summarise the spectrum of information provided by an increasing number of EEG-fMRI case-series, case studies and group studies in patients with epilepsy, for its potential role to elucidate epileptic generators and networks. We conclude that EEG-fMRI provides a multidimensional view that contributes valuable clinical information to localize the epileptic focus with potential important implications for the surgical treatment of some patients with drug-resistant epilepsy, and insights into the resting state and

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.

PubMed

Sauwen, N; Acou, M; Van Cauter, S; Sima, D M; Veraart, J; Maes, F; Himmelreich, U; Achten, E; Van Huffel, S

2016-01-01

Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

[Fusion of MRI, fMRI and intraoperative MRI data. Methods and clinical significance exemplified by neurosurgical interventions].

PubMed

Moche, M; Busse, H; Dannenberg, C; Schulz, T; Schmitgen, A; Trantakis, C; Winkler, D; Schmidt, F; Kahn, T

2001-11-01

The aim of this work was to realize and clinically evaluate an image fusion platform for the integration of preoperative MRI and fMRI data into the intraoperative images of an interventional MRI system with a focus on neurosurgical procedures. A vertically open 0.5 T MRI scanner was equipped with a dedicated navigation system enabling the registration of additional imaging modalities (MRI, fMRI, CT) with the intraoperatively acquired data sets. These merged image data served as the basis for interventional planning and multimodal navigation. So far, the system has been used in 70 neurosurgical interventions (13 of which involved image data fusion--requiring 15 minutes extra time). The augmented navigation system is characterized by a higher frame rate and a higher image quality as compared to the system-integrated navigation based on continuously acquired (near) real time images. Patient movement and tissue shifts can be immediately detected by monitoring the morphological differences between both navigation scenes. The multimodal image fusion allowed a refined navigation planning especially for the resection of deeply seated brain lesions or pathologies close to eloquent areas. Augmented intraoperative orientation and instrument guidance improve the safety and accuracy of neurosurgical interventions.

MRI-Based Computed Tomography Metal Artifact Correction Method for Improving Proton Range Calculation Accuracy

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

Park, Peter C.; Schreibmann, Eduard; Roper, Justin

2015-03-15

Purpose: Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. Methods and Materials: The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR.more » Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. Results: The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. Conclusions: Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts.« less

An Adaptive MR-CT Registration Method for MRI-guided Prostate Cancer Radiotherapy

PubMed Central

Zhong, Hualiang; Wen, Ning; Gordon, James; Elshaikh, Mohamed A; Movsas, Benjamin; Chetty, Indrin J.

2015-01-01

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ/cm3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during

An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy

NASA Astrophysics Data System (ADS)

Zhong, Hualiang; Wen, Ning; Gordon, James J.; Elshaikh, Mohamed A.; Movsas, Benjamin; Chetty, Indrin J.

2015-04-01

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm-3, and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume

A Metal-Free Method for Producing MRI Contrast at Amyloid-Beta

PubMed Central

Hilt, Silvia; Tang, Tang; Walton, Jeffrey H.; Budamagunta, Madhu; Maezawa, Izumi; Kálai, Tamás; Hideg, Kálmán; Singh, Vikrant; Wulff, Heike; Gong, Qizhi; Jin, Lee-Way; Louie, Angelique; Voss, John C.

2017-01-01

Alzheimer’s disease (AD) is characterized by depositions of the amyloid-β (Aβ) peptide in the brain. The disease process develops over decades, with substantial neurological loss occurring before a clinical diagnosis of dementia can be rendered. It is therefore imperative to develop methods that permit early detection and monitoring of disease progression. In addition, the multifactorial pathogenesis of AD has identified several potential avenues for AD intervention. Thus, evaluation of therapeutic candidates over lengthy trial periods also demands a practical, noninvasive method for measuring Aβ in the brain. Magnetic resonance imaging (MRI) is the obvious choice for such measurements, but contrast enhancement for Aβ has only been achieved using Gd(III)-based agents. There is great interest in gadolinium-free methods to image the brain. In this study, we provide the first demonstration that a nitroxide-based small-molecule produces MRI contrast in brain specimens with elevated levels of Aβ. The molecule is comprised of a fluorene (a molecule with high affinity for Aβ) and a nitroxide spin label (a paramagnetic MRI contrast species). Labeling of brain specimens with the spin-labeled fluorene produces negative contrast in samples from AD model mice whereas no negative contrast is seen in specimens harvested from wild-type mice. Injection of SLF into live mice resulted in good brain penetration, with the compound able to generate contrast 24-hr post injection. These results provide a proof of concept method that can be used for early, noninvasive, gadolinium-free detection of amyloid plaques by magnetic resonance imaging (MRI). PMID:27911291

[MRI methods for pulmonary ventilation and perfusion imaging].

PubMed

Sommer, G; Bauman, G

2016-02-01

Separate assessment of respiratory mechanics, gas exchange and pulmonary circulation is essential for the diagnosis and therapy of pulmonary diseases. Due to the global character of the information obtained clinical lung function tests are often not sufficiently specific in the differential diagnosis or have a limited sensitivity in the detection of early pathological changes. The standard procedures of pulmonary imaging are computed tomography (CT) for depiction of the morphology as well as perfusion/ventilation scintigraphy and single photon emission computed tomography (SPECT) for functional assessment. Magnetic resonance imaging (MRI) with hyperpolarized gases, O2-enhanced MRI, MRI with fluorinated gases and Fourier decomposition MRI (FD-MRI) are available for assessment of pulmonary ventilation. For assessment of pulmonary perfusion dynamic contrast-enhanced MRI (DCE-MRI), arterial spin labeling (ASL) and FD-MRI can be used. Imaging provides a more precise insight into the pathophysiology of pulmonary function on a regional level. The advantages of MRI are a lack of ionizing radiation, which allows a protective acquisition of dynamic data as well as the high number of available contrasts and therefore accessible lung function parameters. Sufficient clinical data exist only for certain applications of DCE-MRI. For the other techniques, only feasibility studies and case series of different sizes are available. The clinical applicability of hyperpolarized gases is limited for technical reasons. The clinical application of the techniques described, except for DCE-MRI, should be restricted to scientific studies.

Use of a 3-Telsa magnet to perform delayed gadolinium-enhanced magnetic resonance imaging of the distal interphalangeal joint of horses with and without naturally occurring osteoarthritis.

PubMed

Bischofberger, Andrea S; Fürst, Anton E; Torgerson, Paul R; Carstens, Ann; Hilbe, Monika; Kircher, Patrick

2018-03-01

OBJECTIVE To characterize delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) features of healthy hyaline cartilage of the distal interphalangeal joint (DIPJ) of horses, to determine whether dGEMRIC can be used to differentiate various stages of naturally occurring osteoarthritis of the DIPJ, and to correlate relaxation times determined by dGEMRIC with the glycosaminoglycan concentration, water content, and macroscopic and histologic findings of hyaline cartilage of DIPJs with and without osteoarthritis. SAMPLE 1 cadaveric forelimb DIPJ from each of 12 adult warmblood horses. PROCEDURES T1-weighted cartilage relaxation times were obtained for predetermined sites of the DIPJ before (T1 preGd ) and after (T1 postGd ) intra-articular gadolinium administration. Corresponding cartilage sites underwent macroscopic, histologic, and immunohistochemical evaluation, and cartilage glycosaminoglycan concentration and water content were determined. Median T1 preGd and T1 postGd were correlated with macroscopic, histologic, and biochemical data. Mixed generalized linear models were created to evaluate the effects of cartilage site, articular surface, and macroscopic and histologic scores on relaxation times. RESULTS 122 cartilage specimens were analyzed. Median T1 postGd was lower than the median T1 preGd for normal and diseased cartilage. Both T1 preGd and T1 postGd were correlated with macroscopic and histologic scores, whereby T1 preGd increased and T1 postGd decreased as osteoarthritis progressed. There was topographic variation of T1 preGd and T1 postGd within the DIPJ. Cartilage glycosaminoglycan concentration and water content were significantly correlated with T1 preGd and macroscopic and histologic scores but were not correlated with T1 postGd . CONCLUSIONS AND CLINICAL RELEVANCE Results indicated that dGEMRIC relaxation times varied for DIPJs with various degrees of osteoarthritis. These findings may help facilitate early detection of osteoarthritis.

Agreement between methods of measurement of mean aortic wall thickness by MRI.

PubMed

Rosero, Eric B; Peshock, Ronald M; Khera, Amit; Clagett, G Patrick; Lo, Hao; Timaran, Carlos

2009-03-01

To assess the agreement between three methods of calculation of mean aortic wall thickness (MAWT) using magnetic resonance imaging (MRI). High-resolution MRI of the infrarenal abdominal aorta was performed on 70 subjects with a history of coronary artery disease who were part of a multi-ethnic population-based sample. MAWT was calculated as the mean distance between the adventitial and luminal aortic boundaries using three different methods: average distance at four standard positions (AWT-4P), average distance at 100 automated positions (AWT-100P), and using a mathematical computation derived from the total vessel and luminal areas (AWT-VA). Bland-Altman plots and Passing-Bablok regression analyses were used to assess agreement between methods. Bland-Altman analyses demonstrated a positive bias of 3.02+/-7.31% between the AWT-VA and the AWT-4P methods, and of 1.76+/-6.82% between the AWT-100P and the AWT-4P methods. Passing-Bablok regression analyses demonstrated constant bias between the AWT-4P method and the other two methods. Proportional bias was, however, not evident among the three methods. MRI methods of measurement of MAWT using a limited number of positions of the aortic wall systematically underestimate the MAWT value compared with the method that calculates MAWT from the vessel areas. Copyright (c) 2009 Wiley-Liss, Inc.

A new method based on Dempster-Shafer theory and fuzzy c-means for brain MRI segmentation

NASA Astrophysics Data System (ADS)

Liu, Jie; Lu, Xi; Li, Yunpeng; Chen, Xiaowu; Deng, Yong

2015-10-01

In this paper, a new method is proposed to decrease sensitiveness to motion noise and uncertainty in magnetic resonance imaging (MRI) segmentation especially when only one brain image is available. The method is approached with considering spatial neighborhood information by fusing the information of pixels with their neighbors with Dempster-Shafer (DS) theory. The basic probability assignment (BPA) of each single hypothesis is obtained from the membership function of applying fuzzy c-means (FCM) clustering to the gray levels of the MRI. Then multiple hypotheses are generated according to the single hypothesis. Then we update the objective pixel’s BPA by fusing the BPA of the objective pixel and those of its neighbors to get the final result. Some examples in MRI segmentation are demonstrated at the end of the paper, in which our method is compared with some previous methods. The results show that the proposed method is more effective than other methods in motion-blurred MRI segmentation.

Signal-to-noise ratio comparison of encoding methods for hyperpolarized noble gas MRI

NASA Technical Reports Server (NTRS)

Zhao, L.; Venkatesh, A. K.; Albert, M. S.; Panych, L. P.

2001-01-01

Some non-Fourier encoding methods such as wavelet and direct encoding use spatially localized bases. The spatial localization feature of these methods enables optimized encoding for improved spatial and temporal resolution during dynamically adaptive MR imaging. These spatially localized bases, however, have inherently reduced image signal-to-noise ratio compared with Fourier or Hadamad encoding for proton imaging. Hyperpolarized noble gases, on the other hand, have quite different MR properties compared to proton, primarily the nonrenewability of the signal. It could be expected, therefore, that the characteristics of image SNR with respect to encoding method will also be very different from hyperpolarized noble gas MRI compared to proton MRI. In this article, hyperpolarized noble gas image SNRs of different encoding methods are compared theoretically using a matrix description of the encoding process. It is shown that image SNR for hyperpolarized noble gas imaging is maximized for any orthonormal encoding method. Methods are then proposed for designing RF pulses to achieve normalized encoding profiles using Fourier, Hadamard, wavelet, and direct encoding methods for hyperpolarized noble gases. Theoretical results are confirmed with hyperpolarized noble gas MRI experiments. Copyright 2001 Academic Press.

PRIM: An Efficient Preconditioning Iterative Reweighted Least Squares Method for Parallel Brain MRI Reconstruction.

PubMed

Xu, Zheng; Wang, Sheng; Li, Yeqing; Zhu, Feiyun; Huang, Junzhou

2018-02-08

The most recent history of parallel Magnetic Resonance Imaging (pMRI) has in large part been devoted to finding ways to reduce acquisition time. While joint total variation (JTV) regularized model has been demonstrated as a powerful tool in increasing sampling speed for pMRI, however, the major bottleneck is the inefficiency of the optimization method. While all present state-of-the-art optimizations for the JTV model could only reach a sublinear convergence rate, in this paper, we squeeze the performance by proposing a linear-convergent optimization method for the JTV model. The proposed method is based on the Iterative Reweighted Least Squares algorithm. Due to the complexity of the tangled JTV objective, we design a novel preconditioner to further accelerate the proposed method. Extensive experiments demonstrate the superior performance of the proposed algorithm for pMRI regarding both accuracy and efficiency compared with state-of-the-art methods.

SU-E-J-221: A Novel Expansion Method for MRI Based Target Delineation in Prostate Radiotherapy

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

Ruiz, B; East Carolina University, Greenville, NC; Feng, Y

Purpose: To compare a novel bladder/rectum carveout expansion method on MRI delineated prostate to standard CT and expansion based methods for maintaining prostate coverage while providing superior bladder and rectal sparing. Methods: Ten prostate cases were planned to include four trials: MRI vs CT delineated prostate/proximal seminal vesicles, and each image modality compared to both standard expansions (8mm 3D expansion and 5mm posterior, i.e. ∼8mm) and carveout method expansions (5mm 3D expansion, 4mm posterior for GTV-CTV excluding expansion into bladder/rectum followed by additional 5mm 3D expansion to PTV, i.e. ∼1cm). All trials were planned to total dose 7920 cGy viamore » IMRT. Evaluation and comparison was made using the following criteria: QUANTEC constraints for bladder/rectum including analysis of low dose regions, changes in PTV volume, total control points, and maximum hot spot. Results: ∼8mm MRI expansion consistently produced the most optimal plan with lowest total control points and best bladder/rectum sparing. However, this scheme had the smallest prostate (average 22.9% reduction) and subsequent PTV volume, consistent with prior literature. ∼1cm MRI had an average PTV volume comparable to ∼8mm CT at 3.79% difference. Bladder QUANTEC constraints were on average less for the ∼1cm MRI as compared to the ∼8mm CT and observed as statistically significant with 2.64% reduction in V65. Rectal constraints appeared to follow the same trend. Case-by-case analysis showed variation in rectal V30 with MRI delineated prostate being most favorable regardless of expansion type. ∼1cm MRI and ∼8mm CT had comparable plan quality. Conclusion: MRI delineated prostate with standard expansions had the smallest PTV leading to margins that may be too tight. Bladder/rectum carveout expansion method on MRI delineated prostate was found to be superior to standard CT based methods in terms of bladder and rectal sparing while maintaining prostate coverage

[Imaging and quantitative measurement of brain extracellular space using MRI Gd-DTPA tracer method].

PubMed

He, Qing-yuan; Han, Hong-bin; Xu, Fang-jing-wei; Yan, Jun-hao; Zeng, Jin-jin; Li, Xiao-gang; Fu, Yu; Peng, Yun; Chen, He; Hou, Chao; Xu, Xiao-juan

2010-04-18

To observe the diffusion of Gd-DTPA in brain extracellular space (ECS) by magnetic resonance imaging(MRI) and investigate the feasibility of ECS measurement by using MRI tracer method in vivo. 2 microL Gd-DTPA was introduced into ECS by caudate nucleus according to stereotaxic atlas in 8 Sprague Dawley(SD) rats (male, 280-320 g). The MRI scans were performed at 1 h, 3 h, 6 h, 9 h and 12 h respectively after administration. MRI appearances of Gd-DTPA diffusion and distribution was observed and compared. The MRI signal enhancement was measured at each time point. The neuroethology assessment was performed after MRI scanning at 12 h. The injection was accurate at the center of the caudate nucleus in 6 rats, while, at the capsula externa in other 2 rats. Gd-DTPA diffused isotropically after it was introduced into caudate nucleus, which spread into lateral cortex at 3 h. The MRI signal enhancement distributed mainly in the middle cerebral artery territory. A significant difference was found between the signal enhancement ratio at 1 h and that at 3 h in the original point of caudate nucleus (t=95.63, P<0.01), and the signal enhancement attenuated following the exponential power function y=1.7886x(-0.1776) (R2=0.94). In 2 rats with the injection point at capsula externa, Gd-DTPA diffused anisotropically along the fiber track of white matter during 1 h to 3 h, and spread into the lateral cortex at 6 h. The diffusion and clearance of Gd-DTPA in brain ECS could be monitored and measured quantitatively in vivo by MRI tracer method.

TU-AB-BRA-09: A Novel Method of Generating Ultrafast Volumetric Cine MRI (VC-MRI) Using Prior 4D-MRI and On-Board Phase-Skipped Encoding Acquisition for Radiotherapy Target Localization

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

Wang, C; Yin, F; Harris, W

Purpose: To develop a technique generating ultrafast on-board VC-MRI using prior 4D-MRI and on-board phase-skipped encoding k-space acquisition for real-time 3D target tracking of liver and lung radiotherapy. Methods: The end-of-expiration (EOE) volume in 4D-MRI acquired during the simulation was selected as the prior volume. 3 major respiratory deformation patterns were extracted through the principal component analysis of the deformation field maps (DFMs) generated between EOE and all other phases. The on-board VC-MRI at each instant was considered as a deformation of the prior volume, and the deformation was modeled as a linear combination of the extracted 3 major deformationmore » patterns. To solve the weighting coefficients of the 3 major patterns, a 2D slice was extracted from VC-MRI volume to match with the 2D on-board sampling data, which was generated by 8-fold phase skipped-encoding k-space acquisition (i.e., sample 1 phase-encoding line out of every 8 lines) to achieve an ultrafast 16–24 volumes/s frame rate. The method was evaluated using XCAT digital phantom to simulate lung cancer patients. The 3D volume of end-ofinhalation (EOI) phase at the treatment day was used as ground-truth onboard VC-MRI with simulated changes in 1) breathing amplitude and 2) breathing amplitude/phase change from the simulation day. A liver cancer patient case was evaluated for in-vivo feasibility demonstration. Results: The comparison between ground truth and estimated on-board VC-MRI shows good agreements. In XCAT study with changed breathing amplitude, the volume-percent-difference(VPD) between ground-truth and estimated tumor volumes at EOI was 6.28% and the Center-of-Mass-Shift(COMS) was 0.82mm; with changed breathing amplitude and phase, the VPD was 8.50% and the COMS was 0.54mm. The study of liver patient case also demonstrated a promising in vivo feasibility of the proposed method Conclusion: Preliminary results suggest the feasibility to estimate ultrafast VC-MRI

[Mechanical Shimming Method and Implementation for Permanent Magnet of MRI System].

PubMed

Xue, Tingqiang; Chen, Jinjun

2015-03-01

A mechanical shimming method and device for permanent magnet of MRI system has been developed to meet its stringent homogeneity requirement without time-consuming passive shimming on site, installation and adjustment efficiency has been increased.

Correction of MRI-induced geometric distortions in whole-body small animal PET-MRI

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

Frohwein, Lynn J., E-mail: frohwein@uni-muenster.de; Schäfers, Klaus P.; Hoerr, Verena

Purpose: The fusion of positron emission tomography (PET) and magnetic resonance imaging (MRI) data can be a challenging task in whole-body PET-MRI. The quality of the registration between these two modalities in large field-of-views (FOV) is often degraded by geometric distortions of the MRI data. The distortions at the edges of large FOVs mainly originate from MRI gradient nonlinearities. This work describes a method to measure and correct for these kind of geometric distortions in small animal MRI scanners to improve the registration accuracy of PET and MRI data. Methods: The authors have developed a geometric phantom which allows themore » measurement of geometric distortions in all spatial axes via control points. These control points are detected semiautomatically in both PET and MRI data with a subpixel accuracy. The spatial transformation between PET and MRI data is determined with these control points via 3D thin-plate splines (3D TPS). The transformation derived from the 3D TPS is finally applied to real MRI mouse data, which were acquired with the same scan parameters used in the phantom data acquisitions. Additionally, the influence of the phantom material on the homogeneity of the magnetic field is determined via field mapping. Results: The spatial shift according to the magnetic field homogeneity caused by the phantom material was determined to a mean of 0.1 mm. The results of the correction show that distortion with a maximum error of 4 mm could be reduced to less than 1 mm with the proposed correction method. Furthermore, the control point-based registration of PET and MRI data showed improved congruence after correction. Conclusions: The developed phantom has been shown to have no considerable negative effect on the homogeneity of the magnetic field. The proposed method yields an appropriate correction of the measured MRI distortion and is able to improve the PET and MRI registration. Furthermore, the method is applicable to whole-body small

A comparison of exogenous and endogenous CEST MRI methods for evaluating in vivo pH.

PubMed

Lindeman, Leila R; Randtke, Edward A; High, Rachel A; Jones, Kyle M; Howison, Christine M; Pagel, Mark D

2018-05-01

Extracellular pH (pHe) is an important biomarker for cancer cell metabolism. Acido-chemical exchange saturation transfer (CEST) MRI uses the contrast agent iopamidol to create spatial maps of pHe. Measurements of amide proton transfer exchange rates (k ex ) from endogenous CEST MRI were compared to pHe measurements by exogenous acido-CEST MRI to determine whether endogenous k ex could be used as a proxy for pHe measurements. Spatial maps of pHe and k ex were obtained using exogenous acidoCEST MRI and an endogenous CEST MRI analyzed with the omega plot method, respectively, to evaluate mouse kidney, a flank tumor model, and a spontaneous lung tumor model. The pHe and k ex results were evaluated using pixelwise comparisons. The k ex values obtained from endogenous CEST measurements did not correlate with the pHe results from exogenous CEST measurements. The k ex measurements were limited to fewer pixels and had a limited dynamic range relative to pHe measurements. Measurements of k ex with endogenous CEST MRI cannot substitute for pHe measurements with acidoCEST MRI. Whereas endogenous CEST MRI may still have good utility for evaluating some specific pathologies, exogenous acido-CEST MRI is more appropriate when evaluating pathologies based on pHe values. Magn Reson Med 79:2766-2772, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

PubMed

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series

PubMed Central

Patel, Ameera X.; Kundu, Prantik; Rubinov, Mikail; Jones, P. Simon; Vértes, Petra E.; Ersche, Karen D.; Suckling, John; Bullmore, Edward T.

2014-01-01

The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N = 22) and a new dataset on adults with stimulant drug dependence (N = 40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www

Use of Brain MRI Atlases to Determine Boundaries of Age-Related Pathology: The Importance of Statistical Method

PubMed Central

Dickie, David Alexander; Job, Dominic E.; Gonzalez, David Rodriguez; Shenkin, Susan D.; Wardlaw, Joanna M.

2015-01-01

Introduction Neurodegenerative disease diagnoses may be supported by the comparison of an individual patient’s brain magnetic resonance image (MRI) with a voxel-based atlas of normal brain MRI. Most current brain MRI atlases are of young to middle-aged adults and parametric, e.g., mean ±standard deviation (SD); these atlases require data to be Gaussian. Brain MRI data, e.g., grey matter (GM) proportion images, from normal older subjects are apparently not Gaussian. We created a nonparametric and a parametric atlas of the normal limits of GM proportions in older subjects and compared their classifications of GM proportions in Alzheimer’s disease (AD) patients. Methods Using publicly available brain MRI from 138 normal subjects and 138 subjects diagnosed with AD (all 55–90 years), we created: a mean ±SD atlas to estimate parametrically the percentile ranks and limits of normal ageing GM; and, separately, a nonparametric, rank order-based GM atlas from the same normal ageing subjects. GM images from AD patients were then classified with respect to each atlas to determine the effect statistical distributions had on classifications of proportions of GM in AD patients. Results The parametric atlas often defined the lower normal limit of the proportion of GM to be negative (which does not make sense physiologically as the lowest possible proportion is zero). Because of this, for approximately half of the AD subjects, 25–45% of voxels were classified as normal when compared to the parametric atlas; but were classified as abnormal when compared to the nonparametric atlas. These voxels were mainly concentrated in the frontal and occipital lobes. Discussion To our knowledge, we have presented the first nonparametric brain MRI atlas. In conditions where there is increasing variability in brain structure, such as in old age, nonparametric brain MRI atlases may represent the limits of normal brain structure more accurately than parametric approaches. Therefore, we

New method for predicting estrogen receptor status utilizing breast MRI texture kinetic analysis

NASA Astrophysics Data System (ADS)

Chaudhury, Baishali; Hall, Lawrence O.; Goldgof, Dmitry B.; Gatenby, Robert A.; Gillies, Robert; Drukteinis, Jennifer S.

2014-03-01

Magnetic Resonance Imaging (MRI) of breast cancer typically shows that tumors are heterogeneous with spatial variations in blood flow and cell density. Here, we examine the potential link between clinical tumor imaging and the underlying evolutionary dynamics behind heterogeneity in the cellular expression of estrogen receptors (ER) in breast cancer. We assume, in an evolutionary environment, that ER expression will only occur in the presence of significant concentrations of estrogen, which is delivered via the blood stream. Thus, we hypothesize, the expression of ER in breast cancer cells will correlate with blood flow on gadolinium enhanced breast MRI. To test this hypothesis, we performed quantitative analysis of blood flow on dynamic contrast enhanced MRI (DCE-MRI) and correlated it with the ER status of the tumor. Here we present our analytic methods, which utilize a novel algorithm to analyze 20 volumetric DCE-MRI breast cancer tumors. The algorithm generates post initial enhancement (PIE) maps from DCE-MRI and then performs texture features extraction from the PIE map, feature selection, and finally classification of tumors into ER positive and ER negative status. The combined gray level co-occurrence matrices, gray level run length matrices and local binary pattern histogram features allow quantification of breast tumor heterogeneity. The algorithm predicted ER expression with an accuracy of 85% using a Naive Bayes classifier in leave-one-out cross-validation. Hence, we conclude that our data supports the hypothesis that imaging characteristics can, through application of evolutionary principles, provide insights into the cellular and molecular properties of cancer cells.

Performance of blind source separation algorithms for fMRI analysis using a group ICA method.

PubMed

Correa, Nicolle; Adali, Tülay; Calhoun, Vince D

2007-06-01

Independent component analysis (ICA) is a popular blind source separation technique that has proven to be promising for the analysis of functional magnetic resonance imaging (fMRI) data. A number of ICA approaches have been used for fMRI data analysis, and even more ICA algorithms exist; however, the impact of using different algorithms on the results is largely unexplored. In this paper, we study the performance of four major classes of algorithms for spatial ICA, namely, information maximization, maximization of non-Gaussianity, joint diagonalization of cross-cumulant matrices and second-order correlation-based methods, when they are applied to fMRI data from subjects performing a visuo-motor task. We use a group ICA method to study variability among different ICA algorithms, and we propose several analysis techniques to evaluate their performance. We compare how different ICA algorithms estimate activations in expected neuronal areas. The results demonstrate that the ICA algorithms using higher-order statistical information prove to be quite consistent for fMRI data analysis. Infomax, FastICA and joint approximate diagonalization of eigenmatrices (JADE) all yield reliable results, with each having its strengths in specific areas. Eigenvalue decomposition (EVD), an algorithm using second-order statistics, does not perform reliably for fMRI data. Additionally, for iterative ICA algorithms, it is important to investigate the variability of estimates from different runs. We test the consistency of the iterative algorithms Infomax and FastICA by running the algorithm a number of times with different initializations, and we note that they yield consistent results over these multiple runs. Our results greatly improve our confidence in the consistency of ICA for fMRI data analysis.

The secret lives of experiments: methods reporting in the fMRI literature.

PubMed

Carp, Joshua

2012-10-15

Replication of research findings is critical to the progress of scientific understanding. Accordingly, most scientific journals require authors to report experimental procedures in sufficient detail for independent researchers to replicate their work. To what extent do research reports in the functional neuroimaging literature live up to this standard? The present study evaluated methods reporting and methodological choices across 241 recent fMRI articles. Many studies did not report critical methodological details with regard to experimental design, data acquisition, and analysis. Further, many studies were underpowered to detect any but the largest statistical effects. Finally, data collection and analysis methods were highly flexible across studies, with nearly as many unique analysis pipelines as there were studies in the sample. Because the rate of false positive results is thought to increase with the flexibility of experimental designs, the field of functional neuroimaging may be particularly vulnerable to false positives. In sum, the present study documented significant gaps in methods reporting among fMRI studies. Improved methodological descriptions in research reports would yield significant benefits for the field. Copyright © 2012 Elsevier Inc. All rights reserved.

Comparative analysis of methods for extracting vessel network on breast MRI images

NASA Astrophysics Data System (ADS)

Gaizer, Bence T.; Vassiou, Katerina G.; Lavdas, Eleftherios; Arvanitis, Dimitrios L.; Fezoulidis, Ioannis V.; Glotsos, Dimitris T.

2017-11-01

Digital processing of MRI images aims to provide an automatized diagnostic evaluation of regular health screenings. Cancerous lesions are proven to cause an alteration in the vessel structure of the diseased organ. Currently there are several methods used for extraction of the vessel network in order to quantify its properties. In this work MRI images (Signa HDx 3.0T, GE Healthcare, courtesy of University Hospital of Larissa) of 30 female breasts were subjected to three different vessel extraction algorithms to determine the location of their vascular network. The first method is an experiment to build a graph over known points of the vessel network; the second algorithm aims to determine the direction and diameter of vessels at these points; the third approach is a seed growing algorithm, spreading selection to neighbors of the known vessel pixels. The possibilities shown by the different methods were analyzed, and quantitative measurements were performed. The data provided by these measurements showed no clear correlation with the presence or malignancy of tumors, based on the radiological diagnosis of skilled physicians.

Toward implementing an MRI-based PET attenuation-correction method for neurologic studies on the MR-PET brain prototype.

PubMed

Catana, Ciprian; van der Kouwe, Andre; Benner, Thomas; Michel, Christian J; Hamm, Michael; Fenchel, Matthias; Fischl, Bruce; Rosen, Bruce; Schmand, Matthias; Sorensen, A Gregory

2010-09-01

Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype. The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the radiofrequency coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method. Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm(-1) to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the radiofrequency coil attenuation can cause large underestimations (i.e., MRI- and CT-based AC methods compare favorably in most of

Advanced MRI in Blast-related TBI

DTIC Science & Technology

2012-07-01

test two advanced MRI methods, DTI and resting-state fMRI, in active-duty military blast-related TBI patients acutely after injury and correlate...Introduction: The purpose of the research effort was to test two advanced MRI methods, DTI and resting-state fMRI, in active-duty military blast-related TBI...clinical follow-up assessments and repeat scans on 78 subjects with TBI and 18 controls. 9) We extensively analyzed DTI , resting-state fMRI, and

Flip-flop method: A new T1-weighted flow-MRI for plants studies.

PubMed

Buy, Simon; Le Floch, Simon; Tang, Ning; Sidiboulenouar, Rahima; Zanca, Michel; Canadas, Patrick; Nativel, Eric; Cardoso, Maida; Alibert, Eric; Dupont, Guillaume; Ambard, Dominique; Maurel, Christophe; Verdeil, Jean-Luc; Bertin, Nadia; Goze-Bac, Christophe; Coillot, Christophe

2018-01-01

The climate warming implies an increase of stress of plants (drought and torrential rainfall). The understanding of plant behavior, in this context, takes a major importance and sap flow measurement in plants remains a key issue for plant understanding. Magnetic Resonance Imaging (MRI) which is well known to be a powerful tool to access water quantity can be used to measure moving water. We describe a novel flow-MRI method which takes advantage of inflow slice sensitivity. The method involves the slice selectivity in the context of multi slice spin echo sequence. Two sequences such as a given slice is consecutively inflow and outflow sensitive are performed, offering the possiblility to perform slow flow sensitive imaging in a quite straigthforward way. The method potential is demonstrated by imaging both a slow flow measurement on a test bench (as low as 10 μm.s-1) and the Poiseuille's profile of xylemian sap flow velocity in the xylematic tissues of a tomato plant stem.

A novel anisotropic fast marching method and its application to blood flow computation in phase-contrast MRI.

PubMed

Schwenke, M; Hennemuth, A; Fischer, B; Friman, O

2012-01-01

Phase-contrast MRI (PC MRI) can be used to assess blood flow dynamics noninvasively inside the human body. The acquired images can be reconstructed into flow vector fields. Traditionally, streamlines can be computed based on the vector fields to visualize flow patterns and particle trajectories. The traditional methods may give a false impression of precision, as they do not consider the measurement uncertainty in the PC MRI images. In our prior work, we incorporated the uncertainty of the measurement into the computation of particle trajectories. As a major part of the contribution, a novel numerical scheme for solving the anisotropic Fast Marching problem is presented. A computing time comparison to state-of-the-art methods is conducted on artificial tensor fields. A visual comparison of healthy to pathological blood flow patterns is given. The comparison shows that the novel anisotropic Fast Marching solver outperforms previous schemes in terms of computing time. The visual comparison of flow patterns directly visualizes large deviations of pathological flow from healthy flow. The novel anisotropic Fast Marching solver efficiently resolves even strongly anisotropic path costs. The visualization method enables the user to assess the uncertainty of particle trajectories derived from PC MRI images.

A Structure Design Method for Reduction of MRI Acoustic Noise.

PubMed

Nan, Jiaofen; Zong, Nannan; Chen, Qiqiang; Zhang, Liangliang; Zheng, Qian; Xia, Yongquan

2017-01-01

The acoustic problem of the split gradient coil is one challenge in a Magnetic Resonance Imaging and Linear Accelerator (MRI-LINAC) system. In this paper, we aimed to develop a scheme to reduce the acoustic noise of the split gradient coil. First, a split gradient assembly with an asymmetric configuration was designed to avoid vibration in same resonant modes for the two assembly cylinders. Next, the outer ends of the split main magnet were constructed using horn structures, which can distribute the acoustic field away from patient region. Finally, a finite element method (FEM) was used to quantitatively evaluate the effectiveness of the above acoustic noise reduction scheme. Simulation results found that the noise could be maximally reduced by 6.9 dB and 5.6 dB inside and outside the central gap of the split MRI system, respectively, by increasing the length of one gradient assembly cylinder by 20 cm. The optimized horn length was observed to be 55 cm, which could reduce noise by up to 7.4 dB and 5.4 dB inside and outside the central gap, respectively. The proposed design could effectively reduce the acoustic noise without any influence on the application of other noise reduction methods.

Unsupervised nonlinear dimensionality reduction machine learning methods applied to multiparametric MRI in cerebral ischemia: preliminary results

NASA Astrophysics Data System (ADS)

Parekh, Vishwa S.; Jacobs, Jeremy R.; Jacobs, Michael A.

2014-03-01

The evaluation and treatment of acute cerebral ischemia requires a technique that can determine the total area of tissue at risk for infarction using diagnostic magnetic resonance imaging (MRI) sequences. Typical MRI data sets consist of T1- and T2-weighted imaging (T1WI, T2WI) along with advanced MRI parameters of diffusion-weighted imaging (DWI) and perfusion weighted imaging (PWI) methods. Each of these parameters has distinct radiological-pathological meaning. For example, DWI interrogates the movement of water in the tissue and PWI gives an estimate of the blood flow, both are critical measures during the evolution of stroke. In order to integrate these data and give an estimate of the tissue at risk or damaged; we have developed advanced machine learning methods based on unsupervised non-linear dimensionality reduction (NLDR) techniques. NLDR methods are a class of algorithms that uses mathematically defined manifolds for statistical sampling of multidimensional classes to generate a discrimination rule of guaranteed statistical accuracy and they can generate a two- or three-dimensional map, which represents the prominent structures of the data and provides an embedded image of meaningful low-dimensional structures hidden in their high-dimensional observations. In this manuscript, we develop NLDR methods on high dimensional MRI data sets of preclinical animals and clinical patients with stroke. On analyzing the performance of these methods, we observed that there was a high of similarity between multiparametric embedded images from NLDR methods and the ADC map and perfusion map. It was also observed that embedded scattergram of abnormal (infarcted or at risk) tissue can be visualized and provides a mechanism for automatic methods to delineate potential stroke volumes and early tissue at risk.

Advanced MRI in Acute Military TBI

DTIC Science & Technology

2015-11-01

advanced MRI methods, DTI and resting-state fMRI correlation analysis, in military TBI patients acutely after injury and correlate findings with TBI...14 4 Introduction The objective of the project was to test two advanced MRI methods, DTI and resting-state fMRI correlation analysis, in...of Concussion Exam (MACE )(44) were reviewed. This brief cognitive test 279 assesses orientation, immediate verbal memory , concentration, and short

Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data.

PubMed

Song, Sutao; Zhan, Zhichao; Long, Zhiying; Zhang, Jiacai; Yao, Li

2011-02-16

Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice.

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.

PubMed

Patel, Ameera X; Kundu, Prantik; Rubinov, Mikail; Jones, P Simon; Vértes, Petra E; Ersche, Karen D; Suckling, John; Bullmore, Edward T

2014-07-15

The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N=22) and a new dataset on adults with stimulant drug dependence (N=40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www

Structure-seeking multilinear methods for the analysis of fMRI data.

PubMed

Andersen, Anders H; Rayens, William S

2004-06-01

In comprehensive fMRI studies of brain function, the data structures often contain higher-order ways such as trial, task condition, subject, and group in addition to the intrinsic dimensions of time and space. While multivariate bilinear methods such as principal component analysis (PCA) have been used successfully for extracting information about spatial and temporal features in data from a single fMRI run, the need to unfold higher-order data sets into bilinear arrays has led to decompositions that are nonunique and to the loss of multiway linkages and interactions present in the data. These additional dimensions or ways can be retained in multilinear models to produce structures that are unique and which admit interpretations that are neurophysiologically meaningful. Multiway analysis of fMRI data from multiple runs of a bilateral finger-tapping paradigm was performed using the parallel factor (PARAFAC) model. A trilinear model was fitted to a data cube of dimensions voxels by time by run. Similarly, a quadrilinear model was fitted to a higher-way structure of dimensions voxels by time by trial by run. The spatial and temporal response components were extracted and validated by comparison to results from traditional SVD/PCA analyses based on scenarios of unfolding into lower-order bilinear structures.

Real-Time Compressive Sensing MRI Reconstruction Using GPU Computing and Split Bregman Methods

PubMed Central

Smith, David S.; Gore, John C.; Yankeelov, Thomas E.; Welch, E. Brian

2012-01-01

Compressive sensing (CS) has been shown to enable dramatic acceleration of MRI acquisition in some applications. Being an iterative reconstruction technique, CS MRI reconstructions can be more time-consuming than traditional inverse Fourier reconstruction. We have accelerated our CS MRI reconstruction by factors of up to 27 by using a split Bregman solver combined with a graphics processing unit (GPU) computing platform. The increases in speed we find are similar to those we measure for matrix multiplication on this platform, suggesting that the split Bregman methods parallelize efficiently. We demonstrate that the combination of the rapid convergence of the split Bregman algorithm and the massively parallel strategy of GPU computing can enable real-time CS reconstruction of even acquisition data matrices of dimension 40962 or more, depending on available GPU VRAM. Reconstruction of two-dimensional data matrices of dimension 10242 and smaller took ~0.3 s or less, showing that this platform also provides very fast iterative reconstruction for small-to-moderate size images. PMID:22481908

Real-Time Compressive Sensing MRI Reconstruction Using GPU Computing and Split Bregman Methods.

PubMed

Smith, David S; Gore, John C; Yankeelov, Thomas E; Welch, E Brian

2012-01-01

Compressive sensing (CS) has been shown to enable dramatic acceleration of MRI acquisition in some applications. Being an iterative reconstruction technique, CS MRI reconstructions can be more time-consuming than traditional inverse Fourier reconstruction. We have accelerated our CS MRI reconstruction by factors of up to 27 by using a split Bregman solver combined with a graphics processing unit (GPU) computing platform. The increases in speed we find are similar to those we measure for matrix multiplication on this platform, suggesting that the split Bregman methods parallelize efficiently. We demonstrate that the combination of the rapid convergence of the split Bregman algorithm and the massively parallel strategy of GPU computing can enable real-time CS reconstruction of even acquisition data matrices of dimension 4096(2) or more, depending on available GPU VRAM. Reconstruction of two-dimensional data matrices of dimension 1024(2) and smaller took ~0.3 s or less, showing that this platform also provides very fast iterative reconstruction for small-to-moderate size images.

A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

PubMed

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lavenne, Franck; Le Bars, Didier; Costes, Nicolas

2013-08-15

MRI templates and digital atlases are needed for automated and reproducible quantitative analysis of non-human primate PET studies. Segmenting brain images via multiple atlases outperforms single-atlas labelling in humans. We present a set of atlases manually delineated on brain MRI scans of the monkey Macaca fascicularis. We use this multi-atlas dataset to evaluate two automated methods in terms of accuracy, robustness and reliability in segmenting brain structures on MRI and extracting regional PET measures. Twelve individual Macaca fascicularis high-resolution 3DT1 MR images were acquired. Four individual atlases were created by manually drawing 42 anatomical structures, including cortical and sub-cortical structures, white matter regions, and ventricles. To create the MRI template, we first chose one MRI to define a reference space, and then performed a two-step iterative procedure: affine registration of individual MRIs to the reference MRI, followed by averaging of the twelve resampled MRIs. Automated segmentation in native space was obtained in two ways: 1) Maximum probability atlases were created by decision fusion of two to four individual atlases in the reference space, and transformation back into the individual native space (MAXPROB)(.) 2) One to four individual atlases were registered directly to the individual native space, and combined by decision fusion (PROPAG). Accuracy was evaluated by computing the Dice similarity index and the volume difference. The robustness and reproducibility of PET regional measurements obtained via automated segmentation was evaluated on four co-registered MRI/PET datasets, which included test-retest data. Dice indices were always over 0.7 and reached maximal values of 0.9 for PROPAG with all four individual atlases. There was no significant mean volume bias. The standard deviation of the bias decreased significantly when increasing the number of individual atlases. MAXPROB performed better when increasing the number of

A methodology for generating normal and pathological brain perfusion SPECT images for evaluation of MRI/SPECT fusion methods: application in epilepsy

NASA Astrophysics Data System (ADS)

Grova, C.; Jannin, P.; Biraben, A.; Buvat, I.; Benali, H.; Bernard, A. M.; Scarabin, J. M.; Gibaud, B.

2003-12-01

Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack of relevant ground truth. We propose a methodology to generate MRI and SPECT datasets dedicated to the evaluation of MRI/SPECT fusion methods and illustrate the method when dealing with ictal SPECT. The method consists in generating normal or pathological SPECT data perfectly aligned with a high-resolution 3D T1-weighted MRI using realistic Monte Carlo simulations that closely reproduce the response of a SPECT imaging system. Anatomical input data for the SPECT simulations are obtained from this 3D T1-weighted MRI, while functional input data result from an inter-individual analysis of anatomically standardized SPECT data. The method makes it possible to control the 'brain perfusion' function by proposing a theoretical model of brain perfusion from measurements performed on real SPECT images. Our method provides an absolute gold standard for assessing MRI/SPECT registration method accuracy since, by construction, the SPECT data are perfectly registered with the MRI data. The proposed methodology has been applied to create a theoretical model of normal brain perfusion and ictal brain perfusion characteristic of mesial temporal lobe epilepsy. To approach realistic and unbiased perfusion models, real SPECT data were corrected for uniform attenuation, scatter and partial volume effect. An anatomic standardization was used to account for anatomic variability between subjects. Realistic simulations of normal and ictal SPECT deduced from these perfusion models are presented. The comparison of real and simulated SPECT images showed relative differences in regional activity concentration of less than 20% in most anatomical structures, for both normal and ictal data, suggesting realistic models of perfusion distributions for evaluation purposes. Inter-hemispheric asymmetry coefficients measured on simulated data were found within

An automatic method of brain tumor segmentation from MRI volume based on the symmetry of brain and level set method

NASA Astrophysics Data System (ADS)

Li, Xiaobing; Qiu, Tianshuang; Lebonvallet, Stephane; Ruan, Su

2010-02-01

This paper presents a brain tumor segmentation method which automatically segments tumors from human brain MRI image volume. The presented model is based on the symmetry of human brain and level set method. Firstly, the midsagittal plane of an MRI volume is searched, the slices with potential tumor of the volume are checked out according to their symmetries, and an initial boundary of the tumor in the slice, in which the tumor is in the largest size, is determined meanwhile by watershed and morphological algorithms; Secondly, the level set method is applied to the initial boundary to drive the curve evolving and stopping to the appropriate tumor boundary; Lastly, the tumor boundary is projected one by one to its adjacent slices as initial boundaries through the volume for the whole tumor. The experiment results are compared with hand tracking of the expert and show relatively good accordance between both.

Nonlinear PET parametric image reconstruction with MRI information using kernel method

NASA Astrophysics Data System (ADS)

Gong, Kuang; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2017-03-01

Positron Emission Tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neurology. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information. Previously we have used kernel learning to embed MR information in static PET reconstruction and direct Patlak reconstruction. Here we extend this method to direct reconstruction of nonlinear parameters in a compartment model by using the alternating direction of multiplier method (ADMM) algorithm. Simulation studies show that the proposed method can produce superior parametric images compared with existing methods.

[Method of correcting sensitivity nonuniformity using gaussian distribution on 3.0 Tesla abdominal MRI].

PubMed

Hayashi, Norio; Miyati, Tosiaki; Takanaga, Masako; Ohno, Naoki; Hamaguchi, Takashi; Kozaka, Kazuto; Sanada, Shigeru; Yamamoto, Tomoyuki; Matsui, Osamu

2011-01-01

In the direction where the phased array coil used in parallel magnetic resonance imaging (MRI) is perpendicular to the arrangement, sensitivity falls significantly. Moreover, in a 3.0 tesla (3T) abdominal MRI, the quality of the image is reduced by changes in the relaxation time, reinforcement of the magnetic susceptibility effect, etc. In a 3T MRI, which has a high resonant frequency, the signal of the depths (central part) is reduced in the trunk part. SCIC, which is sensitivity correction processing, has inadequate correction processing, such as that edges are emphasized and the central part is corrected. Therefore, we used 3T with a Gaussian distribution. The uneven compensation processing for sensitivity of an abdomen MR image was considered. The correction processing consisted of the following methods. 1) The center of gravity of the domain of the human body in an abdomen MR image was calculated. 2) The correction coefficient map was created from the center of gravity using the Gaussian distribution. 3) The sensitivity correction image was created from the correction coefficient map and the original picture image. Using the Gaussian correction to process the image, the uniformity calculated using the NEMA method was improved significantly compared to the original image of a phantom. In a visual evaluation by radiologists, the uniformity was improved significantly using the Gaussian correction processing. Because of the homogeneous improvement of the abdomen image taken using 3T MRI, the Gaussian correction processing is considered to be a very useful technique.

Constructing fMRI connectivity networks: a whole brain functional parcellation method for node definition.

PubMed

Maggioni, Eleonora; Tana, Maria Gabriella; Arrigoni, Filippo; Zucca, Claudio; Bianchi, Anna Maria

2014-05-15

Functional Magnetic Resonance Imaging (fMRI) is used for exploring brain functionality, and recently it was applied for mapping the brain connection patterns. To give a meaningful neurobiological interpretation to the connectivity network, it is fundamental to properly define the network framework. In particular, the choice of the network nodes may affect the final connectivity results and the consequent interpretation. We introduce a novel method for the intra subject topological characterization of the nodes of fMRI brain networks, based on a whole brain parcellation scheme. The proposed whole brain parcellation algorithm divides the brain into clusters that are homogeneous from the anatomical and functional point of view, each of which constitutes a node. The functional parcellation described is based on the Tononi's cluster index, which measures instantaneous correlation in terms of intrinsic and extrinsic statistical dependencies. The method performance and reliability were first tested on simulated data, then on a real fMRI dataset acquired on healthy subjects during visual stimulation. Finally, the proposed algorithm was applied to epileptic patients' fMRI data recorded during seizures, to verify its usefulness as preparatory step for effective connectivity analysis. For each patient, the nodes of the network involved in ictal activity were defined according to the proposed parcellation scheme and Granger Causality Analysis (GCA) was applied to infer effective connectivity. We showed that the algorithm 1) performed well on simulated data, 2) was able to produce reliable inter subjects results and 3) led to a detailed definition of the effective connectivity pattern. Copyright © 2014 Elsevier B.V. All rights reserved.

Three-dimensional MRI-linac intra-fraction guidance using multiple orthogonal cine-MRI planes

NASA Astrophysics Data System (ADS)

Bjerre, Troels; Crijns, Sjoerd; Rosenschöld, Per Munck af; Aznar, Marianne; Specht, Lena; Larsen, Rasmus; Keall, Paul

2013-07-01

The introduction of integrated MRI-radiation therapy systems will offer live intra-fraction imaging. We propose a feasible low-latency multi-plane MRI-linac guidance strategy. In this work we demonstrate how interleaved acquired, orthogonal cine-MRI planes can be used for low-latency tracking of the 3D trajectory of a soft-tissue target structure. The proposed strategy relies on acquiring a pre-treatment 3D breath-hold scan, extracting a 3D target template and performing template matching between this 3D template and pairs of orthogonal 2D cine-MRI planes intersecting the target motion path. For a 60 s free-breathing series of orthogonal cine-MRI planes, we demonstrate that the method was capable of accurately tracking the respiration related 3D motion of the left kidney. Quantitative evaluation of the method using a dataset designed for this purpose revealed a translational error of 1.15 mm for a translation of 39.9 mm. We have demonstrated how interleaved acquired, orthogonal cine-MRI planes can be used for online tracking of soft-tissue target volumes.

Three-dimensional MRI-linac intra-fraction guidance using multiple orthogonal cine-MRI planes.

PubMed

Bjerre, Troels; Crijns, Sjoerd; af Rosenschöld, Per Munck; Aznar, Marianne; Specht, Lena; Larsen, Rasmus; Keall, Paul

2013-07-21

The introduction of integrated MRI-radiation therapy systems will offer live intra-fraction imaging. We propose a feasible low-latency multi-plane MRI-linac guidance strategy. In this work we demonstrate how interleaved acquired, orthogonal cine-MRI planes can be used for low-latency tracking of the 3D trajectory of a soft-tissue target structure. The proposed strategy relies on acquiring a pre-treatment 3D breath-hold scan, extracting a 3D target template and performing template matching between this 3D template and pairs of orthogonal 2D cine-MRI planes intersecting the target motion path. For a 60 s free-breathing series of orthogonal cine-MRI planes, we demonstrate that the method was capable of accurately tracking the respiration related 3D motion of the left kidney. Quantitative evaluation of the method using a dataset designed for this purpose revealed a translational error of 1.15 mm for a translation of 39.9 mm. We have demonstrated how interleaved acquired, orthogonal cine-MRI planes can be used for online tracking of soft-tissue target volumes.

Brain tumor segmentation in MRI by using the fuzzy connectedness method

NASA Astrophysics Data System (ADS)

Liu, Jian-Guo; Udupa, Jayaram K.; Hackney, David; Moonis, Gul

2001-07-01

The aim of this paper is the precise and accurate quantification of brain tumor via MRI. This is very useful in evaluating disease progression, response to therapy, and the need for changes in treatment plans. We use multiple MRI protocols including FLAIR, T1, and T1 with Gd enhancement to gather information about different aspects of the tumor and its vicinity- edema, active regions, and scar left over due to surgical intervention. We have adapted the fuzzy connectedness framework to segment tumor and to measure its volume. The method requires only limited user interaction in routine clinical MRI. The first step in the process is to apply an intensity normalization method to the images so that the same body region has the same tissue meaning independent of the scanner and patient. Subsequently, a fuzzy connectedness algorithm is utilized to segment the different aspects of the tumor. The system has been tested, for its precision, accuracy, and efficiency, utilizing 40 patient studies. The percent coefficient of variation (% CV) in volume due to operator subjectivity in specifying seeds for fuzzy connectedness segmentation is less than 1%. The mean operator and computer time taken per study is 3 minutes. The package is designed to run under operator supervision. Delineation has been found to agree with the operators' visual inspection most of the time except in some cases when the tumor is close to the boundary of the brain. In the latter case, the scalp is included in the delineation and an operator has to exclude this manually. The methodology is rapid, robust, consistent, yielding highly reproducible measurements, and is likely to become part of the routine evaluation of brain tumor patients in our health system.

fMRI during natural sleep as a method to study brain function during early childhood.

PubMed

Redcay, Elizabeth; Kennedy, Daniel P; Courchesne, Eric

2007-12-01

Many techniques to study early functional brain development lack the whole-brain spatial resolution that is available with fMRI. We utilized a relatively novel method in which fMRI data were collected from children during natural sleep. Stimulus-evoked responses to auditory and visual stimuli as well as stimulus-independent functional networks were examined in typically developing 2-4-year-old children. Reliable fMRI data were collected from 13 children during presentation of auditory stimuli (tones, vocal sounds, and nonvocal sounds) in a block design. Twelve children were presented with visual flashing lights at 2.5 Hz. When analyses combined all three types of auditory stimulus conditions as compared to rest, activation included bilateral superior temporal gyri/sulci (STG/S) and right cerebellum. Direct comparisons between conditions revealed significantly greater responses to nonvocal sounds and tones than to vocal sounds in a number of brain regions including superior temporal gyrus/sulcus, medial frontal cortex and right lateral cerebellum. The response to visual stimuli was localized to occipital cortex. Furthermore, stimulus-independent functional connectivity MRI analyses (fcMRI) revealed functional connectivity between STG and other temporal regions (including contralateral STG) and medial and lateral prefrontal regions. Functional connectivity with an occipital seed was localized to occipital and parietal cortex. In sum, 2-4 year olds showed a differential fMRI response both between stimulus modalities and between stimuli in the auditory modality. Furthermore, superior temporal regions showed functional connectivity with numerous higher-order regions during sleep. We conclude that the use of sleep fMRI may be a valuable tool for examining functional brain organization in young children.

A brain MRI bias field correction method created in the Gaussian multi-scale space

NASA Astrophysics Data System (ADS)

Chen, Mingsheng; Qin, Mingxin

2017-07-01

A pre-processing step is needed to correct for the bias field signal before submitting corrupted MR images to such image-processing algorithms. This study presents a new bias field correction method. The method creates a Gaussian multi-scale space by the convolution of the inhomogeneous MR image with a two-dimensional Gaussian function. In the multi-Gaussian space, the method retrieves the image details from the differentiation of the original image and convolution image. Then, it obtains an image whose inhomogeneity is eliminated by the weighted sum of image details in each layer in the space. Next, the bias field-corrected MR image is retrieved after the Υ correction, which enhances the contrast and brightness of the inhomogeneity-eliminated MR image. We have tested the approach on T1 MRI and T2 MRI with varying bias field levels and have achieved satisfactory results. Comparison experiments with popular software have demonstrated superior performance of the proposed method in terms of quantitative indices, especially an improvement in subsequent image segmentation.

Comparative Study of SVM Methods Combined with Voxel Selection for Object Category Classification on fMRI Data

PubMed Central

Song, Sutao; Zhan, Zhichao; Long, Zhiying; Zhang, Jiacai; Yao, Li

2011-01-01

Background Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Methodology/Principal Findings Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. Conclusions/Significance The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal

MRI in ocular drug delivery

PubMed Central

Li, S. Kevin; Lizak, Martin J.; Jeong, Eun-Kee

2008-01-01

Conventional pharmacokinetic methods for studying ocular drug delivery are invasive and cannot be conveniently applied to humans. The advancement of MRI technology has provided new opportunities in ocular drug-delivery research. MRI provides a means to non-invasively and continuously monitor ocular drug-delivery systems with a contrast agent or compound labeled with a contrast agent. It is a useful technique in pharmacokinetic studies, evaluation of drug-delivery methods, and drug-delivery device testing. Although the current status of the technology presents some major challenges to pharmaceutical research using MRI, it has a lot of potential. In the past decade, MRI has been used to examine ocular drug delivery via the subconjunctival route, intravitreal injection, intrascleral injection to the suprachoroidal space, episcleral and intravitreal implants, periocular injections, and ocular iontophoresis. In this review, the advantages and limitations of MRI in the study of ocular drug delivery are discussed. Different MR contrast agents and MRI techniques for ocular drug-delivery research are compared. Ocular drug-delivery studies using MRI are reviewed. PMID:18186077

PET/MRI for neurologic applications.

PubMed

Catana, Ciprian; Drzezga, Alexander; Heiss, Wolf-Dieter; Rosen, Bruce R

2012-12-01

PET and MRI provide complementary information in the study of the human brain. Simultaneous PET/MRI data acquisition allows the spatial and temporal correlation of the measured signals, creating opportunities impossible to realize using stand-alone instruments. This paper reviews the methodologic improvements and potential neurologic and psychiatric applications of this novel technology. We first present methods for improving the performance and information content of each modality by using the information provided by the other technique. On the PET side, we discuss methods that use the simultaneously acquired MRI data to improve the PET data quantification. On the MRI side, we present how improved PET quantification can be used to validate several MRI techniques. Finally, we describe promising research, translational, and clinical applications that can benefit from these advanced tools.

Realistic simulated MRI and SPECT databases. Application to SPECT/MRI registration evaluation.

PubMed

Aubert-Broche, Berengere; Grova, Christophe; Reilhac, Anthonin; Evans, Alan C; Collins, D Louis

2006-01-01

This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods. Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy. We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity nonuniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.

A new integrated dual time-point amyloid PET/MRI data analysis method.

PubMed

Cecchin, Diego; Barthel, Henryk; Poggiali, Davide; Cagnin, Annachiara; Tiepolt, Solveig; Zucchetta, Pietro; Turco, Paolo; Gallo, Paolo; Frigo, Anna Chiara; Sabri, Osama; Bui, Franco

2017-11-01

In the initial evaluation of patients with suspected dementia and Alzheimer's disease, there is no consensus on how to perform semiquantification of amyloid in such a way that it: (1) facilitates visual qualitative interpretation, (2) takes the kinetic behaviour of the tracer into consideration particularly with regard to at least partially correcting for blood flow dependence, (3) analyses the amyloid load based on accurate parcellation of cortical and subcortical areas, (4) includes partial volume effect correction (PVEC), (5) includes MRI-derived topographical indexes, (6) enables application to PET/MRI images and PET/CT images with separately acquired MR images, and (7) allows automation. A method with all of these characteristics was retrospectively tested in 86 subjects who underwent amyloid ( 18 F-florbetaben) PET/MRI in a clinical setting (using images acquired 90-110 min after injection, 53 were classified visually as amyloid-negative and 33 as amyloid-positive). Early images after tracer administration were acquired between 0 and 10 min after injection, and later images were acquired between 90 and 110 min after injection. PVEC of the PET data was carried out using the geometric transfer matrix method. Parametric images and some regional output parameters, including two innovative "dual time-point" indexes, were obtained. Subjects classified visually as amyloid-positive showed a sparse tracer uptake in the primary sensory, motor and visual areas in accordance with the isocortical stage of the topographic distribution of the amyloid plaque (Braak stages V/VI). In patients classified visually as amyloid-negative, the method revealed detectable levels of tracer uptake in the basal portions of the frontal and temporal lobes, areas that are known to be sites of early deposition of amyloid plaques that probably represented early accumulation (Braak stage A) that is typical of normal ageing. There was a strong correlation between age and the indexes of the

Patch-based generation of a pseudo CT from conventional MRI sequences for MRI-only radiotherapy of the brain

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

Andreasen, Daniel, E-mail: dana@dtu.dk; Van Leemput, Koen; Hansen, Rasmus H.

Purpose: In radiotherapy (RT) based on magnetic resonance imaging (MRI) as the only modality, the information on electron density must be derived from the MRI scan by creating a so-called pseudo computed tomography (pCT). This is a nontrivial task, since the voxel-intensities in an MRI scan are not uniquely related to electron density. To solve the task, voxel-based or atlas-based models have typically been used. The voxel-based models require a specialized dual ultrashort echo time MRI sequence for bone visualization and the atlas-based models require deformable registrations of conventional MRI scans. In this study, we investigate the potential of amore » patch-based method for creating a pCT based on conventional T{sub 1}-weighted MRI scans without using deformable registrations. We compare this method against two state-of-the-art methods within the voxel-based and atlas-based categories. Methods: The data consisted of CT and MRI scans of five cranial RT patients. To compare the performance of the different methods, a nested cross validation was done to find optimal model parameters for all the methods. Voxel-wise and geometric evaluations of the pCTs were done. Furthermore, a radiologic evaluation based on water equivalent path lengths was carried out, comparing the upper hemisphere of the head in the pCT and the real CT. Finally, the dosimetric accuracy was tested and compared for a photon treatment plan. Results: The pCTs produced with the patch-based method had the best voxel-wise, geometric, and radiologic agreement with the real CT, closely followed by the atlas-based method. In terms of the dosimetric accuracy, the patch-based method had average deviations of less than 0.5% in measures related to target coverage. Conclusions: We showed that a patch-based method could generate an accurate pCT based on conventional T{sub 1}-weighted MRI sequences and without deformable registrations. In our evaluations, the method performed better than existing voxel

A stereotactic method for image-guided transcranial magnetic stimulation validated with fMRI and motor-evoked potentials.

PubMed

Neggers, S F W; Langerak, T R; Schutter, D J L G; Mandl, R C W; Ramsey, N F; Lemmens, P J J; Postma, A

2004-04-01

Transcranial Magnetic Stimulation (TMS) delivers short magnetic pulses that penetrate the skull unattenuated, disrupting neural processing in a noninvasive, reversible way. To disrupt specific neural processes, coil placement over the proper site is critical. Therefore, a neural navigator (NeNa) was developed. NeNa is a frameless stereotactic device using structural and functional magnetic resonance imaging (fMRI) data to guide TMS coil placement. To coregister the participant's head to his MRI, 3D cursors are moved to anatomical landmarks on a skin rendering of the participants MRI on a screen, and measured at the head with a position measurement device. A method is proposed to calculate a rigid body transformation that can coregister both sets of coordinates under realistic noise conditions. After coregistration, NeNa visualizes in real time where the device is located with respect to the head, brain structures, and activated areas, enabling precise placement of the TMS coil over a predefined target region. NeNa was validated by stimulating 5 x 5 positions around the 'motor hotspot' (thumb movement area), which was marked on the scalp guided by individual fMRI data, while recording motor-evoked potentials (MEPs) from the abductor pollicis brevis (APB). The distance between the center of gravity (CoG) of MEP responses and the location marked on the scalp overlying maximum fMRI activation was on average less then 5 mm. The present results demonstrate that NeNa is a reliable method for image-guided TMS coil placement.

Studying neuroanatomy using MRI.

PubMed

Lerch, Jason P; van der Kouwe, André J W; Raznahan, Armin; Paus, Tomáš; Johansen-Berg, Heidi; Miller, Karla L; Smith, Stephen M; Fischl, Bruce; Sotiropoulos, Stamatios N

2017-02-23

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging and disease. Developments in MRI acquisition, image processing and data modeling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and for inferring microstructural properties; we also describe key artifacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, although methods need to improve and caution is required in interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works.

Quantitative Chemical Shift-Encoded MRI Is an Accurate Method to Quantify Hepatic Steatosis

PubMed Central

Kühn, Jens-Peter; Hernando, Diego; Mensel, Birger; Krüger, Paul C.; Ittermann, Till; Mayerle, Julia; Hosten, Norbert; Reeder, Scott B.

2014-01-01

Purpose To compare the accuracy of liver fat quantification using a three-echo chemical shift-encoded magnetic resonance imaging (MRI) technique without and with correction for confounders with spectroscopy (MRS) as the reference standard. Materials and Methods Fifty patients (23 women, mean age 56.6 ± 13.2 years) with fatty liver disease were enrolled. Patients underwent T2-corrected single-voxel MRS and a three-echo chemical shift-encoded gradient echo (GRE) sequence at 3.0T. MRI fat fraction (FF) was calculated without and with T2* and T1 correction and multispectral modeling of fat and compared with MRS-FF using linear regression. Results The spectroscopic range of liver fat was 0.11%–38.7%. Excellent correlation between MRS-FF and MRI-FF was observed when using T2* correction (R2=0.96). With use of T2* correction alone, the slope was significantly different from 1 (1.16 ± 0.03, P < 0.001) and the intercept was different from 0 (1.14% ± 0.50%, P < 0.023). This slope was significantly different than 1.0 when no T1 correction was used (P=0.001). When T2*, T1, and spectral complexity of fat were addressed, the results showed equivalence between fat quantification using MRI and MRS (slope: 1.02 ± 0.03, P=0.528; intercept: 0.26% ± 0.46%, P=0.572). Conclusion Complex three-echo chemical shift-encoded MRI is equivalent to MRS for quantifying liver fat, but only with correction for T2* decay and T1 recovery and use of spectral modeling of fat. This is necessary because T2* decay, T1 recovery, and multispectral complexity of fat are processes which may otherwise bias the measurements. PMID:24123655

Quantitative analysis of image quality for acceptance and commissioning of an MRI simulator with a semiautomatic method.

PubMed

Chen, Xinyuan; Dai, Jianrong

2018-05-01

Magnetic Resonance Imaging (MRI) simulation differs from diagnostic MRI in purpose, technical requirements, and implementation. We propose a semiautomatic method for image acceptance and commissioning for the scanner, the radiofrequency (RF) coils, and pulse sequences for an MRI simulator. The ACR MRI accreditation large phantom was used for image quality analysis with seven parameters. Standard ACR sequences with a split head coil were adopted to examine the scanner's basic performance. The performance of simulation RF coils were measured and compared using the standard sequence with different clinical diagnostic coils. We used simulation sequences with simulation coils to test the quality of image and advanced performance of the scanner. Codes and procedures were developed for semiautomatic image quality analysis. When using standard ACR sequences with a split head coil, image quality passed all ACR recommended criteria. The image intensity uniformity with a simulation RF coil decreased about 34% compared with the eight-channel diagnostic head coil, while the other six image quality parameters were acceptable. Those two image quality parameters could be improved to more than 85% by built-in intensity calibration methods. In the simulation sequences test, the contrast resolution was sensitive to the FOV and matrix settings. The geometric distortion of simulation sequences such as T1-weighted and T2-weighted images was well-controlled in the isocenter and 10 cm off-center within a range of ±1% (2 mm). We developed a semiautomatic image quality analysis method for quantitative evaluation of images and commissioning of an MRI simulator. The baseline performances of simulation RF coils and pulse sequences have been established for routine QA. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

An update on risk factors for cartilage loss in knee osteoarthritis assessed using MRI-based semiquantitative grading methods.

PubMed

Alizai, Hamza; Roemer, Frank W; Hayashi, Daichi; Crema, Michel D; Felson, David T; Guermazi, Ali

2015-03-01

Arthroscopy-based semiquantitative scoring systems such as Outerbridge and Noyes' scores were the first to be developed for the purpose of grading cartilage defects. As magnetic resonance imaging (MRI) became available for evaluation of the osteoarthritic knee joint, these systems were adapted for use with MRI. Later on, grading methods such as the Whole Organ Magnetic Resonance Score, the Boston-Leeds Osteoarthritis Knee Score and the MRI Osteoarthritis Knee Score were designed specifically for performing whole-organ assessment of the knee joint structures, including cartilage. Cartilage grades on MRI obtained with these scoring systems represent optimal outcome measures for longitudinal studies, and are designed to enhance understanding of the knee osteoarthritis disease process. The purpose of this narrative review is to describe cartilage assessment in knee osteoarthritis using currently available MRI-based semiquantitative whole-organ scoring systems, and to provide an update on the risk factors for cartilage loss in knee osteoarthritis as assessed with these scoring systems.

A quantitative comparison of two methods to correct eddy current-induced distortions in DT-MRI.

PubMed

Muñoz Maniega, Susana; Bastin, Mark E; Armitage, Paul A

2007-04-01

Eddy current-induced geometric distortions of single-shot, diffusion-weighted, echo-planar (DW-EP) images are a major confounding factor to the accurate determination of water diffusion parameters in diffusion tensor MRI (DT-MRI). Previously, it has been suggested that these geometric distortions can be removed from brain DW-EP images using affine transformations determined from phantom calibration experiments using iterative cross-correlation (ICC). Since this approach was first described, a number of image-based registration methods have become available that can also correct eddy current-induced distortions in DW-EP images. However, as yet no study has investigated whether separate eddy current calibration or image-based registration provides the most accurate way of removing these artefacts from DT-MRI data. Here we compare how ICC phantom calibration and affine FLIRT (http://www.fmrib.ox.ac.uk), a popular image-based multi-modal registration method that can correct both eddy current-induced distortions and bulk subject motion, perform when registering DW-EP images acquired with different slice thicknesses (2.8 and 5 mm) and b-values (1000 and 3000 s/mm(2)). With the use of consistency testing, it was found that ICC was a more robust algorithm for correcting eddy current-induced distortions than affine FLIRT, especially at high b-value and small slice thickness. In addition, principal component analysis demonstrated that the combination of ICC phantom calibration (to remove eddy current-induced distortions) with rigid body FLIRT (to remove bulk subject motion) provided a more accurate registration of DT-MRI data than that achieved by affine FLIRT.

Pharmacological MRI (phMRI) of the Human Central Nervous System.

PubMed

Lanfermann, H; Schindler, C; Jordan, J; Krug, N; Raab, P

2015-10-01

Pharmacological magnetic resonance imaging (phMRI) of the central nervous system (CNS) addresses the increasing demands in the biopharma industry for new methods that can accurately predict, as early as possible, whether novel CNS agents will be effective and safe. Imaging of physiological and molecular-level function can provide a more direct measure of a drug mechanism of action, enabling more predictive measures of drug activity. The availability of phMRI of the nervous system within the professional infrastructure of the Clinical Research Center (CRC) Hannover as proof of concept center ensures that advances in basic science progress swiftly into benefits for patients. Advanced standardized MRI techniques including quantitative MRI, kurtosis determination, functional MRI, and spectroscopic imaging of the entire brain are necessary for phMRI. As a result, MR scanners will evolve into high-precision measuring instruments for assessment of desirable and undesirable effects of drugs as the basic precondition for individually tailored therapy. The CRC's Imaging Unit with high-end large-scale equipment will allow the following unique opportunities: for example, identification of MR-based biomarkers to assess the effect of drugs (surrogate parameters), establishment of normal levels and reference ranges for MRI-based biomarkers, evaluation of the most relevant MRI sequences for drug monitoring in outpatient care. Another very important prerequisite for phMRI is the MHH Core Facility as the scientific and operational study unit of the CRC partner Hannover Medical School. This unit is responsible for the study coordination, conduction, complete study logistics, administration, and application of the quality assurance system based on required industry standards.

Data-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI.

PubMed

Featherstone, Adam K; O'Connor, James P B; Little, Ross A; Watson, Yvonne; Cheung, Sue; Babur, Muhammad; Williams, Kaye J; Matthews, Julian C; Parker, Geoff J M

2018-04-01

Previous work has shown that combining dynamic contrast-enhanced (DCE)-MRI and oxygen-enhanced (OE)-MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data-driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE-MRI data. DCE-MRI and OE-MRI were performed on nine U87 (glioblastoma) and seven Calu6 (non-small cell lung cancer) murine xenograft tumors. Area under the curve and principal component analysis features were calculated and clustered separately using Gaussian mixture modelling. Evaluation metrics were calculated to determine the optimum feature set and cluster number. Outputs were quantitatively compared with a previous non data-driven approach. The optimum method located six robustly identifiable clusters in the data, yielding tumor region maps with spatially contiguous regions in a rim-core structure, suggesting a biological basis. Mean within-cluster enhancement curves showed physiologically distinct, intuitive kinetics of enhancement. Regions of DCE/OE-MRI enhancement mismatch were located, and voxel categorization agreed well with the previous non data-driven approach (Cohen's kappa = 0.61, proportional agreement = 0.75). The proposed method locates similar regions to the previous published method of binarization of DCE/OE-MRI enhancement, but renders a finer segmentation of intra-tumoral oxygenation and perfusion. This could aid in understanding the tumor microenvironment and its heterogeneity. Magn Reson Med 79:2236-2245, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley

Fully automated processing of fMRI data in SPM: from MRI scanner to PACS.

PubMed

Maldjian, Joseph A; Baer, Aaron H; Kraft, Robert A; Laurienti, Paul J; Burdette, Jonathan H

2009-01-01

Here we describe the Wake Forest University Pipeline, a fully automated method for the processing of fMRI data using SPM. The method includes fully automated data transfer and archiving from the point of acquisition, real-time batch script generation, distributed grid processing, interface to SPM in MATLAB, error recovery and data provenance, DICOM conversion and PACS insertion. It has been used for automated processing of fMRI experiments, as well as for the clinical implementation of fMRI and spin-tag perfusion imaging. The pipeline requires no manual intervention, and can be extended to any studies requiring offline processing.

Teaching Dental Students to Understand the Temporomandibular Joint Using MRI: Comparison of Conventional and Digital Learning Methods.

PubMed

Arús, Nádia A; da Silva, Átila M; Duarte, Rogério; da Silveira, Priscila F; Vizzotto, Mariana B; da Silveira, Heraldo L D; da Silveira, Heloisa E D

2017-06-01

The aims of this study were to evaluate and compare the performance of dental students in interpreting the temporomandibular joint (TMJ) with magnetic resonance imaging (MRI) scans using two learning methods (conventional and digital interactive learning) and to examine the usability of the digital learning object (DLO). The DLO consisted of tutorials about MRI and anatomic and functional aspects of the TMJ. In 2014, dental students in their final year of study who were enrolled in the elective "MRI Interpretation of the TMJ" course comprised the study sample. After exclusions for nonattendance and other reasons, 29 of the initial 37 students participated in the study, for a participation rate of 78%. The participants were divided into two groups: a digital interactive learning group (n=14) and a conventional learning group (n=15). Both methods were assessed by an objective test applied before and after training and classes. Aspects such as support and training requirements, complexity, and consistency of the DLO were also evaluated using the System Usability Scale (SUS). A significant between-group difference in the posttest results was found, with the conventional learning group scoring better than the DLO group, indicated by mean scores of 9.20 and 8.11, respectively, out of 10. However, when the pretest and posttest results were compared, both groups showed significantly improved performance. The SUS score was 89, which represented a high acceptance of the DLO by the users. The students who used the conventional method of learning showed superior performance in interpreting the TMJ using MRI compared to the group that used digital interactive learning.

Cellular Imaging With MRI.

PubMed

Makela, Ashley V; Murrell, Donna H; Parkins, Katie M; Kara, Jenna; Gaudet, Jeffrey M; Foster, Paula J

2016-10-01

Cellular magnetic resonance imaging (MRI) is an evolving field of imaging with strong translational and research potential. The ability to detect, track, and quantify cells in vivo and over time allows for studying cellular events related to disease processes and may be used as a biomarker for decisions about treatments and for monitoring responses to treatments. In this review, we discuss methods for labeling cells, various applications for cellular MRI, the existing limitations, strategies to address these shortcomings, and clinical cellular MRI.

A New Method for Preparing Mesenchymal Stem Cells and Labeling with Ferumoxytol for Cell Tracking by MRI.

PubMed

Liu, Li; Tseng, Lanya; Ye, Qing; Wu, Yijen L; Bain, Daniel J; Ho, Chien

2016-05-18

Mesenchymal stem cells (MSCs) are among the major stem cells used for cell therapy and regenerative medicine. In-vivo cell-tracking by magnetic resonance imaging (MRI) is crucial for regenerative medicine, allowing verification that the transplanted cells reach the targeted sites. Cellular MRI combined with superparamagnetic iron-oxide (SPIO) contrast agents is an effective cell-tracking method. Here, we are reporting a new "bio-mimicry" method by making use of the "in-vivo environment" of MSCs to prepare native MSCs, so that (i) the phagocytic activity of cultured MSCs can be recovered and expanded MSCs can be ex-vivo labeled with Ferumoxytol, which is currently the only FDA approved SPIO nanoparticles for human use. Using our new method, 7-day cultured MSCs regain the capability to take up Ferumoxytol and exhibit an intracellular iron concentration of 2.50 ± 0.50 pg/MSC, comparable to that obtained by using Ferumoxytol-heparin-protamine nanocomplex; and (ii) cells can be re-sized to more native size, reducing from 32.0 ± 7.2 μm to 19.5 ± 5.2 μm. Our method can be very useful for expanding MSCs and labeling with Ferumoxytol, without the need for transfection agents and/or electroporation, allowing cell-tracking by MRI in both pre-clinical and clinical studies.

A New Method for Preparing Mesenchymal Stem Cells and Labeling with Ferumoxytol for Cell Tracking by MRI

PubMed Central

Liu, Li; Tseng, Lanya; Ye, Qing; Wu, Yijen L.; Bain, Daniel J.; Ho, Chien

2016-01-01

Mesenchymal stem cells (MSCs) are among the major stem cells used for cell therapy and regenerative medicine. In-vivo cell-tracking by magnetic resonance imaging (MRI) is crucial for regenerative medicine, allowing verification that the transplanted cells reach the targeted sites. Cellular MRI combined with superparamagnetic iron-oxide (SPIO) contrast agents is an effective cell-tracking method. Here, we are reporting a new “bio-mimicry” method by making use of the “in-vivo environment” of MSCs to prepare native MSCs, so that (i) the phagocytic activity of cultured MSCs can be recovered and expanded MSCs can be ex-vivo labeled with Ferumoxytol, which is currently the only FDA approved SPIO nanoparticles for human use. Using our new method, 7-day cultured MSCs regain the capability to take up Ferumoxytol and exhibit an intracellular iron concentration of 2.50 ± 0.50 pg/MSC, comparable to that obtained by using Ferumoxytol-heparin-protamine nanocomplex; and (ii) cells can be re-sized to more native size, reducing from 32.0 ± 7.2 μm to 19.5 ± 5.2 μm. Our method can be very useful for expanding MSCs and labeling with Ferumoxytol, without the need for transfection agents and/or electroporation, allowing cell-tracking by MRI in both pre-clinical and clinical studies. PMID:27188664

SU-D-207A-06: Pediatric Abdominal Organ Motion Quantified Via a Novel 4D MRI Method

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

Uh, J; Krasin, MJ; Lucas, JT

Purpose: To develop a 4D MRI method for assessing respiration-induced abdominal organ motion in children receiving radiation therapy. Methods: A 4D MRI using internal image-based respiratory surrogate has been developed and implemented on a clinical scanner (1.5T Siemens Avanto). Ten patients (younger group: N=6, 2–5 years, anesthetized; older group: N=4, 11–15 years) with neuroblastoma, Wilm’s tumor rhabdomyosarcoma, or desmoplastic small round cell tumor received free breathing 4D MRI scans for treatment planning. Coronal image slices of the entire abdomen were retrospectively constructed in 10 respiratory phases. A B-spline deformable registration (Metz et al. 2011) was performed on 4D datasets tomore » automatically derive motion trajectories of selected anatomical landmarks, including the dome and the center of the liver, and the superior edges of kidneys and spleen. The extents of the motion in three dimensions (anteroposterior, AP; mediolateral, ML; superoinferior, SI) and the correlations between organ motion trajectories were quantified. Results: The 4D MRI scans were successfully performed in <20 minutes for all patients without the use of any external device. Organ motion extents were larger in adolescents (kidneys: 3–13 mm SI, liver and spleen: 6–18 mm SI) than in younger children (kidneys:<3mm in all directions; liver and spleen: 1–8 mm SI, 1–5 mm ML and AP). The magnitude of respiratory motion in some adolescents may warrant special motion management. Motion trajectories were not synchronized across selected anatomical landmarks, particularly in the ML and AP directions, indicating inter- and intra-organ variations of the respiratory-induced motion. Conclusion: The developed 4D MRI acquisition and motion analysis methods provide a non-ionizing, non-invasive approach to automatically measure the organ motion trajectory in the pediatric abdomen. It is useful for defining ITV and PRV, monitoring changes in target motion patterns during

Appraising the Role of Iron in Brain Aging and Cognition: Promises and Limitations of MRI Methods

PubMed Central

Daugherty, Ana M; Raz, Naftali

2015-01-01

Age-related increase in frailty is accompanied by a fundamental shift in cellular iron homeostasis. By promoting oxidative stress, the intracellular accumulation of non-heme iron outside of binding complexes contributes to chronic inflammation and interferes with normal brain metabolism. In the absence of direct non-invasive biomarkers of brain oxidative stress, iron accumulation estimated in vivo may serve as its proxy indicator. Hence, developing reliable in vivo measurements of brain iron content via magnetic resonance imaging (MRI) is of significant interest in human neuroscience. To date, by estimating brain iron content through various MRI methods, significant age differences and age-related increases in iron content of the basal ganglia have been revealed across multiple samples. Less consistent are the findings that pertain to the relationship between elevated brain iron content and systemic indices of vascular and metabolic dysfunction. Only a handful of cross-sectional investigations have linked high iron content in various brain regions and poor performance on assorted cognitive tests. The even fewer longitudinal studies indicate that iron accumulation may precede shrinkage of the basal ganglia and thus predict poor maintenance of cognitive functions. This rapidly developing field will benefit from introduction of higher-field MRI scanners, improvement in iron-sensitive and -specific acquisition sequences and post-processing analytic and computational methods, as well as accumulation of data from long-term longitudinal investigations. This review describes the potential advantages and promises of MRI-based assessment of brain iron, summarizes recent findings and highlights the limitations of the current methodology. PMID:26248580

An MRI-Compatible Robotic System With Hybrid Tracking for MRI-Guided Prostate Intervention

PubMed Central

Krieger, Axel; Iordachita, Iulian I.; Guion, Peter; Singh, Anurag K.; Kaushal, Aradhana; Ménard, Cynthia; Pinto, Peter A.; Camphausen, Kevin; Fichtinger, Gabor

2012-01-01

This paper reports the development, evaluation, and first clinical trials of the access to the prostate tissue (APT) II system—a scanner independent system for magnetic resonance imaging (MRI)-guided transrectal prostate interventions. The system utilizes novel manipulator mechanics employing a steerable needle channel and a novel six degree-of-freedom hybrid tracking method, comprising passive fiducial tracking for initial registration and subsequent incremental motion measurements. Targeting accuracy of the system in prostate phantom experiments and two clinical human-subject procedures is shown to compare favorably with existing systems using passive and active tracking methods. The portable design of the APT II system, using only standard MRI image sequences and minimal custom scanner interfacing, allows the system to be easily used on different MRI scanners. PMID:22009867

MRI-Based Nonrigid Motion Correction in Simultaneous PET/MRI

PubMed Central

Chun, Se Young; Reese, Timothy G.; Ouyang, Jinsong; Guerin, Bastien; Catana, Ciprian; Zhu, Xuping; Alpert, Nathaniel M.; El Fakhri, Georges

2014-01-01

Respiratory and cardiac motion is the most serious limitation to whole-body PET, resulting in spatial resolution close to 1 cm. Furthermore, motion-induced inconsistencies in the attenuation measurements often lead to significant artifacts in the reconstructed images. Gating can remove motion artifacts at the cost of increased noise. This paper presents an approach to respiratory motion correction using simultaneous PET/MRI to demonstrate initial results in phantoms, rabbits, and nonhuman primates and discusses the prospects for clinical application. Methods Studies with a deformable phantom, a free-breathing primate, and rabbits implanted with radioactive beads were performed with simultaneous PET/MRI. Motion fields were estimated from concurrently acquired tagged MR images using 2 B-spline nonrigid image registration methods and incorporated into a PET list-mode ordered-subsets expectation maximization algorithm. Using the measured motion fields to transform both the emission data and the attenuation data, we could use all the coincidence data to reconstruct any phase of the respiratory cycle. We compared the resulting SNR and the channelized Hotelling observer (CHO) detection signal-to-noise ratio (SNR) in the motion-corrected reconstruction with the results obtained from standard gating and uncorrected studies. Results Motion correction virtually eliminated motion blur without reducing SNR, yielding images with SNR comparable to those obtained by gating with 5–8 times longer acquisitions in all studies. The CHO study in dynamic phantoms demonstrated a significant improvement (166%–276%) in lesion detection SNR with MRI-based motion correction as compared with gating (P < 0.001). This improvement was 43%–92% for large motion compared with lesion detection without motion correction (P < 0.001). CHO SNR in the rabbit studies confirmed these results. Conclusion Tagged MRI motion correction in simultaneous PET/MRI significantly improves lesion detection

Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods

NASA Astrophysics Data System (ADS)

Maximov, Ivan I.; Vinding, Mads S.; Tse, Desmond H. Y.; Nielsen, Niels Chr.; Shah, N. Jon

2015-05-01

There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community.

Emerging MRI Methods in Translational Cardiovascular Research

PubMed Central

Vandsburger, Moriel H; Epstein, Frederick H

2011-01-01

Cardiac magnetic resonance imaging (CMR) has become a reference standard modality for imaging of left ventricular (LV) structure and function, and, using late gadolinium enhancement, for imaging myocardial infarction. Emerging CMR techniques enable a more comprehensive examination of the heart, making CMR an excellent tool for use in translational cardiovascular research. Specifically, emerging CMR methods have been developed to measure the extent of myocardial edema, changes in ventricular mechanics, changes in tissue composition as a result of fibrosis, and changes in myocardial perfusion as a function of both disease and infarct healing. New CMR techniques also enable the tracking of labeled cells, molecular imaging of biomarkers of disease, and changes in calcium flux in cardiomyocytes. In addition, MRI can quantify blood flow velocity and wall shear stress in large blood vessels. Almost all of these techniques can be applied in both pre-clinical and clinical settings, enabling both the techniques themselves and the knowledge gained using such techniques in pre-clinical research to be translated from the lab bench to the patient bedside. PMID:21452060

Feasibility study on 3D image reconstruction from 2D orthogonal cine-MRI for MRI-guided radiotherapy.

PubMed

Paganelli, Chiara; Lee, Danny; Kipritidis, John; Whelan, Brendan; Greer, Peter B; Baroni, Guido; Riboldi, Marco; Keall, Paul

2018-02-11

In-room MRI is a promising image guidance strategy in external beam radiotherapy to acquire volumetric information for moving targets. However, limitations in spatio-temporal resolution led several authors to use 2D orthogonal images for guidance. The aim of this work is to present a method to concurrently compensate for non-rigid tumour motion and provide an approach for 3D reconstruction from 2D orthogonal cine-MRI slices for MRI-guided treatments. Free-breathing sagittal/coronal interleaved 2D cine-MRI were acquired in addition to a pre-treatment 3D volume in two patients. We performed deformable image registration (DIR) between cine-MRI slices and corresponding slices in the pre-treatment 3D volume. Based on an extrapolation of the interleaved 2D motion fields, the 3D motion field was estimated and used to warp the pre-treatment volume. Due to the lack of a ground truth for patients, the method was validated on a digital 4D lung phantom. On the phantom, the 3D reconstruction method was able to compensate for tumour motion and compared favourably to the results of previously adopted strategies. The difference in the 3D motion fields between the phantom and the extrapolated motion was 0.4 ± 0.3 mm for tumour and 0.8 ± 1.5 mm for whole anatomy, demonstrating feasibility of performing a 3D volumetric reconstruction directly from 2D orthogonal cine-MRI slices. Application of the method to patient data confirmed the feasibility of utilizing this method in real world scenarios. Preliminary results on phantom and patient cases confirm the feasibility of the proposed approach in an MRI-guided scenario, especially for non-rigid tumour motion compensation. © 2018 The Royal Australian and New Zealand College of Radiologists.

Cardiac MRI in patients with complex CHD following primary or secondary implantation of MRI-conditional pacemaker system.

PubMed

Al-Wakeel, Nadya; O h-Ici, Darach; Schmitt, Katharina R; Messroghli, Daniel R; Riesenkampff, Eugénie; Berger, Felix; Kuehne, Titus; Peters, Bjoern

2016-02-01

In patients with CHD, cardiac MRI is often indicated for functional and anatomical assessment. With the recent introduction of MRI-conditional pacemaker systems, cardiac MRI has become accessible for patients with pacemakers. The present clinical study aims to evaluate safety, susceptibility artefacts, and image reading of cardiac MRI in patients with CHD and MRI-conditional pacemaker systems. Material and methods CHD patients with MRI-conditional pacemaker systems and a clinical need for cardiac MRI were examined with a 1.5-T MRI system. Lead function was tested before and after MRI. Artefacts and image readings were evaluated using a four-point grading scale. A total of nine patients with CHD (mean age 34.0 years, range 19.5-53.6 years) received a total of 11 cardiac MRI examinations. Owing to clinical indications, seven patients had previously been converted from conventional to MRI-conditional pacemaker systems. All MRI examinations were completed without adverse effects. Device testing immediately after MRI and at follow-up showed no alteration of pacemaker device and lead function. Clinical questions could be addressed and answered in all patients. Cardiac MRI can be performed safely with high certainty of diagnosis in CHD patients with MRI-conditional pacemaker systems. In case of clinically indicated lead and box changing, CHD patients with non-MRI-conditional pacemaker systems should be considered for complete conversion to MRI-conditional systems.

Optogenetic Functional MRI

PubMed Central

Lin, Peter; Fang, Zhongnan; Liu, Jia; Lee, Jin Hyung

2016-01-01

The investigation of the functional connectivity of precise neural circuits across the entire intact brain can be achieved through optogenetic functional magnetic resonance imaging (ofMRI), which is a novel technique that combines the relatively high spatial resolution of high-field fMRI with the precision of optogenetic stimulation. Fiber optics that enable delivery of specific wavelengths of light deep into the brain in vivo are implanted into regions of interest in order to specifically stimulate targeted cell types that have been genetically induced to express light-sensitive trans-membrane conductance channels, called opsins. fMRI is used to provide a non-invasive method of determining the brain's global dynamic response to optogenetic stimulation of specific neural circuits through measurement of the blood-oxygen-level-dependent (BOLD) signal, which provides an indirect measurement of neuronal activity. This protocol describes the construction of fiber optic implants, the implantation surgeries, the imaging with photostimulation and the data analysis required to successfully perform ofMRI. In summary, the precise stimulation and whole-brain monitoring ability of ofMRI are crucial factors in making ofMRI a powerful tool for the study of the connectomics of the brain in both healthy and diseased states. PMID:27167840

An accurate segmentation method for volumetry of brain tumor in 3D MRI

NASA Astrophysics Data System (ADS)

Wang, Jiahui; Li, Qiang; Hirai, Toshinori; Katsuragawa, Shigehiko; Li, Feng; Doi, Kunio

2008-03-01

Accurate volumetry of brain tumors in magnetic resonance imaging (MRI) is important for evaluating the interval changes in tumor volumes during and after treatment, and also for planning of radiation therapy. In this study, an automated volumetry method for brain tumors in MRI was developed by use of a new three-dimensional (3-D) image segmentation technique. First, the central location of a tumor was identified by a radiologist, and then a volume of interest (VOI) was determined automatically. To substantially simplify tumor segmentation, we transformed the 3-D image of the tumor into a two-dimensional (2-D) image by use of a "spiral-scanning" technique, in which a radial line originating from the center of the tumor scanned the 3-D image spirally from the "north pole" to the "south pole". The voxels scanned by the radial line provided a transformed 2-D image. We employed dynamic programming to delineate an "optimal" outline of the tumor in the transformed 2-D image. We then transformed the optimal outline back into 3-D image space to determine the volume of the tumor. The volumetry method was trained and evaluated by use of 16 cases with 35 brain tumors. The agreement between tumor volumes provided by computer and a radiologist was employed as a performance metric. Our method provided relatively accurate results with a mean agreement value of 88%.

Optimizing methods for linking cinematic features to fMRI data.

PubMed

Kauttonen, Janne; Hlushchuk, Yevhen; Tikka, Pia

2015-04-15

One of the challenges of naturalistic neurosciences using movie-viewing experiments is how to interpret observed brain activations in relation to the multiplicity of time-locked stimulus features. As previous studies have shown less inter-subject synchronization across viewers of random video footage than story-driven films, new methods need to be developed for analysis of less story-driven contents. To optimize the linkage between our fMRI data collected during viewing of a deliberately non-narrative silent film 'At Land' by Maya Deren (1944) and its annotated content, we combined the method of elastic-net regularization with the model-driven linear regression and the well-established data-driven independent component analysis (ICA) and inter-subject correlation (ISC) methods. In the linear regression analysis, both IC and region-of-interest (ROI) time-series were fitted with time-series of a total of 36 binary-valued and one real-valued tactile annotation of film features. The elastic-net regularization and cross-validation were applied in the ordinary least-squares linear regression in order to avoid over-fitting due to the multicollinearity of regressors, the results were compared against both the partial least-squares (PLS) regression and the un-regularized full-model regression. Non-parametric permutation testing scheme was applied to evaluate the statistical significance of regression. We found statistically significant correlation between the annotation model and 9 ICs out of 40 ICs. Regression analysis was also repeated for a large set of cubic ROIs covering the grey matter. Both IC- and ROI-based regression analyses revealed activations in parietal and occipital regions, with additional smaller clusters in the frontal lobe. Furthermore, we found elastic-net based regression more sensitive than PLS and un-regularized regression since it detected a larger number of significant ICs and ROIs. Along with the ISC ranking methods, our regression analysis proved

Spatially constrained incoherent motion method improves diffusion-weighted MRI signal decay analysis in the liver and spleen

PubMed Central

Taimouri, Vahid; Afacan, Onur; Perez-Rossello, Jeannette M.; Callahan, Michael J.; Mulkern, Robert V.; Warfield, Simon K.; Freiman, Moti

2015-01-01

Purpose: To evaluate the effect of the spatially constrained incoherent motion (SCIM) method on improving the precision and robustness of fast and slow diffusion parameter estimates from diffusion-weighted MRI in liver and spleen in comparison to the independent voxel-wise intravoxel incoherent motion (IVIM) model. Methods: We collected diffusion-weighted MRI (DW-MRI) data of 29 subjects (5 healthy subjects and 24 patients with Crohn’s disease in the ileum). We evaluated parameters estimates’ robustness against different combinations of b-values (i.e., 4 b-values and 7 b-values) by comparing the variance of the estimates obtained with the SCIM and the independent voxel-wise IVIM model. We also evaluated the improvement in the precision of parameter estimates by comparing the coefficient of variation (CV) of the SCIM parameter estimates to that of the IVIM. Results: The SCIM method was more robust compared to IVIM (up to 70% in liver and spleen) for different combinations of b-values. Also, the CV values of the parameter estimations using the SCIM method were significantly lower compared to repeated acquisition and signal averaging estimated using IVIM, especially for the fast diffusion parameter in liver (CVIV IM = 46.61 ± 11.22, CVSCIM = 16.85 ± 2.160, p < 0.001) and spleen (CVIV IM = 95.15 ± 19.82, CVSCIM = 52.55 ± 1.91, p < 0.001). Conclusions: The SCIM method characterizes fast and slow diffusion more precisely compared to the independent voxel-wise IVIM model fitting in the liver and spleen. PMID:25832079

Individualized Functional Parcellation of the Human Amygdala Using a Semi-supervised Clustering Method: A 7T Resting State fMRI Study.

PubMed

Zhang, Xianchang; Cheng, Hewei; Zuo, Zhentao; Zhou, Ke; Cong, Fei; Wang, Bo; Zhuo, Yan; Chen, Lin; Xue, Rong; Fan, Yong

2018-01-01

The amygdala plays an important role in emotional functions and its dysfunction is considered to be associated with multiple psychiatric disorders in humans. Cytoarchitectonic mapping has demonstrated that the human amygdala complex comprises several subregions. However, it's difficult to delineate boundaries of these subregions in vivo even if using state of the art high resolution structural MRI. Previous attempts to parcellate this small structure using unsupervised clustering methods based on resting state fMRI data suffered from the low spatial resolution of typical fMRI data, and it remains challenging for the unsupervised methods to define subregions of the amygdala in vivo . In this study, we developed a novel brain parcellation method to segment the human amygdala into spatially contiguous subregions based on 7T high resolution fMRI data. The parcellation was implemented using a semi-supervised spectral clustering (SSC) algorithm at an individual subject level. Under guidance of prior information derived from the Julich cytoarchitectonic atlas, our method clustered voxels of the amygdala into subregions according to similarity measures of their functional signals. As a result, three distinct amygdala subregions can be obtained in each hemisphere for every individual subject. Compared with the cytoarchitectonic atlas, our method achieved better performance in terms of subregional functional homogeneity. Validation experiments have also demonstrated that the amygdala subregions obtained by our method have distinctive, lateralized functional connectivity (FC) patterns. Our study has demonstrated that the semi-supervised brain parcellation method is a powerful tool for exploring amygdala subregional functions.

A Method for Safety Testing of Radiofrequency/Microwave-Emitting Devices Using MRI

PubMed Central

Alon, Leeor; Cho, Gene Y.; Yang, Xing; Sodickson, Daniel K.; Deniz, Cem M.

2015-01-01

Purpose Strict regulations are imposed on the amount of radiofrequency (RF) energy that devices can emit to prevent excessive deposition of RF energy into the body. In this study, we investigated the application of MR temperature mapping and 10-g average specific absorption rate (SAR) computation for safety evaluation of RF-emitting devices. Methods Quantification of the RF power deposition was shown for an MRI-compatible dipole antenna and a non–MRI-compatible mobile phone via phantom temperature change measurements. Validation of the MR temperature mapping method was demonstrated by comparison with physical temperature measurements and electromagnetic field simulations. MR temperature measurements alongside physical property measurements were used to reconstruct 10-g average SAR. Results The maximum temperature change for a dipole antenna and the maximum 10-g average SAR were 1.83° C and 12.4 W/kg, respectively, for simulations and 1.73° C and 11.9 W/kg, respectively, for experiments. The difference between MR and probe thermometry was <0.15° C. The maximum temperature change and the maximum 10-g average SAR for a cell phone radiating at maximum output for 15 min was 1.7° C and 0.54 W/kg, respectively. Conclusion Information acquired using MR temperature mapping and thermal property measurements can assess RF/microwave safety with high resolution and fidelity. PMID:25424724

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods

PubMed Central

de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C. W.; Petersen, Esben T.; De Vis, Jill B.

2018-01-01

Objective In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T1-based brain segmentation methods. Materials and methods Ten healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice with repositioning in between. The scan protocol consisted of a low resolution (LR) CSF sequence (0:57min), a high resolution (HR) CSF sequence (3:21min) and a 3D T1-weighted sequence (6:47min). Data of the HR 3D-T1-weighted images were downsampled to obtain LR T1-weighted images (reconstructed imaging time: 1:59 min). Data of the CSF MRI sequences was automatically segmented using in-house software. The 3D T1-weighted images were segmented using FSL (5.0), SPM12 and FreeSurfer (5.3.0). Results The mean absolute differences for BPV and ICV between the first and second scan for CSF LR (BPV/ICV: 12±9/7±4cc) and CSF HR (5±5/4±2cc) were comparable to FSL HR (9±11/19±23cc), FSL LR (7±4, 6±5cc), FreeSurfer HR (5±3/14±8cc), FreeSurfer LR (9±8, 12±10cc), and SPM HR (5±3/4±7cc), and SPM LR (5±4, 5±3cc). The correlation between the measured volumes of the CSF sequences and that measured by FSL, FreeSurfer and SPM HR and LR was very good (all Pearson’s correlation coefficients >0.83, R2 .67–.97). The results from the downsampled data and the high-resolution data were similar. Conclusion Both CSF MRI sequences have a precision comparable to, and a very good correlation with established 3D T1-based automated segmentations methods for the segmentation of BPV and ICV. However, the short imaging time of the fast CSF MRI sequence is superior to the 3D T1 sequence on which

[MRI semiotics features of experimental acute intracerebral hematomas].

PubMed

Burenchev, D V; Skvortsova, V I; Tvorogova, T V; Guseva, O I; Gubskiĭ, L V; Kupriianov, D A; Pirogov, Iu A

2009-01-01

The aim of this study was to assess the possibility of revealing intracerebral hematomas (ICH), using MRI, within the first hours after onset and to determine their MRI semiotics features. Thirty animals with experimental ICH were studied. A method of two-stage introduction of autologous blood was used to develop ICH as human spontaneous intracranial hematomas. Within 3-5h after blood introduction to the rat brain. The control MRI was performed in the 3rd and 7th days after blood injections. ICH were definitely identified in the first MRI scans. The MRI semiotics features of acute ICH and their transformations were assessed. The high sensitivity of MRI to ICH as well as the uniform manifestations in all animals were shown. In conclusion, the method has high specificity for acute ICH detection.

Dictionary learning and time sparsity in dynamic MRI.

PubMed

Caballero, Jose; Rueckert, Daniel; Hajnal, Joseph V

2012-01-01

Sparse representation methods have been shown to tackle adequately the inherent speed limits of magnetic resonance imaging (MRI) acquisition. Recently, learning-based techniques have been used to further accelerate the acquisition of 2D MRI. The extension of such algorithms to dynamic MRI (dMRI) requires careful examination of the signal sparsity distribution among the different dimensions of the data. Notably, the potential of temporal gradient (TG) sparsity in dMRI has not yet been explored. In this paper, a novel method for the acceleration of cardiac dMRI is presented which investigates the potential benefits of enforcing sparsity constraints on patch-based learned dictionaries and TG at the same time. We show that an algorithm exploiting sparsity on these two domains can outperform previous sparse reconstruction techniques.

Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods.

PubMed

Maximov, Ivan I; Vinding, Mads S; Tse, Desmond H Y; Nielsen, Niels Chr; Shah, N Jon

2015-05-01

There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community. Copyright © 2015 Elsevier Inc. All rights reserved.

Delayed gadolinium-enhanced MRI of cartilage and T2 mapping for evaluation of reparative cartilage-like tissue after autologous chondrocyte implantation associated with Atelocollagen-based scaffold in the knee.

PubMed

Tadenuma, Taku; Uchio, Yuji; Kumahashi, Nobuyuki; Fukuba, Eiji; Kitagaki, Hajime; Iwasa, Junji; Ochi, Mitsuo

2016-10-01

To elucidate the quality of tissue-engineered cartilage after an autologous chondrocyte implantation (ACI) technique with Atelocollagen gel as a scaffold in the knee in the short- to midterm postoperatively, we assessed delayed gadolinium-enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC) and T2 mapping and clarified the relationship between T1 and T2 values and clinical results. In this cross-sectional study, T1 and T2 mapping were performed on 11 knees of 8 patients (mean age at ACI, 37.2 years) with a 3.0-T MRI scanner. T1implant and T2implant values were compared with those of the control cartilage region (T1control and T2control). Lysholm scores were also assessed for clinical evaluation. The relationships between the T1 and T2 values and the clinical Lysholm score were also assessed. There were no significant differences in the T1 values between the T1implant (386.64 ± 101.78 ms) and T1control (375.82 ± 62.89 ms) at the final follow-up. The implants showed significantly longer T2 values compared to the control cartilage (53.83 ± 13.89 vs. 38.21 ± 4.43 ms). The postoperative Lysholm scores were significantly higher than the preoperative scores. A significant correlation was observed between T1implant and clinical outcomes, but not between T2implant and clinical outcomes. Third-generation ACI implants might have obtained an almost equivalent glycosaminoglycan concentration compared to the normal cartilage, but they had lower collagen density at least 3 years after transplantation. The T1implant value, but not the T2 value, might be a predictor of clinical outcome after ACI.

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods.

PubMed

van der Kleij, Lisa A; de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C W; Petersen, Esben T; De Vis, Jill B

2018-01-01

In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T1-based brain segmentation methods. Ten healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice with repositioning in between. The scan protocol consisted of a low resolution (LR) CSF sequence (0:57min), a high resolution (HR) CSF sequence (3:21min) and a 3D T1-weighted sequence (6:47min). Data of the HR 3D-T1-weighted images were downsampled to obtain LR T1-weighted images (reconstructed imaging time: 1:59 min). Data of the CSF MRI sequences was automatically segmented using in-house software. The 3D T1-weighted images were segmented using FSL (5.0), SPM12 and FreeSurfer (5.3.0). The mean absolute differences for BPV and ICV between the first and second scan for CSF LR (BPV/ICV: 12±9/7±4cc) and CSF HR (5±5/4±2cc) were comparable to FSL HR (9±11/19±23cc), FSL LR (7±4, 6±5cc), FreeSurfer HR (5±3/14±8cc), FreeSurfer LR (9±8, 12±10cc), and SPM HR (5±3/4±7cc), and SPM LR (5±4, 5±3cc). The correlation between the measured volumes of the CSF sequences and that measured by FSL, FreeSurfer and SPM HR and LR was very good (all Pearson's correlation coefficients >0.83, R2 .67-.97). The results from the downsampled data and the high-resolution data were similar. Both CSF MRI sequences have a precision comparable to, and a very good correlation with established 3D T1-based automated segmentations methods for the segmentation of BPV and ICV. However, the short imaging time of the fast CSF MRI sequence is superior to the 3D T1 sequence on which segmentation with established methods is performed.

A comparison of five standard methods for evaluating image intensity uniformity in partially parallel imaging MRI

PubMed Central

Goerner, Frank L.; Duong, Timothy; Stafford, R. Jason; Clarke, Geoffrey D.

2013-01-01

Purpose: To investigate the utility of five different standard measurement methods for determining image uniformity for partially parallel imaging (PPI) acquisitions in terms of consistency across a variety of pulse sequences and reconstruction strategies. Methods: Images were produced with a phantom using a 12-channel head matrix coil in a 3T MRI system (TIM TRIO, Siemens Medical Solutions, Erlangen, Germany). Images produced using echo-planar, fast spin echo, gradient echo, and balanced steady state free precession pulse sequences were evaluated. Two different PPI reconstruction methods were investigated, generalized autocalibrating partially parallel acquisition algorithm (GRAPPA) and modified sensitivity-encoding (mSENSE) with acceleration factors (R) of 2, 3, and 4. Additionally images were acquired with conventional, two-dimensional Fourier imaging methods (R = 1). Five measurement methods of uniformity, recommended by the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) were considered. The methods investigated were (1) an ACR method and a (2) NEMA method for calculating the peak deviation nonuniformity, (3) a modification of a NEMA method used to produce a gray scale uniformity map, (4) determining the normalized absolute average deviation uniformity, and (5) a NEMA method that focused on 17 areas of the image to measure uniformity. Changes in uniformity as a function of reconstruction method at the same R-value were also investigated. Two-way analysis of variance (ANOVA) was used to determine whether R-value or reconstruction method had a greater influence on signal intensity uniformity measurements for partially parallel MRI. Results: Two of the methods studied had consistently negative slopes when signal intensity uniformity was plotted against R-value. The results obtained comparing mSENSE against GRAPPA found no consistent difference between GRAPPA and mSENSE with regard to signal intensity uniformity

PCA-based groupwise image registration for quantitative MRI.

PubMed

Huizinga, W; Poot, D H J; Guyader, J-M; Klaassen, R; Coolen, B F; van Kranenburg, M; van Geuns, R J M; Uitterdijk, A; Polfliet, M; Vandemeulebroucke, J; Leemans, A; Niessen, W J; Klein, S

2016-04-01

Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as

Comparison of fMRI analysis methods for heterogeneous BOLD responses in block design studies.

PubMed

Liu, Jia; Duffy, Ben A; Bernal-Casas, David; Fang, Zhongnan; Lee, Jin Hyung

2017-02-15

A large number of fMRI studies have shown that the temporal dynamics of evoked BOLD responses can be highly heterogeneous. Failing to model heterogeneous responses in statistical analysis can lead to significant errors in signal detection and characterization and alter the neurobiological interpretation. However, to date it is not clear that, out of a large number of options, which methods are robust against variability in the temporal dynamics of BOLD responses in block-design studies. Here, we used rodent optogenetic fMRI data with heterogeneous BOLD responses and simulations guided by experimental data as a means to investigate different analysis methods' performance against heterogeneous BOLD responses. Evaluations are carried out within the general linear model (GLM) framework and consist of standard basis sets as well as independent component analysis (ICA). Analyses show that, in the presence of heterogeneous BOLD responses, conventionally used GLM with a canonical basis set leads to considerable errors in the detection and characterization of BOLD responses. Our results suggest that the 3rd and 4th order gamma basis sets, the 7th to 9th order finite impulse response (FIR) basis sets, the 5th to 9th order B-spline basis sets, and the 2nd to 5th order Fourier basis sets are optimal for good balance between detection and characterization, while the 1st order Fourier basis set (coherence analysis) used in our earlier studies show good detection capability. ICA has mostly good detection and characterization capabilities, but detects a large volume of spurious activation with the control fMRI data. Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluation of MRI acquisition workflow with lean six sigma method: case study of liver and knee examinations.

PubMed

Roth, Christopher J; Boll, Daniel T; Wall, Lisa K; Merkle, Elmar M

2010-08-01

The purpose of this investigation was to assess workflow for medical imaging studies, specifically comparing liver and knee MRI examinations by use of the Lean Six Sigma methodologic framework. The hypothesis tested was that the Lean Six Sigma framework can be used to quantify MRI workflow and to identify sources of inefficiency to target for sequence and protocol improvement. Audio-video interleave streams representing individual acquisitions were obtained with graphic user interface screen capture software in the examinations of 10 outpatients undergoing MRI of the liver and 10 outpatients undergoing MRI of the knee. With Lean Six Sigma methods, the audio-video streams were dissected into value-added time (true image data acquisition periods), business value-added time (time spent that provides no direct patient benefit but is requisite in the current system), and non-value-added time (scanner inactivity while awaiting manual input). For overall MRI table time, value-added time was 43.5% (range, 39.7-48.3%) of the time for liver examinations and 89.9% (range, 87.4-93.6%) for knee examinations. Business value-added time was 16.3% of the table time for the liver and 4.3% of the table time for the knee examinations. Non-value-added time was 40.2% of the overall table time for the liver and 5.8% for the knee examinations. Liver MRI examinations consume statistically significantly more non-value-added and business value-added times than do knee examinations, primarily because of respiratory command management and contrast administration. Workflow analyses and accepted inefficiency reduction frameworks can be applied with use of a graphic user interface screen capture program.

Resting-state fMRI data reflects default network activity rather than null data: A defense of commonly employed methods to correct for multiple comparisons.

PubMed

Slotnick, Scott D

2017-07-01

Analysis of functional magnetic resonance imaging (fMRI) data typically involves over one hundred thousand independent statistical tests; therefore, it is necessary to correct for multiple comparisons to control familywise error. In a recent paper, Eklund, Nichols, and Knutsson used resting-state fMRI data to evaluate commonly employed methods to correct for multiple comparisons and reported unacceptable rates of familywise error. Eklund et al.'s analysis was based on the assumption that resting-state fMRI data reflect null data; however, their 'null data' actually reflected default network activity that inflated familywise error. As such, Eklund et al.'s results provide no basis to question the validity of the thousands of published fMRI studies that have corrected for multiple comparisons or the commonly employed methods to correct for multiple comparisons.

Sub-band denoising and spline curve fitting method for hemodynamic measurement in perfusion MRI

NASA Astrophysics Data System (ADS)

Lin, Hong-Dun; Huang, Hsiao-Ling; Hsu, Yuan-Yu; Chen, Chi-Chen; Chen, Ing-Yi; Wu, Liang-Chi; Liu, Ren-Shyan; Lin, Kang-Ping

2003-05-01

In clinical research, non-invasive MR perfusion imaging is capable of investigating brain perfusion phenomenon via various hemodynamic measurements, such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean trasnit time (MTT). These hemodynamic parameters are useful in diagnosing brain disorders such as stroke, infarction and periinfarct ischemia by further semi-quantitative analysis. However, the accuracy of quantitative analysis is usually affected by poor signal-to-noise ratio image quality. In this paper, we propose a hemodynamic measurement method based upon sub-band denoising and spline curve fitting processes to improve image quality for better hemodynamic quantitative analysis results. Ten sets of perfusion MRI data and corresponding PET images were used to validate the performance. For quantitative comparison, we evaluate gray/white matter CBF ratio. As a result, the hemodynamic semi-quantitative analysis result of mean gray to white matter CBF ratio is 2.10 +/- 0.34. The evaluated ratio of brain tissues in perfusion MRI is comparable to PET technique is less than 1-% difference in average. Furthermore, the method features excellent noise reduction and boundary preserving in image processing, and short hemodynamic measurement time.

Imaging transplanted stem cells in real time using an MRI dual-contrast method

PubMed Central

Ngen, Ethel J.; Wang, Lee; Kato, Yoshinori; Krishnamachary, Balaji; Zhu, Wenlian; Gandhi, Nishant; Smith, Barbara; Armour, Michael; Wong, John; Gabrielson, Kathleen; Artemov, Dmitri

2015-01-01

Stem cell therapies are currently being investigated for the repair of brain injuries. Although exogenous stem cell labelling with superparamagnetic iron oxide nanoparticles (SPIONs) prior to transplantation provides a means to noninvasively monitor stem cell transplantation by magnetic resonance imaging (MRI), monitoring cell death is still a challenge. Here, we investigate the feasibility of using an MRI dual-contrast technique to detect cell delivery, cell migration and cell death after stem cell transplantation. Human mesenchymal stem cells were dual labelled with SPIONs and gadolinium-based chelates (GdDTPA). The viability, proliferation rate, and differentiation potential of the labelled cells were then evaluated. The feasibility of this MRI technique to distinguish between live and dead cells was next evaluated using MRI phantoms, and in vivo using both immune-competent and immune-deficient mice, following the induction of brain injury in the mice. All results were validated with bioluminescence imaging. In live cells, a negative (T2/T2*) MRI contrast predominates, and is used to track cell delivery and cell migration. Upon cell death, a diffused positive (T1) MRI contrast is generated in the vicinity of the dead cells, and serves as an imaging marker for cell death. Ultimately, this technique could be used to manage stem cell therapies. PMID:26330231

Imaging transplanted stem cells in real time using an MRI dual-contrast method.

PubMed

Ngen, Ethel J; Wang, Lee; Kato, Yoshinori; Krishnamachary, Balaji; Zhu, Wenlian; Gandhi, Nishant; Smith, Barbara; Armour, Michael; Wong, John; Gabrielson, Kathleen; Artemov, Dmitri

2015-09-02

Stem cell therapies are currently being investigated for the repair of brain injuries. Although exogenous stem cell labelling with superparamagnetic iron oxide nanoparticles (SPIONs) prior to transplantation provides a means to noninvasively monitor stem cell transplantation by magnetic resonance imaging (MRI), monitoring cell death is still a challenge. Here, we investigate the feasibility of using an MRI dual-contrast technique to detect cell delivery, cell migration and cell death after stem cell transplantation. Human mesenchymal stem cells were dual labelled with SPIONs and gadolinium-based chelates (GdDTPA). The viability, proliferation rate, and differentiation potential of the labelled cells were then evaluated. The feasibility of this MRI technique to distinguish between live and dead cells was next evaluated using MRI phantoms, and in vivo using both immune-competent and immune-deficient mice, following the induction of brain injury in the mice. All results were validated with bioluminescence imaging. In live cells, a negative (T2/T2*) MRI contrast predominates, and is used to track cell delivery and cell migration. Upon cell death, a diffused positive (T1) MRI contrast is generated in the vicinity of the dead cells, and serves as an imaging marker for cell death. Ultimately, this technique could be used to manage stem cell therapies.

A review of MRI evaluation of demyelination in cuprizone murine model

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

Krutenkova, E., E-mail: len--k@yandex.ru; Pan, E.; Khodanovich, M., E-mail: khodanovich@mail.tsu.ru

The cuprizone mouse model of non-autoimmune demyelination reproduces some phenomena of multiple sclerosis and is appropriate for validation and specification of a new method of non-invasive diagnostics. In the review new data which are collected using the new MRI method are compared with one or more conventional MRI tools. Also the paper reviewed the validation of MRI approaches using histological or immunohistochemical methods. Luxol fast blue histological staining and myelin basic protein immunostaining is widespread. To improve the accuracy of non-invasive conventional MRI, multimodal scanning could be applied. The new quantitative MRI method of fast mapping of the macromolecular protonmore » fraction is a reliable biomarker of myelin in the brain and can be used for research of demyelination in animals. To date, a validation of MPF method on the CPZ mouse model of demyelination is not performed, although this method is probably the best way to evaluate demyelination using MRI.« less

A review of MRI evaluation of demyelination in cuprizone murine model

NASA Astrophysics Data System (ADS)

Krutenkova, E.; Pan, E.; Khodanovich, M.

2015-11-01

The cuprizone mouse model of non-autoimmune demyelination reproduces some phenomena of multiple sclerosis and is appropriate for validation and specification of a new method of non-invasive diagnostics. In the review new data which are collected using the new MRI method are compared with one or more conventional MRI tools. Also the paper reviewed the validation of MRI approaches using histological or immunohistochemical methods. Luxol fast blue histological staining and myelin basic protein immunostaining is widespread. To improve the accuracy of non-invasive conventional MRI, multimodal scanning could be applied. The new quantitative MRI method of fast mapping of the macromolecular proton fraction is a reliable biomarker of myelin in the brain and can be used for research of demyelination in animals. To date, a validation of MPF method on the CPZ mouse model of demyelination is not performed, although this method is probably the best way to evaluate demyelination using MRI.

Comprehensive MRI simulation methodology using a dedicated MRI scanner in radiation oncology for external beam radiation treatment planning

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

Paulson, Eric S., E-mail: epaulson@mcw.edu; Erickson, Beth; Schultz, Chris

Purpose: The use of magnetic resonance imaging (MRI) in radiation oncology is expanding rapidly, and more clinics are integrating MRI into their radiation therapy workflows. However, radiation therapy presents a new set of challenges and places additional constraints on MRI compared to diagnostic radiology that, if not properly addressed, can undermine the advantages MRI offers for radiation treatment planning (RTP). The authors introduce here strategies to manage several challenges of using MRI for virtual simulation in external beam RTP. Methods: A total of 810 clinical MRI simulation exams were performed using a dedicated MRI scanner for external beam RTP ofmore » brain, breast, cervix, head and neck, liver, pancreas, prostate, and sarcoma cancers. Patients were imaged in treatment position using MRI-optimal immobilization devices. Radiofrequency (RF) coil configurations and scan protocols were optimized based on RTP constraints. Off-resonance and gradient nonlinearity-induced geometric distortions were minimized or corrected prior to using images for RTP. A multidisciplinary MRI simulation guide, along with window width and level presets, was created to standardize use of MR images during RTP. A quality assurance program was implemented to maintain accuracy and repeatability of MRI simulation exams. Results: The combination of a large bore scanner, high field strength, and circumferentially wrapped, flexible phased array RF receive coils permitted acquisition of thin slice images with high contrast-to-noise ratio (CNR) and image intensity uniformity, while simultaneously accommodating patient setup and immobilization devices. Postprocessing corrections and alternative acquisition methods were required to reduce or correct off-resonance and gradient nonlinearity induced geometric distortions. Conclusions: The methodology described herein contains practical strategies the authors have implemented through lessons learned performing clinical MRI simulation exams

Comparison of multi-subject ICA methods for analysis of fMRI data

PubMed Central

Erhardt, Erik Barry; Rachakonda, Srinivas; Bedrick, Edward; Allen, Elena; Adali, Tülay; Calhoun, Vince D.

2010-01-01

Spatial independent component analysis (ICA) applied to functional magnetic resonance imaging (fMRI) data identifies functionally connected networks by estimating spatially independent patterns from their linearly mixed fMRI signals. Several multi-subject ICA approaches estimating subject-specific time courses (TCs) and spatial maps (SMs) have been developed, however there has not yet been a full comparison of the implications of their use. Here, we provide extensive comparisons of four multi-subject ICA approaches in combination with data reduction methods for simulated and fMRI task data. For multi-subject ICA, the data first undergo reduction at the subject and group levels using principal component analysis (PCA). Comparisons of subject-specific, spatial concatenation, and group data mean subject-level reduction strategies using PCA and probabilistic PCA (PPCA) show that computationally intensive PPCA is equivalent to PCA, and that subject-specific and group data mean subject-level PCA are preferred because of well-estimated TCs and SMs. Second, aggregate independent components are estimated using either noise free ICA or probabilistic ICA (PICA). Third, subject-specific SMs and TCs are estimated using back-reconstruction. We compare several direct group ICA (GICA) back-reconstruction approaches (GICA1-GICA3) and an indirect back-reconstruction approach, spatio-temporal regression (STR, or dual regression). Results show the earlier group ICA (GICA1) approximates STR, however STR has contradictory assumptions and may show mixed-component artifacts in estimated SMs. Our evidence-based recommendation is to use GICA3, introduced here, with subject-specific PCA and noise-free ICA, providing the most robust and accurate estimated SMs and TCs in addition to offering an intuitive interpretation. PMID:21162045

[Determination of joint contact area using MRI].

PubMed

Yoshida, Hidenori; Kobayashi, Koichi; Sakamoto, Makoto; Tanabe, Yuji

2009-10-20

Elevated contact stress on the articular joints has been hypothesized to contribute to articular cartilage wear and joint pain. However, given the limitations of using contact stress and areas from human cadaver specimens to estimate articular joint stress, there is need for an in vivo method to obtain such data. Magnetic resonance imaging (MRI) has been shown to be a valid method of quantifying the human joint contact area, indicating the potential for in vivo assessment. The purpose of this study was to describe a method of quantifying the tibiofemoral joint contact area using MRI. The validity of this technique was established in porcine cadaver specimens by comparing the contact area obtained from MRI with the contact area obtained using pressure-sensitive film (PSF). In particular, we assessed the actual condition of contact by using the ratio of signal intensity of MR images of cartilage surfaces. Two fresh porcine cadaver knees were used. A custom loading apparatus was designed to apply a compressive load to the tibiofemoral joint. We measured the contact area by using MRI and PSF methods. When the ratio of signal intensity of the cartilage surface was 0.9, the error of the contact area between the MR image and PSF was about 6%. These results suggest that this MRI method may be a valuable tool in quantifying joint contact area in vivo.

TH-C-BRD-06: A Novel MRI Based CT Artifact Correction Method for Improving Proton Range Calculation in the Presence of Severe CT Artifacts

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

Park, P; Schreibmann, E; Fox, T

2014-06-15

Purpose: Severe CT artifacts can impair our ability to accurately calculate proton range thereby resulting in a clinically unacceptable treatment plan. In this work, we investigated a novel CT artifact correction method based on a coregistered MRI and investigated its ability to estimate CT HU and proton range in the presence of severe CT artifacts. Methods: The proposed method corrects corrupted CT data using a coregistered MRI to guide the mapping of CT values from a nearby artifact-free region. First patient MRI and CT images were registered using 3D deformable image registration software based on B-spline and mutual information. Themore » CT slice with severe artifacts was selected as well as a nearby slice free of artifacts (e.g. 1cm away from the artifact). The two sets of paired MRI and CT images at different slice locations were further registered by applying 2D deformable image registration. Based on the artifact free paired MRI and CT images, a comprehensive geospatial analysis was performed to predict the correct CT HU of the CT image with severe artifact. For a proof of concept, a known artifact was introduced that changed the ground truth CT HU value up to 30% and up to 5cm error in proton range. The ability of the proposed method to recover the ground truth was quantified using a selected head and neck case. Results: A significant improvement in image quality was observed visually. Our proof of concept study showed that 90% of area that had 30% errors in CT HU was corrected to 3% of its ground truth value. Furthermore, the maximum proton range error up to 5cm was reduced to 4mm error. Conclusion: MRI based CT artifact correction method can improve CT image quality and proton range calculation for patients with severe CT artifacts.« less

Head MRI

MedlinePlus

... the head; MRI - cranial; NMR - cranial; Cranial MRI; Brain MRI; MRI - brain; MRI - head ... the test, tell your provider if you have: Brain aneurysm clips An artificial heart valves Heart defibrillator ...

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning.

PubMed

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-07

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-01

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water

Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient.

PubMed

Feng, Shuo; Ji, Jim

2014-04-01

Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns.

Medical image segmentation using 3D MRI data

NASA Astrophysics Data System (ADS)

Voronin, V.; Marchuk, V.; Semenishchev, E.; Cen, Yigang; Agaian, S.

2017-05-01

Precise segmentation of three-dimensional (3D) magnetic resonance imaging (MRI) image can be a very useful computer aided diagnosis (CAD) tool in clinical routines. Accurate automatic extraction a 3D component from images obtained by magnetic resonance imaging (MRI) is a challenging segmentation problem due to the small size objects of interest (e.g., blood vessels, bones) in each 2D MRA slice and complex surrounding anatomical structures. Our objective is to develop a specific segmentation scheme for accurately extracting parts of bones from MRI images. In this paper, we use a segmentation algorithm to extract the parts of bones from Magnetic Resonance Imaging (MRI) data sets based on modified active contour method. As a result, the proposed method demonstrates good accuracy in a comparison between the existing segmentation approaches on real MRI data.

Behavior, neuropsychology and fMRI.

PubMed

Bennett, Maxwell R; Hatton, Sean; Hermens, Daniel F; Lagopoulos, Jim

Cognitive neuroscientists in the late 20th century began the task of identifying the part(s) of the brain concerned with normal behavior as manifest in the psychological capacities as affective powers, reasoning, behaving purposively and the pursuit of goals, following introduction of the 'functional magnetic resonance imaging' (fMRI) method for identifying brain activity. For this research program to be successful two questions require satisfactory answers. First, as the fMRI method can currently only be used on stationary subjects, to what extent can neuropsychological tests applicable to such stationary subjects be correlated with normal behavior. Second, to what extent can correlations between the various neuropsychological tests on the one hand, and sites of brain activity determined with fMRI on the other, be regarded as established. The extent to which these questions have yet received satisfactory answers is reviewed, and suggestions made both for improving correlations of neuropsychological tests with behavior as well as with the results of fMRI-based observations. Copyright © 2016. Published by Elsevier Ltd.

Trans-dimensional MCMC methods for fully automatic motion analysis in tagged MRI.

PubMed

Smal, Ihor; Carranza-Herrezuelo, Noemí; Klein, Stefan; Niessen, Wiro; Meijering, Erik

2011-01-01

Tagged magnetic resonance imaging (tMRI) is a well-known noninvasive method allowing quantitative analysis of regional heart dynamics. Its clinical use has so far been limited, in part due to the lack of robustness and accuracy of existing tag tracking algorithms in dealing with low (and intrinsically time-varying) image quality. In this paper, we propose a novel probabilistic method for tag tracking, implemented by means of Bayesian particle filtering and a trans-dimensional Markov chain Monte Carlo (MCMC) approach, which efficiently combines information about the imaging process and tag appearance with prior knowledge about the heart dynamics obtained by means of non-rigid image registration. Experiments using synthetic image data (with ground truth) and real data (with expert manual annotation) from preclinical (small animal) and clinical (human) studies confirm that the proposed method yields higher consistency, accuracy, and intrinsic tag reliability assessment in comparison with other frequently used tag tracking methods.

MRI EVALUATION OF KNEE CARTILAGE

PubMed Central

Rodrigues, Marcelo Bordalo; Camanho, Gilberto Luís

2015-01-01

Through the ability of magnetic resonance imaging (MRI) to characterize soft tissue noninvasively, it has become an excellent method for evaluating cartilage. The development of new and faster methods allowed increased resolution and contrast in evaluating chondral structure, with greater diagnostic accuracy. In addition, physiological techniques for cartilage assessment that can detect early changes before the appearance of cracks and erosion have been developed. In this updating article, the various techniques for chondral assessment using knee MRI will be discussed and demonstrated. PMID:27022562

SU-F-BRF-10: Deformable MRI to CT Validation Employing Same Day Planning MRI for Surrogate Analysis

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

Padgett, K; Stoyanova, R; Johnson, P

Purpose: To compare rigid and deformable registrations of the prostate in the multi-modality setting (diagnostic-MRI to planning-CT) by utilizing a planning-MRI as a surrogate. The surrogate allows for the direct quantitative analysis which can be difficult in the multi-modality domain where intensity mapping differs. Methods: For ten subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day in which the planning CT was collected (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets.more » The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. The deformed MRI was then rigidly aligned to the planning MRI which was used as the surrogate for the planning-CT. Agreement between the two MRI datasets was scored using intensity based metrics including Pearson correlation and normalized mutual information, NMI. A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb and combined areas. A similar method was used to assess a rigid registration between the diagnostic-MRI and planning-CT. Results: Utilizing the NMI, the deformable registrations were superior to the rigid registrations in 9 of 10 cases demonstrating a 15.94% improvement (p-value < 0.001) within the combined area. The Pearson correlation showed similar results with the deformable registration superior in the same number of cases and demonstrating a 6.97% improvement (p-value <0.011). Conclusion: Validating deformable multi-modality registrations using spatial intensity based metrics is difficult due to the inherent differences in intensity mapping. This population provides an ideal testing ground for MRI to CT deformable registrations by obviating

Feasibility of texture analysis for the assessment of biochemical changes in meniscal tissue on T1 maps calculated from delayed gadolinium-enhanced magnetic resonance imaging of cartilage data: comparison with conventional relaxation time measurements.

PubMed

Mayerhoefer, Marius E; Welsch, Goetz H; Riegler, Georg; Mamisch, Tallal C; Materka, Andrzej; Weber, Michael; El-Rabadi, Karem; Friedrich, Klaus M; Dirisamer, Albert; Trattnig, Siegfried

2010-09-01

To (1) establish the feasibility of texture analysis for the in vivo assessment of biochemical changes in meniscal tissue on delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC), and (2) compare textural with conventional T1 relaxation time measurements calculated from dGEMRIC data ("T1(Gd) relaxation times"). We enrolled 10 asymptomatic volunteers (7 men and 3 women; mean age, 27.2 +/- 4.5 years), without a history of meniscus damage, in our study. MRI of the right knee was performed at 3.0 T. An isotropic, 3-dimensional (3D), double-echo steady-state sequences was used for morphologic evaluation, and a dual flip angle 3D gradient echo sequence was used for T1(Gd) mapping. All MRI scans were performed 90 minutes after injection of 0.2 mmol/kg of Gd-diethylenetriamine pentaacetic acid (DTPA), and subsequently, during application of a compressive force (50% of the body weight) in the axial direction. Regions of interest, covering the central portions of the posterior horn of the medial meniscus, were defined on 3 adjacent sagittal sections. Based on the relaxation time maps, mean T1(Gd), as well as the T1(Gd) texture features derived from the co-occurrence matrix (COC: Angular Second Moment, Entropy, Inverse Difference Moment) and wavelet transform (WAV: WavEnLL, WavEnHL, WavEnHH, WavEnLH), were calculated. Paired t tests were used to assess differences between baseline and compression, and intraclass correlation coefficients (ICC) were calculated to establish the intrarater reliability of the measurements. Mean T1(Gd) (-67.3 ms, P = 0.011), Angular Second Moment (-0.0002, P = 0.009), Entropy (+0.033, P = 0.025), WavEnLL (+1011.16, P = 0.002), WavEnHL (+18.64, P = 0.012), and WavEnLH (+72.74, P = 0.035) differed significantly between baseline and compression. Intrarater reliability was substantial for mean T1(Gd) relaxation times (ICC = 0.99-1.0), and also for T1(Gd) co-occurrence matrix (ICC = 0.63-0.92) and WAV (ICC = 0.86-0.98) features

Application of fractal dimension method of functional MRI time-series to limbic dysregulation in anxiety study.

PubMed

Olejarczyk, Elzbieta

2007-01-01

Functional magnetic resonance imaging (fMRI) allows to investigate the amplitude of activation in neural networks of brain. In this work we present the results of fMRI time-series analysis performed to identify the process of dysregulation of dynamic interaction between different limbic system regions in healthy adults in state of increased anxiety. The results obtain for 65 healthy adults using nonlinear dynamics methods like fractal dimension confirm the key roles of the bilateral amygdala, bilateral hippocampus, BA9 (dorsolateral prefrontal cortex), and BA45 (ventromedial prefrontal cortex) in modulating emotional response in healthy adults. For different regions of interest (ROIs) significant correlations were found not only for the neutral respective rest but also for fear and angry contrasts.

Advanced flow MRI: emerging techniques and applications

PubMed Central

Markl, M.; Schnell, S.; Wu, C.; Bollache, E.; Jarvis, K.; Barker, A. J.; Robinson, J. D.; Rigsby, C. K.

2016-01-01

Magnetic resonance imaging (MRI) techniques provide non-invasive and non-ionising methods for the highly accurate anatomical depiction of the heart and vessels throughout the cardiac cycle. In addition, the intrinsic sensitivity of MRI to motion offers the unique ability to acquire spatially registered blood flow simultaneously with the morphological data, within a single measurement. In clinical routine, flow MRI is typically accomplished using methods that resolve two spatial dimensions in individual planes and encode the time-resolved velocity in one principal direction, typically oriented perpendicular to the two-dimensional (2D) section. This review describes recently developed advanced MRI flow techniques, which allow for more comprehensive evaluation of blood flow characteristics, such as real-time flow imaging, 2D multiple-venc phase contrast MRI, four-dimensional (4D) flow MRI, quantification of complex haemodynamic properties, and highly accelerated flow imaging. Emerging techniques and novel applications are explored. In addition, applications of these new techniques for the improved evaluation of cardiovascular (aorta, pulmonary arteries, congenital heart disease, atrial fibrillation, coronary arteries) as well as cerebrovascular disease (intra-cranial arteries and veins) are presented. PMID:26944696

Current whole-body MRI applications in the neurofibromatoses

PubMed Central

Fayad, Laura M.; Khan, Muhammad Shayan; Bredella, Miriam A.; Harris, Gordon J.; Evans, D. Gareth; Farschtschi, Said; Jacobs, Michael A.; Chhabra, Avneesh; Salamon, Johannes M.; Wenzel, Ralph; Mautner, Victor F.; Dombi, Eva; Cai, Wenli; Plotkin, Scott R.; Blakeley, Jaishri O.

2016-01-01

Objectives: The Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) International Collaboration Whole-Body MRI (WB-MRI) Working Group reviewed the existing literature on WB-MRI, an emerging technology for assessing disease in patients with neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN), to recommend optimal image acquisition and analysis methods to enable WB-MRI as an endpoint in NF clinical trials. Methods: A systematic process was used to review all published data about WB-MRI in NF syndromes to assess diagnostic accuracy, feasibility and reproducibility, and data about specific techniques for assessment of tumor burden, characterization of neoplasms, and response to therapy. Results: WB-MRI at 1.5T or 3.0T is feasible for image acquisition. Short tau inversion recovery (STIR) sequence is used in all investigations to date, suggesting consensus about the utility of this sequence for detection of WB tumor burden in people with NF. There are insufficient data to support a consensus statement about the optimal imaging planes (axial vs coronal) or 2D vs 3D approaches. Functional imaging, although used in some NF studies, has not been systematically applied or evaluated. There are no comparative studies between regional vs WB-MRI or evaluations of WB-MRI reproducibility. Conclusions: WB-MRI is feasible for identifying tumors using both 1.5T and 3.0T systems. The STIR sequence is a core sequence. Additional investigation is needed to define the optimal approach for volumetric analysis, the reproducibility of WB-MRI in NF, and the diagnostic performance of WB-MRI vs regional MRI. PMID:27527647

MRI with intrathecal MRI gadolinium contrast medium administration: a possible method to assess glymphatic function in human brain.

PubMed

Eide, Per Kristian; Ringstad, Geir

2015-11-01

Recently, the "glymphatic system" of the brain has been discovered in rodents, which is a paravascular, transparenchymal route for clearance of excess brain metabolites and distribution of compounds in the cerebrospinal fluid. It has already been demonstrated that intrathecally administered gadolinium (Gd) contrast medium distributes along this route in rats, but so far not in humans. A 27-year-old woman underwent magnetic resonance imaging (MRI) with intrathecal administration of gadobutrol, which distributed throughout her entire brain after 1 and 4.5 h. MRI with intrathecal Gd may become a tool to study glymphatic function in the human brain.

MRI with intrathecal MRI gadolinium contrast medium administration: a possible method to assess glymphatic function in human brain

PubMed Central

Ringstad, Geir

2015-01-01

Recently, the “glymphatic system” of the brain has been discovered in rodents, which is a paravascular, transparenchymal route for clearance of excess brain metabolites and distribution of compounds in the cerebrospinal fluid. It has already been demonstrated that intrathecally administered gadolinium (Gd) contrast medium distributes along this route in rats, but so far not in humans. A 27-year-old woman underwent magnetic resonance imaging (MRI) with intrathecal administration of gadobutrol, which distributed throughout her entire brain after 1 and 4.5 h. MRI with intrathecal Gd may become a tool to study glymphatic function in the human brain. PMID:26634147

Heart MRI

MedlinePlus

Magnetic resonance imaging - cardiac; Magnetic resonance imaging - heart; Nuclear magnetic resonance - cardiac; NMR - cardiac; MRI of the heart; Cardiomyopathy - MRI; Heart failure - MRI; Congenital heart disease - MRI

Efficient method to design RF pulses for parallel excitation MRI using gridding and conjugate gradient

PubMed Central

Feng, Shuo

2014-01-01

Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns. PMID:24834420

Imaging of prostate cancer: a platform for 3D co-registration of in-vivo MRI ex-vivo MRI and pathology

NASA Astrophysics Data System (ADS)

Orczyk, Clément; Mikheev, Artem; Rosenkrantz, Andrew; Melamed, Jonathan; Taneja, Samir S.; Rusinek, Henry

2012-02-01

Objectives: Multi-parametric MRI is emerging as a promising method for prostate cancer diagnosis. prognosis and treatment planning. However, the localization of in-vivo detected lesions and pathologic sites of cancer remains a significant challenge. To overcome this limitation we have developed and tested a system for co-registration of in-vivo MRI, ex-vivo MRI and histology. Materials and Methods: Three men diagnosed with localized prostate cancer (ages 54-72, PSA levels 5.1-7.7 ng/ml) were prospectively enrolled in this study. All patients underwent 3T multi-parametric MRI that included T2W, DCEMRI, and DWI prior to robotic-assisted prostatectomy. Ex-vivo multi-parametric MRI was performed on fresh prostate specimen. Excised prostates were then sliced at regular intervals and photographed both before and after fixation. Slices were perpendicular to the main axis of the posterior capsule, i.e., along the direction of the rectal wall. Guided by the location of the urethra, 2D digital images were assembled into 3D models. Cancer foci, extra-capsular extensions and zonal margins were delineated by the pathologist and included in 3D histology data. A locally-developed software was applied to register in-vivo, ex-vivo and histology using an over-determined set of anatomical landmarks placed in anterior fibro-muscular stroma, central. transition and peripheral zones. The mean root square distance across corresponding control points was used to assess co-registration error. Results: Two specimens were pT3a and one pT2b (negative margin) at pathology. The software successfully fused invivo MRI. ex-vivo MRI fresh specimen and histology using appropriate (rigid and affine) transformation models with mean square error of 1.59 mm. Coregistration accuracy was confirmed by multi-modality viewing using operator-guided variable transparency. Conclusion: The method enables successful co-registration of pre-operative MRI, ex-vivo MRI and pathology and it provides initial evidence

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

WE-G-BRD-06: Volumetric Cine MRI (VC-MRI) Estimated Based On Prior Knowledge for On-Board Target Localization

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

Harris, W; Yin, F; Cai, J

Purpose: To develop a technique to generate on-board VC-MRI using patient prior 4D-MRI, motion modeling and on-board 2D-cine MRI for real-time 3D target verification of liver and lung radiotherapy. Methods: The end-expiration phase images of a 4D-MRI acquired during patient simulation are used as patient prior images. Principal component analysis (PCA) is used to extract 3 major respiratory deformation patterns from the Deformation Field Maps (DFMs) generated between end-expiration phase and all other phases. On-board 2D-cine MRI images are acquired in the axial view. The on-board VC-MRI at any instant is considered as a deformation of the prior MRI atmore » the end-expiration phase. The DFM is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by matching the corresponding 2D slice of the estimated VC-MRI with the acquired single 2D-cine MRI. The method was evaluated using both XCAT (a computerized patient model) simulation of lung cancer patients and MRI data from a real liver cancer patient. The 3D-MRI at every phase except end-expiration phase was used to simulate the ground-truth on-board VC-MRI at different instances, and the center-tumor slice was selected to simulate the on-board 2D-cine images. Results: Image subtraction of ground truth with estimated on-board VC-MRI shows fewer differences than image subtraction of ground truth with prior image. Excellent agreement between profiles was achieved. The normalized cross correlation coefficients between the estimated and ground-truth in the axial, coronal and sagittal views for each time step were >= 0.982, 0.905, 0.961 for XCAT data and >= 0.998, 0.911, 0.9541 for patient data. For XCAT data, the maximum-Volume-Percent-Difference between ground-truth and estimated tumor volumes was 1.6% and the maximum-Center-of-Mass-Shift was 0.9 mm. Conclusion: Preliminary studies demonstrated the feasibility to estimate real-time VC-MRI for on

TH-A-BRF-08: Deformable Registration of MRI and CT Images for MRI-Guided Radiation Therapy

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

Zhong, H; Wen, N; Gordon, J

2014-06-15

Purpose: To evaluate the quality of a commercially available MRI-CT image registration algorithm and then develop a method to improve the performance of this algorithm for MRI-guided prostate radiotherapy. Methods: Prostate contours were delineated on ten pairs of MRI and CT images using Eclipse. Each pair of MRI and CT images was registered with an intensity-based B-spline algorithm implemented in Velocity. A rectangular prism that contains the prostate volume was partitioned into a tetrahedral mesh which was aligned to the CT image. A finite element method (FEM) was developed on the mesh with the boundary constraints assigned from the Velocitymore » generated displacement vector field (DVF). The resultant FEM displacements were used to adjust the Velocity DVF within the prism. Point correspondences between the CT and MR images identified within the prism could be used as additional boundary constraints to enforce the model deformation. The FEM deformation field is smooth in the interior of the prism, and equal to the Velocity displacements at the boundary of the prism. To evaluate the Velocity and FEM registration results, three criteria were used: prostate volume conservation and center consistence under contour mapping, and unbalanced energy of their deformation maps. Results: With the DVFs generated by the Velocity and FEM simulations, the prostate contours were warped from MRI to CT images. With the Velocity DVFs, the prostate volumes changed 10.2% on average, in contrast to 1.8% induced by the FEM DVFs. The average of the center deviations was 0.36 and 0.27 cm, and the unbalance energy was 2.65 and 0.38 mJ/cc3 for the Velocity and FEM registrations, respectively. Conclusion: The adaptive FEM method developed can be used to reduce the error of the MIbased registration algorithm implemented in Velocity in the prostate region, and consequently may help improve the quality of MRI-guided radiation therapy.« less

Thermal noise calculation method for precise estimation of the signal-to-noise ratio of ultra-low-field MRI with an atomic magnetometer.

PubMed

Yamashita, Tatsuya; Oida, Takenori; Hamada, Shoji; Kobayashi, Tetsuo

2012-02-01

In recent years, there has been considerable interest in developing an ultra-low-field magnetic resonance imaging (ULF-MRI) system using an optically pumped atomic magnetometer (OPAM). However, a precise estimation of the signal-to-noise ratio (SNR) of ULF-MRI has not been carried out. Conventionally, to calculate the SNR of an MR image, thermal noise, also called Nyquist noise, has been estimated by considering a resistor that is electrically equivalent to a biological-conductive sample and is connected in series to a pickup coil. However, this method has major limitations in that the receiver has to be a coil and that it cannot be applied directly to a system using OPAM. In this paper, we propose a method to estimate the thermal noise of an MRI system using OPAM. We calculate the thermal noise from the variance of the magnetic sensor output produced by current-dipole moments that simulate thermally fluctuating current sources in a biological sample. We assume that the random magnitude of the current dipole in each volume element of the biological sample is described by the Maxwell-Boltzmann distribution. The sensor output produced by each current-dipole moment is calculated either by an analytical formula or a numerical method based on the boundary element method. We validate the proposed method by comparing our results with those obtained by conventional methods that consider resistors connected in series to a pickup coil using single-layered sphere, multi-layered sphere, and realistic head models. Finally, we apply the proposed method to the ULF-MRI model using OPAM as the receiver with multi-layered sphere and realistic head models and estimate their SNR. Copyright © 2011 Elsevier Inc. All rights reserved.

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

Ultra-low field MRI: bringing MRI to new arenas

DOE PAGES

Magnelind, Per Erik; Matlashov, Andrei Nikolaevich; Newman, Shaun Garrett; ...

2016-11-01

Conventional magnetic resonance imaging (MRI) is moving toward the use of stronger and stronger magnetic fields with 3T, and even 7 T systems being increasingly used in routine clinical applications. However there is another branch of MRI, namely Ultra Low Field MRI (ULF-MRI) where the magnetic fields during readout are several orders of magnitude smaller, namely 1–100 μT. While conventional high-field MRI remains the gold standard there are several situations such as in military emergencies or in developing countries where for cost and logistical reasons, conventional MRI is not practical. In such scenarios, ULF-MRI could provide a solution. Lastly, thismore » article describes the basic principles and the potential of ULF-MRI.« less

Ultra-low field MRI: bringing MRI to new arenas

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

Magnelind, Per Erik; Matlashov, Andrei Nikolaevich; Newman, Shaun Garrett

Conventional magnetic resonance imaging (MRI) is moving toward the use of stronger and stronger magnetic fields with 3T, and even 7 T systems being increasingly used in routine clinical applications. However there is another branch of MRI, namely Ultra Low Field MRI (ULF-MRI) where the magnetic fields during readout are several orders of magnitude smaller, namely 1–100 μT. While conventional high-field MRI remains the gold standard there are several situations such as in military emergencies or in developing countries where for cost and logistical reasons, conventional MRI is not practical. In such scenarios, ULF-MRI could provide a solution. Lastly, thismore » article describes the basic principles and the potential of ULF-MRI.« less

Optimization of the reference region method for dual pharmacokinetic modeling using Gd-DTPA/MRI and (18) F-FDG/PET.

PubMed

Poulin, Éric; Lebel, Réjean; Croteau, Étienne; Blanchette, Marie; Tremblay, Luc; Lecomte, Roger; Bentourkia, M'hamed; Lepage, Martin

2015-02-01

The combination of MRI and positron emission tomography (PET) offers new possibilities for the development of novel methodologies. In pharmacokinetic image analysis, the blood concentration of the imaging compound as a function of time, [i.e., the arterial input function (AIF)] is required for MRI and PET. In this study, we tested whether an AIF extracted from a reference region (RR) in MRI can be used as a surrogate for the manually sampled (18) F-FDG AIF for pharmacokinetic modeling. An MRI contrast agent, gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA) and a radiotracer, (18) F-fluorodeoxyglucose ((18) F-FDG), were simultaneously injected in a F98 glioblastoma rat model. A correction to the RR AIF for Gd-DTPA is proposed to adequately represent the manually sampled AIF. A previously published conversion method was applied to convert this AIF into a (18) F-FDG AIF. The tumor metabolic rate of glucose (TMRGlc) calculated with the manually sampled (18) F-FDG AIF, the (18) F-FDG AIF converted from the RR AIF and the (18) F-FDG AIF converted from the corrected RR AIF were found not statistically different (P>0.05). An AIF derived from an RR in MRI can be accurately converted into a (18) F-FDG AIF and used in PET pharmacokinetic modeling. © 2014 Wiley Periodicals, Inc.

Efficacy Evaluation of Different Wavelet Feature Extraction Methods on Brain MRI Tumor Detection

NASA Astrophysics Data System (ADS)

Nabizadeh, Nooshin; John, Nigel; Kubat, Miroslav

2014-03-01

Automated Magnetic Resonance Imaging brain tumor detection and segmentation is a challenging task. Among different available methods, feature-based methods are very dominant. While many feature extraction techniques have been employed, it is still not quite clear which of feature extraction methods should be preferred. To help improve the situation, we present the results of a study in which we evaluate the efficiency of using different wavelet transform features extraction methods in brain MRI abnormality detection. Applying T1-weighted brain image, Discrete Wavelet Transform (DWT), Discrete Wavelet Packet Transform (DWPT), Dual Tree Complex Wavelet Transform (DTCWT), and Complex Morlet Wavelet Transform (CMWT) methods are applied to construct the feature pool. Three various classifiers as Support Vector Machine, K Nearest Neighborhood, and Sparse Representation-Based Classifier are applied and compared for classifying the selected features. The results show that DTCWT and CMWT features classified with SVM, result in the highest classification accuracy, proving of capability of wavelet transform features to be informative in this application.

Volume estimation of brain abnormalities in MRI data

NASA Astrophysics Data System (ADS)

Suprijadi, Pratama, S. H.; Haryanto, F.

2014-02-01

The abnormality of brain tissue always becomes a crucial issue in medical field. This medical condition can be recognized through segmentation of certain region from medical images obtained from MRI dataset. Image processing is one of computational methods which very helpful to analyze the MRI data. In this study, combination of segmentation and rendering image were used to isolate tumor and stroke. Two methods of thresholding were employed to segment the abnormality occurrence, followed by filtering to reduce non-abnormality area. Each MRI image is labeled and then used for volume estimations of tumor and stroke-attacked area. The algorithms are shown to be successful in isolating tumor and stroke in MRI images, based on thresholding parameter and stated detection accuracy.

NMR and MRI apparatus and method

DOEpatents

Clarke, John; Kelso, Nathan; Lee, SeungKyun; Moessle, Michael; Myers, Whittier; McDermott, Robert; ten Haken, Bernard; Pines, Alexander; Trabesinger, Andreas

2007-03-06

Nuclear magnetic resonance (NMR) signals are detected in microtesla fields. Prepolarization in millitesla fields is followed by detection with an untuned dc superconducting quantum interference device (SQUID) magnetometer. Because the sensitivity of the SQUID is frequency independent, both signal-to-noise ratio (SNR) and spectral resolution are enhanced by detecting the NMR signal in extremely low magnetic fields, where the NMR lines become very narrow even for grossly inhomogeneous measurement fields. Additional signal to noise benefits are obtained by use of a low noise polarization coil, comprising litz wire or superconducting materials. MRI in ultralow magnetic field is based on the NMR at ultralow fields. Gradient magnetic fields are applied, and images are constructed from the detected NMR signals.

MRI Post-processing in Pre-surgical Evaluation

PubMed Central

Wang, Z. Irene; Alexopoulos, Andreas V.

2016-01-01

Purpose of Review Advanced MRI post-processing techniques are increasingly used to complement visual analysis and elucidate structural epileptogenic lesions. This review summarizes recent developments in MRI post-processing in the context of epilepsy pre-surgical evaluation, with the focus on patients with unremarkable MRI by visual analysis (i.e., “nonlesional” MRI). Recent Findings Various methods of MRI post-processing have been reported to show additional clinical values in the following areas: (1) lesion detection on an individual level; (2) lesion confirmation for reducing the risk of over reading the MRI; (3) detection of sulcal/gyral morphologic changes that are particularly difficult for visual analysis; and (4) delineation of cortical abnormalities extending beyond the visible lesion. Future directions to improve performance of MRI post-processing include using higher magnetic field strength for better signal and contrast to noise ratio, adopting a multi-contrast frame work, and integration with other noninvasive modalities. Summary MRI post-processing can provide essential value to increase the yield of structural MRI and should be included as part of the presurgical evaluation of nonlesional epilepsies. MRI post-processing allows for more accurate identification/delineation of cortical abnormalities, which should then be more confidently targeted and mapped. PMID:26900745

Dental MRI using wireless intraoral coils

NASA Astrophysics Data System (ADS)

Ludwig, Ute; Eisenbeiss, Anne-Katrin; Scheifele, Christian; Nelson, Katja; Bock, Michael; Hennig, Jürgen; von Elverfeldt, Dominik; Herdt, Olga; Flügge, Tabea; Hövener, Jan-Bernd

2016-03-01

Currently, the gold standard for dental imaging is projection radiography or cone-beam computed tomography (CBCT). These methods are fast and cost-efficient, but exhibit poor soft tissue contrast and expose the patient to ionizing radiation (X-rays). The need for an alternative imaging modality e.g. for soft tissue management has stimulated a rising interest in dental magnetic resonance imaging (MRI) which provides superior soft tissue contrast. Compared to X-ray imaging, however, so far the spatial resolution of MRI is lower and the scan time is longer. In this contribution, we describe wireless, inductively-coupled intraoral coils whose local sensitivity enables high resolution MRI of dental soft tissue. In comparison to CBCT, a similar image quality with complementary contrast was obtained ex vivo. In-vivo, a voxel size of the order of 250•250•500 μm3 was achieved in 4 min only. Compared to dental MRI acquired with clinical equipment, the quality of the images was superior in the sensitive volume of the coils and is expected to improve the planning of interventions and monitoring thereafter. This method may enable a more accurate dental diagnosis and avoid unnecessary interventions, improving patient welfare and bringing MRI a step closer to becoming a radiation-free alternative for dental imaging.

"MRI Stealth" robot for prostate interventions.

PubMed

Stoianovici, Dan; Song, Danny; Petrisor, Doru; Ursu, Daniel; Mazilu, Dumitru; Muntener, Michael; Mutener, Michael; Schar, Michael; Patriciu, Alexandru

2007-01-01

The paper reports an important achievement in MRI instrumentation, a pneumatic, fully actuated robot located within the scanner alongside the patient and operating under remote control based on the images. Previous MRI robots commonly used piezoelectric actuation limiting their compatibility. Pneumatics is an ideal choice for MRI compatibility because it is decoupled from electromagnetism, but pneumatic actuators were hardly controllable. This achievement was possible due to a recent technology breakthrough, the invention of a new type of pneumatic motor, PneuStep 1, designed for the robot reported here with uncompromised MRI compatibility, high-precision, and medical safety. MrBot is one of the "MRI stealth" robots today (the second is described in this issue by Zangos et al.). Both of these systems are also multi-imager compatible, being able to operate with the imager of choice or cross-imaging modalities. For MRI compatibility the robot is exclusively constructed of nonmagnetic and dielectric materials such as plastics, ceramics, crystals, rubbers and is electricity free. Light-based encoding is used for feedback, so that all electric components are distally located outside the imager's room. MRI robots are modern, digital medical instruments in line with advanced imaging equipment and methods. These allow for accessing patients within closed bore scanners and performing interventions under direct (in scanner) imaging feedback. MRI robots could allow e.g. to biopsy small lesions imaged with cutting edge cancer imaging methods, or precisely deploy localized therapy at cancer foci. Our robot is the first to show the feasibility of fully automated in-scanner interventions. It is customized for the prostate and operates transperineally for needle interventions. It can accommodate various needle drivers for different percutaneous procedures such as biopsy, thermal ablations, or brachytherapy. The first needle driver is customized for fully automated low

Automated Robust Image Segmentation: Level Set Method Using Nonnegative Matrix Factorization with Application to Brain MRI.

PubMed

Dera, Dimah; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

2016-07-01

We address the problem of fully automated region discovery and robust image segmentation by devising a new deformable model based on the level set method (LSM) and the probabilistic nonnegative matrix factorization (NMF). We describe the use of NMF to calculate the number of distinct regions in the image and to derive the local distribution of the regions, which is incorporated into the energy functional of the LSM. The results demonstrate that our NMF-LSM method is superior to other approaches when applied to synthetic binary and gray-scale images and to clinical magnetic resonance images (MRI) of the human brain with and without a malignant brain tumor, glioblastoma multiforme. In particular, the NMF-LSM method is fully automated, highly accurate, less sensitive to the initial selection of the contour(s) or initial conditions, more robust to noise and model parameters, and able to detect as small distinct regions as desired. These advantages stem from the fact that the proposed method relies on histogram information instead of intensity values and does not introduce nuisance model parameters. These properties provide a general approach for automated robust region discovery and segmentation in heterogeneous images. Compared with the retrospective radiological diagnoses of two patients with non-enhancing grade 2 and 3 oligodendroglioma, the NMF-LSM detects earlier progression times and appears suitable for monitoring tumor response. The NMF-LSM method fills an important need of automated segmentation of clinical MRI.

PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method.

PubMed

Haddadpour, Mozhdeh; Daneshvar, Sabalan; Seyedarabi, Hadi

2017-08-01

The process of medical image fusion is combining two or more medical images such as Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) and mapping them to a single image as fused image. So purpose of our study is assisting physicians to diagnose and treat the diseases in the least of the time. We used Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) as input images, so fused them based on combination of two dimensional Hilbert transform (2-D HT) and Intensity Hue Saturation (IHS) method. Evaluation metrics that we apply are Discrepancy (D k ) as an assessing spectral features and Average Gradient (AG k ) as an evaluating spatial features and also Overall Performance (O.P) to verify properly of the proposed method. In this paper we used three common evaluation metrics like Average Gradient (AG k ) and the lowest Discrepancy (D k ) and Overall Performance (O.P) to evaluate the performance of our method. Simulated and numerical results represent the desired performance of proposed method. Since that the main purpose of medical image fusion is preserving both spatial and spectral features of input images, so based on numerical results of evaluation metrics such as Average Gradient (AG k ), Discrepancy (D k ) and Overall Performance (O.P) and also desired simulated results, it can be concluded that our proposed method can preserve both spatial and spectral features of input images. Copyright © 2017 Chang Gung University. Published by Elsevier B.V. All rights reserved.

Vessel wall characterization using quantitative MRI: what's in a number?

PubMed

Coolen, Bram F; Calcagno, Claudia; van Ooij, Pim; Fayad, Zahi A; Strijkers, Gustav J; Nederveen, Aart J

2018-02-01

The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.

Real-time adaptive methods for treatment of mobile organs by MRI-controlled high-intensity focused ultrasound.

PubMed

de Senneville, Baudouin Denis; Mougenot, Charles; Moonen, Chrit T W

2007-02-01

Focused ultrasound (US) is a unique and noninvasive technique for local deposition of thermal energy deep inside the body. MRI guidance offers the additional benefits of excellent target visualization and continuous temperature mapping. However, treating a moving target poses severe problems because 1) motion-related thermometry artifacts must be corrected, 2) the US focal point must be relocated according to the target displacement. In this paper a complete MRI-compatible, high-intensity focused US (HIFU) system is described together with adaptive methods that allow continuous MR thermometry and therapeutic US with real-time tracking of a moving target, online motion correction of the thermometry maps, and regional temperature control based on the proportional, integral, and derivative method. The hardware is based on a 256-element phased-array transducer with rapid electronic displacement of the focal point. The exact location of the target during US firing is anticipated using automatic analysis of periodic motions. The methods were tested with moving phantoms undergoing either rigid body or elastic periodical motions. The results show accurate tracking of the focal point. Focal and regional temperature control is demonstrated with a performance similar to that obtained with stationary phantoms. Copyright (c) 2007 Wiley-Liss, Inc.

Advances in locally constrained k-space-based parallel MRI.

PubMed

Samsonov, Alexey A; Block, Walter F; Arunachalam, Arjun; Field, Aaron S

2006-02-01

In this article, several theoretical and methodological developments regarding k-space-based, locally constrained parallel MRI (pMRI) reconstruction are presented. A connection between Parallel MRI with Adaptive Radius in k-Space (PARS) and GRAPPA methods is demonstrated. The analysis provides a basis for unified treatment of both methods. Additionally, a weighted PARS reconstruction is proposed, which may absorb different weighting strategies for improved image reconstruction. Next, a fast and efficient method for pMRI reconstruction of data sampled on non-Cartesian trajectories is described. In the new technique, the computational burden associated with the numerous matrix inversions in the original PARS method is drastically reduced by limiting direct calculation of reconstruction coefficients to only a few reference points. The rest of the coefficients are found by interpolating between the reference sets, which is possible due to the similar configuration of points participating in reconstruction for highly symmetric trajectories, such as radial and spirals. As a result, the time requirements are drastically reduced, which makes it practical to use pMRI with non-Cartesian trajectories in many applications. The new technique was demonstrated with simulated and actual data sampled on radial trajectories. Copyright 2006 Wiley-Liss, Inc.

Assessment of radiofrequency ablation margin by MRI-MRI image fusion in hepatocellular carcinoma

PubMed Central

Wang, Xiao-Li; Li, Kai; Su, Zhong-Zhen; Huang, Ze-Ping; Wang, Ping; Zheng, Rong-Qin

2015-01-01

AIM: To investigate the feasibility and clinical value of magnetic resonance imaging (MRI)-MRI image fusion in assessing the ablative margin (AM) for hepatocellular carcinoma (HCC). METHODS: A newly developed ultrasound workstation for MRI-MRI image fusion was used to evaluate the AM of 62 tumors in 52 HCC patients after radiofrequency ablation (RFA). The lesions were divided into two groups: group A, in which the tumor was completely ablated and 5 mm AM was achieved (n = 32); and group B, in which the tumor was completely ablated but 5 mm AM was not achieved (n = 29). To detect local tumor progression (LTP), all patients were followed every two months by contrast-enhanced ultrasound, contrast-enhanced MRI or computed tomography (CT) in the first year after RFA. Then, the follow-up interval was prolonged to every three months after the first year. RESULTS: Of the 62 tumors, MRI-MRI image fusion was successful in 61 (98.4%); the remaining case had significant deformation of the liver and massive ascites after RFA. The time required for creating image fusion and AM evaluation was 15.5 ± 5.5 min (range: 8-22 min) and 9.6 ± 3.2 min (range: 6-14 min), respectively. The follow-up period ranged from 1-23 mo (14.2 ± 5.4 mo). In group A, no LTP was detected in 32 lesions, whereas in group B, LTP was detected in 4 of 29 tumors, which occurred at 2, 7, 9, and 15 mo after RFA. The frequency of LTP in group B (13.8%; 4/29) was significantly higher than that in group A (0/32, P = 0.046). All of the LTPs occurred in the area in which the 5 mm AM was not achieved. CONCLUSION: The MRI-MRI image fusion using an ultrasound workstation is feasible and useful for evaluating the AM after RFA for HCC. PMID:25954109

Magnetic Resonance Imaging (MRI) -- Head

MedlinePlus Videos and Cool Tools

... are clearer and more detailed than other imaging methods. This exam does not use ionizing radiation and ... clearer and more detailed than with other imaging methods. This detail makes MRI an invaluable tool in ...

An automated method for mapping human tissue permittivities by MRI in hyperthermia treatment planning.

PubMed

Farace, P; Pontalti, R; Cristoforetti, L; Antolini, R; Scarpa, M

1997-11-01

This paper presents an automatic method to obtain tissue complex permittivity values to be used as input data in the computer modelling for hyperthermia treatment planning. Magnetic resonance (MR) images were acquired and the tissue water content was calculated from the signal intensity of the image pixels. The tissue water content was converted into complex permittivity values by monotonic functions based on mixture theory. To obtain a water content map by MR imaging a gradient-echo pulse sequence was used and an experimental procedure was set up to correct for relaxation and radiofrequency field inhomogeneity effects on signal intensity. Two approaches were followed to assign the permittivity values to fat-rich tissues: (i) fat-rich tissue localization by a segmentation procedure followed by assignment of tabulated permittivity values; (ii) water content evaluation by chemical shift imaging followed by permittivity calculation. Tests were performed on phantoms of known water content to establish the reliability of the proposed method. MRI data were acquired and processed pixel-by-pixel according to the outlined procedure. The signal intensity in the phantom images correlated well with water content. Experiments were performed on volunteers' healthy tissue. In particular two anatomical structures were chosen to calculate permittivity maps: the head and the thigh. The water content and electric permittivity values were obtained from the MRI data and compared to others in the literature. A good agreement was found for muscle, cerebrospinal fluid (CSF) and white and grey matter. The advantages of the reported method are discussed in the light of possible application in hyperthermia treatment planning.

Combination of rs-fMRI and sMRI Data to Discriminate Autism Spectrum Disorders in Young Children Using Deep Belief Network.

PubMed

Akhavan Aghdam, Maryam; Sharifi, Arash; Pedram, Mir Mohsen

2018-05-07

In recent years, the use of advanced magnetic resonance (MR) imaging methods such as functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) has recorded a great increase in neuropsychiatric disorders. Deep learning is a branch of machine learning that is increasingly being used for applications of medical image analysis such as computer-aided diagnosis. In a bid to classify and represent learning tasks, this study utilized one of the most powerful deep learning algorithms (deep belief network (DBN)) for the combination of data from Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) datasets. The DBN was employed so as to focus on the combination of resting-state fMRI (rs-fMRI), gray matter (GM), and white matter (WM) data. This was done based on the brain regions that were defined using the automated anatomical labeling (AAL), in order to classify autism spectrum disorders (ASDs) from typical controls (TCs). Since the diagnosis of ASD is much more effective at an early age, only 185 individuals (116 ASD and 69 TC) ranging in age from 5 to 10 years were included in this analysis. In contrast, the proposed method is used to exploit the latent or abstract high-level features inside rs-fMRI and sMRI data while the old methods consider only the simple low-level features extracted from neuroimages. Moreover, combining multiple data types and increasing the depth of DBN can improve classification accuracy. In this study, the best combination comprised rs-fMRI, GM, and WM for DBN of depth 3 with 65.56% accuracy (sensitivity = 84%, specificity = 32.96%, F1 score = 74.76%) obtained via 10-fold cross-validation. This result outperforms previously presented methods on ABIDE I dataset.

Common MRI acquisition non-idealities significantly impact the output of the boundary shift integral method of measuring brain atrophy on serial MRI.

PubMed

Preboske, Gregory M; Gunter, Jeff L; Ward, Chadwick P; Jack, Clifford R

2006-05-01

Measuring rates of brain atrophy from serial magnetic resonance imaging (MRI) studies is an attractive way to assess disease progression in neurodegenerative disorders, particularly Alzheimer's disease (AD). A widely recognized approach is the boundary shift integral (BSI). The objective of this study was to evaluate how several common scan non-idealities affect the output of the BSI algorithm. We created three types of image non-idealities between the image volumes in a serial pair used to measure between-scan change: inconsistent image contrast between serial scans, head motion, and poor signal-to-noise (SNR). In theory the BSI volume difference measured between each pair of images should be zero and any deviation from zero should represent corruption of the BSI measurement by some non-ideality intentionally introduced into the second scan in the pair. Two different BSI measures were evaluated, whole brain and ventricle. As the severity of motion, noise, and non-congruent image contrast increased in the second scan, the calculated BSI values deviated progressively more from the expected value of zero. This study illustrates the magnitude of the error in measures of change in brain and ventricle volume across serial MRI scans that can result from commonly encountered deviations from ideal image quality. The magnitudes of some of the measurement errors seen in this study exceed the disease effect in AD shown in various publications, which range from 1% to 2.78% per year for whole brain atrophy and 5.4% to 13.8% per year for ventricle expansion (Table 1). For example, measurement error may exceed 100% if image contrast properties dramatically differ between the two scans in a measurement pair. Methods to maximize consistency of image quality over time are an essential component of any quantitative serial MRI study.

Predicting response before initiation of neoadjuvant chemotherapy in breast cancer using new methods for the analysis of dynamic contrast enhanced MRI (DCE MRI) data

NASA Astrophysics Data System (ADS)

DeGrandchamp, Joseph B.; Whisenant, Jennifer G.; Arlinghaus, Lori R.; Abramson, V. G.; Yankeelov, Thomas E.; Cárdenas-Rodríguez, Julio

2016-03-01

The pharmacokinetic parameters derived from dynamic contrast enhanced (DCE) MRI have shown promise as biomarkers for tumor response to therapy. However, standard methods of analyzing DCE MRI data (Tofts model) require high temporal resolution, high signal-to-noise ratio (SNR), and the Arterial Input Function (AIF). Such models produce reliable biomarkers of response only when a therapy has a large effect on the parameters. We recently reported a method that solves the limitations, the Linear Reference Region Model (LRRM). Similar to other reference region models, the LRRM needs no AIF. Additionally, the LRRM is more accurate and precise than standard methods at low SNR and slow temporal resolution, suggesting LRRM-derived biomarkers could be better predictors. Here, the LRRM, Non-linear Reference Region Model (NRRM), Linear Tofts model (LTM), and Non-linear Tofts Model (NLTM) were used to estimate the RKtrans between muscle and tumor (or the Ktrans for Tofts) and the tumor kep,TOI for 39 breast cancer patients who received neoadjuvant chemotherapy (NAC). These parameters and the receptor statuses of each patient were used to construct cross-validated predictive models to classify patients as complete pathological responders (pCR) or non-complete pathological responders (non-pCR) to NAC. Model performance was evaluated using area under the ROC curve (AUC). The AUC for receptor status alone was 0.62, while the best performance using predictors from the LRRM, NRRM, LTM, and NLTM were AUCs of 0.79, 0.55, 0.60, and 0.59 respectively. This suggests that the LRRM can be used to predict response to NAC in breast cancer.

SU-E-J-192: Verification of 4D-MRI Internal Target Volume Using Cine MRI

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

Lafata, K; Czito, B; Palta, M

Purpose: To investigate the accuracy of 4D-MRI in determining the Internal Target Volume (ITV) used in radiation oncology treatment planning of liver cancers. Cine MRI is used as the standard baseline in establishing the feasibility and accuracy of 4D-MRI tumor motion within the liver. Methods: IRB approval was obtained for this retrospective study. Analysis was performed on MR images from four patients receiving external beam radiation therapy for liver cancer at our institution. Eligible patients received both Cine and 4D-MRI scans before treatment. Cine images were acquired sagittally in real time at a slice bisecting the tumor, while 4D imagesmore » were acquired volumetrically. Cine MR DICOM headers were manipulated such that each respiratory frame was assigned a unique slice location. This approach permitted the treatment planning system (Eclipse, Varian Medical Systems) to recognize a complete respiratory cycle as a “volume”, where the gross tumor was contoured temporally. Software was developed to calculate the union of all frame contours in the structure set, resulting in the corresponding plane of the ITV projecting through the middle of the tumor, defined as the Internal Target Area (ITA). This was repeated for 4D-MRI, at the corresponding slice location, allowing a direct comparison of ITAs obtained from each modality. Results: Four patients have been analyzed. ITAs contoured from 4D-MRI correlate with contours from Cine MRI. The mean error of 4D values relative to Cine values is 7.67 +/− 2.55 %. No single ITA contoured from 4D-MRI demonstrated more than 10.5 % error compared to its Cine MRI counterpart. Conclusion: Motion management is a significant aspect of treatment planning within dynamic environments such as the liver, where diaphragmatic and cardiac activity influence plan accuracy. This small pilot study suggests that 4D-MRI based ITA measurements agree with Cine MRI based measurements, an important step towards clinical implementation

Estimating neural response functions from fMRI

PubMed Central

Kumar, Sukhbinder; Penny, William

2014-01-01

This paper proposes a methodology for estimating Neural Response Functions (NRFs) from fMRI data. These NRFs describe non-linear relationships between experimental stimuli and neuronal population responses. The method is based on a two-stage model comprising an NRF and a Hemodynamic Response Function (HRF) that are simultaneously fitted to fMRI data using a Bayesian optimization algorithm. This algorithm also produces a model evidence score, providing a formal model comparison method for evaluating alternative NRFs. The HRF is characterized using previously established “Balloon” and BOLD signal models. We illustrate the method with two example applications based on fMRI studies of the auditory system. In the first, we estimate the time constants of repetition suppression and facilitation, and in the second we estimate the parameters of population receptive fields in a tonotopic mapping study. PMID:24847246

Comparison of fMRI analysis methods for heterogeneous BOLD responses in block design studies

PubMed Central

Bernal-Casas, David; Fang, Zhongnan; Lee, Jin Hyung

2017-01-01

A large number of fMRI studies have shown that the temporal dynamics of evoked BOLD responses can be highly heterogeneous. Failing to model heterogeneous responses in statistical analysis can lead to significant errors in signal detection and characterization and alter the neurobiological interpretation. However, to date it is not clear that, out of a large number of options, which methods are robust against variability in the temporal dynamics of BOLD responses in block-design studies. Here, we used rodent optogenetic fMRI data with heterogeneous BOLD responses and simulations guided by experimental data as a means to investigate different analysis methods’ performance against heterogeneous BOLD responses. Evaluations are carried out within the general linear model (GLM) framework and consist of standard basis sets as well as independent component analysis (ICA). Analyses show that, in the presence of heterogeneous BOLD responses, conventionally used GLM with a canonical basis set leads to considerable errors in the detection and characterization of BOLD responses. Our results suggest that the 3rd and 4th order gamma basis sets, the 7th to 9th order finite impulse response (FIR) basis sets, the 5th to 9th order B-spline basis sets, and the 2nd to 5th order Fourier basis sets are optimal for good balance between detection and characterization, while the 1st order Fourier basis set (coherence analysis) used in our earlier studies show good detection capability. ICA has mostly good detection and characterization capabilities, but detects a large volume of spurious activation with the control fMRI data. PMID:27993672

MRI of plants and foods

NASA Astrophysics Data System (ADS)

Van As, Henk; van Duynhoven, John

2013-04-01

The importance and prospects for MRI as applied to intact plants and to foods are presented in view of one of humanity's most pressing concerns, the sustainable and healthy feeding of a worldwide increasing population. Intact plants and foods have in common that their functionality is determined by complex multiple length scale architectures. Intact plants have an additional level of complexity since they are living systems which critically depend on transport and signalling processes between and within tissues and organs. The combination of recent cutting-edge technical advances and integration of MRI accessible parameters has the perspective to contribute to breakthroughs in understanding complex regulatory plant performance mechanisms. In food science and technology MRI allows for quantitative multi-length scale structural assessment of food systems, non-invasive monitoring of heat and mass transport during shelf-life and processing, and for a unique view on food properties under shear. These MRI applications are powerful enablers of rationally (re)designed food formulations and processes. Limitations and bottlenecks of the present plant and food MRI methods are mainly related to short T2 values and susceptibility artefacts originating from small air spaces in tissues/materials. We envisage cross-fertilisation of solutions to overcome these hurdles in MRI applications in plants and foods. For both application areas we witness a development where MRI is moving from highly specialised equipment to mobile and downscaled versions to be used by a broad user base in the field, greenhouse, food laboratory or factory.

A method for safety testing of radiofrequency/microwave-emitting devices using MRI.

PubMed

Alon, Leeor; Cho, Gene Y; Yang, Xing; Sodickson, Daniel K; Deniz, Cem M

2015-11-01

Strict regulations are imposed on the amount of radiofrequency (RF) energy that devices can emit to prevent excessive deposition of RF energy into the body. In this study, we investigated the application of MR temperature mapping and 10-g average specific absorption rate (SAR) computation for safety evaluation of RF-emitting devices. Quantification of the RF power deposition was shown for an MRI-compatible dipole antenna and a non-MRI-compatible mobile phone via phantom temperature change measurements. Validation of the MR temperature mapping method was demonstrated by comparison with physical temperature measurements and electromagnetic field simulations. MR temperature measurements alongside physical property measurements were used to reconstruct 10-g average SAR. The maximum temperature change for a dipole antenna and the maximum 10-g average SAR were 1.83°C and 12.4 W/kg, respectively, for simulations and 1.73°C and 11.9 W/kg, respectively, for experiments. The difference between MR and probe thermometry was <0.15°C. The maximum temperature change and the maximum 10-g average SAR for a cell phone radiating at maximum output for 15 min was 1.7°C and 0.54 W/kg, respectively. Information acquired using MR temperature mapping and thermal property measurements can assess RF/microwave safety with high resolution and fidelity. © 2014 Wiley Periodicals, Inc.

Complete fourier direct magnetic resonance imaging (CFD-MRI) for diffusion MRI

PubMed Central

Özcan, Alpay

2013-01-01

The foundation for an accurate and unifying Fourier-based theory of diffusion weighted magnetic resonance imaging (DW–MRI) is constructed by carefully re-examining the first principles of DW–MRI signal formation and deriving its mathematical model from scratch. The derivations are specifically obtained for DW–MRI signal by including all of its elements (e.g., imaging gradients) using complex values. Particle methods are utilized in contrast to conventional partial differential equations approach. The signal is shown to be the Fourier transform of the joint distribution of number of the magnetic moments (at a given location at the initial time) and magnetic moment displacement integrals. In effect, the k-space is augmented by three more dimensions, corresponding to the frequency variables dual to displacement integral vectors. The joint distribution function is recovered by applying the Fourier transform to the complete high-dimensional data set. In the process, to obtain a physically meaningful real valued distribution function, phase corrections are applied for the re-establishment of Hermitian symmetry in the signal. Consequently, the method is fully unconstrained and directly presents the distribution of displacement integrals without any assumptions such as symmetry or Markovian property. The joint distribution function is visualized with isosurfaces, which describe the displacement integrals, overlaid on the distribution map of the number of magnetic moments with low mobility. The model provides an accurate description of the molecular motion measurements via DW–MRI. The improvement of the characterization of tissue microstructure leads to a better localization, detection and assessment of biological properties such as white matter integrity. The results are demonstrated on the experimental data obtained from an ex vivo baboon brain. PMID:23596401

Coil compression in simultaneous multislice functional MRI with concentric ring slice-GRAPPA and SENSE.

PubMed

Chu, Alan; Noll, Douglas C

2016-10-01

Simultaneous multislice (SMS) imaging is a useful way to accelerate functional magnetic resonance imaging (fMRI). As acceleration becomes more aggressive, an increasingly larger number of receive coils are required to separate the slices, which significantly increases the computational burden. We propose a coil compression method that works with concentric ring non-Cartesian SMS imaging and should work with Cartesian SMS as well. We evaluate the method on fMRI scans of several subjects and compare it to standard coil compression methods. The proposed method uses a slice-separation k-space kernel to simultaneously compress coil data into a set of virtual coils. Five subjects were scanned using both non-SMS fMRI and SMS fMRI with three simultaneous slices. The SMS fMRI scans were processed using the proposed method, along with other conventional methods. Code is available at https://github.com/alcu/sms. The proposed method maintained functional activation with a fewer number of virtual coils than standard SMS coil compression methods. Compression of non-SMS fMRI maintained activation with a slightly lower number of virtual coils than the proposed method, but does not have the acceleration advantages of SMS fMRI. The proposed method is a practical way to compress and reconstruct concentric ring SMS data and improves the preservation of functional activation over standard coil compression methods in fMRI. Magn Reson Med 76:1196-1209, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

[Basic assessment of the CNR measurement method of MRI system in phantom-suggestion for improvement in the CNR evaluation method].

PubMed

Wada, Yoichi; Hara, Takanori; Miyati, Tosiaki

2008-02-20

Many methods of measuring contrast-to-noise ratio (CNR) in magnetic resonance imaging (MRI) have been proposed. However, it is not clear which method is best for evaluating clinical or phantom images. In this study we examined the characteristics of the methods of evaluation proposed in the past, and we proposed new CNR evaluation method that improved noise evaluation. We examined the relationship of theoretical CNR value and measurement value when measurement sensitivity was changed. We measured the relationship between number of signal averaged (NSA) and value of CNR. The CNR value changed greatly according to where noise was measured. The measuring method that we proposed in this study was superior for the following reasons: the measurement point of noise and signal are the same; the influence of the low frequency element is slight; and the correlation of measurements and theoretical value is high. The method that we proposed in this study is useful for evaluating phantom images.

4D flow imaging with MRI

PubMed Central

Stankovic, Zoran; Allen, Bradley D.; Garcia, Julio; Jarvis, Kelly B.

2014-01-01

Magnetic resonance imaging (MRI) has become an important tool for the clinical evaluation of patients with cardiovascular disease. Since its introduction in the late 1980s, 2-dimensional phase contrast MRI (2D PC-MRI) has become a routine part of standard-of-care cardiac MRI for the assessment of regional blood flow in the heart and great vessels. More recently, time-resolved PC-MRI with velocity encoding along all three flow directions and three-dimensional (3D) anatomic coverage (also termed ‘4D flow MRI’) has been developed and applied for the evaluation of cardiovascular hemodynamics in multiple regions of the human body. 4D flow MRI allows for the comprehensive evaluation of complex blood flow patterns by 3D blood flow visualization and flexible retrospective quantification of flow parameters. Recent technical developments, including the utilization of advanced parallel imaging techniques such as k-t GRAPPA, have resulted in reasonable overall scan times, e.g., 8-12 minutes for 4D flow MRI of the aorta and 10-20 minutes for whole heart coverage. As a result, the application of 4D flow MRI in a clinical setting has become more feasible, as documented by an increased number of recent reports on the utility of the technique for the assessment of cardiac and vascular hemodynamics in patient studies. A number of studies have demonstrated the potential of 4D flow MRI to provide an improved assessment of hemodynamics which might aid in the diagnosis and therapeutic management of cardiovascular diseases. The purpose of this review is to describe the methods used for 4D flow MRI acquisition, post-processing and data analysis. In addition, the article provides an overview of the clinical applications of 4D flow MRI and includes a review of applications in the heart, thoracic aorta and hepatic system. PMID:24834414

Distortion correction for diffusion-weighted MRI tractography and fMRI in the temporal lobes.

PubMed

Embleton, Karl V; Haroon, Hamied A; Morris, David M; Ralph, Matthew A Lambon; Parker, Geoff J M

2010-10-01

Single shot echo-planar imaging (EPI) sequences are currently the most commonly used sequences for diffusion-weighted imaging (DWI) and functional magnetic resonance imaging (fMRI) as they allow relatively high signal to noise with rapid acquisition time. A major drawback of EPI is the substantial geometric distortion and signal loss that can occur due to magnetic field inhomogeneities close to air-tissue boundaries. If DWI-based tractography and fMRI are to be applied to these regions, then the distortions must be accurately corrected to achieve meaningful results. We describe robust acquisition and processing methods for correcting such distortions in spin echo (SE) EPI using a variant of the reversed direction k space traversal method with a number of novel additions. We demonstrate that dual direction k space traversal with maintained diffusion-encoding gradient strength and direction results in correction of the great majority of eddy current-associated distortions in DWI, in addition to those created by variations in magnetic susceptibility. We also provide examples to demonstrate that the presence of severe distortions cannot be ignored if meaningful tractography results are desired. The distortion correction routine was applied to SE-EPI fMRI acquisitions and allowed detection of activation in the temporal lobe that had been previously found using PET but not conventional fMRI. © 2010 Wiley-Liss, Inc.

Directly detected 55Mn MRI: Application to phantoms for human hyperpolarized 13C MRI development

PubMed Central

von Morze, Cornelius; Carvajal, Lucas; Reed, Galen D.; Swisher, Christine Leon; Tropp, James; Vigneron, Daniel B.

2014-01-01

In this work we demonstrate for the first time directly detected manganese-55 (55Mn) MRI using a clinical 3T MRI scanner designed for human hyperpolarized 13C clinical studies with no additional hardware modifications. Due to the similar frequency of the 55Mn and 13C resonances, the use of aqueous permanganate for large, signal-dense, and cost-effective “13C” MRI phantoms was investigated, addressing the clear need for new phantoms for these studies. Due to 100% natural abundance, higher intrinsic sensitivity, and favorable relaxation properties, 55Mn MRI of aqueous permanganate demonstrates dramatically increased sensitivity over typical 13C phantom MRI, at greatly reduced cost as compared with large 13C-enriched phantoms. A large sensitivity advantage (22-fold) was demonstrated. A cylindrical phantom (d= 8 cm) containing concentrated aqueous sodium permanganate (2.7M) was scanned rapidly by 55Mn MRI in a human head coil tuned for 13C, using a balanced SSFP acquisition. The requisite penetration of RF magnetic fields into concentrated permanganate was investigated by experiments and high frequency electromagnetic simulations, and found to be sufficient for 55Mn MRI with reasonably sized phantoms. A sub-second slice-selective acquisition yielded mean image SNR of ~60 at 0.5cm3 spatial resolution, distributed with minimum central signal ~40% of the maximum edge signal. We anticipate that permanganate phantoms will be very useful for testing HP 13C coils and methods designed for human studies. PMID:25179135

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

Semi-automatic 10/20 Identification Method for MRI-Free Probe Placement in Transcranial Brain Mapping Techniques.

PubMed

Xiao, Xiang; Zhu, Hao; Liu, Wei-Jie; Yu, Xiao-Ting; Duan, Lian; Li, Zheng; Zhu, Chao-Zhe

2017-01-01

The International 10/20 system is an important head-surface-based positioning system for transcranial brain mapping techniques, e.g., fNIRS and TMS. As guidance for probe placement, the 10/20 system permits both proper ROI coverage and spatial consistency among multiple subjects and experiments in a MRI-free context. However, the traditional manual approach to the identification of 10/20 landmarks faces problems in reliability and time cost. In this study, we propose a semi-automatic method to address these problems. First, a novel head surface reconstruction algorithm reconstructs head geometry from a set of points uniformly and sparsely sampled on the subject's head. Second, virtual 10/20 landmarks are determined on the reconstructed head surface in computational space. Finally, a visually-guided real-time navigation system guides the experimenter to each of the identified 10/20 landmarks on the physical head of the subject. Compared with the traditional manual approach, our proposed method provides a significant improvement both in reliability and time cost and thus could contribute to improving both the effectiveness and efficiency of 10/20-guided MRI-free probe placement.

Anatomo-clinical overlapping maps (AnaCOM): a new method to create anatomo-functional maps from neuropsychological tests and structural MRI scan of subjects with brain lesions

NASA Astrophysics Data System (ADS)

Kinkingnehun, Serge R. J.; du Boisgueheneuc, Foucaud; Golmard, Jean-Louis; Zhang, Sandy X.; Levy, Richard; Dubois, Bruno

2004-04-01

We have developed a new technique to analyze correlations between brain anatomy and its neurological functions. The technique is based on the anatomic MRI of patients with brain lesions who are administered neuropsychological tests. Brain lesions of the MRI scans are first manually segmented. The MRI volumes are then normalized to a reference map, using the segmented area as a mask. After normalization, the brain lesions of the MRI are segmented again in order to redefine the border of the lesions in the context of the normalized brain. Once the MRI is segmented, the patient's score on the neuropsychological test is assigned to each voxel in the lesioned area, while the rest of the voxels of the image are set to 0. Subsequently, the individual patient's MRI images are superimposed, and each voxel is reassigned the average score of the patients who have a lesion at that voxel. A threshold is applied to remove regions having less than three overlaps. This process leads to an anatomo-functional map that links brain areas to functional loss. Other maps can be created to aid in analyzing the functional maps, such as one that indicates the 95% confidence interval of the averaged scores for each area. This anatomo-clinical overlapping map (AnaCOM) method was used to obtain functional maps from patients with lesions in the superior frontal gyrus. By finding particular subregions more responsible for a particular deficit, this method can generate new hypotheses to be tested by conventional group methods.

MRI of human hair.

PubMed

Mattle, Eveline; Weiger, Markus; Schmidig, Daniel; Boesiger, Peter; Fey, Michael

2009-06-01

Hair care for humans is a major world industry with specialised tools, chemicals and techniques. Studying the effect of hair care products has become a considerable field of research, and besides mechanical and optical testing numerous advanced analytical techniques have been employed in this area. In the present work, another means of studying the properties of hair is added by demonstrating the feasibility of magnetic resonance imaging (MRI) of the human hair. Established dedicated nuclear magnetic resonance microscopy hardware (solenoidal radiofrequency microcoils and planar field gradients) and methods (constant time imaging) were adapted to the specific needs of hair MRI. Images were produced at a spatial resolution high enough to resolve the inner structure of the hair, showing contrast between cortex and medulla. Quantitative evaluation of a scan series with different echo times provided a T*(2) value of 2.6 ms for the cortex and a water content of about 90% for hairs saturated with water. The demonstration of the feasibility of hair MRI potentially adds a new tool to the large variety of analytical methods used nowadays in the development of hair care products.

Comparison between Breast MRI and Contrast-Enhanced Spectral Mammography

PubMed Central

Łuczyńska, Elżbieta; Heinze-Paluchowska, Sylwia; Hendrick, Edward; Dyczek, Sonia; Ryś, Janusz; Herman, Krzysztof; Blecharz, Paweł; Jakubowicz, Jerzy

2015-01-01

Background The main goal of this study was to compare contrast-enhanced spectral mammography (CESM) and breast magnetic resonance imaging (MRI) with histopathological results and to compare the sensitivity, accuracy, and positive and negative predictive values for both imaging modalities. Material/Methods After ethics approval, CESM and MRI examinations were performed in 102 patients who had suspicious lesions described in conventional mammography. All visible lesions were evaluated independently by 2 experienced radiologists using BI-RADS classifications (scale 1–5). Dimensions of lesions measured with each modality were compared to postoperative histopathology results. Results There were 102 patients entered into CESM/MRI studies and 118 lesions were identified by the combination of CESM and breast MRI. Histopathology confirmed that 81 of 118 lesions were malignant and 37 were benign. Of the 81 malignant lesions, 72 were invasive cancers and 9 were in situ cancers. Sensitivity was 100% with CESM and 93% with breast MRI. Accuracy was 79% with CESM and 73% with breast MRI. ROC curve areas based on BI-RADS were 0.83 for CESM and 0.84 for breast MRI. Lesion size estimates on CESM and breast MRI were similar, both slightly larger than those from histopathology. Conclusions Our results indicate that CESM has the potential to be a valuable diagnostic method that enables accurate detection of malignant breast lesions, has high negative predictive value, and a false-positive rate similar to that of breast MRI. PMID:25963880

MRI-determined liver proton density fat fraction, with MRS validation: Comparison of regions of interest sampling methods in patients with type 2 diabetes.

PubMed

Vu, Kim-Nhien; Gilbert, Guillaume; Chalut, Marianne; Chagnon, Miguel; Chartrand, Gabriel; Tang, An

2016-05-01

To assess the agreement between published magnetic resonance imaging (MRI)-based regions of interest (ROI) sampling methods using liver mean proton density fat fraction (PDFF) as the reference standard. This retrospective, internal review board-approved study was conducted in 35 patients with type 2 diabetes. Liver PDFF was measured by magnetic resonance spectroscopy (MRS) using a stimulated-echo acquisition mode sequence and MRI using a multiecho spoiled gradient-recalled echo sequence at 3.0T. ROI sampling methods reported in the literature were reproduced and liver mean PDFF obtained by whole-liver segmentation was used as the reference standard. Intraclass correlation coefficients (ICCs), Bland-Altman analysis, repeated-measures analysis of variance (ANOVA), and paired t-tests were performed. ICC between MRS and MRI-PDFF was 0.916. Bland-Altman analysis showed excellent intermethod agreement with a bias of -1.5 ± 2.8%. The repeated-measures ANOVA found no systematic variation of PDFF among the nine liver segments. The correlation between liver mean PDFF and ROI sampling methods was very good to excellent (0.873 to 0.975). Paired t-tests revealed significant differences (P < 0.05) with ROI sampling methods that exclusively or predominantly sampled the right lobe. Significant correlations with mean PDFF were found with sampling methods that included higher number of segments, total area equal or larger than 5 cm(2) , or sampled both lobes (P = 0.001, 0.023, and 0.002, respectively). MRI-PDFF quantification methods should sample each liver segment in both lobes and include a total surface area equal or larger than 5 cm(2) to provide a close estimate of the liver mean PDFF. © 2015 Wiley Periodicals, Inc.

Motion correction in MRI of the brain

PubMed Central

Godenschweger, F; Kägebein, U; Stucht, D; Yarach, U; Sciarra, A; Yakupov, R; Lüsebrink, F; Schulze, P; Speck, O

2016-01-01

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed. PMID:26864183

Motion correction in MRI of the brain

NASA Astrophysics Data System (ADS)

Godenschweger, F.; Kägebein, U.; Stucht, D.; Yarach, U.; Sciarra, A.; Yakupov, R.; Lüsebrink, F.; Schulze, P.; Speck, O.

2016-03-01

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed.

Preprocessing film-copied MRI for studying morphological brain changes.

PubMed

Pham, Tuan D; Eisenblätter, Uwe; Baune, Bernhard T; Berger, Klaus

2009-06-15

The magnetic resonance imaging (MRI) of the brain is one of the important data items for studying memory and morbidity in elderly as these images can provide useful information through the quantitative measures of various regions of interest of the brain. As an effort to fully automate the biomedical analysis of the brain that can be combined with the genetic data of the same human population and where the records of the original MRI data are missing, this paper presents two effective methods for addressing this imaging problem. The first method handles the restoration of the film-copied MRI. The second method involves the segmentation of the image data. Experimental results and comparisons with other methods suggest the usefulness of the proposed image analysis methodology.

MRI for peripheral artery disease: Introductory physics for vascular physicians.

PubMed

Roy, Trisha L; Forbes, Thomas L; Dueck, Andrew D; Wright, Graham A

2018-04-01

Magnetic resonance imaging (MRI) has advanced significantly in the past decade and provides a safe and non-invasive method of evaluating peripheral artery disease (PAD), with and without using exogenous contrast agents. MRI offers a promising alternative for imaging patients but the complexity of MRI can make it less accessible for physicians to understand or use. This article provides a brief introduction to the technical principles of MRI for physicians who manage PAD patients. We discuss the basic principles of how MRI works and tailor the discussion to how MRI can evaluate anatomic characteristics of peripheral arterial lesions.

[Recent advances in newborn MRI].

PubMed

Morel, B; Hornoy, P; Husson, B; Bloch, I; Adamsbaum, C

2014-07-01

The accurate morphological exploration of the brain is a major challenge in neonatology that advances in magnetic resonance imaging (MRI) can now provide. MRI is the gold standard if an hypoxic ischemic pathology is suspected in a full term neonate. In prematures, the specific role of MRI remains to be defined, secondary to US in any case. We present a state of the art of hardware and software technical developments in MRI. The increase in magnetic field strength (3 tesla) and the emergence of new MRI sequences provide access to new information. They both have positive and negative consequences on the daily clinical data acquisition use. The semiology of brain imaging in full term newborns and prematures is more extensive and complex and thereby more difficult to interpret. The segmentation of different brain structures in the newborn, even very premature, is now available. It is now possible to dissociate the cortex and basal ganglia from the cerebral white matter, to calculate the volume of anatomical structures, which improves the morphometric quantification and the understanding of the normal and abnormal brain development. MRI is a powerful tool to analyze the neonatal brain. The relevance of the diagnostic contribution requires an adaptation of the parameters of the sequences to acquire and of the image processing methods. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

PubMed

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method

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

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.

Purpose: Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment. Methods: In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandularmore » tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's pairedt-test, and Dice's similarity coefficients (DSC). Results: The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers’ manual segmentation, the proposed FCM-Atlas method achieves a correlation ofr

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method

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

Wu, Shandong; Weinstein, Susan P.; Conant, Emily F.

2013-12-15

Purpose: Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment. Methods: In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandularmore » tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's pairedt-test, and Dice's similarity coefficients (DSC). Results: The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers’ manual segmentation, the proposed FCM-Atlas method achieves a correlation ofr

Connective tissue of cervical carcinoma xenografts: associations with tumor hypoxia and interstitial fluid pressure and its assessment by DCE-MRI and DW-MRI.

PubMed

Hompland, Tord; Ellingsen, Christine; Galappathi, Kanthi; Rofstad, Einar K

2014-01-01

Abstract Background. A high fraction of stroma in malignant tissues is associated with tumor progression, metastasis, and poor prognosis. Possible correlations between the stromal and physiologic microenvironments of tumors and the potential of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance imaging (MRI) in quantification of the stromal microenvironment were investigated in this study. Material and methods. CK-160 cervical carcinoma xenografts were used as preclinical tumor model. A total of 43 tumors were included in the study, and of these tumors, 17 were used to search for correlations between the stromal and physiologic microenvironments, 11 were subjected to DCE-MRI, and 15 were subjected to DW-MRI. DCE-MRI and DW-MRI were carried out at 1.5 T with a clinical MR scanner and a slotted tube resonator transceiver coil constructed for mice. Fraction of connective tissue (CTFCol) and fraction of hypoxic tissue (HFPim) were determined by immunohistochemistry. A Millar SPC 320 catheter was used to measure tumor interstitial fluid pressure (IFP). Results. CTFCol showed a positive correlation to IFP and an inverse correlation to HFPim. The apparent diffusion coefficient assessed by DW-MRI was inversely correlated to CTFCol, whereas no correlation was found between DCE-MRI-derived parameters and CTFCol. Conclusion. DW-MRI is a potentially useful method for characterizing the stromal microenvironment of tumors.

WE-B-BRD-00: MRI for Radiation Oncology

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

NONE

The use of MRI in radiation therapy is rapidly increasing. Applications vary from the MRI simulator, to the MRI fused with CT, and to the integrated MRI+RT system. Compared with the standard MRI QA, a broader scope of QA features has to be defined in order to maximize the benefits of using MRI in radiation therapy. These QA features include geometric fidelity, image registration, motion management, cross-system alignment, and hardware interference. Advanced MRI techniques require a specific type of QA, as they are being widely used in radiation therapy planning, dose calculations, post-implant dosimetry, and prognoses. A vigorous and adaptivemore » QA program is crucial to defining the responsibility of the entire radiation therapy group and detecting deviations from the performance of high-quality treatment. As a drastic departure from CT simulation, MRI simulation requires changes in the work flow of treatment planning and image guidance. MRI guided radiotherapy platforms are being developed and commercialized to take the advantage of the advance in knowledge, technology and clinical experience. This symposium will from an educational perspective discuss the scope and specific issues related to MRI guided radiotherapy. Learning Objectives: Understand the difference between a standard and a radiotherapy-specific MRI QA program. Understand the effects of MRI artifacts (geometric distortion and motion) on radiotherapy. Understand advanced MRI techniques (ultrashort echo, fast MRI including dynamic MRI and 4DMRI, diffusion, perfusion, and MRS) and related QA. Understand the methods to prepare MRI for treatment planning (electron density assignment, multimodality image registration, segmentation and motion management). Current status of MRI guided treatment platforms. Dr. Jihong Wang has a research grant with Elekta-MRL project. Dr. Ke Sheng receives research grants from Varian Medical systems.« less

Three-dimensional liver motion tracking using real-time two-dimensional MRI

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

Brix, Lau, E-mail: lau.brix@stab.rm.dk; Ringgaard, Steffen; Sørensen, Thomas Sangild

2014-04-15

Purpose: Combined magnetic resonance imaging (MRI) systems and linear accelerators for radiotherapy (MR-Linacs) are currently under development. MRI is noninvasive and nonionizing and can produce images with high soft tissue contrast. However, new tracking methods are required to obtain fast real-time spatial target localization. This study develops and evaluates a method for tracking three-dimensional (3D) respiratory liver motion in two-dimensional (2D) real-time MRI image series with high temporal and spatial resolution. Methods: The proposed method for 3D tracking in 2D real-time MRI series has three steps: (1) Recording of a 3D MRI scan and selection of a blood vessel (ormore » tumor) structure to be tracked in subsequent 2D MRI series. (2) Generation of a library of 2D image templates oriented parallel to the 2D MRI image series by reslicing and resampling the 3D MRI scan. (3) 3D tracking of the selected structure in each real-time 2D image by finding the template and template position that yield the highest normalized cross correlation coefficient with the image. Since the tracked structure has a known 3D position relative to each template, the selection and 2D localization of a specific template translates into quantification of both the through-plane and in-plane position of the structure. As a proof of principle, 3D tracking of liver blood vessel structures was performed in five healthy volunteers in two 5.4 Hz axial, sagittal, and coronal real-time 2D MRI series of 30 s duration. In each 2D MRI series, the 3D localization was carried out twice, using nonoverlapping template libraries, which resulted in a total of 12 estimated 3D trajectories per volunteer. Validation tests carried out to support the tracking algorithm included quantification of the breathing induced 3D liver motion and liver motion directionality for the volunteers, and comparison of 2D MRI estimated positions of a structure in a watermelon with the actual positions. Results: Axial

Sensitivity and specificity of a new MRI method evaluating temporo-mandibular joint disc-condyle relationships: an in vivo study.

PubMed

Benbelaïd, R; Fleiter, B

2006-03-01

The aim of this study was to evaluate sensitivity and specificity of a new method to locate temporo-mandibular joint (TMJ) disc using magnetic resonance imaging (MRI) and analyze disc-condyle relationships, in asymptomatic subjects and patients with disc displacement. Twenty-nine sagittal MRI of 16 subjects, 8 asymptomatic volunteers and 8 subjects with anterior disc displacement, were carried out during controlled opening from intercuspal position up to a 25 mm opening. Selected sections were analyzed with a graphic computerized system of coordinates. The total surface area (TS) of disc section was separated into anterior surface area (AS) and posterior surface area. Areas were determined by computer. Two trained examiners drew images at random. The reliability of AS/TS ratio index was evaluated in a previous study. AS/TS ratio sensitivity (Se) and specificity (Sp) were calculated closed mouth, 5 mm open and 25 mm open mouth. Best sensitivity (Se=0.63) and specificity (Sp=0.81) were obtained when MRI was realized with closed mouth and 25 mm open mouth. Lower sensitivity was observed when MRI was performed either with closed mouth (Se=0.54) or 25 mm open mouth (Se=0.18). Lower specificity was observed with 5 mm open mouth (Sp=0.68). In conclusion, it was confirmed as well that MRI of anterior disc displacement should be performed with closed mouth and opened mouth. Thus, further studies are required to assess disc displacement and mechanical alterations and to evaluate the risk of direct damage on TMJ tissues.

Effects of B1 inhomogeneity correction for three-dimensional variable flip angle T1 measurements in hip dGEMRIC at 3 T and 1.5 T.

PubMed

Siversson, Carl; Chan, Jenny; Tiderius, Carl-Johan; Mamisch, Tallal Charles; Jellus, Vladimir; Svensson, Jonas; Kim, Young-Jo

2012-06-01

Delayed gadolinium-enhanced MRI of cartilage is a technique for studying the development of osteoarthritis using quantitative T(1) measurements. Three-dimensional variable flip angle is a promising method for performing such measurements rapidly, by using two successive spoiled gradient echo sequences with different excitation pulse flip angles. However, the three-dimensional variable flip angle method is very sensitive to inhomogeneities in the transmitted B(1) field in vivo. In this study, a method for correcting for such inhomogeneities, using an additional B(1) mapping spin-echo sequence, was evaluated. Phantom studies concluded that three-dimensional variable flip angle with B(1) correction calculates accurate T(1) values also in areas with high B(1) deviation. Retrospective analysis of in vivo hip delayed gadolinium-enhanced MRI of cartilage data from 40 subjects showed the difference between three-dimensional variable flip angle with and without B(1) correction to be generally two to three times higher at 3 T than at 1.5 T. In conclusion, the B(1) variations should always be taken into account, both at 1.5 T and at 3 T. Copyright © 2011 Wiley-Liss, Inc.

Bone and cartilage characteristics in postmenopausal women with mild knee radiographic osteoarthritis and those without radiographic osteoarthritis

PubMed Central

Multanen, J.; Heinonen, A.; Häkkinen, A.; Kautiainen, H.; Kujala, U.M.; Lammentausta, E.; Jämsä, T.; Kiviranta, I.; Nieminen, M.T.

2015-01-01

Objectives: To evaluate the association between radiographically-assessed knee osteoarthritis and femoral neck bone characteristics in women with mild knee radiographic osteoarthritis and those without radiographic osteoarthritis. Methods: Ninety postmenopausal women (mean age [SD], 58 [4] years; height, 163 [6] cm; weight, 71 [11] kg) participated in this cross-sectional study. The severity of radiographic knee osteoarthritis was defined using Kellgren-Lawrence grades 0=normal (n=12), 1=doubtful (n=25) or 2=minimal (n=53). Femoral neck bone mineral content (BMC), section modulus (Z), and cross-sectional area (CSA) were measured with DXA. The biochemical composition of ipsilateral knee cartilage was estimated using quantitative MRI measures, T2 mapping and dGEMRIC. The associations between radiographic knee osteoarthritis grades and bone and cartilage characteristics were analyzed using generalized linear models. Results: Age-, height-, and weight-adjusted femoral neck BMC (p for linearity=0.019), Z (p for linearity=0.033), and CSA (p for linearity=0.019) increased significantly with higher knee osteoarthritis grades. There was no linear relationship between osteoarthritis grades and knee cartilage indices. Conclusions: Increased DXA assessed hip bone strength is related to knee osteoarthritis severity. These results are hypothesis driven that there is an inverse relationship between osteoarthritis and osteoporosis. However, MRI assessed measures of cartilage do not discriminate mild radiographic osteoarthritis severity. PMID:25730654

Perfusion MRI: The Five Most Frequently Asked Clinical Questions

PubMed Central

Essig, Marco; Nguyen, Thanh Binh; Shiroishi, Mark S.; Saake, Marc; Provenzale, James M.; Enterline, David S.; Anzalone, Nicoletta; Dörfler, Arnd; Rovira, Àlex; Wintermark, Max; Law, Meng

2013-01-01

OBJECTIVE This article addresses questions that radiologists frequently ask when planning, performing, processing, and interpreting MRI perfusion studies in CNS imaging. CONCLUSION Perfusion MRI is a promising tool in assessing stroke, brain tumors, and neurodegenerative diseases. Most of the impediments that have limited the use of perfusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols. PMID:23971482

Contrast agent enhanced pQCT of articular cartilage

NASA Astrophysics Data System (ADS)

Kallioniemi, A. S.; Jurvelin, J. S.; Nieminen, M. T.; Lammi, M. J.; Töyräs, J.

2007-02-01

The delayed gadolinium enhanced MRI of cartilage (dGEMRIC) technique is the only non-invasive means to estimate proteoglycan (PG) content in articular cartilage. In dGEMRIC, the anionic paramagnetic contrast agent gadopentetate distributes in inverse relation to negatively charged PGs, leading to a linear relation between T1,Gd and spatial PG content in tissue. In the present study, for the first time, contrast agent enhanced peripheral quantitative computed tomography (pQCT) was applied, analogously to dGEMRIC, for the quantitative detection of spatial PG content in cartilage. The suitability of two anionic radiographic contrast agents, gadopentetate and ioxaglate, to detect enzymatically induced PG depletion in articular cartilage was investigated. First, the interrelationships of x-ray absorption, as measured with pQCT, and the contrast agent solution concentration were investigated. Optimal contrast agent concentrations for the following experiments were selected. Second, diffusion rates for both contrast agents were investigated in intact (n = 3) and trypsin-degraded (n = 3) bovine patellar cartilage. The contrast agent concentration of the cartilaginous layer was measured prior to and 2-27 h after immersion. Optimal immersion time for the further experiments was selected. Third, the suitability of gadopentetate and ioxaglate enhanced pQCT to detect the enzymatically induced specific PG depletion was investigated by determining the contrast agent concentrations and uronic acid and water contents in digested and intact osteochondral samples (n = 16). After trypsin-induced PG loss (-70%, p < 0.05) the penetration of gadopentetate and ioxaglate increased (p < 0.05) by 34% and 48%, respectively. Gadopentetate and ioxaglate concentrations both showed strong correlation (r = -0.95, r = -0.94, p < 0.01, respectively) with the uronic acid content. To conclude, contrast agent enhanced pQCT provides a technique to quantify PG content in normal and experimentally

fMRI and EEG responses to periodic visual stimulation.

PubMed

Guy, C N; ffytche, D H; Brovelli, A; Chumillas, J

1999-08-01

EEG/VEP and fMRI responses to periodic visual stimulation are reported. The purpose of these experiments was to look for similar patterns in the time series produced by each method to help understand the relationship between the two. The stimulation protocol was the same for both sets of experiments and consisted of five complete cycles of checkerboard pattern reversal at 1.87 Hz for 30 s followed by 30 s of a stationary checkerboard. The fMRI data was analyzed using standard methods, while the EEG was analyzed with a new measurement of activation-the VEPEG. Both VEPEG and fMRI time series contain the fundamental frequency of the stimulus and quasi harmonic components-an unexplained double frequency commonly found in fMRI data. These results have prompted a reappraisal of the methods for analyzing fMRI data and have suggested a connection between our findings and much older published invasive electrophysiological measurements of blood flow and the partial pressures of oxygen and carbon dioxide. Overall our new analysis suggests that fMRI signals are strongly dependant on hydraulic blood flow effects. We distinguish three categories of fMRI signal corresponding to: focal activated regions of brain tissue; diffuse nonspecific regions of steal; and major cerebral vessels of arterial supply or venous drainage. Each category of signal has its own finger print in frequency, amplitude, and phase. Finally, we put forward the hypothesis that modulations in blood flow are not only the consequence but are also the cause of modulations in functional activity. Copyright 1999 Academic Press.

The Physics and Mathematics of MRI

NASA Astrophysics Data System (ADS)

Ansorge, Richard; Graves, Martin

2016-10-01

Magnetic Resonance Imaging is a very important clinical imaging tool. It combines different fields of physics and engineering in a uniquely complex way. MRI is also surprisingly versatile, `pulse sequences' can be designed to yield many different types of contrast. This versatility is unique to MRI. This short book gives both an in depth account of the methods used for the operation and construction of modern MRI systems and also the principles of sequence design and many examples of applications. An important additional feature of this book is the detailed discussion of the mathematical principles used in building optimal MRI systems and for sequence design. The mathematical discussion is very suitable for undergraduates attending medical physics courses. It is also more complete than usually found in alternative books for physical scientists or more clinically orientated works.

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

PubMed Central

Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

2016-01-01

The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821

“MRI Stealth” robot for prostate interventions

PubMed Central

STOIANOVICI, DAN; SONG, DANNY; PETRISOR, DORU; URSU, DANIEL; MAZILU, DUMITRU; MUTENER, MICHAEL; SCHAR, MICHAEL; PATRICIU, ALEXANDRU

2011-01-01

The paper reports an important achievement in MRI instrumentation, a pneumatic, fully actuated robot located within the scanner alongside the patient and operating under remote control based on the images. Previous MRI robots commonly used piezoelectric actuation limiting their compatibility. Pneumatics is an ideal choice for MRI compatibility because it is decoupled from electromagnetism, but pneumatic actuators were hardly controllable. This achievement was possible due to a recent technology breakthrough, the invention of a new type of pneumatic motor, PneuStep (1), designed for the robot reported here with uncompromised MRI compatibility, high-precision, and medical safety. MrBot is one of the “MRI stealth” robots today (the second is described in this issue by Zangos et al.). Both of these systems are also multi-imager compatible, being able to operate with the imager of choice or cross-imaging modalities. For MRI compatibility the robot is exclusively constructed of nonmagnetic and dielectric materials such as plastics, ceramics, crystals, rubbers and is electricity free. Light-based encoding is used for feedback, so that all electric components are distally located outside the imager’s room. MRI robots are modern, digital medical instruments in line with advanced imaging equipment and methods. These allow for accessing patients within closed bore scanners and performing interventions under direct (in scanner) imaging feedback. MRI robots could allow e.g. to biopsy small lesions imaged with cutting edge cancer imaging methods, or precisely deploy localized therapy at cancer foci. Our robot is the first to show the feasibility of fully automated in-scanner interventions. It is customized for the prostate and operates transperineally for needle interventions. It can accommodate various needle drivers for different percutaneous procedures such as biopsy, thermal ablations, or brachytherapy. The first needle driver is customized for fully automated low

Magnetic Resonance Medical Imaging (MRI)-from the inside

NASA Astrophysics Data System (ADS)

Bottomley, Paul

There are about 36,000 magnetic resonance imaging (MRI) scanners in the world, with annual sales of 2500. In the USA about 34 million MRI studies are done annually, and 60-70% of all scanners operate at 1.5 Tesla (T). In 1982 there were none. How MRI got to be-and how it got to1.5T is the subject of this talk. Its an insider's view-mine-as a physics PhD student at Nottingham University when MRI (almost) began, through to the invention of the 1.5T clinical MRI scanner at GE's research center in Schenectady NY.Before 1977 all MRI was done on laboratory nuclear magnetic resonance instruments used for analyzing small specimens via chemical shift spectroscopy (MRS). It began with Lauterbur's 1973 observation that turning up the spectrometer's linear gradient magnetic field, generated a spectrum that was a 1D projection of the sample in the direction of the gradient. What followed in the 70's was the development of 3 key methods of 3D spatial localization that remain fundamental to MRI today.As the 1980's began, the once unimaginable prospect of upscaling from 2cm test-tubes to human body-sized magnets, gradient and RF transmit/receive systems, was well underway, evolving from arm-sized, to whole-body electromagnet-based systems operating at <0.2T. I moved to Johns Hopkins University to apply MRI methods to localized MRS and study cardiac metabolism, and then to GE to build a whole-body MRS machine. The largest uniform magnet possible-then, a 1.5T superconducting system-was required. Body MRI was first thought impossible above 0.35T due to RF penetration, detector coil and signal-to-noise ratio (SNR) issues. When GE finally did take on MRI, their plan was to drop the field to 0.3T. We opted to make MRI work at 1.5T instead. The result was a scanner that could study both anatomy and metabolism with a SNR way beyond its lower field rivals. MRI's success truly reflects the team efforts of many: from the NMR physics to the engineering of magnets, gradient and RF systems.

Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform

PubMed Central

Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart

2014-01-01

Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331

TU-CD-BRA-04: Evaluation of An Atlas-Based Segmentation Method for Prostate and Peripheral Zone Regions On MRI

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

Nelson, AS; Piper, J; Curry, K

2015-06-15

Purpose: Prostate MRI plays an important role in diagnosis, biopsy guidance, and therapy planning for prostate cancer. Prostate MRI contours can be used to aid in image fusion for ultrasound biopsy guidance and delivery of radiation. Our goal in this study is to evaluate an automatic atlas-based segmentation method for generating prostate and peripheral zone (PZ) contours on MRI. Methods: T2-weighted MRIs were acquired on 3T-Discovery MR750 System (GE, Milwaukee). The Volumes of Interest (VOIs): prostate and PZ were outlined by an expert radiation oncologist and used to create an atlas library for atlas-based segmentation. The atlas-segmentation accuracy was evaluatedmore » using a leave-one-out analysis. The method involved automatically finding the atlas subject that best matched the test subject followed by a normalized intensity-based free-form deformable registration of the atlas subject to the test subject. The prostate and PZ contours were transformed to the test subject using the same deformation. For each test subject the three best matches were used and the final contour was combined using Majority Vote. The atlas-segmentation process was fully automatic. Dice similarity coefficients (DSC) and mean Hausdorff values were used for comparison. Results: VOIs contours were available for 28 subjects. For the prostate, the atlas-based segmentation method resulted in an average DSC of 0.88+/−0.08 and a mean Hausdorff distance of 1.1+/−0.9mm. The number of patients (#) in DSC ranges are as follows: 0.60–0.69(1), 0.70–0.79(2), 0.80–0.89(13), >0.89(11). For the PZ, the average DSC was 0.72+/−0.17 and average Hausdorff of 0.9+/−0.9mm. The number of patients (#) in DSC ranges are as follows: <0.60(4), 0.60–0.69(6), 0.70–0.79(7), 0.80–0.89(9), >0.89(1). Conclusion: The MRI atlas-based segmentation method achieved good results for both the whole prostate and PZ compared to expert defined VOIs. The technique is fast, fully automatic, and has the

SU-F-J-112: Clinical Feasibility Test of An RF Pulse-Based MRI Method for the Quantitative Fat-Water Segmentation

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

Yee, S; Wloch, J; Pirkola, M

Purpose: Quantitative fat-water segmentation is important not only because of the clinical utility of fat-suppressed MRI images in better detecting lesions of clinical significance (in the midst of bright fat signal) but also because of the possible physical need, in which CT-like images based on the materials’ photon attenuation properties may have to be generated from MR images; particularly, as in the case of MR-only radiation oncology environment to obtain radiation dose calculation or as in the case of hybrid PET/MR modality to obtain attenuation correction map for the quantitative PET reconstruction. The majority of such fat-water quantitative segmentations havemore » been performed by utilizing the Dixon’s method and its variations, which have to enforce the proper settings (often predefined) of echo time (TE) in the pulse sequences. Therefore, such methods have been unable to be directly combined with those ultrashort TE (UTE) sequences that, taking the advantage of very low TE values (∼ 10’s microsecond), might be beneficial to directly detect bones. Recently, an RF pulse-based method (http://dx.doi.org/10.1016/j.mri.2015.11.006), termed as PROD pulse method, was introduced as a method of quantitative fat-water segmentation that does not have to depend on predefined TE settings. Here, the clinical feasibility of this method is verified in brain tumor patients by combining the PROD pulse with several sequences. Methods: In a clinical 3T MRI, the PROD pulse was combined with turbo spin echo (e.g. TR=1500, TE=16 or 60, ETL=15) or turbo field echo (e.g. TR=5.6, TE=2.8, ETL=12) sequences without specifying TE values. Results: The fat-water segmentation was possible without having to set specific TE values. Conclusion: The PROD pulse method is clinically feasible. Although not yet combined with UTE sequences in our laboratory, the method is potentially compatible with UTE sequences, and thus, might be useful to directly segment fat, water, bone and air.« less

Arm MRI scan

MedlinePlus

... MRI and often available in the emergency room. Alternative Names MRI - arm; Wrist MRI; MRI - wrist; Elbow ... any medical emergency or for the diagnosis or treatment of any medical condition. A licensed physician should ...

Image formation in diffusion MRI: A review of recent technical developments

PubMed Central

Miller, Karla L.

2017-01-01

Diffusion magnetic resonance imaging (MRI) is a standard imaging tool in clinical neurology, and is becoming increasingly important for neuroscience studies due to its ability to depict complex neuroanatomy (eg, white matter connectivity). Single‐shot echo‐planar imaging is currently the predominant formation method for diffusion MRI, but suffers from blurring, distortion, and low spatial resolution. A number of methods have been proposed to address these limitations and improve diffusion MRI acquisition. Here, the recent technical developments for image formation in diffusion MRI are reviewed. We discuss three areas of advance in diffusion MRI: improving image fidelity, accelerating acquisition, and increasing the signal‐to‐noise ratio. Level of Evidence: 5 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:646–662 PMID:28194821

Battlefield MRI

DOE PAGES

Espy, Michelle

2015-06-01

Magnetic Resonance Imaging is the best method for non-invasive imaging of soft tissue anatomy, saving countless lives each year. It is regarded as the gold standard for diagnosis of mild to moderate traumatic brain injuries. Furthermore, conventional MRI relies on very high, fixed strength magnetic fields (> 1.5 T) with parts-per-million homogeneity, which requires very large and expensive magnets.

Battlefield MRI

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

Espy, Michelle

Magnetic Resonance Imaging is the best method for non-invasive imaging of soft tissue anatomy, saving countless lives each year. It is regarded as the gold standard for diagnosis of mild to moderate traumatic brain injuries. Furthermore, conventional MRI relies on very high, fixed strength magnetic fields (> 1.5 T) with parts-per-million homogeneity, which requires very large and expensive magnets.

The evolving role of MRI in the assessment of coronary artery disease.

PubMed

Blackwell, G G; Pohost, G M

1995-04-13

Magnetic resonance imaging (MRI) methods are positioned to make a major impact in the care of patients with ischemic heart disease. Further advances are to be expected in the area of myocardial perfusion imaging and noninvasive MRI coronary "angiography." Work also continues in determining quantitative flow via MRI. Although expensive, the unique ability of MRI methods to provide multiple pieces of information in a single examination may make this technology cost effective. The concept of a "one-step shop" is progressing steadily toward a clinical reality.

Derivation and validation of simple anthropometric equations to predict adipose tissue mass and total fat mass with MRI as the reference method

PubMed Central

Al-Gindan, Yasmin Y.; Hankey, Catherine R.; Govan, Lindsay; Gallagher, Dympna; Heymsfield, Steven B.; Lean, Michael E. J.

2017-01-01

The reference organ-level body composition measurement method is MRI. Practical estimations of total adipose tissue mass (TATM), total adipose tissue fat mass (TATFM) and total body fat are valuable for epidemiology, but validated prediction equations based on MRI are not currently available. We aimed to derive and validate new anthropometric equations to estimate MRI-measured TATM/TATFM/total body fat and compare them with existing prediction equations using older methods. The derivation sample included 416 participants (222 women), aged between 18 and 88 years with BMI between 15·9 and 40·8 (kg/m2). The validation sample included 204 participants (110 women), aged between 18 and 86 years with BMI between 15·7 and 36·4 (kg/m2). Both samples included mixed ethnic/racial groups. All the participants underwent whole-body MRI to quantify TATM (dependent variable) and anthropometry (independent variables). Prediction equations developed using stepwise multiple regression were further investigated for agreement and bias before validation in separate data sets. Simplest equations with optimal R2 and Bland–Altman plots demonstrated good agreement without bias in the validation analyses: men: TATM (kg) = 0·198 weight (kg) + 0·478 waist (cm) − 0·147 height (cm) − 12·8 (validation: R2 0·79, CV = 20 %, standard error of the estimate (SEE)=3·8 kg) and women: TATM (kg)=0·789 weight (kg) + 0·0786 age (years) − 0·342 height (cm) + 24·5 (validation: R2 0·84, CV = 13 %, SEE = 3·0 kg). Published anthropometric prediction equations, based on MRI and computed tomographic scans, correlated strongly with MRI-measured TATM: (R2 0·70 – 0·82). Estimated TATFM correlated well with published prediction equations for total body fat based on underwater weighing (R2 0·70–0·80), with mean bias of 2·5–4·9 kg, correctable with log-transformation in most equations. In conclusion, new equations, using simple anthropometric measurements, estimated MRI-measured TATM

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

PubMed Central

Velikina, Julia V.; Block, Walter F.; Kijowski, Richard; Samsonov, Alexey A.

2017-01-01

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexibl representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplifie treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure. PMID:28113746

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

PubMed

Liu, Fang; Velikina, Julia V; Block, Walter F; Kijowski, Richard; Samsonov, Alexey A

2017-02-01

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexible representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplified treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed  ∼ 200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.

FPGA-based RF interference reduction techniques for simultaneous PET-MRI

NASA Astrophysics Data System (ADS)

Gebhardt, P.; Wehner, J.; Weissler, B.; Botnar, R.; Marsden, P. K.; Schulz, V.

2016-05-01

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET-MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling-decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion II D PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field distribution

FPGA-based RF interference reduction techniques for simultaneous PET–MRI

PubMed Central

Gebhardt, P; Wehner, J; Weissler, B; Botnar, R; Marsden, P K; Schulz, V

2016-01-01

Abstract The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET–MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling–decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion IID PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field

FPGA-based RF interference reduction techniques for simultaneous PET-MRI.

PubMed

Gebhardt, P; Wehner, J; Weissler, B; Botnar, R; Marsden, P K; Schulz, V

2016-05-07

The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) as a multi-modal imaging technique is considered very promising and powerful with regard to in vivo disease progression examination, therapy response monitoring and drug development. However, PET-MRI system design enabling simultaneous operation with unaffected intrinsic performance of both modalities is challenging. As one of the major issues, both the PET detectors and the MRI radio-frequency (RF) subsystem are exposed to electromagnetic (EM) interference, which may lead to PET and MRI signal-to-noise ratio (SNR) deteriorations. Early digitization of electronic PET signals within the MRI bore helps to preserve PET SNR, but occurs at the expense of increased amount of PET electronics inside the MRI and associated RF field emissions. This raises the likelihood of PET-related MRI interference by coupling into the MRI RF coil unwanted spurious signals considered as RF noise, as it degrades MRI SNR and results in MR image artefacts. RF shielding of PET detectors is a commonly used technique to reduce PET-related RF interferences, but can introduce eddy-current-related MRI disturbances and hinder the highest system integration. In this paper, we present RF interference reduction methods which rely on EM field coupling-decoupling principles of RF receive coils rather than suppressing emitted fields. By modifying clock frequencies and changing clock phase relations of digital circuits, the resulting RF field emission is optimised with regard to a lower field coupling into the MRI RF coil, thereby increasing the RF silence of PET detectors. Our methods are demonstrated by performing FPGA-based clock frequency and phase shifting of digital silicon photo-multipliers (dSiPMs) used in the PET modules of our MR-compatible Hyperion II (D) PET insert. We present simulations and magnetic-field map scans visualising the impact of altered clock phase pattern on the spatial RF field

Preliminary experience with a novel method of three-dimensional co-registration of prostate cancer digital histology and in vivo multiparametric MRI.

PubMed

Orczyk, C; Rusinek, H; Rosenkrantz, A B; Mikheev, A; Deng, F-M; Melamed, J; Taneja, S S

2013-12-01

To assess a novel method of three-dimensional (3D) co-registration of prostate cancer digital histology and in-vivo multiparametric magnetic resonance imaging (mpMRI) image sets for clinical usefulness. A software platform was developed to achieve 3D co-registration. This software was prospectively applied to three patients who underwent radical prostatectomy. Data comprised in-vivo mpMRI [T2-weighted, dynamic contrast-enhanced weighted images (DCE); apparent diffusion coefficient (ADC)], ex-vivo T2-weighted imaging, 3D-rebuilt pathological specimen, and digital histology. Internal landmarks from zonal anatomy served as reference points for assessing co-registration accuracy and precision. Applying a method of deformable transformation based on 22 internal landmarks, a 1.6 mm accuracy was reached to align T2-weighted images and the 3D-rebuilt pathological specimen, an improvement over rigid transformation of 32% (p = 0.003). The 22 zonal anatomy landmarks were more accurately mapped using deformable transformation than rigid transformation (p = 0.0008). An automatic method based on mutual information, enabled automation of the process and to include perfusion and diffusion MRI images. Evaluation of co-registration accuracy using the volume overlap index (Dice index) met clinically relevant requirements, ranging from 0.81-0.96 for sequences tested. Ex-vivo images of the specimen did not significantly improve co-registration accuracy. This preliminary analysis suggests that deformable transformation based on zonal anatomy landmarks is accurate in the co-registration of mpMRI and histology. Including diffusion and perfusion sequences in the same 3D space as histology is essential further clinical information. The ability to localize cancer in 3D space may improve targeting for image-guided biopsy, focal therapy, and disease quantification in surveillance protocols. Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Comparison between target magnetic resonance imaging (MRI) in-gantry and cognitively directed transperineal or transrectal-guided prostate biopsies for Prostate Imaging-Reporting and Data System (PI-RADS) 3-5 MRI lesions.

PubMed

Yaxley, Anna J; Yaxley, John W; Thangasamy, Isaac A; Ballard, Emma; Pokorny, Morgan R

2017-11-01

To compare the detection rates of prostate cancer (PCa) in men with Prostate Imaging-Reporting and Data System (PI-RADS) 3-5 abnormalities on 3-Tesla multiparametric (mp) magnetic resonance imaging (MRI) using in-bore MRI-guided biopsy compared with cognitively directed transperineal (cTP) biopsy and transrectal ultrasonography (cTRUS) biopsy. This was a retrospective single-centre study of consecutive men attending the private practice clinic of an experienced urologist performing MRI-guided biopsy and an experienced urologist performing cTP and cTRUS biopsy techniques for PI-RADS 3-5 lesions identified on 3-Tesla mpMRI. There were 595 target mpMRI lesions from 482 men with PI-RADS 3-5 regions of interest during 483 episodes of biopsy. The abnormal mpMRI target lesion was biopsied using the MRI-guided method for 298 biopsies, the cTP method for 248 biopsies and the cTRUS method for 49 biopsies. There were no significant differences in PCa detection among the three biopsy methods in PI-RADS 3 (48.9%, 40.0% and 44.4%, respectively), PI-RADS 4 (73.2%, 81.0% and 85.0%, respectively) or PI-RADS 5 (95.2, 92.0% and 95.0%, respectively) lesions, and there was no significant difference in detection of significant PCa among the biopsy methods in PI-RADS 3 (42.2%, 30.0% and 33.3%, respectively), PI-RADS 4 (66.8%, 66.0% and 80.0%, respectively) or PI-RADS 5 (90.5%, 89.8% and 90.0%, respectively) lesions. There were also no differences in PCa or significant PCa detection based on lesion location or size among the methods. We found no significant difference in the ability to detect PCa or significant PCa using targeted MRI-guided, cTP or cTRUS biopsy methods. Identification of an abnormal area on mpMRI appears to be more important in increasing the detection of PCa than the technique used to biopsy an MRI abnormality. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Exploiting the wavelet structure in compressed sensing MRI.

PubMed

Chen, Chen; Huang, Junzhou

2014-12-01

Sparsity has been widely utilized in magnetic resonance imaging (MRI) to reduce k-space sampling. According to structured sparsity theories, fewer measurements are required for tree sparse data than the data only with standard sparsity. Intuitively, more accurate image reconstruction can be achieved with the same number of measurements by exploiting the wavelet tree structure in MRI. A novel algorithm is proposed in this article to reconstruct MR images from undersampled k-space data. In contrast to conventional compressed sensing MRI (CS-MRI) that only relies on the sparsity of MR images in wavelet or gradient domain, we exploit the wavelet tree structure to improve CS-MRI. This tree-based CS-MRI problem is decomposed into three simpler subproblems then each of the subproblems can be efficiently solved by an iterative scheme. Simulations and in vivo experiments demonstrate the significant improvement of the proposed method compared to conventional CS-MRI algorithms, and the feasibleness on MR data compared to existing tree-based imaging algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.

Fetal MRI: A Technical Update with Educational Aspirations

PubMed Central

Gholipour, Ali; Estroff, Judith A.; Barnewolt, Carol E.; Robertson, Richard L.; Grant, P. Ellen; Gagoski, Borjan; Warfield, Simon K.; Afacan, Onur; Connolly, Susan A.; Neil, Jeffrey J.; Wolfberg, Adam; Mulkern, Robert V.

2015-01-01

Fetal magnetic resonance imaging (MRI) examinations have become well-established procedures at many institutions and can serve as useful adjuncts to ultrasound (US) exams when diagnostic doubts remain after US. Due to fetal motion, however, fetal MRI exams are challenging and require the MR scanner to be used in a somewhat different mode than that employed for more routine clinical studies. Herein we review the techniques most commonly used, and those that are available, for fetal MRI with an emphasis on the physics of the techniques and how to deploy them to improve success rates for fetal MRI exams. By far the most common technique employed is single-shot T2-weighted imaging due to its excellent tissue contrast and relative immunity to fetal motion. Despite the significant challenges involved, however, many of the other techniques commonly employed in conventional neuro- and body MRI such as T1 and T2*-weighted imaging, diffusion and perfusion weighted imaging, as well as spectroscopic methods remain of interest for fetal MR applications. An effort to understand the strengths and limitations of these basic methods within the context of fetal MRI is made in order to optimize their use and facilitate implementation of technical improvements for the further development of fetal MR imaging, both in acquisition and post-processing strategies. PMID:26225129

Quantification of liver fat with respiratory-gated quantitative chemical shift encoded MRI.

PubMed

Motosugi, Utaroh; Hernando, Diego; Bannas, Peter; Holmes, James H; Wang, Kang; Shimakawa, Ann; Iwadate, Yuji; Taviani, Valentina; Rehm, Jennifer L; Reeder, Scott B

2015-11-01

To evaluate free-breathing chemical shift-encoded (CSE) magnetic resonance imaging (MRI) for quantification of hepatic proton density fat-fraction (PDFF). A secondary purpose was to evaluate hepatic R2* values measured using free-breathing quantitative CSE-MRI. Fifty patients (mean age, 56 years) were prospectively recruited and underwent the following four acquisitions to measure PDFF and R2*; 1) conventional breath-hold CSE-MRI (BH-CSE); 2) respiratory-gated CSE-MRI using respiratory bellows (BL-CSE); 3) respiratory-gated CSE-MRI using navigator echoes (NV-CSE); and 4) single voxel MR spectroscopy (MRS) as the reference standard for PDFF. Image quality was evaluated by two radiologists. MRI-PDFF measured from the three CSE-MRI methods were compared with MRS-PDFF using linear regression. The PDFF and R2* values were compared using two one-sided t-test to evaluate statistical equivalence. There was no significant difference in the image quality scores among the three CSE-MRI methods for either PDFF (P = 1.000) or R2* maps (P = 0.359-1.000). Correlation coefficients (95% confidence interval [CI]) for the PDFF comparisons were 0.98 (0.96-0.99) for BH-, 0.99 (0.97-0.99) for BL-, and 0.99 (0.98-0.99) for NV-CSE. The statistical equivalence test revealed that the mean difference in PDFF and R2* between any two of the three CSE-MRI methods was less than ±1 percentage point (pp) and ±5 s(-1) , respectively (P < 0.046). Respiratory-gated CSE-MRI with respiratory bellows or navigator echo are feasible methods to quantify liver PDFF and R2* and are as valid as the standard breath-hold technique. © 2015 Wiley Periodicals, Inc.

[MRI of the pineal gland].

PubMed

Langevad, Line; Madsen, Camilla Gøbel; Siebner, Hartwig; Garde, Ellen

2014-11-10

The pineal gland (CP) is located centrally in the brain and produces melatonin. Cysts and concrements are frequent findings on MRI but their significance is still unclear. The visualization of CP is difficult due to its location and surrounding structures and so far, no standardized method exists. New studies suggest a correlation between CP-morphology and melatonin secretion as well as a connection between melatonin, disturbed circadian rhythm, and the development of cancer and cardiovascular diseases, underlining the need for a standardized approach to CP on MRI.

The physics of functional magnetic resonance imaging (fMRI)

NASA Astrophysics Data System (ADS)

Buxton, Richard B.

2013-09-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

The physics of functional magnetic resonance imaging (fMRI)

PubMed Central

Buxton, Richard B

2015-01-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology. PMID:24006360

The physics of functional magnetic resonance imaging (fMRI).

PubMed

Buxton, Richard B

2013-09-01

Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm(3) spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

Split gradient coils for simultaneous PET-MRI

PubMed Central

Poole, Michael; Bowtell, Richard; Green, Dan; Pittard, Simon; Lucas, Alun; Hawkes, Rob; Carpenter, Adrian

2015-01-01

Combining positron emission tomography (PET) and MRI necessarily involves an engineering tradeoff as the equipment needed for the two modalities vies for the space closest to the region where the signals originate. In one recently described scanner configuration for simultaneous positron emission tomography–MRI, the positron emission tomography detection scintillating crystals reside in an 80-mm gap between the 2 halves of a 1-T split-magnet cryostat. A novel set of gradient and shim coils has been specially designed for this split MRI scanner to include an 110-mm gap from which wires are excluded so as not to interfere with positron detection. An inverse boundary element method was necessarily employed to design the three orthogonal, shielded gradient coils and shielded Z0 shim coil. The coils have been constructed and tested in the hybrid positron emission tomography-MRI system and successfully used in simultaneous positron emission tomography-MRI experiments. PMID:19780167

Task-Related Edge Density (TED)—A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain

PubMed Central

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach “Task-related Edge Density” (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function. PMID:27341204

Functional connectomics from resting-state fMRI

PubMed Central

Smith, Stephen M; Vidaurre, Diego; Beckmann, Christian F; Glasser, Matthew F; Jenkinson, Mark; Miller, Karla L; Nichols, Thomas E; Robinson, Emma; Salimi-Khorshidi, Gholamreza; Woolrich, Mark W; Barch, Deanna M; Uğurbil, Kamil; Van Essen, David C

2014-01-01

Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project, and highlight some upcoming challenges in functional connectomics. PMID:24238796

WE-G-BRD-09: Novel MRI Compatible Electron Accelerator for MRI-Linac Radiotherapy

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

Whelan, B; Keall, P; Gierman, S

Purpose: MRI guided radiotherapy is a rapidly growing field; however current linacs are not designed to operate in MRI fringe fields. As such, current MRI- Linac systems require magnetic shielding, impairing MR image quality and system flexibility. Here, we present a bespoke electron accelerator concept with robust operation in in-line magnetic fields. Methods: For in-line MRI-Linac systems, electron gun performance is the major constraint on accelerator performance. To overcome this, we propose placing a cathode directly within the first accelerating cavity. Such a configuration is used extensively in high energy particle physics, but not previously for radiotherapy. Benchmarked computational modellingmore » (CST, Darmstadt, Germany) was employed to design and assess a 5.5 cell side coupled accelerator with a temperature limited thermionic cathode in the first accelerating cell. This simulation was coupled to magnetic fields from a 1T MRI model to assess robustness in magnetic fields for Source to Isocenter Distance between 1 and 2 meters. Performance was compared to a conventional electron gun based system in the same magnetic field. Results: A temperature limited cathode (work function 1.8eV, temperature 1245K, emission constant 60A/K/cm{sup 2}) will emit a mean current density of 24mA/mm{sup 2} (Richardson’s Law). We modeled a circular cathode with radius 2mm and mean current 300mA. Capture efficiency of the device was 43%, resulting in target current of 130 mA. The electron beam had a FWHM of 0.2mm, and mean energy of 5.9MeV (interquartile spread of 0.1MeV). Such an electron beam is suitable for radiotherapy, comparing favourably to conventional systems. This model was robust to operation the MRI fringe field, with a maximum current loss of 6% compared to 85% for the conventional system. Conclusion: The bespoke electron accelerator is robust to operation in in-line magnetic fields. This will enable MRI-Linacs with no accelerator magnetic shielding, and

Genes involved in prostate cancer progression determine MRI visibility

PubMed Central

Li, Ping; You, Sungyong; Nguyen, Christopher; Wang, Yanping; Kim, Jayoung; Sirohi, Deepika; Ziembiec, Asha; Luthringer, Daniel; Lin, Shih-Chieh; Daskivich, Timothy; Wu, Jonathan; Freeman, Michael R; Saouaf, Rola; Li, Debiao; Kim, Hyung L.

2018-01-01

MRI is used to image prostate cancer and target tumors for biopsy or therapeutic ablation. The objective was to understand the biology of tumors not visible on MRI that may go undiagnosed and untreated. Methods: Prostate cancers visible or invisible on multiparametric MRI were macrodissected and examined by RNAseq. Differentially expressed genes (DEGs) based on MRI visibility status were cross-referenced with publicly available gene expression databases to identify genes associated with disease progression. Genes with potential roles in determining MRI visibility and disease progression were knocked down in murine prostate cancer xenografts, and imaged by MRI. Results: RNAseq identified 1,654 DEGs based on MRI visibility status. Comparison of DEGs based on MRI visibility and tumor characteristics revealed that Gleason score (dissimilarity test, p<0.0001) and tumor size (dissimilarity test, p<0.039) did not completely determine MRI visibility. Genes in previously reported prognostic signatures significantly correlated with MRI visibility suggesting that MRI visibility was prognostic. Cross-referencing DEGs with external datasets identified four genes (PHYHD1, CENPF, ALDH2, GDF15) that predict MRI visibility, progression free survival and metastatic deposits. Genetic modification of a human prostate cancer cell line to induce miR-101 and suppress CENPF decreased cell migration and invasion. As prostate cancer xenografts in mice, these cells had decreased visibility on diffusion weighted MRI and decreased perfusion, which correlated with immunostaining showing decreased cell density and proliferation. Conclusions: Genes involved in prostate cancer prognosis and metastasis determine MRI visibility, indicating that MRI visibility has prognostic significance. MRI visibility was associated with genetic features linked to poor prognosis. PMID:29556354

Quantitative chemical shift-encoded MRI is an accurate method to quantify hepatic steatosis.

PubMed

Kühn, Jens-Peter; Hernando, Diego; Mensel, Birger; Krüger, Paul C; Ittermann, Till; Mayerle, Julia; Hosten, Norbert; Reeder, Scott B

2014-06-01

To compare the accuracy of liver fat quantification using a three-echo chemical shift-encoded magnetic resonance imaging (MRI) technique without and with correction for confounders with spectroscopy (MRS) as the reference standard. Fifty patients (23 women, mean age 56.6 ± 13.2 years) with fatty liver disease were enrolled. Patients underwent T2-corrected single-voxel MRS and a three-echo chemical shift-encoded gradient echo (GRE) sequence at 3.0T. MRI fat fraction (FF) was calculated without and with T2* and T1 correction and multispectral modeling of fat and compared with MRS-FF using linear regression. The spectroscopic range of liver fat was 0.11%-38.7%. Excellent correlation between MRS-FF and MRI-FF was observed when using T2* correction (R(2)  = 0.96). With use of T2* correction alone, the slope was significantly different from 1 (1.16 ± 0.03, P < 0.001) and the intercept was different from 0 (1.14% ± 0.50%, P < 0.023). This slope was significantly different than 1.0 when no T1 correction was used (P = 0.001). When T2*, T1, and spectral complexity of fat were addressed, the results showed equivalence between fat quantification using MRI and MRS (slope: 1.02 ± 0.03, P = 0.528; intercept: 0.26% ± 0.46%, P = 0.572). Complex three-echo chemical shift-encoded MRI is equivalent to MRS for quantifying liver fat, but only with correction for T2* decay and T1 recovery and use of spectral modeling of fat. This is necessary because T2* decay, T1 recovery, and multispectral complexity of fat are processes which may otherwise bias the measurements. Copyright © 2013 Wiley Periodicals, Inc.

Whole-body MRI including diffusion-weighted MRI compared with 5-HTP PET/CT in the detection of neuroendocrine tumors

PubMed Central

Carlbom, Lina; Caballero-Corbalán, José; Granberg, Dan; Sörensen, Jens; Eriksson, Barbro; Ahlström, Håkan

2017-01-01

Aim We wanted to explore if whole-body magnetic resonance imaging (MRI) including diffusion-weighted (DW) and liver-specific contrast agent-enhanced imaging could be valuable in lesion detection of neuroendocrine tumors (NET). [11C]-5-Hydroxytryptophan positron emission tomography/computed tomography (5-HTP PET/CT) was used for comparison. Materials and methods Twenty-one patients with NET were investigated with whole-body MRI, including DW imaging (DWI) and contrast-enhanced imaging of the liver, and whole-body 5-HTP PET/CT. Seven additional patients underwent upper abdomen MRI including DWI, liver-specific contrast agent-enhanced imaging, and 5-HTP PET/CT. Results There was a patient-based concordance of 61% and a lesion-based concordance of 53% between the modalities. MRI showed good concordance with PET in detecting bone metastases but was less sensitive in detecting metastases in mediastinal lymph nodes. MRI detected more liver metastases than 5-HTP PET/CT. Conclusion Whole-body MRI with DWI did not detect all NET lesions found with whole-body 5-HTP PET/CT. Our findings indicate that MRI of the liver including liver-specific contrast agent-enhanced imaging and DWI could be a useful complement to whole-body 5-HTP PET/CT. PMID:27894208

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

High spatial resolution compressed sensing (HSPARSE) functional MRI.

PubMed

Fang, Zhongnan; Van Le, Nguyen; Choy, ManKin; Lee, Jin Hyung

2016-08-01

To propose a novel compressed sensing (CS) high spatial resolution functional MRI (fMRI) method and demonstrate the advantages and limitations of using CS for high spatial resolution fMRI. A randomly undersampled variable density spiral trajectory enabling an acceleration factor of 5.3 was designed with a balanced steady state free precession sequence to achieve high spatial resolution data acquisition. A modified k-t SPARSE method was then implemented and applied with a strategy to optimize regularization parameters for consistent, high quality CS reconstruction. The proposed method improves spatial resolution by six-fold with 12 to 47% contrast-to-noise ratio (CNR), 33 to 117% F-value improvement and maintains the same temporal resolution. It also achieves high sensitivity of 69 to 99% compared the original ground-truth, small false positive rate of less than 0.05 and low hemodynamic response function distortion across a wide range of CNRs. The proposed method is robust to physiological noise and enables detection of layer-specific activities in vivo, which cannot be resolved using the highest spatial resolution Nyquist acquisition. The proposed method enables high spatial resolution fMRI that can resolve layer-specific brain activity and demonstrates the significant improvement that CS can bring to high spatial resolution fMRI. Magn Reson Med 76:440-455, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Dual-TRACER: High resolution fMRI with constrained evolution reconstruction.

PubMed

Li, Xuesong; Ma, Xiaodong; Li, Lyu; Zhang, Zhe; Zhang, Xue; Tong, Yan; Wang, Lihong; Sen Song; Guo, Hua

2018-01-01

fMRI with high spatial resolution is beneficial for studies in psychology and neuroscience, but is limited by various factors such as prolonged imaging time, low signal to noise ratio and scarcity of advanced facilities. Compressed Sensing (CS) based methods for accelerating fMRI data acquisition are promising. Other advanced algorithms like k-t FOCUSS or PICCS have been developed to improve performance. This study aims to investigate a new method, Dual-TRACER, based on Temporal Resolution Acceleration with Constrained Evolution Reconstruction (TRACER), for accelerating fMRI acquisitions using golden angle variable density spiral. Both numerical simulations and in vivo experiments at 3T were conducted to evaluate and characterize this method. Results show that Dual-TRACER can provide functional images with a high spatial resolution (1×1mm 2 ) under an acceleration factor of 20 while maintaining hemodynamic signals well. Compared with other investigated methods, dual-TRACER provides a better signal recovery, higher fMRI sensitivity and more reliable activation detection. Copyright © 2017 Elsevier Inc. All rights reserved.

RF HEATING OF MRI-ASSISTED CATHETER STEERING COILS FOR INTERVENTIONAL MRI

PubMed Central

Settecase, Fabio; Hetts, Steven W.; Martin, Alastair J.; Roberts, Timothy P. L.; Bernhardt, Anthony F.; Evans, Lee; Malba, Vincent; Saeed, Maythem; Arenson, Ronald L.; Kucharzyk, Walter; Wilson, Mark W.

2010-01-01

RATIONALE AND OBJECTIVES To assess magnetic resonance imaging (MRI) radiofrequency (RF) related heating of conductive wire coils used in magnetically steerable endovascular catheters. MATERIALS AND METHODS A 3-axis microcoil was fabricated onto a 1.8 Fr catheter tip. In vitro testing was performed in a 1.5 T MRI system using an agarose gel filled vessel phantom, a transmit/receive body RF coil and a steady state free precession (SSFP) pulse sequence, and a fluoroptic thermometry system. Temperature was measured without simulated blood flow at varying distances from magnet isocenter and varying flip angles. Additional experiments were performed with laser-lithographed single-axis microcoil-tipped microcatheters in air and in a saline bath with varied grounding of the microcoil wires. Preliminary in vivo evaluation of RF heating was performed in pigs at 1.5 T with coil-tipped catheters in various positions in the common carotid arteries with SSFP pulse sequence on and off, and under physiologic flow and zero flow conditions. RESULTS In tissue-mimicking agarose gel, RF heating resulted in a maximal temperature increase of 0.35°C after 15 minutes of imaging, 15 cm from magnet isocenter. For a single axis microcoil, maximal temperature increases were 0.73-1.91°C in air and 0.45-0.55°C in saline. In vivo, delayed contrast enhanced MRI revealed no evidence of vascular injury and histopathological sections from the common carotid arteries confirmed the lack of vascular damage. CONCLUSIONS Microcatheter tip microcoils for endovascular catheter steering in MRI experience minimal RF heating under the conditions tested. These data provide the basis for further in vivo testing of this promising technology for endovascular interventional MRI. PMID:21075019

Implementation of time-efficient adaptive sampling function design for improved undersampled MRI reconstruction

NASA Astrophysics Data System (ADS)

Choi, Jinhyeok; Kim, Hyeonjin

2016-12-01

To improve the efficacy of undersampled MRI, a method of designing adaptive sampling functions is proposed that is simple to implement on an MR scanner and yet effectively improves the performance of the sampling functions. An approximation of the energy distribution of an image (E-map) is estimated from highly undersampled k-space data acquired in a prescan and efficiently recycled in the main scan. An adaptive probability density function (PDF) is generated by combining the E-map with a modeled PDF. A set of candidate sampling functions are then prepared from the adaptive PDF, among which the one with maximum energy is selected as the final sampling function. To validate its computational efficiency, the proposed method was implemented on an MR scanner, and its robust performance in Fourier-transform (FT) MRI and compressed sensing (CS) MRI was tested by simulations and in a cherry tomato. The proposed method consistently outperforms the conventional modeled PDF approach for undersampling ratios of 0.2 or higher in both FT-MRI and CS-MRI. To fully benefit from undersampled MRI, it is preferable that the design of adaptive sampling functions be performed online immediately before the main scan. In this way, the proposed method may further improve the efficacy of the undersampled MRI.

Whole-brain spectroscopic MRI biomarkers identify infiltrating margins in glioblastoma patients

PubMed Central

Cordova, James S.; Shu, Hui-Kuo G.; Liang, Zhongxing; Gurbani, Saumya S.; Cooper, Lee A. D.; Holder, Chad A.; Olson, Jeffrey J.; Kairdolf, Brad; Schreibmann, Eduard; Neill, Stewart G.; Hadjipanayis, Constantinos G.; Shim, Hyunsuk

2016-01-01

Background The standard of care for glioblastoma (GBM) is maximal safe resection followed by radiation therapy with chemotherapy. Currently, contrast-enhanced MRI is used to define primary treatment volumes for surgery and radiation therapy. However, enhancement does not identify the tumor entirely, resulting in limited local control. Proton spectroscopic MRI (sMRI), a method reporting endogenous metabolism, may better define the tumor margin. Here, we develop a whole-brain sMRI pipeline and validate sMRI metrics with quantitative measures of tumor infiltration. Methods Whole-brain sMRI metabolite maps were coregistered with surgical planning MRI and imported into a neuronavigation system to guide tissue sampling in GBM patients receiving 5-aminolevulinic acid fluorescence-guided surgery. Samples were collected from regions with metabolic abnormalities in a biopsy-like fashion before bulk resection. Tissue fluorescence was measured ex vivo using a hand-held spectrometer. Tissue samples were immunostained for Sox2 and analyzed to quantify the density of staining cells using a novel digital pathology image analysis tool. Correlations among sMRI markers, Sox2 density, and ex vivo fluorescence were evaluated. Results Spectroscopic MRI biomarkers exhibit significant correlations with Sox2-positive cell density and ex vivo fluorescence. The choline to N-acetylaspartate ratio showed significant associations with each quantitative marker (Pearson's ρ = 0.82, P < .001 and ρ = 0.36, P < .0001, respectively). Clinically, sMRI metabolic abnormalities predated contrast enhancement at sites of tumor recurrence and exhibited an inverse relationship with progression-free survival. Conclusions As it identifies tumor infiltration and regions at high risk for recurrence, sMRI could complement conventional MRI to improve local control in GBM patients. PMID:26984746

Double temporal sparsity based accelerated reconstruction of compressively sensed resting-state fMRI.

PubMed

Aggarwal, Priya; Gupta, Anubha

2017-12-01

A number of reconstruction methods have been proposed recently for accelerated functional Magnetic Resonance Imaging (fMRI) data collection. However, existing methods suffer with the challenge of greater artifacts at high acceleration factors. This paper addresses the issue of accelerating fMRI collection via undersampled k-space measurements combined with the proposed method based on l 1 -l 1 norm constraints, wherein we impose first l 1 -norm sparsity on the voxel time series (temporal data) in the transformed domain and the second l 1 -norm sparsity on the successive difference of the same temporal data. Hence, we name the proposed method as Double Temporal Sparsity based Reconstruction (DTSR) method. The robustness of the proposed DTSR method has been thoroughly evaluated both at the subject level and at the group level on real fMRI data. Results are presented at various acceleration factors. Quantitative analysis in terms of Peak Signal-to-Noise Ratio (PSNR) and other metrics, and qualitative analysis in terms of reproducibility of brain Resting State Networks (RSNs) demonstrate that the proposed method is accurate and robust. In addition, the proposed DTSR method preserves brain networks that are important for studying fMRI data. Compared to the existing methods, the DTSR method shows promising potential with an improvement of 10-12 dB in PSNR with acceleration factors upto 3.5 on resting state fMRI data. Simulation results on real data demonstrate that DTSR method can be used to acquire accelerated fMRI with accurate detection of RSNs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Brain Tumor Image Segmentation in MRI Image

NASA Astrophysics Data System (ADS)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

An Introduction to Normalization and Calibration Methods in Functional MRI

ERIC Educational Resources Information Center

Liu, Thomas T.; Glover, Gary H.; Mueller, Bryon A.; Greve, Douglas N.; Brown, Gregory G.

2013-01-01

In functional magnetic resonance imaging (fMRI), the blood oxygenation level dependent (BOLD) signal is often interpreted as a measure of neural activity. However, because the BOLD signal reflects the complex interplay of neural, vascular, and metabolic processes, such an interpretation is not always valid. There is growing evidence that changes…

On the feasibility of concurrent human TMS-EEG-fMRI measurements

PubMed Central

Reithler, Joel; Schuhmann, Teresa; de Graaf, Tom; Uludağ, Kâmil; Goebel, Rainer; Sack, Alexander T.

2013-01-01

Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware. PMID:23221407

Pairwise Classifier Ensemble with Adaptive Sub-Classifiers for fMRI Pattern Analysis.

PubMed

Kim, Eunwoo; Park, HyunWook

2017-02-01

The multi-voxel pattern analysis technique is applied to fMRI data for classification of high-level brain functions using pattern information distributed over multiple voxels. In this paper, we propose a classifier ensemble for multiclass classification in fMRI analysis, exploiting the fact that specific neighboring voxels can contain spatial pattern information. The proposed method converts the multiclass classification to a pairwise classifier ensemble, and each pairwise classifier consists of multiple sub-classifiers using an adaptive feature set for each class-pair. Simulated and real fMRI data were used to verify the proposed method. Intra- and inter-subject analyses were performed to compare the proposed method with several well-known classifiers, including single and ensemble classifiers. The comparison results showed that the proposed method can be generally applied to multiclass classification in both simulations and real fMRI analyses.

Evaluation of background parenchymal enhancement on breast MRI: a systematic review

PubMed Central

Signori, Alessio; Valdora, Francesca; Rossi, Federica; Calabrese, Massimo; Durando, Manuela; Mariscotto, Giovanna; Tagliafico, Alberto

2017-01-01

Objective: To perform a systematic review of the methods used for background parenchymal enhancement (BPE) evaluation on breast MRI. Methods: Studies dealing with BPE assessment on breast MRI were retrieved from major medical libraries independently by four reviewers up to 6 October 2015. The keywords used for database searching are “background parenchymal enhancement”, “parenchymal enhancement”, “MRI” and “breast”. The studies were included if qualitative and/or quantitative methods for BPE assessment were described. Results: Of the 420 studies identified, a total of 52 articles were included in the systematic review. 28 studies performed only a qualitative assessment of BPE, 13 studies performed only a quantitative assessment and 11 studies performed both qualitative and quantitative assessments. A wide heterogeneity was found in the MRI sequences and in the quantitative methods used for BPE assessment. Conclusion: A wide variability exists in the quantitative evaluation of BPE on breast MRI. More studies focused on a reliable and comparable method for quantitative BPE assessment are needed. Advances in knowledge: More studies focused on a quantitative BPE assessment are needed. PMID:27925480

A Method to Convert MRI Images of Temperature Change Into Images of Absolute Temperature in Solid Tumors

PubMed Central

Davis, Ryan M.; Viglianti, Benjamin L.; Yarmolenko, Pavel; Park, Ji-Young; Stauffer, Paul; Needham, David; Dewhirst, Mark W.

2013-01-01

Purpose During hyperthermia (HT), the therapeutic response of tumors varies substantially within the target temperature range (39–43°C). Current thermometry methods are either invasive or measure only temperature change, which limits the ability to study tissue responses to HT. This study combines manganese-containing low-temperature sensitive liposomes (Mn-LTSL) with proton resonance frequency shift (PRFS) thermometry to measure absolute temperature in tumors with high spatial and temporal resolution using MRI. Methods Liposomes were loaded with 300mM MnSO4. The phase transition temperature (Tm) of Mn-LTSL samples was measured by differential scanning calorimetry (DSC). The release of manganese from Mn-LTSL in saline was characterized with inductively-coupled plasma atomic emission spectroscopy. A 2T GE small animal scanner was used to acquire dynamic T1-weighted images and temperature change images of Mn-LTSL in saline phantoms and fibrosarcoma-bearing Fisher 344 rats receiving hyperthermia after Mn-LTSL injection. Results The Tm of Mn-LTSL in rat blood was 42.9 ± 0.2 °C (DSC). For Mn-LTSL samples (0.06mM – 0.5mM Mn2+ in saline) heated monotonically from 30°C to 50°C, a peak in the rate of MRI signal enhancement occurred at 43.1 ± 0.3 °C. The same peak in signal enhancement rate was observed during heating of fibrosarcoma tumors (N=3) after injection of Mn-LTSL, and the peak was used to convert temperature change images into absolute temperature. Accuracies of calibrated temperature measurements were in the range 0.9 – 1.8°C. Conclusion The release of Mn2+ from Mn-LTSL affects the rate of MR signal enhancement which enables conversion of MRI-based temperature change images to absolute temperature. PMID:23957326

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI.

PubMed

Mehranian, Abolfazl; Arabi, Hossein; Zaidi, Habib

2016-04-15

In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly challenged by the need of deriving accurate attenuation maps from MR images. A number of strategies have been developed for MRI-guided attenuation correction with different degrees of success. In this work, we compare the quantitative performance of three generic AC methods, including standard 3-class MR segmentation-based, advanced atlas-registration-based and emission-based approaches in the context of brain time-of-flight (TOF) PET/MRI. Fourteen patients referred for diagnostic MRI and (18)F-FDG PET/CT brain scans were included in this comparative study. For each study, PET images were reconstructed using four different attenuation maps derived from CT-based AC (CTAC) serving as reference, standard 3-class MR-segmentation, atlas-registration and emission-based AC methods. To generate 3-class attenuation maps, T1-weighted MRI images were segmented into background air, fat and soft-tissue classes followed by assignment of constant linear attenuation coefficients of 0, 0.0864 and 0.0975 cm(-1) to each class, respectively. A robust atlas-registration based AC method was developed for pseudo-CT generation using local weighted fusion of atlases based on their morphological similarity to target MR images. Our recently proposed MRI-guided maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm was employed to estimate the attenuation map from TOF emission data. The performance of the different AC algorithms in terms of prediction of bones and quantification of PET tracer uptake was objectively evaluated with respect to reference CTAC maps and CTAC-PET images. Qualitative evaluation showed that the MLAA-AC method could sparsely estimate bones and accurately differentiate them from air cavities. It was found that the atlas-AC method can accurately predict bones with variable errors in defining air cavities. Quantitative assessment of bone extraction accuracy based on

Laminar fMRI and computational theories of brain function.

PubMed

Stephan, K E; Petzschner, F H; Kasper, L; Bayer, J; Wellstein, K V; Stefanics, G; Pruessmann, K P; Heinzle, J

2017-11-02

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Intra- and inter-examination repeatability of magnetic resonance spectroscopy, magnitude-based MRI, and complex-based MRI for estimation of hepatic proton density fat fraction in overweight and obese children and adults

PubMed Central

Tyagi, Avishkar; Yeganeh, Omid; Levin, Yakir; Hooker, Jonathan C.; Hamilton, Gavin C.; Wolfson, Tanya; Gamst, Anthony; Zand, Amir K.; Heba, Elhamy; Loomba, Rohit; Schwimmer, Jeffrey; Middleton, Michael S.; Sirlin, Claude B.

2016-01-01

Purpose Determine intra- and inter-examination repeatability of magnitude-based magnetic resonance imaging (MRI-M), complex-based magnetic resonance imaging (MRI-C), and magnetic resonance spectroscopy (MRS) at 3T for estimating hepatic proton density fat fraction (PDFF), and using MRS as a reference, confirm MRI-M and MRI-C accuracy. Methods Twenty-nine overweight and obese pediatric (n = 20) and adult (n = 9) subjects (23 male, 6 female) underwent three same-day 3T MR examinations. In each examination MRI-M, MRI-C, and single-voxel MRS were acquired three times. For each MRI acquisition, hepatic PDFF was estimated at the MRS voxel location. Intra- and inter-examination repeatability were assessed by computing standard deviations (SDs) and intra-class correlation coefficients (ICCs). Aggregate SD was computed for each method as the square root of the average of first repeat variances. MRI-M and MRI-C PDFF estimation accuracy was assessed using linear regression with MRS as a reference. Results For MRI-M, MRI-C, and MRS acquisitions, respectively, mean intra-examination SDs were 0.25%, 0.42%, and 0.49%; mean intra-examination ICCs were 0.999, 0.997, and 0.995; mean inter-examination SDs were 0.42%, 0.45%, and 0.46%; and inter-examination ICCs were 0.995, 0.992, and 0.990. Aggregate SD for each method was <0.9%. Using MRS as a reference, regression slope, intercept, average bias, and R2, respectively, for MRI-M were 0.99%, 1.73%, 1.61%, and 0.986, and for MRI-C were 0.96%, 0.43%, 0.40%, and 0.991. Conclusion MRI-M, MRI-C, and MRS showed high intra- and inter-examination hepatic PDFF estimation repeatability in overweight and obese subjects. Longitudinal hepatic PDFF change >1.8% (twice the maximum aggregate SD) may represent real change rather than measurement imprecision. Further research is needed to assess whether examinations performed on different days or with different MR technologists affect repeatability of MRS voxel placement and MRS-based PDFF measurements

MRI diffusion tensor reconstruction with PROPELLER data acquisition.

PubMed

Cheryauka, Arvidas B; Lee, James N; Samsonov, Alexei A; Defrise, Michel; Gullberg, Grant T

2004-02-01

MRI diffusion imaging is effective in measuring the diffusion tensor in brain, cardiac, liver, and spinal tissue. Diffusion tensor tomography MRI (DTT MRI) method is based on reconstructing the diffusion tensor field from measurements of projections of the tensor field. Projections are obtained by appropriate application of rotated diffusion gradients. In the present paper, the potential of a novel data acquisition scheme, PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction), is examined in combination with DTT MRI for its capability and sufficiency for diffusion imaging. An iterative reconstruction algorithm is used to reconstruct the diffusion tensor field from rotated diffusion weighted blades by appropriate rotated diffusion gradients. DTT MRI with PROPELLER data acquisition shows significant potential to reduce the number of weighted measurements, avoid ambiguity in reconstructing diffusion tensor parameters, increase signal-to-noise ratio, and decrease the influence of signal distortion.

Manganese-Enhanced MRI: Biological Applications in Neuroscience.

PubMed

Malheiros, Jackeline Moraes; Paiva, Fernando Fernandes; Longo, Beatriz Monteiro; Hamani, Clement; Covolan, Luciene

2015-01-01

Magnetic resonance imaging (MRI) is an excellent non-invasive tool to investigate biological systems. The administration of the paramagnetic divalent ion manganese (Mn(2+)) enhances MRI contrast in vivo. Due to similarities between Mn(2+) and calcium (Ca(2+)), the premise of manganese-enhanced MRI (MEMRI) is that the former may enter neurons and other excitable cells through voltage-gated Ca(2+) channels. As such, MEMRI has been used to trace neuronal pathways, define morphological boundaries, and study connectivity in morphological and functional imaging studies. In this article, we provide a brief overview of MEMRI and discuss recently published data to illustrate the usefulness of this method, particularly in animal models.

Diagnostic accuracy of MRI in the measurement of glenoid bone loss.

PubMed

Gyftopoulos, Soterios; Hasan, Saqib; Bencardino, Jenny; Mayo, Jason; Nayyar, Samir; Babb, James; Jazrawi, Laith

2012-10-01

The purpose of this study is to assess the accuracy of MRI quantification of glenoid bone loss and to compare the diagnostic accuracy of MRI to CT in the measurement of glenoid bone loss. MRI, CT, and 3D CT examinations of 18 cadaveric glenoids were obtained after the creation of defects along the anterior and anteroinferior glenoid. The defects were measured by three readers separately and blindly using the circle method. These measurements were compared with measurements made on digital photographic images of the cadaveric glenoids. Paired sample Student t tests were used to compare the imaging modalities. Concordance correlation coefficients were also calculated to measure interobserver agreement. Our data show that MRI could be used to accurately measure glenoid bone loss with a small margin of error (mean, 3.44%; range, 2.06-5.94%) in estimated percentage loss. MRI accuracy was similar to that of both CT and 3D CT for glenoid loss measurements in our study for the readers familiar with the circle method, with 1.3% as the maximum expected difference in accuracy of the percentage bone loss between the different modalities (95% confidence). Glenoid bone loss can be accurately measured on MRI using the circle method. The MRI quantification of glenoid bone loss compares favorably to measurements obtained using 3D CT and CT. The accuracy of the measurements correlates with the level of training, and a learning curve is expected before mastering this technique.

Benign and malignant skull-involved lesions: discriminative value of conventional CT and MRI combined with diffusion-weighted MRI.

PubMed

Tu, Zhanhai; Xiao, Zebin; Zheng, Yingyan; Huang, Hongjie; Yang, Libin; Cao, Dairong

2018-01-01

Background Little is known about the value of computed tomography (CT) and magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) in distinguishing malignant from benign skull-involved lesions. Purpose To evaluate the discriminative value of DWI combined with conventional CT and MRI for differentiating between benign and malignant skull-involved lesions. Material and Methods CT and MRI findings of 58 patients with pathologically proven skull-involved lesions (43 benign and 15 malignant) were retrospectively reviewed. Conventional CT and MRI characteristics and apparent diffusion coefficient (ADC) value of the two groups were evaluated and compared. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter separately and together. Results The presence of cortical defects or break-through and ill-defined margins were associated with malignant skull-involved lesions (both P < 0.05). Malignant skull-involved lesions demonstrated a significantly lower ADC ( P = 0.016) than benign lesions. ROC curve analyses indicated that a combination of CT, MRI, and DWI with an ADC ≤ 0.703 × 10 -3 mm 2 /s showed optimal sensitivity, while DWI along showed optimal specificity of 88.4% in differentiating between benign and malignant skull-involved lesions. Conclusion The combination of CT, MRI, and DWI can help to differentiate malignant from benign skull-involved lesions. CT + MRI + DWI offers optimal sensitivity, while DWI offers optimal specificity.

Update on the MRI Core of the Alzheimer's Disease Neuroimaging Initiative

PubMed Central

Jack, Clifford R; Bernstein, Matt A; Borowski, Bret J; Gunter, Jeffrey L; Fox, Nick C; Thompson, Paul M; Schuff, Norbert; Krueger, Gunnar; Killiany, Ronald J; DeCarli, Charles S; Dale, Anders M; Weiner, Michael W

2010-01-01

Functions of the ADNI MRI core fall into three categories: (1) those of the central MRI core lab at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data, and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI-GO”) and future (“ADNI-2”, if funded) MRI protocol will be to maintain MRI methodological consistency in previously enrolled “ADNI-1” subjects who are followed longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor specific pilot sub-studies of arterial spin labeling perfusion, resting state functional connectivity and diffusion tensor imaging. One each of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multi-center (but single vendor) setting for these three emerging MRI applications. PMID:20451869

Simple SPION Incubation as an Efficient Intracellular Labeling Method for Tracking Neural Progenitor Cells Using MRI

PubMed Central

D. M., Jayaseema; Lai, Jiann-Shiun; Hueng, Dueng-Yuan; Chang, Chen

2013-01-01

Cellular magnetic resonance imaging (MRI) has been well-established for tracking neural progenitor cells (NPC). Superparamagnetic iron oxide nanoparticles (SPIONs) approved for clinical application are the most common agents used for labeling. Conventionally, transfection agents (TAs) were added with SPIONs to facilitate cell labeling because SPIONs in the native unmodified form were deemed inefficient for intracellular labeling. However, compelling evidence also shows that simple SPION incubation is not invariably ineffective. The labeling efficiency can be improved by prolonged incubation and elevated iron doses. The goal of the present study was to establish simple SPION incubation as an efficient intracellular labeling method. To this end, NPCs derived from the neonatal subventricular zone were incubated with SPIONs (Feridex®) and then evaluated in vitro with regard to the labeling efficiency and biological functions. The results showed that, following 48 hours of incubation at 75 µg/ml, nearly all NPCs exhibited visible SPION intake. Evidence from light microscopy, electron microscopy, chemical analysis, and magnetic resonance imaging confirmed the effectiveness of the labeling. Additionally, biological assays showed that the labeled NPCs exhibited unaffected viability, oxidative stress, apoptosis and differentiation. In the demonstrated in vivo cellular MRI experiment, the hypointensities representing the SPION labeled NPCs remained observable throughout the entire tracking period. The findings indicate that simple SPION incubation without the addition of TAs is an efficient intracellular magnetic labeling method. This simple approach may be considered as an alternative approach to the mainstream labeling method that involves the use of TAs. PMID:23468856

A new bias field correction method combining N3 and FCM for improved segmentation of breast density on MRI.

PubMed

Lin, Muqing; Chan, Siwa; Chen, Jeon-Hor; Chang, Daniel; Nie, Ke; Chen, Shih-Ting; Lin, Cheng-Ju; Shih, Tzu-Ching; Nalcioglu, Orhan; Su, Min-Ying

2011-01-01

Quantitative breast density is known as a strong risk factor associated with the development of breast cancer. Measurement of breast density based on three-dimensional breast MRI may provide very useful information. One important step for quantitative analysis of breast density on MRI is the correction of field inhomogeneity to allow an accurate segmentation of the fibroglandular tissue (dense tissue). A new bias field correction method by combining the nonparametric nonuniformity normalization (N3) algorithm and fuzzy-C-means (FCM)-based inhomogeneity correction algorithm is developed in this work. The analysis is performed on non-fat-sat T1-weighted images acquired using a 1.5 T MRI scanner. A total of 60 breasts from 30 healthy volunteers was analyzed. N3 is known as a robust correction method, but it cannot correct a strong bias field on a large area. FCM-based algorithm can correct the bias field on a large area, but it may change the tissue contrast and affect the segmentation quality. The proposed algorithm applies N3 first, followed by FCM, and then the generated bias field is smoothed using Gaussian kernal and B-spline surface fitting to minimize the problem of mistakenly changed tissue contrast. The segmentation results based on the N3+FCM corrected images were compared to the N3 and FCM alone corrected images and another method, coherent local intensity clustering (CLIC), corrected images. The segmentation quality based on different correction methods were evaluated by a radiologist and ranked. The authors demonstrated that the iterative N3+FCM correction method brightens the signal intensity of fatty tissues and that separates the histogram peaks between the fibroglandular and fatty tissues to allow an accurate segmentation between them. In the first reading session, the radiologist found (N3+FCM > N3 > FCM) ranking in 17 breasts, (N3+FCM > N3 = FCM) ranking in 7 breasts, (N3+FCM = N3 > FCM) in 32 breasts, (N3+FCM = N3 = FCM) in 2 breasts, and (N3 > N3

Comparison of BOLD, diffusion-weighted fMRI and ADC-fMRI for stimulation of the primary visual system with a block paradigm.

PubMed

Nicolas, R; Gros-Dagnac, H; Aubry, F; Celsis, P

2017-06-01

The blood oxygen level-dependent (BOLD) effect is extensively used for functional MRI (fMRI) but presents some limitations. Diffusion-weighted fMRI (DfMRI) has been proposed as a method more tightly linked to neuronal activity. This work proposes a protocol of DfMRI acquired for several b-values and diffusion directions that is compared to gradient-echo BOLD (GE-BOLD) and to repeated spin-echo BOLD (SE-BOLD, acquisitions performed with b=0s/mm 2 ), which was also used to ensure the reproducibility of the response. A block stimulation paradigm of the primary visual system (V1) was performed in 12 healthy subjects with checkerboard alternations (2Hz frequency). DfMRI was performed at 3T with 5 b-values (b=1500, 1000, 500, 250, 0s/mm 2 ) with TR/TE=1004/93ms, Δ/δ=45.4ms/30ms, and 6 spatial directions for diffusion measures. GE-BOLD was performed with a similar block stimulation design timing. Apparent Diffusion Coefficient (ADC)-fMRI was computed with all b-values used. An identical Z-score level was used for all fMRI modalities for the comparison of volumes of activation. ADC-fMRI and SE-BOLD fMRI activation locations were compared in a voxel-based analysis to a cytoarchitectural probability map of V1. SE-BOLD activation volumes represented only 55% of the GE-BOLD activation volumes (P<0.0001). DfMRI activation volumes averaged for all b-values acquired represented only 12% of GE-BOLD (P<0.0001) and only 22% of SE-BOLD activation volumes (P<0.005). Compared to SE-BOLD-fMRI, ADC-fMRI activations showed fewer pixels outside of V1 and a higher average probability of belonging to V1. DfMRI and ADC-fMRI acquisition at 3T could be easily post-processed with common neuro-imaging software. DfMRI and ADC-fMRI activation volumes were significantly smaller than those obtained with SE-BOLD. ADC-fMRI activations were more precisely localized in V1 than those of SE-BOLD-fMRI. This validated the increased capability of ADC-fMRI compared to BOLD to enhance the precision of

MRI of chemical reactions and processes.

PubMed

Britton, Melanie M

2017-08-01

As magnetic resonance imaging (MRI) can spatially resolve a wealth of molecular information available from nuclear magnetic resonance (NMR), it is able to non-invasively visualise the composition, properties and reactions of a broad range of spatially-heterogeneous molecular systems. Hence, MRI is increasingly finding applications in the study of chemical reactions and processes in a diverse range of environments and technologies. This article will explain the basic principles of MRI and how it can be used to visualise chemical composition and molecular properties, providing an overview of the variety of information available. Examples are drawn from the disciplines of chemistry, chemical engineering, environmental science, physics, electrochemistry and materials science. The review introduces a range of techniques used to produce image contrast, along with the chemical and molecular insight accessible through them. Methods for mapping the distribution of chemical species, using chemical shift imaging or spatially-resolved spectroscopy, are reviewed, as well as methods for visualising physical state, temperature, current density, flow velocities and molecular diffusion. Strategies for imaging materials with low signal intensity, such as those containing gases or low sensitivity nuclei, using compressed sensing, para-hydrogen or polarisation transfer, are discussed. Systems are presented which encapsulate the diversity of chemical and physical parameters observable by MRI, including one- and two-phase flow in porous media, chemical pattern formation, phase transformations and hydrodynamic (fingering) instabilities. Lastly, the emerging area of electrochemical MRI is discussed, with studies presented on the visualisation of electrochemical deposition and dissolution processes during corrosion and the operation of batteries, supercapacitors and fuel cells. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Pelvis MRI scan

MedlinePlus

... and most often available in the emergency room. Alternative Names MRI - pelvis; MRI - hips; Pelvic MRI with ... any medical emergency or for the diagnosis or treatment of any medical condition. A licensed physician should ...

Brain tumor segmentation using holistically nested neural networks in MRI images.

PubMed

Zhuge, Ying; Krauze, Andra V; Ning, Holly; Cheng, Jason Y; Arora, Barbara C; Camphausen, Kevin; Miller, Robert W

2017-10-01

Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used technique employed in the diagnosis and management of gliomas in clinical practice. MRI is also the standard imaging modality used to delineate the brain tumor target as part of treatment planning for the administration of radiation therapy. Despite more than 20 yr of research and development, computational brain tumor segmentation in MRI images remains a challenging task. We are presenting a novel method of automatic image segmentation based on holistically nested neural networks that could be employed for brain tumor segmentation of MRI images. Two preprocessing techniques were applied to MRI images. The N4ITK method was employed for correction of bias field distortion. A novel landmark-based intensity normalization method was developed so that tissue types have a similar intensity scale in images of different subjects for the same MRI protocol. The holistically nested neural networks (HNN), which extend from the convolutional neural networks (CNN) with a deep supervision through an additional weighted-fusion output layer, was trained to learn the multiscale and multilevel hierarchical appearance representation of the brain tumor in MRI images and was subsequently applied to produce a prediction map of the brain tumor on test images. Finally, the brain tumor was obtained through an optimum thresholding on the prediction map. The proposed method was evaluated on both the Multimodal Brain Tumor Image Segmentation (BRATS) Benchmark 2013 training datasets, and clinical data from our institute. A dice similarity coefficient (DSC) and sensitivity of 0.78 and 0.81 were achieved on 20 BRATS 2013 training datasets with high-grade gliomas (HGG), based on a two-fold cross-validation. The HNN model built on the BRATS 2013 training data was applied to ten clinical datasets with HGG from a locally developed database. DSC and sensitivity of

Registration of MRI to Intraoperative Radiographs for Target Localization in Spinal Interventions

PubMed Central

De Silva, T; Uneri, A; Ketcha, M D; Reaungamornrat, S; Goerres, J; Jacobson, M W; Vogt, S; Kleinszig, G; Khanna, A J; Wolinsky, J-P; Siewerdsen, J H

2017-01-01

Purpose Decision support to assist in target vertebra localization could provide a useful aid to safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT to intraoperative radiographs to reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred to as MR-LevelCheck) to perform 3D-2D registration based on a preoperative MRI to accommodate the increasingly common clinical scenario in which MRI is used instead of CT for preoperative planning. Methods Straightforward adaptation of gradient/intensity-based methods appropriate to CT-to-radiograph registration is confounded by large mismatch and noncorrespondence in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation step using vertebra centroids as seed points (automatically defined within existing workflow). Forwards projections are computed using segmented MRI and registered to radiographs via gradient orientation (GO) similarity and the CMA-ES (Covariance-Matrix-Adaptation Evolutionary-Strategy) optimizer. The method was tested in an IRB-approved study involving 10 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Results The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch and large capture range. Robust registration performance was achieved with projection distance error (PDE) (median ± iqr) = 4.3 ± 2.6 mm (median ± iqr) and 0% failure rate. Segmentation accuracy for the continuous max-flow method yielded Dice coefficient = 88.1 ± 5.2, Accuracy = 90.6 ± 5.7, RMSE = 1.8 ± 0.6 mm, and contour affinity ratio (CAR) = 0.82 ± 0.08. Registration performance was found to be robust for segmentation methods exhibiting RMSE < 3 mm and CAR > 0.50. Conclusion The MR-LevelCheck method provides a

Performance Comparison of 1.5 T Endorectal Coil MRI with Non-Endorectal Coil 3.0 T MRI in Patients with Prostate Cancer

PubMed Central

Shah, Zarine K.; Elias, Saba N.; Abaza, Ronney; Zynger, Debra L.; DeRenne, Lawrence A.; Knopp, Michael V.; Guo, Beibei; Schurr, Ryan; Heymsfield, Steven B.; Jia, Guang

2015-01-01

Rationale and Objectives To compare prostate morphology, image quality, and diagnostic performance of 1.5 T endorectal coil MRI and 3.0 T non-endorectal coil MRI in patients with prostate cancer. Materials and Methods MR images obtained of 83 patients with prostate cancer using 1.5 T MRI systems with an endorectal coil were compared to images collected from 83 patients with a 3.0 T MRI system. Prostate diameters were measured and image quality was evaluated by one ABR-certified radiologist (Reader 1) and one ABR-certified diagnostic medical physicist (Reader 2). The likelihood of the peripheral zone cancer presence in each sextant and local extent were rated and compared with histopathologic findings. Results Prostate anterior-posterior diameter measured by both readers was significantly shorter with 1.5 T endorectal MRI than with 3.0 T MRI. The overall image quality score difference was significant only for Reader 1. Both readers found that the two MRI systems provided similar diagnostic accuracy in cancer localization, extraprostatic extension, and seminal vesicle involvement. Conclusion Non-endorectal coil 3.0 T MRI provides prostate images that are natural in shape and that have comparable image quality to those obtained at 1.5 T with an endorectal coil, but not superior diagnostic performance. These findings suggest an opportunity exists for improving technical aspects of 3.0 T prostate MRI. PMID:25579637

Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries using Structural Coupling and Compressive Sensing

PubMed Central

Xi, Yan; Zhao, Jun; Bennett, James R.; Stacy, Mitchel R.; Sinusas, Albert J.; Wang, Ge

2016-01-01

Objective A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. Significance Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. Methods In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and hence would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. Results Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset based experiments, and has yielded promising results. PMID:26672028

Diffusion MRI and its role in neuropsychology

PubMed Central

Mueller, Bryon A; Lim, Kelvin O; Hemmy, Laura; Camchong, Jazmin

2015-01-01

Diffusion Magnetic Resonance Imaging (dMRI) is a popular method used by neuroscientists to uncover unique information about the structural connections within the brain. dMRI is a non-invasive imaging methodology in which image contrast is based on the diffusion of water molecules in tissue. While applicable to many tissues in the body, this review focuses exclusively on the use of dMRI to examine white matter in the brain. In this review, we begin with a definition of diffusion and how diffusion is measured with MRI. Next we introduce the diffusion tensor model, the predominant model used in dMRI. We then describe acquisition issues related to acquisition parameters and scanner hardware and software. Sources of artifacts are then discussed, followed by a brief review of analysis approaches. We provide an overview of the limitations of the traditional diffusion tensor model, and highlight several more sophisticated non-tensor models that better describe the complex architecture of the brain’s white matter. We then touch on reliability and validity issues of diffusion measurements. Finally, we describe examples of ways in which dMRI has been applied to studies of brain disorders and how identified alterations relate to symptomatology and cognition. PMID:26255305

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning.

PubMed

Gou, Shuiping; Wang, Yueyue; Wu, Jiaolong; Lee, Percy; Sheng, Ke

2015-04-01

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing. To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth. In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth. Image blurring in dMRI images can be effectively reduced using a

A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjects.

PubMed

Cacha, L A; Parida, S; Dehuri, S; Cho, S-B; Poznanski, R R

2016-12-01

The huge number of voxels in fMRI over time poses a major challenge to for effective analysis. Fast, accurate, and reliable classifiers are required for estimating the decoding accuracy of brain activities. Although machine-learning classifiers seem promising, individual classifiers have their own limitations. To address this limitation, the present paper proposes a method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification for application across multiple subjects. Similarly, the fuzzy integral (FI) approach has been employed as an efficient tool for combining different classifiers. The FI approach led to the development of a classifiers ensemble technique that performs better than any of the single classifier by reducing the misclassification, the bias, and the variance. The proposed method successfully classified the different cognitive states for multiple subjects with high accuracy of classification. Comparison of the performance improvement, while applying ensemble neural networks method, vs. that of the individual neural network strongly points toward the usefulness of the proposed method.

Dipy, a library for the analysis of diffusion MRI data.

PubMed

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing.

MRI-guided brain PET image filtering and partial volume correction

NASA Astrophysics Data System (ADS)

Yan, Jianhua; Chu-Shern Lim, Jason; Townsend, David W.

2015-02-01

Positron emission tomography (PET) image quantification is a challenging problem due to limited spatial resolution of acquired data and the resulting partial volume effects (PVE), which depend on the size of the structure studied in relation to the spatial resolution and which may lead to over or underestimation of the true tissue tracer concentration. In addition, it is usually necessary to perform image smoothing either during image reconstruction or afterwards to achieve a reasonable signal-to-noise ratio. Typically, an isotropic Gaussian filtering (GF) is used for this purpose. However, the noise suppression is at the cost of deteriorating spatial resolution. As hybrid imaging devices such as PET/MRI have become available, the complementary information derived from high definition morphologic images could be used to improve the quality of PET images. In this study, first of all, we propose an MRI-guided PET filtering method by adapting a recently proposed local linear model and then incorporate PVE into the model to get a new partial volume correction (PVC) method without parcellation of MRI. In addition, both the new filtering and PVC are voxel-wise non-iterative methods. The performance of the proposed methods were investigated with simulated dynamic FDG brain dataset and 18F-FDG brain data of a cervical cancer patient acquired with a simultaneous hybrid PET/MR scanner. The initial simulation results demonstrated that MRI-guided PET image filtering can produce less noisy images than traditional GF and bias and coefficient of variation can be further reduced by MRI-guided PET PVC. Moreover, structures can be much better delineated in MRI-guided PET PVC for real brain data.

Dipy, a library for the analysis of diffusion MRI data

PubMed Central

Garyfallidis, Eleftherios; Brett, Matthew; Amirbekian, Bagrat; Rokem, Ariel; van der Walt, Stefan; Descoteaux, Maxime; Nimmo-Smith, Ian

2014-01-01

Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the local configuration of white matter nerve fiber bundles and infer the trajectory of bundles connecting different parts of the brain. Dipy gathers implementations of many different methods in dMRI, including: diffusion signal pre-processing; reconstruction of diffusion distributions in individual voxels; fiber tractography and fiber track post-processing, analysis and visualization. Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface. We have implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography. In addition, cutting edge novel reconstruction techniques are implemented, such as constrained spherical deconvolution and diffusion spectrum imaging (DSI) with deconvolution, as well as methods for probabilistic tracking and original methods for tractography clustering. Many additional utility functions are provided to calculate various statistics, informative visualizations, as well as file-handling routines to assist in the development and use of novel techniques. In contrast to many other scientific software projects, Dipy is not being developed by a single research group. Rather, it is an open project that encourages contributions from any scientist/developer through GitHub and open discussions on the project mailing list. Consequently, Dipy today has an international team of contributors, spanning seven different academic institutions in five countries and three continents, which is still growing. PMID:24600385

Application of artificial neural network to fMRI regression analysis.

PubMed

Misaki, Masaya; Miyauchi, Satoru

2006-01-15

We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.

NMR, MRI, and spectroscopic MRI in inhomogeneous fields

DOEpatents

Demas, Vasiliki; Pines, Alexander; Martin, Rachel W; Franck, John; Reimer, Jeffrey A

2013-12-24

A method for locally creating effectively homogeneous or "clean" magnetic field gradients (of high uniformity) for imaging (with NMR, MRI, or spectroscopic MRI) both in in-situ and ex-situ systems with high degrees of inhomogeneous field strength. THe method of imaging comprises: a) providing a functional approximation of an inhomogeneous static magnetic field strength B.sub.0({right arrow over (r)}) at a spatial position {right arrow over (r)}; b) providing a temporal functional approximation of {right arrow over (G)}.sub.shim(t) with i basis functions and j variables for each basis function, resulting in v.sub.ij variables; c) providing a measured value .OMEGA., which is an temporally accumulated dephasing due to the inhomogeneities of B.sub.0({right arrow over(r)}); and d) minimizing a difference in the local dephasing angle .phi.({right arrow over (r)},t)=.gamma..intg..sub.0.sup.t{square root over (|{right arrow over (B)}.sub.1({right arrow over (r)},t')|.sup.2+({right arrow over (r)}{right arrow over (G)}.sub.shimG.sub.shim(t')+.parallel.{right arrow over (B)}.sub.0({right arrow over (r)}).parallel..DELTA..omega.({right arrow over (r)},t'/.gamma/).sup.2)}dt'-.OMEGA. by varying the v.sub.ij variables to form a set of minimized v.sub.ij variables. The method requires calibration of the static fields prior to minimization, but may thereafter be implemented without such calibration, may be used in open or closed systems, and potentially portable systems.

Topologically preserving straightening of spinal cord MRI.

PubMed

De Leener, Benjamin; Mangeat, Gabriel; Dupont, Sara; Martin, Allan R; Callot, Virginie; Stikov, Nikola; Fehlings, Michael G; Cohen-Adad, Julien

2017-10-01

To propose a robust and accurate method for straightening magnetic resonance (MR) images of the spinal cord, based on spinal cord segmentation, that preserves spinal cord topology and that works for any MRI contrast, in a context of spinal cord template-based analysis. The spinal cord curvature was computed using an iterative Non-Uniform Rational B-Spline (NURBS) approximation. Forward and inverse deformation fields for straightening were computed by solving analytically the straightening equations for each image voxel. Computational speed-up was accomplished by solving all voxel equation systems as one single system. Straightening accuracy (mean and maximum distance from straight line), computational time, and robustness to spinal cord length was evaluated using the proposed and the standard straightening method (label-based spline deformation) on 3T T 2 - and T 1 -weighted images from 57 healthy subjects and 33 patients with spinal cord compression due to degenerative cervical myelopathy (DCM). The proposed algorithm was more accurate, more robust, and faster than the standard method (mean distance = 0.80 vs. 0.83 mm, maximum distance = 1.49 vs. 1.78 mm, time = 71 vs. 174 sec for the healthy population and mean distance = 0.65 vs. 0.68 mm, maximum distance = 1.28 vs. 1.55 mm, time = 32 vs. 60 sec for the DCM population). A novel image straightening method that enables template-based analysis of quantitative spinal cord MRI data is introduced. This algorithm works for any MRI contrast and was validated on healthy and patient populations. The presented method is implemented in the Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1209-1219. © 2017 International Society for Magnetic Resonance in Medicine.

DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction.

PubMed

Yang, Guang; Yu, Simiao; Dong, Hao; Slabaugh, Greg; Dragotti, Pier Luigi; Ye, Xujiong; Liu, Fangde; Arridge, Simon; Keegan, Jennifer; Guo, Yike; Firmin, David; Keegan, Jennifer; Slabaugh, Greg; Arridge, Simon; Ye, Xujiong; Guo, Yike; Yu, Simiao; Liu, Fangde; Firmin, David; Dragotti, Pier Luigi; Yang, Guang; Dong, Hao

2018-06-01

Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging-based fast MRI, which utilizes multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning-based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training data sets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN)-based model is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilize our U-Net based generator, which provides an end-to-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency-domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CS-MRI reconstruction methods and newly investigated deep learning approaches. Compared with these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing.

Artifacts Quantification of Metal Implants in MRI

NASA Astrophysics Data System (ADS)

Vrachnis, I. N.; Vlachopoulos, G. F.; Maris, T. G.; Costaridou, L. I.

2017-11-01

The presence of materials with different magnetic properties, such as metal implants, causes distortion of the magnetic field locally, resulting in signal voids and pile ups, i.e. susceptibility artifacts in MRI. Quantitative and unbiased measurement of the artifact is prerequisite for optimization of acquisition parameters. In this study an image gradient based segmentation method is proposed for susceptibility artifact quantification. The method captures abrupt signal alterations by calculation of the image gradient. Then the artifact is quantified in terms of its extent by an automated cross entropy thresholding method as image area percentage. The proposed method for artifact quantification was tested in phantoms containing two orthopedic implants with significantly different magnetic permeabilities. The method was compared against a method proposed in the literature, considered as a reference, demonstrating moderate to good correlation (Spearman’s rho = 0.62 and 0.802 in case of titanium and stainless steel implants). The automated character of the proposed quantification method seems promising towards MRI acquisition parameter optimization.

Manganese-Enhanced MRI: Biological Applications in Neuroscience

PubMed Central

Malheiros, Jackeline Moraes; Paiva, Fernando Fernandes; Longo, Beatriz Monteiro; Hamani, Clement; Covolan, Luciene

2015-01-01

Magnetic resonance imaging (MRI) is an excellent non-invasive tool to investigate biological systems. The administration of the paramagnetic divalent ion manganese (Mn2+) enhances MRI contrast in vivo. Due to similarities between Mn2+ and calcium (Ca2+), the premise of manganese-enhanced MRI (MEMRI) is that the former may enter neurons and other excitable cells through voltage-gated Ca2+ channels. As such, MEMRI has been used to trace neuronal pathways, define morphological boundaries, and study connectivity in morphological and functional imaging studies. In this article, we provide a brief overview of MEMRI and discuss recently published data to illustrate the usefulness of this method, particularly in animal models. PMID:26217304

Application of advanced machine learning methods on resting-state fMRI network for identification of mild cognitive impairment and Alzheimer's disease.

PubMed

Khazaee, Ali; Ebrahimzadeh, Ata; Babajani-Feremi, Abbas

2016-09-01

The study of brain networks by resting-state functional magnetic resonance imaging (rs-fMRI) is a promising method for identifying patients with dementia from healthy controls (HC). Using graph theory, different aspects of the brain network can be efficiently characterized by calculating measures of integration and segregation. In this study, we combined a graph theoretical approach with advanced machine learning methods to study the brain network in 89 patients with mild cognitive impairment (MCI), 34 patients with Alzheimer's disease (AD), and 45 age-matched HC. The rs-fMRI connectivity matrix was constructed using a brain parcellation based on a 264 putative functional areas. Using the optimal features extracted from the graph measures, we were able to accurately classify three groups (i.e., HC, MCI, and AD) with accuracy of 88.4 %. We also investigated performance of our proposed method for a binary classification of a group (e.g., MCI) from two other groups (e.g., HC and AD). The classification accuracies for identifying HC from AD and MCI, AD from HC and MCI, and MCI from HC and AD, were 87.3, 97.5, and 72.0 %, respectively. In addition, results based on the parcellation of 264 regions were compared to that of the automated anatomical labeling atlas (AAL), consisted of 90 regions. The accuracy of classification of three groups using AAL was degraded to 83.2 %. Our results show that combining the graph measures with the machine learning approach, on the basis of the rs-fMRI connectivity analysis, may assist in diagnosis of AD and MCI.

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

PubMed

Soltaninejad, Mohammadreza; Yang, Guang; Lambrou, Tryphon; Allinson, Nigel; Jones, Timothy L; Barrick, Thomas R; Howe, Franklyn A; Ye, Xujiong

2018-04-01

Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management. Copyright © 2018 Elsevier B.V. All rights reserved.

QUESPOWR MRI: QUantification of Exchange as a function of Saturation Power On the Water Resonance

PubMed Central

Randtke, Edward A.; Pagel, Mark D.; Cárdenas-Rodríguez, Julio

2018-01-01

QUantification of Exchange as a function of Saturation Power On the Water Resonance (QUESPOWR) MRI is a new method that can estimate chemical exchange rates. This method acquires a series of OPARACHEE MRI acquisitions with a range of RF powers for the WALTZ16* pulse train, which are applied on the water resonance. A QUESPOWR plot can be generated from the power dependence of the % water signal, which is similar to a QUESP plot that is generated from CEST MRI acquisition methods with RF saturation applied off-resonance from water. A QUESPOWR plot can be quantitatively analyzed using linear fitting methods to provide estimates of average chemical exchange rates. Analyses of the shapes of QUESPOWR plots can also be used to estimate relative differences in average chemical exchange rates and concentrations of biomolecules. The performance of QUESPOWR MRI was assessed via simulations, an in vitro study with iopamidol, and an in vivo study with a mouse model of mammary carcinoma. The results showed that QUESPOWR MRI is especially sensitive to chemical exchange between water and biomolecules that have intermediate to fast chemical exchange rates and chemical shifts that are close to water, which are notoriously difficult to assess with other CEST MRI methods. In addition, in vivo QUESPOWR MRI detected acidic tumor tissues relative to normal tissues that are pH-neutral, and therefore may be a new paradigm for tumor detection with MRI. PMID:27404128

Custom fit 3D-printed brain holders for comparison of histology with MRI in marmosets.

PubMed

Guy, Joseph R; Sati, Pascal; Leibovitch, Emily; Jacobson, Steven; Silva, Afonso C; Reich, Daniel S

2016-01-15

MRI has the advantage of sampling large areas of tissue and locating areas of interest in 3D space in both living and ex vivo systems, whereas histology has the ability to examine thin slices of ex vivo tissue with high detail and specificity. Although both are valuable tools, it is currently difficult to make high-precision comparisons between MRI and histology due to large differences inherent to the techniques. A method combining the advantages would be an asset to understanding the pathological correlates of MRI. 3D-printed brain holders were used to maintain marmoset brains in the same orientation during acquisition of ex vivo MRI and pathologic cutting of the tissue. The results of maintaining this same orientation show that sub-millimeter, discrete neuropathological features in marmoset brain consistently share size, shape, and location between histology and ex vivo MRI, which facilitates comparison with serial imaging acquired in vivo. Existing methods use computational approaches sensitive to data input in order to warp histologic images to match large-scale features on MRI, but the new method requires no warping of images, due to a preregistration accomplished in the technique, and is insensitive to data formatting and artifacts in both MRI and histology. The simple method of using 3D-printed brain holders to match brain orientation during pathologic sectioning and MRI acquisition enables rapid and precise comparison of small features seen on MRI to their underlying histology. Published by Elsevier B.V.

Mean apparent propagator (MAP) MRI: a novel diffusion imaging method for mapping tissue microstructure.

PubMed

Özarslan, Evren; Koay, Cheng Guan; Shepherd, Timothy M; Komlosh, Michal E; İrfanoğlu, M Okan; Pierpaoli, Carlo; Basser, Peter J

2013-09-01

Diffusion-weighted magnetic resonance (MR) signals reflect information about underlying tissue microstructure and cytoarchitecture. We propose a quantitative, efficient, and robust mathematical and physical framework for representing diffusion-weighted MR imaging (MRI) data obtained in "q-space," and the corresponding "mean apparent propagator (MAP)" describing molecular displacements in "r-space." We also define and map novel quantitative descriptors of diffusion that can be computed robustly using this MAP-MRI framework. We describe efficient analytical representation of the three-dimensional q-space MR signal in a series expansion of basis functions that accurately describes diffusion in many complex geometries. The lowest order term in this expansion contains a diffusion tensor that characterizes the Gaussian displacement distribution, equivalent to diffusion tensor MRI (DTI). Inclusion of higher order terms enables the reconstruction of the true average propagator whose projection onto the unit "displacement" sphere provides an orientational distribution function (ODF) that contains only the orientational dependence of the diffusion process. The representation characterizes novel features of diffusion anisotropy and the non-Gaussian character of the three-dimensional diffusion process. Other important measures this representation provides include the return-to-the-origin probability (RTOP), and its variants for diffusion in one- and two-dimensions-the return-to-the-plane probability (RTPP), and the return-to-the-axis probability (RTAP), respectively. These zero net displacement probabilities measure the mean compartment (pore) volume and cross-sectional area in distributions of isolated pores irrespective of the pore shape. MAP-MRI represents a new comprehensive framework to model the three-dimensional q-space signal and transform it into diffusion propagators. Experiments on an excised marmoset brain specimen demonstrate that MAP-MRI provides several novel

Characterizing the functional MRI response using Tikhonov regularization.

PubMed

Vakorin, Vasily A; Borowsky, Ron; Sarty, Gordon E

2007-09-20

The problem of evaluating an averaged functional magnetic resonance imaging (fMRI) response for repeated block design experiments was considered within a semiparametric regression model with autocorrelated residuals. We applied functional data analysis (FDA) techniques that use a least-squares fitting of B-spline expansions with Tikhonov regularization. To deal with the noise autocorrelation, we proposed a regularization parameter selection method based on the idea of combining temporal smoothing with residual whitening. A criterion based on a generalized chi(2)-test of the residuals for white noise was compared with a generalized cross-validation scheme. We evaluated and compared the performance of the two criteria, based on their effect on the quality of the fMRI response. We found that the regularization parameter can be tuned to improve the noise autocorrelation structure, but the whitening criterion provides too much smoothing when compared with the cross-validation criterion. The ultimate goal of the proposed smoothing techniques is to facilitate the extraction of temporal features in the hemodynamic response for further analysis. In particular, these FDA methods allow us to compute derivatives and integrals of the fMRI signal so that fMRI data may be correlated with behavioral and physiological models. For example, positive and negative hemodynamic responses may be easily and robustly identified on the basis of the first derivative at an early time point in the response. Ultimately, these methods allow us to verify previously reported correlations between the hemodynamic response and the behavioral measures of accuracy and reaction time, showing the potential to recover new information from fMRI data. 2007 John Wiley & Sons, Ltd

Data collection and analysis strategies for phMRI.

PubMed

Mandeville, Joseph B; Liu, Christina H; Vanduffel, Wim; Marota, John J A; Jenkins, Bruce G

2014-09-01

Although functional MRI traditionally has been applied mainly to study changes in task-induced brain function, evolving acquisition methodologies and improved knowledge of signal mechanisms have increased the utility of this method for studying responses to pharmacological stimuli, a technique often dubbed "phMRI". The proliferation of higher magnetic field strengths and the use of exogenous contrast agent have boosted detection power, a critical factor for successful phMRI due to the restricted ability to average multiple stimuli within subjects. Receptor-based models of neurovascular coupling, including explicit pharmacological models incorporating receptor densities and affinities and data-driven models that incorporate weak biophysical constraints, have demonstrated compelling descriptions of phMRI signal induced by dopaminergic stimuli. This report describes phMRI acquisition and analysis methodologies, with an emphasis on data-driven analyses. As an example application, statistically efficient data-driven regressors were used to describe the biphasic response to the mu-opioid agonist remifentanil, and antagonism using dopaminergic and GABAergic ligands revealed modulation of the mesolimbic pathway. Results illustrate the power of phMRI as well as our incomplete understanding of mechanisms underlying the signal. Future directions are discussed for phMRI acquisitions in human studies, for evolving analysis methodologies, and for interpretative studies using the new generation of simultaneous PET/MRI scanners. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Copyright © 2014 Elsevier Ltd. All rights reserved.

Respiratory motion-resolved, self-gated 4D-MRI using Rotating Cartesian K-space (ROCK): Initial clinical experience on an MRI-guided radiotherapy system.

PubMed

Han, Fei; Zhou, Ziwu; Du, Dongsu; Gao, Yu; Rashid, Shams; Cao, Minsong; Shaverdian, Narek; Hegde, John V; Steinberg, Michael; Lee, Percy; Raldow, Ann; Low, Daniel A; Sheng, Ke; Yang, Yingli; Hu, Peng

2018-06-01

To optimize and evaluate the respiratory motion-resolved, self-gated 4D-MRI using Rotating Cartesian K-space (ROCK-4D-MRI) method in a 0.35 T MRI-guided radiotherapy (MRgRT) system. The study included seven patients with abdominal tumors treated on the MRgRT system. ROCK-4D-MRI and 2D-CINE, was performed immediately after one of the treatment fractions. Motion quantification based on 4D-MRI was compared with those based on 2D-CINE. The image quality of 4D-MRI was evaluated against 4D-CT. The gross tumor volumes (GTV) were defined based on individual respiratory phases of both 4D-MRI and 4D-CT and compared for their variability over the respiratory cycle. The motion measurements based on 4D-MRI matched well with 2D-CINE, with differences of 1.04 ± 0.52 mm in the superior-inferior and 0.54 ± 0.21 mm in the anterior-posterior directions. The image quality scores of 4D-MRI were significantly higher than 4D-CT, with better tumor contrast (3.29 ± 0.76 vs. 1.86 ± 0.90) and less motion artifacts (3.57 ± 0.53 vs. 2.29 ± 0.95). The GTVs were more consistent in 4D-MRI than in 4D-CT, with significantly smaller GTV variability (9.31 ± 4.58% vs. 34.27 ± 23.33%). Our study demonstrated the clinical feasibility of using the ROCK-4D-MRI to acquire high quality, respiratory motion-resolved 4D-MRI in a low-field MRgRT system. The 4D-MRI image could provide accurate dynamic information for radiotherapy treatment planning. Copyright © 2018 Elsevier B.V. All rights reserved.

MRI in multiple sclerosis: current status and future prospects

PubMed Central

Bakshi, Rohit; Thompson, Alan J; Rocca, Maria A; Pelletier, Daniel; Dousset, Vincent; Barkhof, Frederik; Inglese, Matilde; Guttmann, Charles R G; Horsfield, Mark A; Filippi, Massimo

2008-01-01

Many promising MRI approaches for research or clinical management of multiple sclerosis (MS) have recently emerged, or are under development or refinement. Advanced MRI methods need to be assessed to determine whether they allow earlier diagnosis or better identification of phenotypes. Improved post-processing should allow more efficient and complete extraction of information from images. Magnetic resonance spectroscopy should improve in sensitivity and specificity with higher field strengths and should enable the detection of a wider array of metabolites. Diffusion imaging is moving closer to the goal of defining structural connectivity and, thereby, determining the functional significance of lesions at specific locations. Cell-specific imaging now seems feasible with new magnetic resonance contrast agents. The imaging of myelin water fraction brings the hope of providing a specific measure of myelin content. Ultra-high-field MRI increases sensitivity, but also presents new technical challenges. Here, we review these recent developments in MRI for MS, and also look forward to refinements in spinal-cord imaging, optic-nerve imaging, perfusion MRI, and functional MRI. Advances in MRI should improve our ability to diagnose, monitor, and understand the pathophysiology of MS. PMID:18565455

FIACH: A biophysical model for automatic retrospective noise control in fMRI.

PubMed

Tierney, Tim M; Weiss-Croft, Louise J; Centeno, Maria; Shamshiri, Elhum A; Perani, Suejen; Baldeweg, Torsten; Clark, Christopher A; Carmichael, David W

2016-01-01

Different noise sources in fMRI acquisition can lead to spurious false positives and reduced sensitivity. We have developed a biophysically-based model (named FIACH: Functional Image Artefact Correction Heuristic) which extends current retrospective noise control methods in fMRI. FIACH can be applied to both General Linear Model (GLM) and resting state functional connectivity MRI (rs-fcMRI) studies. FIACH is a two-step procedure involving the identification and correction of non-physiological large amplitude temporal signal changes and spatial regions of high temporal instability. We have demonstrated its efficacy in a sample of 42 healthy children while performing language tasks that include overt speech with known activations. We demonstrate large improvements in sensitivity when FIACH is compared with current methods of retrospective correction. FIACH reduces the confounding effects of noise and increases the study's power by explaining significant variance that is not contained within the commonly used motion parameters. The method is particularly useful in detecting activations in inferior temporal regions which have proven problematic for fMRI. We have shown greater reproducibility and robustness of fMRI responses using FIACH in the context of task induced motion. In a clinical setting this will translate to increasing the reliability and sensitivity of fMRI used for the identification of language lateralisation and eloquent cortex. FIACH can benefit studies of cognitive development in young children, patient populations and older adults. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Fuzzy cluster analysis of high-field functional MRI data.

PubMed

Windischberger, Christian; Barth, Markus; Lamm, Claus; Schroeder, Lee; Bauer, Herbert; Gur, Ruben C; Moser, Ewald

2003-11-01

Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast today is an established brain research method and quickly gains acceptance for complementary clinical diagnosis. However, neither the basic mechanisms like coupling between neuronal activation and haemodynamic response are known exactly, nor can the various artifacts be predicted or controlled. Thus, modeling functional signal changes is non-trivial and exploratory data analysis (EDA) may be rather useful. In particular, identification and separation of artifacts as well as quantification of expected, i.e. stimulus correlated, and novel information on brain activity is important for both, new insights in neuroscience and future developments in functional MRI of the human brain. After an introduction on fuzzy clustering and very high-field fMRI we present several examples where fuzzy cluster analysis (FCA) of fMRI time series helps to identify and locally separate various artifacts. We also present and discuss applications and limitations of fuzzy cluster analysis in very high-field functional MRI: differentiate temporal patterns in MRI using (a) a test object with static and dynamic parts, (b) artifacts due to gross head motion artifacts. Using a synthetic fMRI data set we quantitatively examine the influences of relevant FCA parameters on clustering results in terms of receiver-operator characteristics (ROC) and compare them with a commonly used model-based correlation analysis (CA) approach. The application of FCA in analyzing in vivo fMRI data is shown for (a) a motor paradigm, (b) data from multi-echo imaging, and (c) a fMRI study using mental rotation of three-dimensional cubes. We found that differentiation of true "neural" from false "vascular" activation is possible based on echo time dependence and specific activation levels, as well as based on their signal time-course. Exploratory data analysis methods in general and fuzzy cluster analysis in particular may

On NUFFT-based gridding for non-Cartesian MRI

NASA Astrophysics Data System (ADS)

Fessler, Jeffrey A.

2007-10-01

For MRI with non-Cartesian sampling, the conventional approach to reconstructing images is to use the gridding method with a Kaiser-Bessel (KB) interpolation kernel. Recently, Sha et al. [L. Sha, H. Guo, A.W. Song, An improved gridding method for spiral MRI using nonuniform fast Fourier transform, J. Magn. Reson. 162(2) (2003) 250-258] proposed an alternative method based on a nonuniform FFT (NUFFT) with least-squares (LS) design of the interpolation coefficients. They described this LS_NUFFT method as shift variant and reported that it yielded smaller reconstruction approximation errors than the conventional shift-invariant KB approach. This paper analyzes the LS_NUFFT approach in detail. We show that when one accounts for a certain linear phase factor, the core of the LS_NUFFT interpolator is in fact real and shift invariant. Furthermore, we find that the KB approach yields smaller errors than the original LS_NUFFT approach. We show that optimizing certain scaling factors can lead to a somewhat improved LS_NUFFT approach, but the high computation cost seems to outweigh the modest reduction in reconstruction error. We conclude that the standard KB approach, with appropriate parameters as described in the literature, remains the practical method of choice for gridding reconstruction in MRI.

TH-EF-BRA-06: A Novel Retrospective 3D K-Space Sorting 4D-MRI Technique Using a Radial K-Space Acquisition MRI Sequence

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

Liu, Y; Subashi, E; Yin, F

Purpose: Current retrospective 4D-MRI provides superior tumor-to-tissue contrast and accurate respiratory motion information for radiotherapy motion management. The developed 4D-MRI techniques based on 2D-MRI image sorting require a high frame-rate of the MR sequences. However, several MRI sequences provide excellent image quality but have low frame-rate. This study aims at developing a novel retrospective 3D k-space sorting 4D-MRI technique using radial k-space acquisition MRI sequences to improve 4D-MRI image quality and temporal-resolution for imaging irregular organ/tumor respiratory motion. Methods: The method is based on a RF-spoiled, steady-state, gradient-recalled sequence with minimal echo time. A 3D radial k-space data acquisition trajectorymore » was used for sampling the datasets. Each radial spoke readout data line starts from the 3D center of Field-of-View. Respiratory signal can be extracted from the k-space center data point of each spoke. The spoke data was sorted based on its self-synchronized respiratory signal using phase sorting. Subsequently, 3D reconstruction was conducted to generate the time-resolved 4D-MRI images. As a feasibility study, this technique was implemented on a digital human phantom XCAT. The respiratory motion was controlled by an irregular motion profile. To validate using k-space center data as a respiratory surrogate, we compared it with the XCAT input controlling breathing profile. Tumor motion trajectories measured on reconstructed 4D-MRI were compared to the average input trajectory. The mean absolute amplitude difference (D) was calculated. Results: The signal extracted from k-space center data matches well with the input controlling respiratory profile of XCAT. The relative amplitude error was 8.6% and the relative phase error was 3.5%. XCAT 4D-MRI demonstrated a clear motion pattern with little serrated artifacts. D of tumor trajectories was 0.21mm, 0.23mm and 0.23mm in SI, AP and ML directions, respectively

Fiber estimation and tractography in diffusion MRI: Development of simulated brain images and comparison of multi-fiber analysis methods at clinical b-values

PubMed Central

Wilkins, Bryce; Lee, Namgyun; Gajawelli, Niharika; Law, Meng; Leporé, Natasha

2015-01-01

Advances in diffusion-weighted magnetic resonance imaging (DW-MRI) have led to many alternative diffusion sampling strategies and analysis methodologies. A common objective among methods is estimation of white matter fiber orientations within each voxel, as doing so permits in-vivo fiber-tracking and the ability to study brain connectivity and networks. Knowledge of how DW-MRI sampling schemes affect fiber estimation accuracy, and consequently tractography and the ability to recover complex white-matter pathways, as well as differences between results due to choice of analysis method and which method(s) perform optimally for specific data sets, all remain important problems, especially as tractography-based studies become common. In this work we begin to address these concerns by developing sets of simulated diffusion-weighted brain images which we then use to quantitatively evaluate the performance of six DW-MRI analysis methods in terms of estimated fiber orientation accuracy, false-positive (spurious) and false-negative (missing) fiber rates, and fiber-tracking. The analysis methods studied are: 1) a two-compartment “ball and stick” model (BSM) (Behrens et al., 2003); 2) a non-negativity constrained spherical deconvolution (CSD) approach (Tournier et al., 2007); 3) analytical q-ball imaging (QBI) (Descoteaux et al., 2007); 4) q-ball imaging with Funk-Radon and Cosine Transform (FRACT) (Haldar and Leahy, 2013); 5) q-ball imaging within constant solid angle (CSA) (Aganj et al., 2010); and 6) a generalized Fourier transform approach known as generalized q-sampling imaging (GQI) (Yeh et al., 2010). We investigate these methods using 20, 30, 40, 60, 90 and 120 evenly distributed q-space samples of a single shell, and focus on a signal-to-noise ratio (SNR = 18) and diffusion-weighting (b = 1000 s/mm2) common to clinical studies. We found the BSM and CSD methods consistently yielded the least fiber orientation error and simultaneously greatest detection rate of

Fiber estimation and tractography in diffusion MRI: development of simulated brain images and comparison of multi-fiber analysis methods at clinical b-values.

PubMed

Wilkins, Bryce; Lee, Namgyun; Gajawelli, Niharika; Law, Meng; Leporé, Natasha

2015-04-01

Advances in diffusion-weighted magnetic resonance imaging (DW-MRI) have led to many alternative diffusion sampling strategies and analysis methodologies. A common objective among methods is estimation of white matter fiber orientations within each voxel, as doing so permits in-vivo fiber-tracking and the ability to study brain connectivity and networks. Knowledge of how DW-MRI sampling schemes affect fiber estimation accuracy, tractography and the ability to recover complex white-matter pathways, differences between results due to choice of analysis method, and which method(s) perform optimally for specific data sets, all remain important problems, especially as tractography-based studies become common. In this work, we begin to address these concerns by developing sets of simulated diffusion-weighted brain images which we then use to quantitatively evaluate the performance of six DW-MRI analysis methods in terms of estimated fiber orientation accuracy, false-positive (spurious) and false-negative (missing) fiber rates, and fiber-tracking. The analysis methods studied are: 1) a two-compartment "ball and stick" model (BSM) (Behrens et al., 2003); 2) a non-negativity constrained spherical deconvolution (CSD) approach (Tournier et al., 2007); 3) analytical q-ball imaging (QBI) (Descoteaux et al., 2007); 4) q-ball imaging with Funk-Radon and Cosine Transform (FRACT) (Haldar and Leahy, 2013); 5) q-ball imaging within constant solid angle (CSA) (Aganj et al., 2010); and 6) a generalized Fourier transform approach known as generalized q-sampling imaging (GQI) (Yeh et al., 2010). We investigate these methods using 20, 30, 40, 60, 90 and 120 evenly distributed q-space samples of a single shell, and focus on a signal-to-noise ratio (SNR = 18) and diffusion-weighting (b = 1000 s/mm(2)) common to clinical studies. We found that the BSM and CSD methods consistently yielded the least fiber orientation error and simultaneously greatest detection rate of fibers. Fiber detection

Pharmacological MRI in animal models: a useful tool for 5-HT research?

PubMed

Martin, Chris; Sibson, Nicola R

2008-11-01

Pharmacological magnetic resonance imaging (phMRI) offers the potential to provide novel insights into the functioning of neurotransmitter systems and drug action in the central nervous system. To date, much of the neuropharmacological research that has applied phMRI techniques has focused on the dopaminergic system with relatively few studies into serotonergic function. In this article, we discuss the current capabilities of, and future potential for phMRI to address fundamental questions in serotonergic research using animal models. Firstly we review existing literature on the application of phMRI to the serotonergic system by exploring 3 broad research themes: (i) the functional anatomy of the serotonergic system; (ii) drug-receptor targeting and distribution; and (iii) disease models and drug development. Subsequently, we discuss the interpretation of phMRI data in terms of neuropharmacological action with a focus on issues specific to neuroimaging studies of the serotonergic system. Unlike other neuroimaging approaches such as positron emission tomography, phMRI methods do not currently offer sensitivity to markers of specific pharmacological action. However, they can provide in vivo markers of the neuropharmacological modulation of neuronal activity across the whole brain with unparalleled spatial and temporal resolution. Furthermore, due to the non-invasive nature of MRI, these markers are readily translatable to human studies. Whilst there are a number of constraints and limitations to phMRI methods that necessitate careful data interpretation, we argue that phMRI could become a valuable research tool in neuropharmacological studies of the serotonergic system.

MRI Scans

MedlinePlus

Magnetic resonance imaging (MRI) uses a large magnet and radio waves to look at organs and structures inside your body. Health care professionals use MRI scans to diagnose a variety of conditions, from torn ...

Multiple velocity encoding in the phase of an MRI signal

NASA Astrophysics Data System (ADS)

Benitez-Read, E. E.

2017-01-01

The measurement of fluid velocity by encoding it in the phase of a magnetic resonance imaging (MRI) signal could allow the discrimination of the stationary spins signals from those of moving spins. This results in a wide variety of applications i.e. in medicine, in order to obtain more than angiograms, blood velocity images of veins, arteries and other vessels without having static tissue perturbing the signal of fluid in motion. The work presented in this paper is a theoretical analysis of some novel methods for multiple fluid velocity encoding in the phase of an MRI signal. These methods are based on a tripolar gradient (TPG) and can be an alternative to the conventional methods based on a bipolar gradient (BPG) and could be more suitable for multiple velocity encoding in the phase of an MRI signal.

TH-A-BRF-11: Image Intensity Non-Uniformities Between MRI Simulation and Diagnostic MRI

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

Paulson, E

2014-06-15

Purpose: MRI simulation for MRI-based radiotherapy demands that patients be setup in treatment position, which frequently involves use of alternative radiofrequency (RF) coil configurations to accommodate immobilized patients. However, alternative RF coil geometries may exacerbate image intensity non-uniformities (IINU) beyond those observed in diagnostic MRI, which may challenge image segmentation and registration accuracy as well as confound studies assessing radiotherapy response when MR simulation images are used as baselines for evaluation. The goal of this work was to determine whether differences in IINU exist between MR simulation and diagnostic MR images. Methods: ACR-MRI phantom images were acquired at 3T usingmore » a spin-echo sequence (TE/TR:20/500ms, rBW:62.5kHz, TH/skip:5/5mm). MR simulation images were obtained by wrapping two flexible phased-array RF coils around the phantom. Diagnostic MR images were obtained by placing the phantom into a commercial phased-array head coil. Pre-scan normalization was enabled in both cases. Images were transferred offline and corrected for IINU using the MNI N3 algorithm. Coefficients of variation (CV=σ/μ) were calculated for each slice. Wilcoxon matched-pairs and Mann-Whitney tests compared CV values between original and N3 images and between MR simulation and diagnostic MR images. Results: Significant differences in CV were detected between original and N3 images in both MRI simulation and diagnostic MRI groups (p=0.010, p=0.010). In addition, significant differences in CV were detected between original MR simulation and original and N3 diagnostic MR images (p=0.0256, p=0.0016). However, no significant differences in CV were detected between N3 MR simulation images and original or N3 diagnostic MR images, demonstrating the importance of correcting MR simulation images beyond pre-scan normalization prior to use in radiotherapy. Conclusions: Alternative RF coil configurations used in MRI simulation can Result in

Monitoring local heating around an interventional MRI antenna with RF radiometry

PubMed Central

Ertürk, M. Arcan; El-Sharkawy, AbdEl-Monem M.; Bottomley, Paul A.

2015-01-01

Purpose: Radiofrequency (RF) radiometry uses thermal noise detected by an antenna to measure the temperature of objects independent of medical imaging technologies such as magnetic resonance imaging (MRI). Here, an active interventional MRI antenna can be deployed as a RF radiometer to measure local heating, as a possible new method of monitoring device safety and thermal therapy. Methods: A 128 MHz radiometer receiver was fabricated to measure the RF noise voltage from an interventional 3 T MRI loopless antenna and calibrated for temperature in a uniformly heated bioanalogous gel phantom. Local heating (ΔT) was induced using the antenna for RF transmission and measured by RF radiometry, fiber-optic thermal sensors, and MRI thermometry. The spatial thermal sensitivity of the antenna radiometer was numerically computed using a method-of-moment electric field analyses. The gel’s thermal conductivity was measured by MRI thermometry, and the localized time-dependent ΔT distribution computed from the bioheat transfer equation and compared with radiometry measurements. A “H-factor” relating the 1 g-averaged ΔT to the radiometric temperature was introduced to estimate peak temperature rise in the antenna’s sensitive region. Results: The loopless antenna radiometer linearly tracked temperature inside a thermally equilibrated phantom up to 73 °C to within ±0.3 °C at a 2 Hz sample rate. Computed and MRI thermometric measures of peak ΔT agreed within 13%. The peak 1 g-average temperature was H = 1.36 ± 0.02 times higher than the radiometric temperature for any media with a thermal conductivity of 0.15–0.50 (W/m)/K, indicating that the radiometer can measure peak 1 g-averaged ΔT in physiologically relevant tissue within ±0.4 °C. Conclusions: Active internal MRI detectors can serve as RF radiometers at the MRI frequency to provide accurate independent measures of local and peak temperature without the artifacts that can accompany MRI thermometry or

Monitoring local heating around an interventional MRI antenna with RF radiometry

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

Ertürk, M. Arcan; El-Sharkawy, AbdEl-Monem M.; Bottomley, Paul A., E-mail: bottoml@mri.jhu.edu

Purpose: Radiofrequency (RF) radiometry uses thermal noise detected by an antenna to measure the temperature of objects independent of medical imaging technologies such as magnetic resonance imaging (MRI). Here, an active interventional MRI antenna can be deployed as a RF radiometer to measure local heating, as a possible new method of monitoring device safety and thermal therapy. Methods: A 128 MHz radiometer receiver was fabricated to measure the RF noise voltage from an interventional 3 T MRI loopless antenna and calibrated for temperature in a uniformly heated bioanalogous gel phantom. Local heating (ΔT) was induced using the antenna for RFmore » transmission and measured by RF radiometry, fiber-optic thermal sensors, and MRI thermometry. The spatial thermal sensitivity of the antenna radiometer was numerically computed using a method-of-moment electric field analyses. The gel’s thermal conductivity was measured by MRI thermometry, and the localized time-dependent ΔT distribution computed from the bioheat transfer equation and compared with radiometry measurements. A “H-factor” relating the 1 g-averaged ΔT to the radiometric temperature was introduced to estimate peak temperature rise in the antenna’s sensitive region. Results: The loopless antenna radiometer linearly tracked temperature inside a thermally equilibrated phantom up to 73 °C to within ±0.3 °C at a 2 Hz sample rate. Computed and MRI thermometric measures of peak ΔT agreed within 13%. The peak 1 g-average temperature was H = 1.36 ± 0.02 times higher than the radiometric temperature for any media with a thermal conductivity of 0.15–0.50 (W/m)/K, indicating that the radiometer can measure peak 1 g-averaged ΔT in physiologically relevant tissue within ±0.4 °C. Conclusions: Active internal MRI detectors can serve as RF radiometers at the MRI frequency to provide accurate independent measures of local and peak temperature without the artifacts that can accompany MRI

A method for multitask fMRI data fusion applied to schizophrenia.

PubMed

Calhoun, Vince D; Adali, Tulay; Kiehl, Kent A; Astur, Robert; Pekar, James J; Pearlson, Godfrey D

2006-07-01

It is becoming common to collect data from multiple functional magnetic resonance imaging (fMRI) paradigms on a single individual. The data from these experiments are typically analyzed separately and sometimes directly subtracted from one another on a voxel-by-voxel basis. These comparative approaches, although useful, do not directly attempt to examine potential commonalities between tasks and between voxels. To remedy this we propose a method to extract maximally spatially independent maps for each task that are "coupled" together by a shared loading parameter. We first compute an activation map for each task and each individual as "features," which are then used to perform joint independent component analysis (jICA) on the group data. We demonstrate our approach on a data set derived from healthy controls and schizophrenia patients, each of which carried out an auditory oddball task and a Sternberg working memory task. Our analysis approach revealed two interesting findings in the data that were missed with traditional analyses. First, consistent with our hypotheses, schizophrenia patients demonstrate "decreased" connectivity in a joint network including portions of regions implicated in two prevalent models of schizophrenia. A second finding is that for the voxels identified by the jICA analysis, the correlation between the two tasks was significantly higher in patients than in controls. This finding suggests that schizophrenia patients activate "more similarly" for both tasks than do controls. A possible synthesis of both findings is that patients are activating less, but also activating with a less-unique set of regions for these very different tasks. Both of the findings described support the claim that examination of joint activation across multiple tasks can enable new questions to be posed about fMRI data. Our approach can also be applied to data using more than two tasks. It thus provides a way to integrate and probe brain networks using a variety of

A Method for Multitask fMRI Data Fusion Applied to Schizophrenia

PubMed Central

Calhoun, Vince D.; Adali, Tulay; Kiehl, Kent A.; Astur, Robert; Pekar, James J.; Pearlson, Godfrey D.

2009-01-01

It is becoming common to collect data from multiple functional magnetic resonance imaging (fMRI) paradigms on a single individual. The data from these experiments are typically analyzed separately and sometimes directly subtracted from one another on a voxel-by-voxel basis. These comparative approaches, although useful, do not directly attempt to examine potential commonalities between tasks and between voxels. To remedy this we propose a method to extract maximally spatially independent maps for each task that are “coupled” together by a shared loading parameter. We first compute an activation map for each task and each individual as “features, ” which are then used to perform joint independent component analysis (jICA) on the group data. We demonstrate our approach on a data set derived from healthy controls and schizophrenia patients, each of which carried out an auditory oddball task and a Sternberg working memory task. Our analysis approach revealed two interesting findings in the data that were missed with traditional analyses. First, consistent with our hypotheses, schizophrenia patients demonstrate “decreased” connectivity in a joint network including portions of regions implicated in two prevalent models of schizophrenia. A second finding is that for the voxels identified by the jICA analysis, the correlation between the two tasks was significantly higher in patients than in controls. This finding suggests that schizophrenia patients activate “more similarly” for both tasks than do controls. A possible synthesis of both findings is that patients are activating less, but also activating with a less-unique set of regions for these very different tasks. Both of the findings described support the claim that examination of joint activation across multiple tasks can enable new questions to be posed about fMRI data. Our approach can also be applied to data using more than two tasks. It thus provides a way to integrate and probe brain networks

Simultaneous Multi-Slice fMRI using Spiral Trajectories

PubMed Central

Zahneisen, Benjamin; Poser, Benedikt A.; Ernst, Thomas; Stenger, V. Andrew

2014-01-01

Parallel imaging methods using multi-coil receiver arrays have been shown to be effective for increasing MRI acquisition speed. However parallel imaging methods for fMRI with 2D sequences show only limited improvements in temporal resolution because of the long echo times needed for BOLD contrast. Recently, Simultaneous Multi-Slice (SMS) imaging techniques have been shown to increase fMRI temporal resolution by factors of four and higher. In SMS fMRI multiple slices can be acquired simultaneously using Echo Planar Imaging (EPI) and the overlapping slices are un-aliased using a parallel imaging reconstruction with multiple receivers. The slice separation can be further improved using the “blipped-CAIPI” EPI sequence that provides a more efficient sampling of the SMS 3D k-space. In this paper a blipped-spiral SMS sequence for ultra-fast fMRI is presented. The blipped-spiral sequence combines the sampling efficiency of spiral trajectories with the SMS encoding concept used in blipped-CAIPI EPI. We show that blipped spiral acquisition can achieve almost whole brain coverage at 3 mm isotropic resolution in 168 ms. It is also demonstrated that the high temporal resolution allows for dynamic BOLD lag time measurement using visual/motor and retinotopic mapping paradigms. The local BOLD lag time within the visual cortex following the retinotopic mapping stimulation of expanding flickering rings is directly measured and easily translated into an eccentricity map of the cortex. PMID:24518259

Free Radical Imaging Using In Vivo Dynamic Nuclear Polarization-MRI.

PubMed

Utsumi, Hideo; Hyodo, Fuminori

2015-01-01

Redox reactions that generate free radical intermediates are essential to metabolic processes, and their intermediates can produce reactive oxygen species, which may promote diseases related to oxidative stress. The development of an in vivo electron spin resonance (ESR) spectrometer and its imaging enables us noninvasive and direct measurement of in vivo free radical reactions in living organisms. The dynamic nuclear polarization magnetic resonance imaging (DNP-MRI), also called PEDRI or OMRI, is also a new imaging method for observing free radical species in vivo. The spatiotemporal resolution of free radical imaging with DNP-MRI is comparable with that in MRI, and each of the radical species can be distinguished in the spectroscopic images by changing the frequency or magnetic field of ESR irradiation. Several kinds of stable nitroxyl radicals were used as spin probes to detect in vivo redox reactions. The signal decay of nitroxyl probes, which is determined with in vivo DNP-MRI, reflects the redox status under oxidative stress, and the signal decay is suppressed by prior administration of antioxidants. In addition, DNP-MRI can also visualize various intermediate free radicals from the intrinsic redox molecules. This noninvasive method, in vivo DNP-MRI, could become a useful tool for investigating the mechanism of oxidative injuries in animal disease models and the in vivo effects of antioxidant drugs. © 2015 Elsevier Inc. All rights reserved.

Comparison between breast MRI and contrast-enhanced spectral mammography.

PubMed

Łuczyńska, Elżbieta; Heinze-Paluchowska, Sylwia; Hendrick, Edward; Dyczek, Sonia; Ryś, Janusz; Herman, Krzysztof; Blecharz, Paweł; Jakubowicz, Jerzy

2015-05-12

The main goal of this study was to compare contrast-enhanced spectral mammography (CESM) and breast magnetic resonance imaging (MRI) with histopathological results and to compare the sensitivity, accuracy, and positive and negative predictive values for both imaging modalities. After ethics approval, CESM and MRI examinations were performed in 102 patients who had suspicious lesions described in conventional mammography. All visible lesions were evaluated independently by 2 experienced radiologists using BI-RADS classifications (scale 1-5). Dimensions of lesions measured with each modality were compared to postoperative histopathology results. There were 102 patients entered into CESM/MRI studies and 118 lesions were identified by the combination of CESM and breast MRI. Histopathology confirmed that 81 of 118 lesions were malignant and 37 were benign. Of the 81 malignant lesions, 72 were invasive cancers and 9 were in situ cancers. Sensitivity was 100% with CESM and 93% with breast MRI. Accuracy was 79% with CESM and 73% with breast MRI. ROC curve areas based on BI-RADS were 0.83 for CESM and 0.84 for breast MRI. Lesion size estimates on CESM and breast MRI were similar, both slightly larger than those from histopathology. Our results indicate that CESM has the potential to be a valuable diagnostic method that enables accurate detection of malignant breast lesions, has high negative predictive value, and a false-positive rate similar to that of breast MRI.

Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project

PubMed Central

Uğurbil, Kamil; Xu, Junqian; Auerbach, Edward J.; Moeller, Steen; Vu, An; Duarte-Carvajalino, Julio M.; Lenglet, Christophe; Wu, Xiaoping; Schmitter, Sebastian; Van de Moortele, Pierre Francois; Strupp, John; Sapiro, Guillermo; De Martino, Federico; Wang, Dingxin; Harel, Noam; Garwood, Michael; Chen, Liyong; Feinberg, David A.; Smith, Stephen M.; Miller, Karla L.; Sotiropoulos, Stamatios N; Jbabdi, Saad; Andersson, Jesper L; Behrens, Timothy EJ; Glasser, Matthew F.; Van Essen, David; Yacoub, Essa

2013-01-01

The human connectome project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce ‘functional connectivity’; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3 Tesla, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 second for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 Tesla magnetic field are also presented, targeting higher resolution, specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields and power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure. PMID:23702417

Using deep learning to segment breast and fibroglandular tissue in MRI volumes.

PubMed

Dalmış, Mehmet Ufuk; Litjens, Geert; Holland, Katharina; Setio, Arnaud; Mann, Ritse; Karssemeijer, Nico; Gubern-Mérida, Albert

2017-02-01

Automated segmentation of breast and fibroglandular tissue (FGT) is required for various computer-aided applications of breast MRI. Traditional image analysis and computer vision techniques, such atlas, template matching, or, edge and surface detection, have been applied to solve this task. However, applicability of these methods is usually limited by the characteristics of the images used in the study datasets, while breast MRI varies with respect to the different MRI protocols used, in addition to the variability in breast shapes. All this variability, in addition to various MRI artifacts, makes it a challenging task to develop a robust breast and FGT segmentation method using traditional approaches. Therefore, in this study, we investigated the use of a deep-learning approach known as "U-net." We used a dataset of 66 breast MRI's randomly selected from our scientific archive, which includes five different MRI acquisition protocols and breasts from four breast density categories in a balanced distribution. To prepare reference segmentations, we manually segmented breast and FGT for all images using an in-house developed workstation. We experimented with the application of U-net in two different ways for breast and FGT segmentation. In the first method, following the same pipeline used in traditional approaches, we trained two consecutive (2C) U-nets: first for segmenting the breast in the whole MRI volume and the second for segmenting FGT inside the segmented breast. In the second method, we used a single 3-class (3C) U-net, which performs both tasks simultaneously by segmenting the volume into three regions: nonbreast, fat inside the breast, and FGT inside the breast. For comparison, we applied two existing and published methods to our dataset: an atlas-based method and a sheetness-based method. We used Dice Similarity Coefficient (DSC) to measure the performances of the automated methods, with respect to the manual segmentations. Additionally, we computed

Automated prostate cancer localization without the need for peripheral zone extraction using multiparametric MRI.

PubMed

Liu, Xin; Yetik, Imam Samil

2011-06-01

Multiparametric magnetic resonance imaging (MRI) has been shown to have higher localization accuracy than transrectal ultrasound (TRUS) for prostate cancer. Therefore, automated cancer segmentation using multiparametric MRI is receiving a growing interest, since MRI can provide both morphological and functional images for tissue of interest. However, all automated methods to this date are applicable to a single zone of the prostate, and the peripheral zone (PZ) of the prostate needs to be extracted manually, which is a tedious and time-consuming job. In this paper, our goal is to remove the need of PZ extraction by incorporating the spatial and geometric information of prostate tumors with multiparametric MRI derived from T2-weighted MRI, diffusion-weighted imaging (DWI) and dynamic contrast enhanced MRI (DCE-MRI). In order to remove the need of PZ extraction, the authors propose a new method to incorporate the spatial information of the cancer. This is done by introducing a new feature called location map. This new feature is constructed by applying a nonlinear transformation to the spatial position coordinates of each pixel, so that the location map implicitly represents the geometric position of each pixel with respect to the prostate region. Then, this new feature is combined with multiparametric MR images to perform tumor localization. The proposed algorithm is applied to multiparametric prostate MRI data obtained from 20 patients with biopsy-confirmed prostate cancer. The proposed method which does not need the masks of PZ was found to have prostate cancer detection specificity of 0.84, sensitivity of 0.80 and dice coefficient value of 0.42. The authors have found that fusing the spatial information allows us to obtain tumor outline without the need of PZ extraction with a considerable success (better or similar performance to methods that require manual PZ extraction). Our experimental results quantitatively demonstrate the effectiveness of the proposed

Effect of pulse sequence parameter selection on signal strength in positive-contrast MRI markers for MRI-based prostate postimplant assessment

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

Lim, Tze Yee

Purpose: For postimplant dosimetric assessment, computed tomography (CT) is commonly used to identify prostate brachytherapy seeds, at the expense of accurate anatomical contouring. Magnetic resonance imaging (MRI) is superior to CT for anatomical delineation, but identification of the negative-contrast seeds is challenging. Positive-contrast MRI markers were proposed to replace spacers to assist seed localization on MRI images. Visualization of these markers under varying scan parameters was investigated. Methods: To simulate a clinical scenario, a prostate phantom was implanted with 66 markers and 86 seeds, and imaged on a 3.0T MRI scanner using a 3D fast radiofrequency-spoiled gradient recalled echo acquisitionmore » with various combinations of scan parameters. Scan parameters, including flip angle, number of excitations, bandwidth, field-of-view, slice thickness, and encoding steps were systematically varied to study their effects on signal, noise, scan time, image resolution, and artifacts. Results: The effects of pulse sequence parameter selection on the marker signal strength and image noise were characterized. The authors also examined the tradeoff between signal-to-noise ratio, scan time, and image artifacts, such as the wraparound artifact, susceptibility artifact, chemical shift artifact, and partial volume averaging artifact. Given reasonable scan time and managable artifacts, the authors recommended scan parameter combinations that can provide robust visualization of the MRI markers. Conclusions: The recommended MRI pulse sequence protocol allows for consistent visualization of the markers to assist seed localization, potentially enabling MRI-only prostate postimplant dosimetry.« less

Method for enhancing cell penetration of Gd3+-based MRI contrast agents by conjugation with hydrophobic fluorescent dyes.

PubMed

Yamane, Takehiro; Hanaoka, Kenjiro; Muramatsu, Yasuaki; Tamura, Keita; Adachi, Yusuke; Miyashita, Yasushi; Hirata, Yasunobu; Nagano, Tetsuo

2011-11-16

Gadolinium ion (Gd(3+)) complexes are commonly used as magnetic resonance imaging (MRI) contrast agents to enhance signals in T(1)-weighted MR images. Recently, several methods to achieve cell-permeation of Gd(3+) complexes have been reported, but more general and efficient methodology is needed. In this report, we describe a novel method to achieve cell permeation of Gd(3+) complexes by using hydrophobic fluorescent dyes as a cell-permeability-enhancing unit. We synthesized Gd(3+) complexes conjugated with boron dipyrromethene (BDP-Gd) and Cy7 dye (Cy7-Gd), and showed that these conjugates can be introduced efficiently into cells. To examine the relationship between cell permeability and dye structure, we further synthesized a series of Cy7-Gd derivatives. On the basis of MR imaging, flow cytometry, and ICP-MS analysis of cells loaded with Cy7-Gd derivatives, highly hydrophobic and nonanionic dyes were effective for enhancing cell permeation of Gd(3+) complexes. Furthermore, the behavior of these Cy7-Gd derivatives was examined in mice. Thus, conjugation of hydrophobic fluorescent dyes appears to be an effective approach to improve the cell permeability of Gd(3+) complexes, and should be applicable for further development of Gd(3+)-based MRI contrast agents.

Folded concave penalized learning in identifying multimodal MRI marker for Parkinson’s disease

PubMed Central

Liu, Hongcheng; Du, Guangwei; Zhang, Lijun; Lewis, Mechelle M.; Wang, Xue; Yao, Tao; Li, Runze; Huang, Xuemei

2016-01-01

Background Brain MRI holds promise to gauge different aspects of Parkinson’s disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data. New method This study introduces folded concave penalized (FCP) sparse logistic regression to identify biomarkers for PD from a large number of potential factors. The proposed statistical procedures target the challenges of high-dimensionality with limited data samples acquired. The maximization problem associated with the sparse logistic regression model is solved by local linear approximation. The proposed procedures then are applied to the empirical analysis of multimodal MRI data. Results From 45 features, the proposed approach identified 15 MRI markers and the UPSIT, which are known to be clinically relevant to PD. By combining the MRI and clinical markers, we can enhance substantially the specificity and sensitivity of the model, as indicated by the ROC curves. Comparison to existing methods We compare the folded concave penalized learning scheme with both the Lasso penalized scheme and the principle component analysis-based feature selection (PCA) in the Parkinson’s biomarker identification problem that takes into account both the clinical features and MRI markers. The folded concave penalty method demonstrates a substantially better clinical potential than both the Lasso and PCA in terms of specificity and sensitivity. Conclusions For the first time, we applied the FCP learning method to MRI biomarker discovery in PD. The proposed approach successfully identified MRI markers that are clinically relevant. Combining these biomarkers with clinical features can substantially enhance performance. PMID:27102045

Bayesian Inference for Functional Dynamics Exploring in fMRI Data.

PubMed

Guo, Xuan; Liu, Bing; Chen, Le; Chen, Guantao; Pan, Yi; Zhang, Jing

2016-01-01

This paper aims to review state-of-the-art Bayesian-inference-based methods applied to functional magnetic resonance imaging (fMRI) data. Particularly, we focus on one specific long-standing challenge in the computational modeling of fMRI datasets: how to effectively explore typical functional interactions from fMRI time series and the corresponding boundaries of temporal segments. Bayesian inference is a method of statistical inference which has been shown to be a powerful tool to encode dependence relationships among the variables with uncertainty. Here we provide an introduction to a group of Bayesian-inference-based methods for fMRI data analysis, which were designed to detect magnitude or functional connectivity change points and to infer their functional interaction patterns based on corresponding temporal boundaries. We also provide a comparison of three popular Bayesian models, that is, Bayesian Magnitude Change Point Model (BMCPM), Bayesian Connectivity Change Point Model (BCCPM), and Dynamic Bayesian Variable Partition Model (DBVPM), and give a summary of their applications. We envision that more delicate Bayesian inference models will be emerging and play increasingly important roles in modeling brain functions in the years to come.

Comparative study of microelectrode recording-based STN location and MRI-based STN location in low to ultra-high field (7.0 T) T2-weighted MRI images

NASA Astrophysics Data System (ADS)

Verhagen, Rens; Schuurman, P. Richard; van den Munckhof, Pepijn; Fiorella Contarino, M.; de Bie, Rob M. A.; Bour, Lo J.

2016-12-01

Objective. The correspondence between the anatomical STN and the STN observed in T2-weighted MRI images used for deep brain stimulation (DBS) targeting remains unclear. Using a new method, we compared the STN borders seen on MRI images with those estimated by intraoperative microelectrode recordings (MER). Approach. We developed a method to automatically generate a detailed estimation of STN shape and the location of its borders, based on multiple-channel MER measurements. In 33 STNs of 19 Parkinson patients, we quantitatively compared the dorsal and lateral borders of this MER-based STN model with the STN borders visualized by 1.5 T (n = 14), 3.0 T (n = 10) and 7.0 T (n = 9) T2-weighted MRI. Main results. The dorsal border was identified more dorsally on coronal T2 MRI than by the MER-based STN model, with a significant difference in the 3.0 T (range 0.97-1.19 mm) and 7.0 T (range 1.23-1.25 mm) groups. The lateral border was significantly more medial on 1.5 T (mean: 1.97 mm) and 3.0 T (mean: 2.49 mm) MRI than in the MER-based STN; a difference that was not found in the 7.0 T group. Significance. The STN extends further in the dorsal direction on coronal T2 MRI images than is measured by MER. Increasing MRI field strength to 3.0 T or 7.0 T yields similar discrepancies between MER and MRI at the dorsal STN border. In contrast, increasing MRI field strength to 7.0 T may be useful for identification of the lateral STN border and thereby improve DBS targeting.

MRI-guided brachytherapy

PubMed Central

Tanderup, Kari; Viswanathan, Akila; Kirisits, Christian; Frank, Steven J.

2014-01-01

The application of MRI-guided brachytherapy has demonstrated significant growth during the last two decades. Clinical improvements in cervix cancer outcomes have been linked to the application of repeated MRI for identification of residual tumor volumes during radiotherapy. This has changed clinical practice in the direction of individualized dose administration, and mounting evidence of improved clinical outcome with regard to local control, overall survival as well as morbidity. MRI-guided prostate HDR and LDR brachytherapy has improved the accuracy of target and organs-at-risk (OAR) delineation, and the potential exists for improved dose prescription and reporting for the prostate gland and organs at risk. Furthermore, MRI-guided prostate brachytherapy has significant potential to identify prostate subvolumes and dominant lesions to allow for dose administration reflecting the differential risk of recurrence. MRI-guided brachytherapy involves advanced imaging, target concepts, and dose planning. The key issue for safe dissemination and implementation of high quality MRI-guided brachytherapy is establishment of qualified multidisciplinary teams and strategies for training and education. PMID:24931089

Efficient gradient calibration based on diffusion MRI

PubMed Central

Teh, Irvin; Maguire, Mahon L.

2016-01-01

Purpose To propose a method for calibrating gradient systems and correcting gradient nonlinearities based on diffusion MRI measurements. Methods The gradient scaling in x, y, and z were first offset by up to 5% from precalibrated values to simulate a poorly calibrated system. Diffusion MRI data were acquired in a phantom filled with cyclooctane, and corrections for gradient scaling errors and nonlinearity were determined. The calibration was assessed with diffusion tensor imaging and independently validated with high resolution anatomical MRI of a second structured phantom. Results The errors in apparent diffusion coefficients along orthogonal axes ranged from −9.2% ± 0.4% to + 8.8% ± 0.7% before calibration and −0.5% ± 0.4% to + 0.8% ± 0.3% after calibration. Concurrently, fractional anisotropy decreased from 0.14 ± 0.03 to 0.03 ± 0.01. Errors in geometric measurements in x, y and z ranged from −5.5% to + 4.5% precalibration and were likewise reduced to −0.97% to + 0.23% postcalibration. Image distortions from gradient nonlinearity were markedly reduced. Conclusion Periodic gradient calibration is an integral part of quality assurance in MRI. The proposed approach is both accurate and efficient, can be setup with readily available materials, and improves accuracy in both anatomical and diffusion MRI to within ±1%. Magn Reson Med 77:170–179, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. PMID:26749277

SU-G-IeP1-13: Sub-Nyquist Dynamic MRI Via Prior Rank, Intensity and Sparsity Model (PRISM)

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

Jiang, B; Gao, H

Purpose: Accelerated dynamic MRI is important for MRI guided radiotherapy. Inspired by compressive sensing (CS), sub-Nyquist dynamic MRI has been an active research area, i.e., sparse sampling in k-t space for accelerated dynamic MRI. This work is to investigate sub-Nyquist dynamic MRI via a previously developed CS model, namely Prior Rank, Intensity and Sparsity Model (PRISM). Methods: The proposed method utilizes PRISM with rank minimization and incoherent sampling patterns for sub-Nyquist reconstruction. In PRISM, the low-rank background image, which is automatically calculated by rank minimization, is excluded from the L1 minimization step of the CS reconstruction to further sparsify themore » residual image, thus allowing for higher acceleration rates. Furthermore, the sampling pattern in k-t space is made more incoherent by sampling a different set of k-space points at different temporal frames. Results: Reconstruction results from L1-sparsity method and PRISM method with 30% undersampled data and 15% undersampled data are compared to demonstrate the power of PRISM for dynamic MRI. Conclusion: A sub- Nyquist MRI reconstruction method based on PRISM is developed with improved image quality from the L1-sparsity method.« less

[RSF model optimization and its application to brain tumor segmentation in MRI].

PubMed

Cheng, Zhaoning; Song, Zhijian

2013-04-01

Magnetic resonance imaging (MRI) is usually obscure and non-uniform in gray, and the tumors inside are poorly circumscribed, hence the automatic tumor segmentation in MRI is very difficult. Region-scalable fitting (RSF) energy model is a new segmentation approach for some uneven grayscale images. However, the level set formulation (LSF) of RSF model is not suitable for the environment with different grey level distribution inside and outside the intial contour, and the complex intensity environment of MRI always makes it hard to get ideal segmentation results. Therefore, we improved the model by a new LSF and combined it with the mean shift method, which can be helpful for tumor segmentation and has better convergence and target direction. The proposed method has been utilized in a series of studies for real MRI images, and the results showed that it could realize fast, accurate and robust segmentations for brain tumors in MRI, which has great clinical significance.

In Vivo Cytometry of Antigen-Specific T Cells Using 19F MRI

PubMed Central

Srinivas, Mangala; Turner, Michael S.; Janjic, Jelena M.; Morel, Penelope A.; Laidlaw, David H.; Ahrens, Eric T.

2009-01-01

Noninvasive methods to image the trafficking of phenotypically defined immune cells are paramount as we attempt to understand adaptive immunity. A 19F MRI-based methodology for tracking and quantifying cells of a defined phenotype is presented. These methods were applied to a murine inflammation model using antigen-specific T cells. The T cells that were intracellularly labeled ex vivo with a perfluoropolyether (PFPE) nanoemulsion and cells were transferred to a host receiving a localized inoculation of antigen. Longitudinal 19F MRI over 21 days revealed a dynamic accumulation and clearance of T cells in the lymph node (LN) draining the antigen. The apparent T-cell numbers were calculated in the LN from the time-lapse 19F MRI data. The effect of in vivo T-cell division on the 19F MRI cell quantification accuracy was investigated using fluorescence assays. Overall, in vivo cytometry using PFPE labeling and 19F MRI is broadly applicable to studies of whole-body cell biodistribution. PMID:19585593

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy.

PubMed

Li, Hua; Chen, Hsin-Chen; Dolly, Steven; Li, Harold; Fischer-Valuck, Benjamin; Victoria, James; Dempsey, James; Ruan, Su; Anastasio, Mark; Mazur, Thomas; Gach, Michael; Kashani, Rojano; Green, Olga; Rodriguez, Vivian; Gay, Hiram; Thorstad, Wade; Mutic, Sasa

2016-08-01

For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Considering the complex H&N structures and ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1

Fast numerical design of spatial-selective rf pulses in MRI using Krotov and quasi-Newton based optimal control methods

NASA Astrophysics Data System (ADS)

Vinding, Mads S.; Maximov, Ivan I.; Tošner, Zdeněk; Nielsen, Niels Chr.

2012-08-01

The use of increasingly strong magnetic fields in magnetic resonance imaging (MRI) improves sensitivity, susceptibility contrast, and spatial or spectral resolution for functional and localized spectroscopic imaging applications. However, along with these benefits come the challenges of increasing static field (B0) and rf field (B1) inhomogeneities induced by radial field susceptibility differences and poorer dielectric properties of objects in the scanner. Increasing fields also impose the need for rf irradiation at higher frequencies which may lead to elevated patient energy absorption, eventually posing a safety risk. These reasons have motivated the use of multidimensional rf pulses and parallel rf transmission, and their combination with tailoring of rf pulses for fast and low-power rf performance. For the latter application, analytical and approximate solutions are well-established in linear regimes, however, with increasing nonlinearities and constraints on the rf pulses, numerical iterative methods become attractive. Among such procedures, optimal control methods have recently demonstrated great potential. Here, we present a Krotov-based optimal control approach which as compared to earlier approaches provides very fast, monotonic convergence even without educated initial guesses. This is essential for in vivo MRI applications. The method is compared to a second-order gradient ascent method relying on the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method, and a hybrid scheme Krotov-BFGS is also introduced in this study. These optimal control approaches are demonstrated by the design of a 2D spatial selective rf pulse exciting the letters "JCP" in a water phantom.

Optshrink LR + S: accelerated fMRI reconstruction using non-convex optimal singular value shrinkage.

PubMed

Aggarwal, Priya; Shrivastava, Parth; Kabra, Tanay; Gupta, Anubha

2017-03-01

This paper presents a new accelerated fMRI reconstruction method, namely, OptShrink LR + S method that reconstructs undersampled fMRI data using a linear combination of low-rank and sparse components. The low-rank component has been estimated using non-convex optimal singular value shrinkage algorithm, while the sparse component has been estimated using convex l 1 minimization. The performance of the proposed method is compared with the existing state-of-the-art algorithms on real fMRI dataset. The proposed OptShrink LR + S method yields good qualitative and quantitative results.

3-T MRI safety assessments of magnetic dental attachments and castable magnetic alloys

PubMed Central

Miyata, K; Abe, Y; Ishii, T; Ishigami, T; Ohtani, K; Nagai, E; Ohyama, T; Umekawa, Y; Nakabayashi, S

2015-01-01

Objectives: To assess the safety of different magnetic dental attachments during 3-T MRI according to the American Society for Testing and Materials F2182-09 and F2052-06e1 standard testing methods and to develop a method to determine MRI compatibility by measuring magnetically induced torque. Methods: The temperature elevations, magnetically induced forces and torques of a ferromagnetic stainless steel keeper, a coping comprising a keeper and a cast magnetic alloy coping were measured on MRI systems. Results: The coping comprising a keeper demonstrated the maximum temperature increase (1.42 °C) for the whole-body-averaged specific absorption rate and was calculated as 2.1 W kg−1 with the saline phantom. All deflection angles exceeded 45°. The cast magnetic alloy coping had the greatest deflection force (0.33 N) during 3-T MRI and torque (1.015 mN m) during 0.3-T MRI. Conclusions: The tested devices showed minimal radiofrequency (RF)-induced heating in a 3-T MR environment, but the cast magnetic alloy coping showed a magnetically induced deflection force and torque approximately eight times that of the keepers. For safety, magnetic dental attachments should be inspected before and after MRI and large prostheses containing cast magnetic alloy should be removed. Although magnetic dental attachments may pose no great risk of RF-induced heating or magnetically induced torque during 3-T MRI, their magnetically induced deflection forces tended to exceed acceptable limits. Therefore, the inspection of such devices before and after MRI is important for patient safety. PMID:25785821

A multi-layer MRI description of Parkinson's disease

NASA Astrophysics Data System (ADS)

La Rocca, M.; Amoroso, N.; Lella, E.; Bellotti, R.; Tangaro, S.

2017-09-01

Magnetic resonance imaging (MRI) along with complex network is currently one of the most widely adopted techniques for detection of structural changes in neurological diseases, such as Parkinson's Disease (PD). In this paper, we present a digital image processing study, within the multi-layer network framework, combining more classifiers to evaluate the informative power of the MRI features, for the discrimination of normal controls (NC) and PD subjects. We define a network for each MRI scan; the nodes are the sub-volumes (patches) the images are divided into and the links are defined using the Pearson's pairwise correlation between patches. We obtain a multi-layer network whose important network features, obtained with different feature selection methods, are used to feed a supervised multi-level random forest classifier which exploits this base of knowledge for accurate classification. Method evaluation has been carried out using T1 MRI scans of 354 individuals, including 177 PD subjects and 177 NC from the Parkinson's Progression Markers Initiative (PPMI) database. The experimental results demonstrate that the features obtained from multiplex networks are able to accurately describe PD patterns. Besides, also if a privileged scale for studying PD disease exists, exploring the informative content of more scales leads to a significant improvement of the performances in the discrimination between disease and healthy subjects. In particular, this method gives a comprehensive overview of brain regions statistically affected by the disease, an additional value to the presented study.

A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer

NASA Astrophysics Data System (ADS)

Li, Xia; Welch, E. Brian; Arlinghaus, Lori R.; Bapsi Chakravarthy, A.; Xu, Lei; Farley, Jaime; Loveless, Mary E.; Mayer, Ingrid A.; Kelley, Mark C.; Meszoely, Ingrid M.; Means-Powell, Julie A.; Abramson, Vandana G.; Grau, Ana M.; Gore, John C.; Yankeelov, Thomas E.

2011-09-01

Quantitative analysis of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data requires the accurate determination of the arterial input function (AIF). A novel method for obtaining the AIF is presented here and pharmacokinetic parameters derived from individual and population-based AIFs are then compared. A Philips 3.0 T Achieva MR scanner was used to obtain 20 DCE-MRI data sets from ten breast cancer patients prior to and after one cycle of chemotherapy. Using a semi-automated method to estimate the AIF from the axillary artery, we obtain the AIF for each patient, AIFind, and compute a population-averaged AIF, AIFpop. The extended standard model is used to estimate the physiological parameters using the two types of AIFs. The mean concordance correlation coefficient (CCC) for the AIFs segmented manually and by the proposed AIF tracking approach is 0.96, indicating accurate and automatic tracking of an AIF in DCE-MRI data of the breast is possible. Regarding the kinetic parameters, the CCC values for Ktrans, vp and ve as estimated by AIFind and AIFpop are 0.65, 0.74 and 0.31, respectively, based on the region of interest analysis. The average CCC values for the voxel-by-voxel analysis are 0.76, 0.84 and 0.68 for Ktrans, vp and ve, respectively. This work indicates that Ktrans and vp show good agreement between AIFpop and AIFind while there is a weak agreement on ve.

Fast MRI-guided vacuum-assisted breast biopsy: initial experience.

PubMed

Liberman, Laura; Morris, Elizabeth A; Dershaw, D David; Thornton, Cynthia M; Van Zee, Kimberly J; Tan, Lee K

2003-11-01

The purpose of this study was to evaluate a new method for performing MRI-guided vacuum-assisted breast biopsy in a study of lesions that had subsequent surgical excision. SUBJECTS AND METHODS. Twenty women scheduled for MRI-guided needle localization and surgical biopsy were prospectively entered in the study. MRI-guided biopsy was performed with a vacuum-assisted probe, followed by placement of a localizing clip, and then needle localization for surgical excision. Vacuum-assisted biopsy and surgical histology were correlated. Vacuum-assisted biopsy was successfully performed in 19 (95%) of the 20 women. The median size of 27 MRI-detected lesions that had biopsy was 1.0 cm (range, 0.4-6.4 cm). Cancer was present in eight (30%) of 27 lesions and in six (32%) of 19 women; among these eight cancers, five were infiltrating and three were ductal carcinoma in situ (DCIS). Among these 27 lesions, histology was benign at vacuum-assisted biopsy and at surgery in 19 (70%), cancer at vacuum-assisted biopsy in six (22%), atypical ductal hyperplasia at vacuum-assisted biopsy and DCIS at surgery in one (4%), and benign at vacuum-assisted biopsy with surgery showing microscopic DCIS that was occult at MRI in one (4%). The median time to perform vacuum-assisted biopsy of a single lesion was 35 min (mean, 35 min; range, 24-48 min). Placement of a localizing clip, attempted in 26 lesions, was successful in 25 (96%) of 26, and the clip was retrieved on specimen radiography in 22 (96%) of 23. One complication occurred: a hematoma that resolved with compression. MRI-guided vacuum-assisted biopsy is a fast, safe, and accurate alternative to surgical biopsy for breast lesions detected on MRI.

Clinical Resting-state fMRI in the Preoperative Setting

PubMed Central

Lee, Megan H.; Miller-Thomas, Michelle M.; Benzinger, Tammie L.; Marcus, Daniel S.; Hacker, Carl D.; Leuthardt, Eric C.; Shimony, Joshua S.

2017-01-01

The purpose of this manuscript is to provide an introduction to resting-state functional magnetic resonance imaging (RS-fMRI) and to review the current application of this new and powerful technique in the preoperative setting using our institute’s extensive experience. RS-fMRI has provided important insights into brain physiology and is an increasingly important tool in the clinical setting. As opposed to task-based functional MRI wherein the subject performs a task while being scanned, RS-fMRI evaluates low-frequency fluctuations in the blood oxygen level dependent (BOLD) signal while the subject is at rest. Multiple resting state networks (RSNs) have been identified, including the somatosensory, language, and visual networks, which are of primary importance for presurgical planning. Over the past 4 years, we have performed over 300 RS-fMRI examinations in the clinical setting and these have been used to localize eloquent somatosensory and language cortices before brain tumor resection. RS-fMRI is particularly useful in this setting for patients who are unable to cooperate with the task-based paradigm, such as young children or those who are sedated, paretic, or aphasic. Although RS-fMRI is still investigational, our experience indicates that this method is ready for clinical application in the presurgical setting. PMID:26848556

Joint fMRI analysis and subject clustering using sparse dictionary learning

NASA Astrophysics Data System (ADS)

Kim, Seung-Jun; Dontaraju, Krishna K.

2017-08-01

Multi-subject fMRI data analysis methods based on sparse dictionary learning are proposed. In addition to identifying the component spatial maps by exploiting the sparsity of the maps, clusters of the subjects are learned by postulating that the fMRI volumes admit a subspace clustering structure. Furthermore, in order to tune the associated hyper-parameters systematically, a cross-validation strategy is developed based on entry-wise sampling of the fMRI dataset. Efficient algorithms for solving the proposed constrained dictionary learning formulations are developed. Numerical tests performed on synthetic fMRI data show promising results and provides insights into the proposed technique.

Wavelet-space Correlation Imaging for High-speed MRI without Motion Monitoring or Data Segmentation

PubMed Central

Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

2014-01-01

Purpose This study aims to 1) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and 2) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Methods Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called “wavelet-space correlation imaging”, is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Results Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Conclusion Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. PMID:25470230

Registration of MRI to intraoperative radiographs for target localization in spinal interventions

NASA Astrophysics Data System (ADS)

De Silva, T.; Uneri, A.; Ketcha, M. D.; Reaungamornrat, S.; Goerres, J.; Jacobson, M. W.; Vogt, S.; Kleinszig, G.; Khanna, A. J.; Wolinsky, J.-P.; Siewerdsen, J. H.

2017-01-01

Decision support to assist in target vertebra localization could provide a useful aid to safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT to intraoperative radiographs to reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred to as MR-LevelCheck) to perform 3D-2D registration based on a preoperative MRI to accommodate the increasingly common clinical scenario in which MRI is used instead of CT for preoperative planning. Straightforward adaptation of gradient/intensity-based methods appropriate to CT-to-radiograph registration is confounded by large mismatch and noncorrespondence in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simple vertebrae segmentation step using vertebra centroids as seed points (automatically defined within existing workflow). Forwards projections are computed using segmented MRI and registered to radiographs via gradient orientation (GO) similarity and the CMA-ES (covariance-matrix-adaptation evolutionary-strategy) optimizer. The method was tested in an IRB-approved study involving 10 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch and large capture range. Robust registration performance was achieved with projection distance error (PDE) (median  ±  IQR)  =  4.3  ±  2.6 mm (median  ±  IQR) and 0% failure rate. Segmentation accuracy for the continuous max-flow method yielded dice coefficient  =  88.1  ±  5.2, accuracy  =  90.6  ±  5.7, RMSE  =  1.8  ±  0.6 mm, and contour affinity ratio (CAR)  =  0.82  ±  0.08. Registration performance was found to be robust for

PET attenuation correction for flexible MRI surface coils in hybrid PET/MRI using a 3D depth camera

NASA Astrophysics Data System (ADS)

Frohwein, Lynn J.; Heß, Mirco; Schlicher, Dominik; Bolwin, Konstantin; Büther, Florian; Jiang, Xiaoyi; Schäfers, Klaus P.

2018-01-01

PET attenuation correction for flexible MRI radio frequency surface coils in hybrid PET/MRI is still a challenging task, as position and shape of these coils conform to large inter-patient variabilities. The purpose of this feasibility study is to develop a novel method for the incorporation of attenuation information about flexible surface coils in PET reconstruction using the Microsoft Kinect V2 depth camera. The depth information is used to determine a dense point cloud of the coil’s surface representing the shape of the coil. From a CT template—acquired once in advance—surface information of the coil is extracted likewise and converted into a point cloud. The two point clouds are then registered using a combination of an iterative-closest-point (ICP) method and a partially rigid registration step. Using the transformation derived through the point clouds, the CT template is warped and thereby adapted to the PET/MRI scan setup. The transformed CT template is converted into an attenuation map from Hounsfield units into linear attenuation coefficients. The resulting fitted attenuation map is then integrated into the MRI-based patient-specific DIXON-based attenuation map of the actual PET/MRI scan. A reconstruction of phantom PET data acquired with the coil present in the field-of-view (FoV), but without the corresponding coil attenuation map, shows large artifacts in regions close to the coil. The overall count loss is determined to be around 13% compared to a PET scan without the coil present in the FoV. A reconstruction using the new μ-map resulted in strongly reduced artifacts as well as increased overall PET intensities with a remaining relative difference of about 1% to a PET scan without the coil in the FoV.

TU-F-BRB-02: Motion Artifacts and Suppression in MRI

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

Zhong, X.

The current clinical standard of organ respiratory imaging, 4D-CT, is fundamentally limited by poor soft-tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose-volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft-tissue contrast. MRI-based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR-based motion management clinically feasible. For example, cine MRI has highmore » temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D-MRI and MRI hybrid treatment machines (i.e. MR-linac or MR-Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI-based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR-based motion management methods and technologies, the state-of-the-art concerning MRI development and clinical application and the barriers to more widespread adoption. Learning Objectives: Discuss the need of MR-based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.« less

TU-F-BRB-00: MRI-Based Motion Management for RT

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

NONE

The current clinical standard of organ respiratory imaging, 4D-CT, is fundamentally limited by poor soft-tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose-volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft-tissue contrast. MRI-based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR-based motion management clinically feasible. For example, cine MRI has highmore » temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D-MRI and MRI hybrid treatment machines (i.e. MR-linac or MR-Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI-based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR-based motion management methods and technologies, the state-of-the-art concerning MRI development and clinical application and the barriers to more widespread adoption. Learning Objectives: Discuss the need of MR-based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.« less

Prostate cancer: computer-aided diagnosis on multiparametric MRI

NASA Astrophysics Data System (ADS)

Marin, Laura; Racoceanu, Daniel; Renard Penna, Raphaele; Ezziane, Malek

2017-11-01

Prostate cancer (PCa) is one of the most common cancers in men, being also the second most deadly cancer after lung cancer. There is increasing interest in active surveillance and minimally invasive focal therapies in PCa to avoid morbidities associated with whole gland therapy. Tumor volume represents an essential prognostic factor of PCa and the definition of index lesion volume is critical for appropriate decision making, especially for image guide focal treatment or in case of active surveillance. Multi-parametric Magnetic Resonance Imaging (mp-MRI) is the modality of choice for the detection and the localization of PCa foci. However, little has been published on mp-MRI accuracy in determining PCa volume, especially at 3T. There is insufficient evidence and no consensus to determine which of the methods for measuring volume is optimal. The objective of this study concerns the elaboration of an algorithm for automatic interpretation of mp-MRI. We determine the accuracy of the proposed method by comparing the prostate tumor volume issued from the automated volumetric mp-MRI measurements of the tumoral region, with manual and semi-automated volumetric measurements done by and respectively with radiologists. Information issued from whole mount histopathology is used to validate the whole approach.

Intra- and inter-examination repeatability of magnetic resonance spectroscopy, magnitude-based MRI, and complex-based MRI for estimation of hepatic proton density fat fraction in overweight and obese children and adults.

PubMed

Tyagi, Avishkar; Yeganeh, Omid; Levin, Yakir; Hooker, Jonathan C; Hamilton, Gavin C; Wolfson, Tanya; Gamst, Anthony; Zand, Amir K; Heba, Elhamy; Loomba, Rohit; Schwimmer, Jeffrey; Middleton, Michael S; Sirlin, Claude B

2015-10-01

Determine intra- and inter-examination repeatability of magnitude-based magnetic resonance imaging (MRI-M), complex-based magnetic resonance imaging (MRI-C), and magnetic resonance spectroscopy (MRS) at 3T for estimating hepatic proton density fat fraction (PDFF), and using MRS as a reference, confirm MRI-M and MRI-C accuracy. Twenty-nine overweight and obese pediatric (n = 20) and adult (n = 9) subjects (23 male, 6 female) underwent three same-day 3T MR examinations. In each examination MRI-M, MRI-C, and single-voxel MRS were acquired three times. For each MRI acquisition, hepatic PDFF was estimated at the MRS voxel location. Intra- and inter-examination repeatability were assessed by computing standard deviations (SDs) and intra-class correlation coefficients (ICCs). Aggregate SD was computed for each method as the square root of the average of first repeat variances. MRI-M and MRI-C PDFF estimation accuracy was assessed using linear regression with MRS as a reference. For MRI-M, MRI-C, and MRS acquisitions, respectively, mean intra-examination SDs were 0.25%, 0.42%, and 0.49%; mean intra-examination ICCs were 0.999, 0.997, and 0.995; mean inter-examination SDs were 0.42%, 0.45%, and 0.46%; and inter-examination ICCs were 0.995, 0.992, and 0.990. Aggregate SD for each method was <0.9%. Using MRS as a reference, regression slope, intercept, average bias, and R (2), respectively, for MRI-M were 0.99%, 1.73%, 1.61%, and 0.986, and for MRI-C were 0.96%, 0.43%, 0.40%, and 0.991. MRI-M, MRI-C, and MRS showed high intra- and inter-examination hepatic PDFF estimation repeatability in overweight and obese subjects. Longitudinal hepatic PDFF change >1.8% (twice the maximum aggregate SD) may represent real change rather than measurement imprecision. Further research is needed to assess whether examinations performed on different days or with different MR technologists affect repeatability of MRS voxel placement and MRS-based PDFF measurements.

Development of a synoptic MRI report for primary rectal cancer.

PubMed

Spiegle, Gillian; Leon-Carlyle, Marisa; Schmocker, Selina; Fruitman, Mark; Milot, Laurent; Gagliardi, Anna R; Smith, Andy J; McLeod, Robin S; Kennedy, Erin D

2009-12-02

Although magnetic resonance imaging (MRI) is an important imaging modality for pre-operative staging and surgical planning of rectal cancer, to date there has been little investigation on the completeness and overall quality of MRI reports. This is important because optimal patient care depends on the quality of the MRI report and clear communication of these reports to treating physicians. Previous work has shown that the use of synoptic pathology reports improves the quality of pathology reports and communication between physicians. The aims of this project are to develop a synoptic MRI report for rectal cancer and determine the enablers and barriers toward the implementation of a synoptic MRI report for rectal cancer in the clinical setting. A three-step Delphi process with an expert panel will extract the key criteria for the MRI report to guide pre-operative chemoradiation and surgical planning following a review of the literature, and a synoptic template will be developed. Furthermore, standardized qualitative research methods will be used to conduct interviews with radiologists to determine the enablers and barriers to the implementation and sustainability of the synoptic MRI report in the clinic setting. Synoptic MRI reports for rectal cancer are currently not used in North America and may improve the overall quality of MRI report and communication between physicians. This may, in turn, lead to improved patient care and outcomes for rectal cancer patients.

Automated determination of arterial input function for DCE-MRI of the prostate

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Chang, Ming-Ching; Gupta, Sandeep

2011-03-01

Prostate cancer is one of the commonest cancers in the world. Dynamic contrast enhanced MRI (DCE-MRI) provides an opportunity for non-invasive diagnosis, staging, and treatment monitoring. Quantitative analysis of DCE-MRI relies on determination of an accurate arterial input function (AIF). Although several methods for automated AIF detection have been proposed in literature, none are optimized for use in prostate DCE-MRI, which is particularly challenging due to large spatial signal inhomogeneity. In this paper, we propose a fully automated method for determining the AIF from prostate DCE-MRI. Our method is based on modeling pixel uptake curves as gamma variate functions (GVF). First, we analytically compute bounds on GVF parameters for more robust fitting. Next, we approximate a GVF for each pixel based on local time domain information, and eliminate the pixels with false estimated AIFs using the deduced upper and lower bounds. This makes the algorithm robust to signal inhomogeneity. After that, according to spatial information such as similarity and distance between pixels, we formulate the global AIF selection as an energy minimization problem and solve it using a message passing algorithm to further rule out the weak pixels and optimize the detected AIF. Our method is fully automated without training or a priori setting of parameters. Experimental results on clinical data have shown that our method obtained promising detection accuracy (all detected pixels inside major arteries), and a very good match with expert traced manual AIF.

EARLY VERSUS LATE MRI IN ASPHYXIATED NEWBORNS TREATED WITH HYPOTHERMIA

PubMed Central

Wintermark, Pia; Hansen, Anne; Soul, Janet; Labrecque, Michelle; Robertson, Richard L.; Warfield, Simon K.

2012-01-01

Objective The purposes of this feasibility study are to assess: (1) the potential utility of early brain magnetic resonance imaging (MRI) in asphyxiated newborns treated with hypothermia; (2) whether early MRI predicts later brain injury observed in these newborns after hypothermia is completed; and (3) whether early MRI indicators of brain injury in these newborns represent reversible changes. Patients and Methods All consecutive asphyxiated term newborns meeting the criteria for therapeutic hypothermia were enrolled prospectively. Each of them underwent 1–2 “early” MRI scans while receiving hypothermia, on day of life (DOL) 1 and DOL 2–3, and also 1–2 “late” MRI scans on DOL 8–13 and at 1 month of age. Results Thirty-seven MRI scans were obtained in twelve asphyxiated neonates treated with induced hypothermia. Four newborns did develop MRI evidence of brain injury, already visible on early MRI scans. The remaining eight newborns did not develop significant MRI evidence of brain injury on any of the MRI scans. In addition, two patients displayed unexpected findings on early MRIs, leading to early termination of hypothermia treatment. Conclusions MRI scans obtained on DOL 2–3 during hypothermia seem to predict later brain injuries in asphyxiated newborns in this feasibility study. Brain injuries identified during this early time appear to represent irreversible changes. Early MRI scans might also be useful to demonstrate unexpected findings not related to hypoxic-ischemic encephalopathy, which could potentially be exacerbated by induced hypothermia. Additional studies with larger numbers of patients will be useful to more definitively confirm these results. PMID:20688865

MRI-Guided Focused Ultrasound Surgery

PubMed Central

Jolesz, Ferenc A.

2014-01-01

MRI-guided focused ultrasound (MRgFUS) surgery is a noninvasive thermal ablation method that uses magnetic resonance imaging (MRI) for target definition, treatment planning, and closed-loop control of energy deposition. Integrating FUS and MRI as a therapy delivery system allows us to localize, target, and monitor in real time, and thus to ablate targeted tissue without damaging normal structures. This precision makes MRgFUS an attractive alternative to surgical resection or radiation therapy of benign and malignant tumors. Already approved for the treatment of uterine fibroids, MRgFUS is in ongoing clinical trials for the treatment of breast, liver, prostate, and brain cancer and for the palliation of pain in bone metastasis. In addition to thermal ablation, FUS, with or without the use of microbubbles, can temporarily change vascular or cell membrane permeability and release or activate various compounds for targeted drug delivery or gene therapy. A disruptive technology, MRgFUS provides new therapeutic approaches and may cause major changes in patient management and several medical disciplines. PMID:19630579

Segmentation of human brain using structural MRI.

PubMed

Helms, Gunther

2016-04-01

Segmentation of human brain using structural MRI is a key step of processing in imaging neuroscience. The methods have undergone a rapid development in the past two decades and are now widely available. This non-technical review aims at providing an overview and basic understanding of the most common software. Starting with the basis of structural MRI contrast in brain and imaging protocols, the concepts of voxel-based and surface-based segmentation are discussed. Special emphasis is given to the typical contrast features and morphological constraints of cortical and sub-cortical grey matter. In addition to the use for voxel-based morphometry, basic applications in quantitative MRI, cortical thickness estimations, and atrophy measurements as well as assignment of cortical regions and deep brain nuclei are briefly discussed. Finally, some fields for clinical applications are given.

Probing the brain with molecular fMRI.

PubMed

Ghosh, Souparno; Harvey, Peter; Simon, Jacob C; Jasanoff, Alan

2018-06-01

One of the greatest challenges of modern neuroscience is to incorporate our growing knowledge of molecular and cellular-scale physiology into integrated, organismic-scale models of brain function in behavior and cognition. Molecular-level functional magnetic resonance imaging (molecular fMRI) is a new technology that can help bridge these scales by mapping defined microscopic phenomena over large, optically inaccessible regions of the living brain. In this review, we explain how MRI-detectable imaging probes can be used to sensitize noninvasive imaging to mechanistically significant components of neural processing. We discuss how a combination of innovative probe design, advanced imaging methods, and strategies for brain delivery can make molecular fMRI an increasingly successful approach for spatiotemporally resolved studies of diverse neural phenomena, perhaps eventually in people. Copyright © 2018 Elsevier Ltd. All rights reserved.

A voxel-based investigation for MRI-only radiotherapy of the brain using ultra short echo times

NASA Astrophysics Data System (ADS)

Edmund, Jens M.; Kjer, Hans M.; Van Leemput, Koen; Hansen, Rasmus H.; Andersen, Jon AL; Andreasen, Daniel

2014-12-01

Radiotherapy (RT) based on magnetic resonance imaging (MRI) as the only modality, so-called MRI-only RT, would remove the systematic registration error between MR and computed tomography (CT), and provide co-registered MRI for assessment of treatment response and adaptive RT. Electron densities, however, need to be assigned to the MRI images for dose calculation and patient setup based on digitally reconstructed radiographs (DRRs). Here, we investigate the geometric and dosimetric performance for a number of popular voxel-based methods to generate a so-called pseudo CT (pCT). Five patients receiving cranial irradiation, each containing a co-registered MRI and CT scan, were included. An ultra short echo time MRI sequence for bone visualization was used. Six methods were investigated for three popular types of voxel-based approaches; (1) threshold-based segmentation, (2) Bayesian segmentation and (3) statistical regression. Each approach contained two methods. Approach 1 used bulk density assignment of MRI voxels into air, soft tissue and bone based on logical masks and the transverse relaxation time T2 of the bone. Approach 2 used similar bulk density assignments with Bayesian statistics including or excluding additional spatial information. Approach 3 used a statistical regression correlating MRI voxels with their corresponding CT voxels. A similar photon and proton treatment plan was generated for a target positioned between the nasal cavity and the brainstem for all patients. The CT agreement with the pCT of each method was quantified and compared with the other methods geometrically and dosimetrically using both a number of reported metrics and introducing some novel metrics. The best geometrical agreement with CT was obtained with the statistical regression methods which performed significantly better than the threshold and Bayesian segmentation methods (excluding spatial information). All methods agreed significantly better with CT than a reference water MRI

A comparison between EEG source localization and fMRI during the processing of emotional visual stimuli

NASA Astrophysics Data System (ADS)

Hu, Jin; Tian, Jie; Pan, Xiaohong; Liu, Jiangang

2007-03-01

The purpose of this paper is to compare between EEG source localization and fMRI during emotional processing. 108 pictures for EEG (categorized as positive, negative and neutral) and 72 pictures for fMRI were presented to 24 healthy, right-handed subjects. The fMRI data were analyzed using statistical parametric mapping with SPM2. LORETA was applied to grand averaged ERP data to localize intracranial sources. Statistical analysis was implemented to compare spatiotemporal activation of fMRI and EEG. The fMRI results are in accordance with EEG source localization to some extent, while part of mismatch in localization between the two methods was also observed. In the future we should apply the method for simultaneous recording of EEG and fMRI to our study.

MRI Safety during Pregnancy

MedlinePlus

... during the exam? Contrast material MRI during pregnancy Magnetic resonance imaging (MRI) If you are pregnant and your doctor wants to perform a magnetic resonance imaging (MRI) exam, there is a possibility that your ...

An MRI-compatible platform for one-dimensional motion management studies in MRI.

PubMed

Nofiele, Joris; Yuan, Qing; Kazem, Mohammad; Tatebe, Ken; Torres, Quinn; Sawant, Amit; Pedrosa, Ivan; Chopra, Rajiv

2016-08-01

Abdominal MRI remains challenging because of respiratory motion. Motion compensation strategies are difficult to compare clinically because of the variability across human subjects. The goal of this study was to evaluate a programmable system for one-dimensional motion management MRI research. A system comprised of a programmable motorized linear stage and computer was assembled and tested in the MRI environment. Tests of the mutual interference between the platform and a whole-body MRI were performed. Organ trajectories generated from a high-temporal resolution scan of a healthy volunteer were used in phantom tests to evaluate the effects of motion on image quality and quantitative MRI measurements. No interference between the motion platform and the MRI was observed, and reliable motion could be produced across a wide range of imaging conditions. Motion-related artifacts commensurate with motion amplitude, frequency, and waveform were observed. T2 measurement of a kidney lesion in an abdominal phantom showed that its value decreased by 67% with physiologic motion, but could be partially recovered with navigator-based motion-compensation. The motion platform can produce reliable linear motion within a whole-body MRI. The system can serve as a foundation for a research platform to investigate and develop motion management approaches for MRI. Magn Reson Med 76:702-712, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy

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

Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin

Purpose: For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Methods: Considering the complex H&N structures andmore » ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity

Evaluation of COPD's diaphragm motion extracted from 4D-MRI

NASA Astrophysics Data System (ADS)

Swastika, Windra; Masuda, Yoshitada; Kawata, Naoko; Matsumoto, Koji; Suzuki, Toshio; Iesato, Ken; Tada, Yuji; Sugiura, Toshihiko; Tanabe, Nobuhiro; Tatsumi, Koichiro; Ohnishi, Takashi; Haneishi, Hideaki

2015-03-01

We have developed a method called intersection profile method to construct a 4D-MRI (3D+time) from time-series of 2D-MRI. The basic idea is to find the best matching of the intersection profile from the time series of 2D-MRI in sagittal plane (navigator slice) and time series of 2D-MRI in coronal plane (data slice). In this study, we use 4D-MRI to semiautomatically extract the right diaphragm motion of 16 subjects (8 healthy subjects and 8 COPD patients). The diaphragm motion is then evaluated quantitatively by calculating the displacement of each subjects and normalized it. We also generate phase-length map to view and locate paradoxical motion of the COPD patients. The quantitative results of the normalized displacement shows that COPD patients tend to have smaller displacement compared to healthy subjects. The average normalized displacement of total 8 COPD patients is 9.4mm and the average of normalized displacement of 8 healthy volunteers is 15.3mm. The generated phase-length maps show that not all of the COPD patients have paradoxical motion, however if it has paradoxical motion, the phase-length map is able to locate where does it occur.

Proton beam deflection in MRI fields: Implications for MRI-guided proton therapy.

PubMed

Oborn, B M; Dowdell, S; Metcalfe, P E; Crozier, S; Mohan, R; Keall, P J

2015-05-01

beam axis and those fired from a point source. This is indicative of the 3D spatially variant nature of the MRI fringe field. For the first time, accurate magnetic and Monte Carlo modeling have been used to assess the transport of generic proton beams toward a 1 T split-bore MRI. Significant rotation is observed in the inline orientation, while more complex deflection and distortion are seen in the perpendicular orientation. The results of this study suggest that due to the complexity and energy-dependent nature of the magnetic deflection and distortion, the pencil beam scanning method will be the only choice for delivering a therapeutic proton beam inside a potential MRI-guided proton therapy system in either the inline or perpendicular orientation. Further to this, significant correction strategies will be required to account for the MRI fringe fields.

Image segmentation and 3D visualization for MRI mammography

NASA Astrophysics Data System (ADS)

Li, Lihua; Chu, Yong; Salem, Angela F.; Clark, Robert A.

2002-05-01

MRI mammography has a number of advantages, including the tomographic, and therefore three-dimensional (3-D) nature, of the images. It allows the application of MRI mammography to breasts with dense tissue, post operative scarring, and silicon implants. However, due to the vast quantity of images and subtlety of difference in MR sequence, there is a need for reliable computer diagnosis to reduce the radiologist's workload. The purpose of this work was to develop automatic breast/tissue segmentation and visualization algorithms to aid physicians in detecting and observing abnormalities in breast. Two segmentation algorithms were developed: one for breast segmentation, the other for glandular tissue segmentation. In breast segmentation, the MRI image is first segmented using an adaptive growing clustering method. Two tracing algorithms were then developed to refine the breast air and chest wall boundaries of breast. The glandular tissue segmentation was performed using an adaptive thresholding method, in which the threshold value was spatially adaptive using a sliding window. The 3D visualization of the segmented 2D slices of MRI mammography was implemented under IDL environment. The breast and glandular tissue rendering, slicing and animation were displayed.

Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods.

PubMed

Georgiadis, Pantelis; Cavouras, Dionisis; Kalatzis, Ioannis; Glotsos, Dimitris; Athanasiadis, Emmanouil; Kostopoulos, Spiros; Sifaki, Koralia; Malamas, Menelaos; Nikiforidis, George; Solomou, Ekaterini

2009-01-01

Three-dimensional (3D) texture analysis of volumetric brain magnetic resonance (MR) images has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to evaluate the efficiency of 3D textural features using a pattern recognition system in the task of discriminating benign, malignant and metastatic brain tissues on T1 postcontrast MR imaging (MRI) series. The dataset consisted of 67 brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed as an ensemble classification scheme employing a support vector machine classifier, specially modified in order to integrate the least squares features transformation logic in its kernel function. The latter, in conjunction with using 3D textural features, enabled boosting up the performance of the system in discriminating metastatic, malignant and benign brain tumors with 77.14%, 89.19% and 93.33% accuracy, respectively. The method was evaluated using an external cross-validation process; thus, results might be considered indicative of the generalization performance of the system to "unseen" cases. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.

Technical Note: Independent component analysis for quality assurance in functional MRI.

PubMed

Astrakas, Loukas G; Kallistis, Nikolaos S; Kalef-Ezra, John A

2016-02-01

Independent component analysis (ICA) is an established method of analyzing human functional MRI (fMRI) data. Here, an ICA-based fMRI quality control (QC) tool was developed and used. ICA-based fMRI QC tool to be used with a commercial phantom was developed. In an attempt to assess the performance of the tool relative to preexisting alternative tools, it was used seven weeks before and eight weeks after repair of a faulty gradient amplifier of a non-state-of-the-art MRI unit. More specifically, its performance was compared with the AAPM 100 acceptance testing and quality assurance protocol and two fMRI QC protocols, proposed by Freidman et al. ["Report on a multicenter fMRI quality assurance protocol," J. Magn. Reson. Imaging 23, 827-839 (2006)] and Stocker et al. ["Automated quality assurance routines for fMRI data applied to a multicenter study," Hum. Brain Mapp. 25, 237-246 (2005)], respectively. The easily developed and applied ICA-based QC protocol provided fMRI QC indices and maps equally sensitive to fMRI instabilities with the indices and maps of other established protocols. The ICA fMRI QC indices were highly correlated with indices of other fMRI QC protocols and in some cases theoretically related to them. Three or four independent components with slow varying time series are detected under normal conditions. ICA applied on phantom measurements is an easy and efficient tool for fMRI QC. Additionally, it can protect against misinterpretations of artifact components as human brain activations. Evaluating fMRI QC indices in the central region of a phantom is not always the optimal choice.

Quantitative Serial MRI of the Treated Fibroid Uterus

PubMed Central

Williams, Alistair R. W.; McKillop, Graham; Walker, Jane; Horne, Andrew W.; Newby, David E.; Anderson, Richard A.; Semple, Scott I.; Marshall, Ian; Lewis, Steff C.; Millar, Robert P.; Bastin, Mark E.; Critchley, Hilary O. D.

2014-01-01

Objective There are no long-term medical treatments for uterine fibroids, and non-invasive biomarkers are needed to evaluate novel therapeutic interventions. The aim of this study was to determine whether serial dynamic contrast-enhanced MRI (DCE-MRI) and magnetization transfer MRI (MT-MRI) are able to detect changes that accompany volume reduction in patients administered GnRH analogue drugs, a treatment which is known to reduce fibroid volume and perfusion. Our secondary aim was to determine whether rapid suppression of ovarian activity by combining GnRH agonist and antagonist therapies results in faster volume reduction. Methods Forty women were assessed for eligibility at gynaecology clinics in the region, of whom thirty premenopausal women scheduled for hysterectomy due to symptomatic fibroids were randomized to three groups, receiving (1) GnRH agonist (Goserelin), (2) GnRH agonist+GnRH antagonist (Goserelin and Cetrorelix) or (3) no treatment. Patients were monitored by serial structural, DCE-MRI and MT-MRI, as well as by ultrasound and serum oestradiol concentration measurements from enrolment to hysterectomy (approximately 3 months). Results A volumetric treatment effect assessed by structural MRI occurred by day 14 of treatment (9% median reduction versus 9% increase in untreated women; P = 0.022) and persisted throughout. Reduced fibroid perfusion and permeability assessed by DCE-MRI occurred later and was demonstrable by 2–3 months (43% median reduction versus 20% increase respectively; P = 0.0093). There was no apparent treatment effect by MT-MRI. Effective suppression of oestradiol was associated with early volume reduction at days 14 (P = 0.041) and 28 (P = 0.0061). Conclusion DCE-MRI is sensitive to the vascular changes thought to accompany successful GnRH analogue treatment of uterine fibroids and should be considered for use in future mechanism/efficacy studies of proposed fibroid drug therapies. GnRH antagonist administration

Toward an MRI-based method to measure non-uniform cartilage deformation: an MRI-cyclic loading apparatus system and steady-state cyclic displacement of articular cartilage under compressive loading.

PubMed

Neu, C P; Hull, M L

2003-04-01

Recent magnetic resonance imaging (MRI) techniques have shown potential for measuring non-uniform deformations throughout the volume (i.e. three-dimensional (3D) deformations) in small orthopedic tissues such as articular cartilage. However, to analyze cartilage deformation using MRI techniques, a system is required which can construct images from multiple acquisitions of MRI signals from the cartilage in both the underformed and deformed states. The objectives of the work reported in this article were to 1) design an apparatus that could apply highly repeatable cyclic compressive loads of 400 N and operate in the bore of an MRI scanner, 2) demonstrate that the apparatus and MRI scanner can be successfully integrated to observe 3D deformations in a phantom material, 3) use the apparatus to determine the load cycle necessary to achieve a steady-state deformation response in normal bovine articular cartilage samples using a flat-surfaced and nonporous indentor in unconfined compression. Composed of electronic and pneumatic components, the apparatus regulated pressure to a double-acting pneumatic cylinder so that (1) load-controlled compression cycles were applied to cartilage samples immersed in a saline bath, (2) loading and recovery periods within a cycle varied in time duration, and (3) load magnitude varied so that the stress applied to cartilage samples was within typical physiological ranges. In addition the apparatus allowed gating for MR image acquisition, and operation within the bore of an MRI scanner without creating image artifacts. The apparatus demonstrated high repeatability in load application with a standard deviation of 1.8% of the mean 400 N load applied. When the apparatus was integrated with an MRI scanner programmed with appropriate pulse sequences, images of a phantom material in both the underformed and deformed states were constructed by assembling data acquired through multiple signal acquisitions. Additionally, the number of cycles to reach

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes

PubMed Central

Funane, Tsukasa; Sato, Hiroki; Yahata, Noriaki; Takizawa, Ryu; Nishimura, Yukika; Kinoshita, Akihide; Katura, Takusige; Atsumori, Hirokazu; Fukuda, Masato; Kasai, Kiyoto; Koizumi, Hideaki; Kiguchi, Masashi

2015-01-01

Abstract. It has been reported that a functional near-infrared spectroscopy (fNIRS) signal can be contaminated by extracerebral contributions. Many algorithms using multidistance separations to address this issue have been proposed, but their spatial separation performance has rarely been validated with simultaneous measurements of fNIRS and functional magnetic resonance imaging (fMRI). We previously proposed a method for discriminating between deep and shallow contributions in fNIRS signals, referred to as the multidistance independent component analysis (MD-ICA) method. In this study, to validate the MD-ICA method from the spatial aspect, multidistance fNIRS, fMRI, and laser-Doppler-flowmetry signals were simultaneously obtained for 12 healthy adult males during three tasks. The fNIRS signal was separated into deep and shallow signals by using the MD-ICA method, and the correlation between the waveforms of the separated fNIRS signals and the gray matter blood oxygenation level–dependent signals was analyzed. A three-way analysis of variance (signal depth×Hb kind×task) indicated that the main effect of fNIRS signal depth on the correlation is significant [F(1,1286)=5.34, p<0.05]. This result indicates that the MD-ICA method successfully separates fNIRS signals into spatially deep and shallow signals, and the accuracy and reliability of the fNIRS signal will be improved with the method. PMID:26157983

Oxidative stress measured in vivo without an exogenous contrast agent using QUEST MRI

NASA Astrophysics Data System (ADS)

Berkowitz, Bruce A.

2018-06-01

Decades of experimental studies have implicated excessive generation of reactive oxygen species (ROS) in the decline of tissue function during normal aging, and as a pathogenic factor in a vast array of fatal or debilitating morbidities. This massive body of work has important clinical implications since many antioxidants are FDA approved, readily cross blood-tissue barriers, and are effective at improving disease outcomes. Yet, the potential benefits of antioxidants have remained largely unrealized in patients because conventional methods cannot determine the dose, timing, and drug combinations to be used in clinical trials to localize and decrease oxidative stress. To address this major problem and improve translational success, new methods are urgently needed that non-invasively measure the same ROS biomarker both in animal models and patients with high spatial resolution. Here, we summarize a transformative solution based on a novel method: QUEnch-assiSTed MRI (QUEST MRI). The QUEST MRI index is a significant antioxidant-induced improvement in pathophysiology, or a reduction in 1/T1 (i.e., R1). The latter form of QUEST MRI provides a unique measure of uncontrolled production of endogenous, paramagnetic reactive oxygen species (ROS). QUEST MRI results to-date have been validated by gold standard oxidative stress assays. QUEST MRI has high translational potential because it does not use an exogenous contrast agent and requires only standard MRI equipment. Summarizing, QUEST MRI is a powerful non-invasive approach with unprecedented potential for (i) bridging antioxidant treatment in animal models and patients, (ii) identifying tissue subregions exhibiting oxidative stress, and (iii) coupling oxidative stress localization with behavioral dysfunction, disease pathology, and genetic vulnerabilities to serve as a marker of susceptibility.

Magnetic Resonance Imaging (MRI) Safety

MedlinePlus

... News Physician Resources Professions Site Index A-Z Magnetic Resonance Imaging (MRI) Safety What is MRI and how does ... What is MRI and how does it work? Magnetic resonance imaging, or MRI, is a way of obtaining detailed ...

MRI Volume Fusion Based on 3D Shearlet Decompositions.

PubMed

Duan, Chang; Wang, Shuai; Wang, Xue Gang; Huang, Qi Hong

2014-01-01

Nowadays many MRI scans can give 3D volume data with different contrasts, but the observers may want to view various contrasts in the same 3D volume. The conventional 2D medical fusion methods can only fuse the 3D volume data layer by layer, which may lead to the loss of interframe correlative information. In this paper, a novel 3D medical volume fusion method based on 3D band limited shearlet transform (3D BLST) is proposed. And this method is evaluated upon MRI T2* and quantitative susceptibility mapping data of 4 human brains. Both the perspective impression and the quality indices indicate that the proposed method has a better performance than conventional 2D wavelet, DT CWT, and 3D wavelet, DT CWT based fusion methods.

Removal of intensity bias in magnitude spin-echo MRI images by nonlinear diffusion filtering

NASA Astrophysics Data System (ADS)

Samsonov, Alexei A.; Johnson, Chris R.

2004-05-01

MRI data analysis is routinely done on the magnitude part of complex images. While both real and imaginary image channels contain Gaussian noise, magnitude MRI data are characterized by Rice distribution. However, conventional filtering methods often assume image noise to be zero mean and Gaussian distributed. Estimation of an underlying image using magnitude data produces biased result. The bias may lead to significant image errors, especially in areas of low signal-to-noise ratio (SNR). The incorporation of the Rice PDF into a noise filtering procedure can significantly complicate the method both algorithmically and computationally. In this paper, we demonstrate that inherent image phase smoothness of spin-echo MRI images could be utilized for separate filtering of real and imaginary complex image channels to achieve unbiased image denoising. The concept is demonstrated with a novel nonlinear diffusion filtering scheme developed for complex image filtering. In our proposed method, the separate diffusion processes are coupled through combined diffusion coefficients determined from the image magnitude. The new method has been validated with simulated and real MRI data. The new method has provided efficient denoising and bias removal in conventional and black-blood angiography MRI images obtained using fast spin echo acquisition protocols.

Novel MRI tests of orocecal transit time and whole gut transit time: studies in normal subjects

PubMed Central

Chaddock, G; Lam, C; Hoad, C L; Costigan, C; Cox, E F; Placidi, E; Thexton, I; Wright, J; Blackshaw, P E; Perkins, A C; Marciani, L; Gowland, P A; Spiller, R C

2014-01-01

Background Colonic transit tests are used to manage patients with Functional Gastrointestinal Disorders. Some tests used expose patients to ionizing radiation. The aim of this study was to compare novel magnetic resonance imaging (MRI) tests for measuring orocecal transit time (OCTT) and whole gut transit time (WGT), which also provide data on colonic volumes. Methods 21 healthy volunteers participated. Study 1: OCTT was determined from the arrival of the head of a meal into the cecum using MRI and the Lactose Ureide breath test (LUBT), performed concurrently. Study 2: WGT was assessed using novel MRI marker capsules and radio-opaque markers (ROMs), taken on the same morning. Studies were repeated 1 week later. Key Results OCTT measured using MRI and LUBT was 225 min (IQR 180–270) and 225 min (IQR 165–278), respectively, correlation rs = 0.28 (ns). WGT measured using MRI marker capsules and ROMs was 28 h (IQR 4–50) and 31 h ± 3 (SEM), respectively, correlation rs = 0.85 (p < 0.0001). Repeatability assessed using the intraclass correlation coefficient (ICC) was 0.45 (p = 0.017) and 0.35 (p = 0.058) for MRI and LUBT OCTT tests. Better repeatability was observed for the WGT tests, ICC being 0.61 for the MRI marker capsules (p = 0.001) and 0.69 for the ROM method (p < 0.001) respectively. Conclusions & Inferences The MRI WGT method is simple, convenient, does not use X-ray and compares well with the widely used ROM method. Both OCTT measurements showed modest reproducibility and the MRI method showed modest inter-observer agreement. PMID:24165044

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

What approach to brain partial volume correction is best for PET/MRI?

NASA Astrophysics Data System (ADS)

Hutton, B. F.; Thomas, B. A.; Erlandsson, K.; Bousse, A.; Reilhac-Laborde, A.; Kazantsev, D.; Pedemonte, S.; Vunckx, K.; Arridge, S. R.; Ourselin, S.

2013-02-01

Many partial volume correction approaches make use of anatomical information, readily available in PET/MRI systems but it is not clear what approach is best. Seven novel approaches to partial volume correction were evaluated, including several post-reconstruction methods and several reconstruction methods that incorporate anatomical information. These were compared with an MRI-independent approach (reblurred van Cittert ) and uncorrected data. Monte Carlo PET data were generated for activity distributions representing both 18F FDG and amyloid tracer uptake. Post-reconstruction methods provided the best recovery with ideal segmentation but were particularly sensitive to mis-registration. Alternative approaches performed better in maintaining lesion contrast (unseen in MRI) with good noise control. These were also relatively insensitive to mis-registration errors. The choice of method will depend on the specific application and reliability of segmentation and registration algorithms.

MRI of retinoblastoma

PubMed Central

Razek, A A K A; Elkhamary, S

2011-01-01

We review the role of MRI in retinoblastoma and simulating lesions. Retinoblastoma is the most common paediatric intra-ocular tumour. It may be endophytic, exophytic or a diffuse infiltrating tumour. MRI can detect intra-ocular, extra-ocular and intracranial extension of the tumour. MRI is essential for monitoring patients after treatment and detection of associated second malignancies. It helps to differentiating the tumour from simulating lesions with leukocoria. PMID:21849363

Quantitative body DW-MRI biomarkers uncertainty estimation using unscented wild-bootstrap.

PubMed

Freiman, M; Voss, S D; Mulkern, R V; Perez-Rossello, J M; Warfield, S K

2011-01-01

We present a new method for the uncertainty estimation of diffusion parameters for quantitative body DW-MRI assessment. Diffusion parameters uncertainty estimation from DW-MRI is necessary for clinical applications that use these parameters to assess pathology. However, uncertainty estimation using traditional techniques requires repeated acquisitions, which is undesirable in routine clinical use. Model-based bootstrap techniques, for example, assume an underlying linear model for residuals rescaling and cannot be utilized directly for body diffusion parameters uncertainty estimation due to the non-linearity of the body diffusion model. To offset this limitation, our method uses the Unscented transform to compute the residuals rescaling parameters from the non-linear body diffusion model, and then applies the wild-bootstrap method to infer the body diffusion parameters uncertainty. Validation through phantom and human subject experiments shows that our method identify the regions with higher uncertainty in body DWI-MRI model parameters correctly with realtive error of -36% in the uncertainty values.

Impact of the MLC on the MRI field distortion of a prototype MRI-linac

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

Kolling, Stefan; Keall, Paul; Oborn, Brad

2013-12-15

Purpose: To cope with intrafraction tumor motion, integrated MRI-linac systems for real-time image guidance are currently under development. The multileaf collimator (MLC) is a key component in every state-of-the-art radiotherapy treatment system, allowing for accurate field shaping and tumor tracking. This work quantifies the magnetic impact of a widely used MLC on the MRI field homogeneity for such a modality.Methods: The finite element method was employed to model a MRI-linac assembly comprised of a 1.0 T split-bore MRI magnet and the key ferromagnetic components of a Varian Millennium 120 MLC, namely, the leaves and motors. Full 3D magnetic field maps ofmore » the system were generated. From these field maps, the peak-to-peak distortion within the MRI imaging volume was evaluated over a 30 cm diameter sphere volume (DSV) around the isocenter and compared to a maximum preshim inhomogeneity of 300 μT. Five parametric studies were performed: (1) The source-to-isocenter distance (SID) was varied from 100 to 200 cm, to span the range of a compact system to that with lower magnetic coupling. (2) The MLC model was changed from leaves only to leaves with motors, to determine the contribution to the total distortion caused by MLC leaves and motors separately. (3) The system was configured in the inline or perpendicular orientation, i.e., the linac treatment beam was oriented parallel or perpendicular to the magnetic field direction. (4) The treatment field size was varied from 0 × 0 to 20×20 cm{sup 2}, to span the range of clinical treatment fields. (5) The coil currents were scaled linearly to produce magnetic field strengths B{sub 0} of 0.5, 1.0, and 1.5 T, to estimate how the MLC impact changes with B{sub 0}.Results: (1) The MLC-induced MRI field distortion fell continuously with increasing SID. (2) MLC leaves and motors were found to contribute to the distortion in approximately equal measure. (3) Due to faster falloff of the fringe field, the field

A guide for effective anatomical vascularization studies: useful ex vivo methods for both CT and MRI imaging before dissection.

PubMed

Renard, Yohann; Hossu, Gabriela; Chen, Bailiang; Krebs, Marine; Labrousse, Marc; Perez, Manuela

2018-01-01

The objective of this study was to develop a simple and useful injection protocol for imaging cadaveric vascularization and dissection. Mixtures of contrast agent and cast product should provide adequate contrast for two types of ex vivo imaging (MRI and CT) and should harden to allow gross dissection of the injected structures. We tested the most popular contrast agents and cast products, and selected the optimal mixture composition based on their availability and ease of use. All mixtures were first tested in vitro to adjust dilution parameters of each contrast agent and to fine-tune MR imaging acquisition sequences. Mixtures were then injected in 24 pig livers and one human pancreas for MR and computed tomography (CT) imaging before anatomical dissection. Colorized latex, gadobutrol and barite mixture met the above objective. Mixtures composed of copper sulfate (CuSO 4 ) gadoxetic acid (for MRI) and iodine (for CT) gave an inhomogeneous signal or extravasation of the contrast agent. Agar did not harden sufficiently for gross dissection but appears useful for CT and magnetic resonance imaging (MRI) studies without dissection. Silicone was very hard to inject but achieved the goals of the study. Resin is particularly difficult to use but could replace latex as an alternative for corrosion instead of dissection. This injection protocol allows CT and MRI images to be obtained of cadaveric vascularization and anatomical casts in the same anatomic specimen. Post-imaging processing software allow easy 3D reconstruction of complex anatomical structures using this technique. Applications are numerous, e.g. surgical training, teaching methods, postmortem anatomic studies, pathologic studies, and forensic diagnoses. © 2017 Anatomical Society.

Fetal MRI versus postnatal imaging in the MR-compatible incubator.

PubMed

Bekiesinska-Figatowska, Monika; Romaniuk-Doroszewska, Anna; Duczkowska, Agnieszka; Duczkowski, Marek; Iwanowska, Beata; Szkudlińska-Pawlak, Sylwia

2016-09-01

One of the aims of fetal magnetic resonance imaging (MRI) is to avoid postnatal scanning. However, clinicians sometimes wish to have postnatal confirmation of prenatal findings. This study's purpose was to check whether there was indeed the added value of neonatal MRI performed in the MR-compatible incubator (INC) after fetal examination. Material consists of 25 neonates (14 girls) who underwent prenatal and postnatal MRI in a 1.5 T scanner, the latter in INC. Mean time of prenatal MRI was 30th gestational week, of postnatal MRI-16th day of life. In 14 cases (56 %) postnatal findings were the same as prenatal ones. In 11 (44 %) postnatal MRI showed some different/new/more precise results, in two the differences were attributed to other factors than the advantage of postnatal MRI over prenatal one. Altogether then postnatal results were partly discordant with prenatal ones in 9/25 cases (36 %). In most cases there was no added value of postnatal MRI as compared to prenatal one. This value lied in small details that could not have been noticed on prenatal MRI or required contrast medium administration to be noticed. On the other hand, MR examination performed with use of the dedicated neonatal coils in the MR-compatible incubator is a safe and reliable method of visualization of these small details with better spatial resolution thus helping to establish final diagnosis, treatment plan and prognosis.

Quantitative evaluation of polymer concentration profile during swelling of hydrophilic matrix tablets using 1H NMR and MRI methods.

PubMed

Baumgartner, Sasa; Lahajnar, Gojmir; Sepe, Ana; Kristl, Julijana

2005-02-01

Many pharmaceutical tablets are based on hydrophilic polymers, which, after exposure to water, form a gel layer around the tablet that limits the dissolution and diffusion of the drug and provides a mechanism for controlled drug release. Our aim was to determine the thickness of the swollen gel layer of matrix tablets and to develop a method for calculating the polymer concentration profile across the gel layer. MR imaging has been used to investigate the in situ swelling behaviour of cellulose ether matrix tablets and NMR spectroscopy experiments were performed on homogeneous hydrogels with known polymer concentration. The MRI results show that the thickest gel layer was observed for hydroxyethylcellulose tablets, followed by definitely thinner but almost equal gel layer for hydroxypropylcellulose and hydroxypropylmethylcellulose of both molecular weights. The water proton NMR relaxation parameters were combined with the MRI data to obtain a quantitative description of the swelling process on the basis of the concentrations and mobilities of water and polymer as functions of time and distance. The different concentration profiles observed after the same swelling time are the consequence of the different polymer characteristics. The procedure developed here could be used as a general method for calculating polymer concentration profiles on other similar polymeric systems.

Patient-Specific Pharmacokinetic Parameter Estimation on Dynamic Contrast-Enhanced MRI of Prostate: Preliminary Evaluation of a Novel AIF-Free Estimation Method

PubMed Central

Ginsburg, Shoshana B.; Taimen, Pekka; Merisaari, Harri; Vainio, Paula; Boström, Peter J.; Aronen, Hannu J.; Jambor, Ivan; Madabhushi, Anant

2017-01-01

Purpose To develop and evaluate a prostate-based method (PBM) for estimating pharmacokinetic parameters on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) by leveraging inherent differences in pharmacokinetic characteristics between the peripheral zone (PZ) and transition zone (TZ). Materials and Methods This retrospective study, approved by the Institutional Review Board, included 40 patients who underwent a multiparametric 3T MRI examination and subsequent radical prostatectomy. A two-step PBM for estimating pharmacokinetic parameters exploited the inherent differences in pharmacokinetic characteristics associated with the TZ and PZ. First, the reference region model was implemented to estimate ratios of Ktrans between normal TZ and PZ. Subsequently, the reference region model was leveraged again to estimate values for Ktrans and ve for every prostate voxel. The parameters of PBM were compared with those estimated using an arterial input function (AIF) derived from the femoral arteries. The ability of the parameters to differentiate prostate cancer (PCa) from benign tissue was evaluated on a voxel and lesion level. Additionally, the effect of temporal downsampling of the DCE MRI data was assessed. Results Significant differences (P < 0.05) in PBM Ktrans between PCa lesions and benign tissue were found in 26/27 patients with TZ lesions and in 33/38 patients with PZ lesions; significant differences in AIF-based Ktrans occurred in 26/27 and 30/38 patients, respectively. The 75th and 100th percentiles of Ktrans and ve estimated using PBM positively correlated with lesion size (P < 0.05). Conclusion Pharmacokinetic parameters estimated via PBM outperformed AIF-based parameters in PCa detection. PMID:27285161

Role of conventional radiology and MRi defecography of pelvic floor hernias

PubMed Central

2013-01-01

Background Purpose of the study is to define the role of conventional radiology and MRI in the evaluation of pelvic floor hernias in female pelvic floor disorders. Methods A MEDLINE and PubMed search was performed for journals before March 2013 with MeSH major terms 'MR Defecography' and 'pelvic floor hernias'. Results The prevalence of pelvic floor hernias at conventional radiology was higher if compared with that at MRI. Concerning the hernia content, there were significantly more enteroceles and sigmoidoceles on conventional radiology than on MRI, whereas, in relation to the hernia development modalities, the prevalence of elytroceles, edroceles, and Douglas' hernias at conventional radiology was significantly higher than that at MRI. Conclusions MRI shows lower sensitivity than conventional radiology in the detection of pelvic floor hernias development. The less-invasive MRI may have a role in a better evaluation of the entire pelvic anatomy and pelvic organ interaction especially in patients with multicompartmental defects, planned for surgery. PMID:24267789

Integrating EEG and fMRI in epilepsy.

PubMed

Formaggio, Emanuela; Storti, Silvia Francesca; Bertoldo, Alessandra; Manganotti, Paolo; Fiaschi, Antonio; Toffolo, Gianna Maria

2011-02-14

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear

WE-AB-BRA-09: Registration of Preoperative MRI to Intraoperative Radiographs for Automatic Vertebral Target Localization

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

De Silva, T; Uneri, A; Ketcha, M

Purpose: Accurate localization of target vertebrae is essential to safe, effective spine surgery, but wrong-level surgery occurs with surprisingly high frequency. Recent research yielded the “LevelCheck” method for 3D-2D registration of preoperative CT to intraoperative radiographs, providing decision support for level localization. We report a new method (MR-LevelCheck) to perform 3D-2D registration based on preoperative MRI, presenting a solution for the increasingly common scenario in which MRI (not CT) is used for preoperative planning. Methods: Direct extension of LevelCheck is confounded by large mismatch in image intensity between MRI and radiographs. The proposed method overcomes such challenges with a simplemore » vertebrae segmentation. Using seed points at centroids, vertebrae are segmented using continuous max-flow method and dilated by 1.8 mm to include surrounding cortical bone (inconspicuous in T2w-MRI). MRI projections are computed (analogous to DRR) using segmentation and registered to intraoperative radiographs. The method was tested in a retrospective IRB-approved study involving 11 patients undergoing cervical, thoracic, or lumbar spine surgery following preoperative MRI. Registration accuracy was evaluated in terms of projection-distance-error (PDE) between the true and estimated location of vertebrae in each radiograph. Results: The method successfully registered each preoperative MRI to intraoperative radiographs and maintained desirable properties of robustness against image content mismatch, and large capture range. Segmentation achieved Dice coefficient = 89.2 ± 2.3 and mean-absolute-distance (MAD) = 1.5 ± 0.3 mm. Registration demonstrated robust performance under realistic patient variations, with PDE = 4.0 ± 1.9 mm (median ± iqr) and converged with run-time = 23.3 ± 1.7 s. Conclusion: The MR-LevelCheck algorithm provides an important extension to a previously validated decision support tool in spine surgery by extending its