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Magnetization Transfer MRI of Breast Cancer in the Community Setting: Reproducibility and Preliminary Results in Neoadjuvant Therapy.
Virostko J, Sorace AG, Wu C, Ekrut D, Jarrett AM, Upadhyaya RM, Avery S, Patt D, Goodgame B, Yankeelov TE
(2019) Tomography 5: 44-52
MeSH Terms: Adult, Breast, Breast Neoplasms, Community Health Centers, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Middle Aged, Neoadjuvant Therapy, Neoplasm, Residual, Pilot Projects, Reproducibility of Results, Treatment Outcome
Show Abstract · Added March 25, 2019
Repeatability and reproducibility of magnetization transfer magnetic resonance imaging of the breast, and the ability of this technique to assess the response of locally advanced breast cancer to neoadjuvant therapy (NAT), are determined. Reproducibility scans at 3 different 3 T scanners, including 2 scanners in community imaging centers, found a 16.3% difference (n = 3) in magnetization transfer ratio (MTR) in healthy breast fibroglandular tissue. Repeatability scans (n = 10) found a difference of ∼8.1% in the MTR measurement of fibroglandular tissue between the 2 measurements. Thus, MTR is repeatable and reproducible in the breast and can be integrated into community imaging clinics. Serial magnetization transfer magnetic resonance imaging performed at longitudinal time points during NAT indicated no significant change in average tumoral MTR during treatment. However, histogram analysis indicated an increase in the dispersion of MTR values of the tumor during NAT, as quantified by higher standard deviation ( = .005), higher full width at half maximum ( = .02), and lower kurtosis ( = .02). Patients' stratification into those with pathological complete response (pCR; n = 6) at the conclusion of NAT and those with residual disease (n = 9) showed wider distribution of tumor MTR values in patients who achieved pCR after 2-4 cycles of NAT, as quantified by higher standard deviation ( = .02), higher full width at half maximum ( = .03), and lower kurtosis ( = .03). Thus, MTR can be used as an imaging metric to assess response to breast NAT.
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14 MeSH Terms
Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs.
Keenan KE, Biller JR, Delfino JG, Boss MA, Does MD, Evelhoch JL, Griswold MA, Gunter JL, Hinks RS, Hoffman SW, Kim G, Lattanzi R, Li X, Marinelli L, Metzger GJ, Mukherjee P, Nordstrom RJ, Peskin AP, Perez E, Russek SE, Sahiner B, Serkova N, Shukla-Dave A, Steckner M, Stupic KF, Wilmes LJ, Wu HH, Zhang H, Jackson EF, Sullivan DC
(2019) J Magn Reson Imaging 49: e26-e39
MeSH Terms: Anthropometry, Breast, Decision Making, Deep Learning, Equipment Design, Female, Humans, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Phantoms, Imaging, Precision Medicine, Radiology, Interventional, Reference Standards, Reference Values, Reproducibility of Results, Robotics, Software
Show Abstract · Added March 5, 2020
LEVEL OF EVIDENCE - 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.
© 2019 International Society for Magnetic Resonance in Medicine.
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19 MeSH Terms
Calcium Scoring for Cardiovascular Computed Tomography: How, When and Why?
Carr JJ
(2019) Radiol Clin North Am 57: 1-12
MeSH Terms: Cardiac-Gated Imaging Techniques, Cardiomyopathies, Coronary Artery Disease, Disease Progression, Humans, Radiographic Image Interpretation, Computer-Assisted, Risk Assessment, Tomography, X-Ray Computed
Show Abstract · Added January 10, 2020
Cardiovascular disease is the leading cause of death in the United States and worldwide. Despite major advances in the treatment of acute myocardial infarction, enhanced prevention of ischemic heart disease remains critical to improving the health of individuals and communities. The computed tomographic coronary artery calcium score is an established imaging biomarker that identifies the presence and amount of coronary atherosclerosis in an individual and their future risk for clinical cardiovascular disease and premature cardiovascular death. This article describes the process of performing a computed tomography scan for coronary artery calcium, quantifying the score and interpreting the results.
Copyright © 2018 Elsevier Inc. All rights reserved.
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A practical protocol for measurements of spinal cord functional connectivity.
Barry RL, Conrad BN, Smith SA, Gore JC
(2018) Sci Rep 8: 16512
MeSH Terms: Adult, Female, Healthy Volunteers, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Models, Neurological, Rest, Spinal Cord, Young Adult
Show Abstract · Added March 26, 2019
Resting state functional magnetic resonance imaging (fMRI) has been used to study human brain function for over two decades, but only recently has this technique been successfully translated to the human spinal cord. The spinal cord is structurally and functionally unique, so resting state fMRI methods developed and optimized for the brain may not be appropriate when applied to the cord. This report therefore investigates the relative impact of different acquisition and processing choices (including run length, echo time, and bandpass filter width) on the detectability of resting state spinal cord networks at 3T. Our results suggest that frequencies beyond 0.08 Hz should be included in resting state analyses, a run length of ~8-12 mins is appropriate for reliable detection of the ventral (motor) network, and longer echo times - yet still shorter than values typically used for fMRI in the brain - may increase the detectability of the dorsal (sensory) network. Further studies are required to more fully understand and interpret the nature of resting state spinal cord networks in health and in disease, and the protocols described in this report are designed to assist such studies.
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11 MeSH Terms
TRACE: A Topological Graph Representation for Automatic Sulcal Curve Extraction.
Lyu I, Kim SH, Woodward ND, Styner MA, Landman BA
(2018) IEEE Trans Med Imaging 37: 1653-1663
MeSH Terms: Algorithms, Brain Mapping, Cerebral Cortex, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male
Show Abstract · Added January 31, 2020
A proper geometric representation of the cortical regions is a fundamental task for cortical shape analysis and landmark extraction. However, a significant challenge has arisen due to the highly variable, convoluted cortical folding patterns. In this paper, we propose a novel topological graph representation for automatic sulcal curve extraction (TRACE). In practice, the reconstructed surface suffers from noise influences introduced during image acquisition/surface reconstruction. In the presence of noise on the surface, TRACE determines stable sulcal fundic regions by employing the line simplification method that prevents the sulcal folding pattern from being significantly smoothed out. The sulcal curves are then traced over the connected graph in the determined regions by the Dijkstra's shortest path algorithm. For validation, we used the state-of-the-art surface reconstruction pipelines on a reproducibility data set. The experimental results showed higher reproducibility and robustness to noise in TRACE than the existing method (Li et al. 2010) with over 20% relative improvement in error for both surface reconstruction pipelines. In addition, the extracted sulcal curves by TRACE were well-aligned with manually delineated primary sulcal curves. We also provided a choice of parameters to control quality of the extracted sulcal curves and showed the influences of the parameter selection on the resulting curves.
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Assessment of renal fibrosis in murine diabetic nephropathy using quantitative magnetization transfer MRI.
Wang F, Katagiri D, Li K, Takahashi K, Wang S, Nagasaka S, Li H, Quarles CC, Zhang MZ, Shimizu A, Gore JC, Harris RC, Takahashi T
(2018) Magn Reson Med 80: 2655-2669
MeSH Terms: Animals, Diabetic Nephropathies, Fibrosis, Image Interpretation, Computer-Assisted, Kidney, Magnetic Resonance Imaging, Mice, Mice, Inbred C57BL, Nitric Oxide Synthase Type III, Normal Distribution, Reproducibility of Results
Show Abstract · Added June 1, 2018
PURPOSE - Renal fibrosis is a hallmark of progressive renal disease; however, current clinical tests are insufficient for assessing renal fibrosis. Here we evaluated the utility of quantitative magnetization transfer MRI in detecting renal fibrosis in a murine model of progressive diabetic nephropathy (DN).
METHODS - The db/db eNOS-/- mice, a well-recognized model of progressive DN, and normal wild-type mice were imaged at 7T. The quantitative magnetization transfer data were collected in coronal plane using a 2D magnetization transfer prepared spoiled gradient echo sequence with a Gaussian-shaped presaturation pulse. Parameters were derived using a two-pool fitting model. A normal range of cortical pool size ratio (PSR) was defined as Mean±2SD of wild-type kidneys (N = 20). The cortical regions whose PSR values exceeded this threshold (threshold PSR) were assessed. The correlations between the PSR-based and histological (collagen IV or picrosirius red stain) fibrosis measurements were evaluated.
RESULTS - Compared with wild-type mice, moderate increases in mean PSR values and scattered clusters of high PSR region were observed in cortex of DN mouse kidneys. Abnormally high PSR regions (% area) that were detected by the threshold PSR were significantly increased in renal cortexes of DN mice. These regions progressively increased on aging and highly correlated with histological fibrosis measures, while the mean PSR values correlated much less.
CONCLUSION - Renal fibrosis in DN can be assessed by the quantitative magnetization transfer MRI and threshold analysis. This technique may be used as a novel imaging biomarker for DN and other renal diseases.
© 2018 International Society for Magnetic Resonance in Medicine.
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11 MeSH Terms
Chemical exchange rotation transfer (CERT) on human brain at 3 Tesla.
Lin EC, Li H, Zu Z, Louie EA, Lankford CL, Dortch RD, Does MD, Gore JC, Gochberg DF
(2018) Magn Reson Med 80: 2609-2617
MeSH Terms: Adult, Algorithms, Brain, Brain Mapping, Brain Neoplasms, Computer Simulation, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Models, Statistical, Protons, Rotation
Show Abstract · Added October 24, 2018
PURPOSE - To test the ability of a novel pulse sequence applied in vivo at 3 Tesla to separate the contributions to the water signal from amide proton transfer (APT) and relayed nuclear Overhauser enhancement (rNOE) from background direct water saturation and semisolid magnetization transfer (MT). The lack of such signal source isolation has confounded conventional chemical exchange saturation transfer (CEST) imaging.
METHODS - We quantified APT and rNOE signals using a chemical exchange rotation transfer (CERT) metric, MTR . A range of duty cycles and average irradiation powers were applied, and results were compared with conventional CEST analyses using asymmetry (MTR ) and extrapolated magnetization transfer (EMR).
RESULTS - Our results indicate that MTR is more specific than MTR and, because it requires as few as 3 data points, is more rapid than methods requiring a complete Z-spectrum, such as EMR. In white matter, APT (1.5 ± 0.5%) and rNOE (2.1 ± 0.7%) were quantified by using MTR with a 30% duty cycle and a 0.5-µT average power. In addition, our results suggest that MTR is insensitive to B inhomogeneity, further magnifying its speed advantage over CEST metrics that require a separate B measurement. However, MTR still has nontrivial sensitivity to B inhomogeneities.
CONCLUSION - We demonstrated that MTR is an alternative metric to evaluate APT and rNOE, which is fast, robust to B inhomogeneity, and easy to process.
© 2018 International Society for Magnetic Resonance in Medicine.
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15 MeSH Terms
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images.
Saltz J, Gupta R, Hou L, Kurc T, Singh P, Nguyen V, Samaras D, Shroyer KR, Zhao T, Batiste R, Van Arnam J, Cancer Genome Atlas Research Network, Shmulevich I, Rao AUK, Lazar AJ, Sharma A, Thorsson V
(2018) Cell Rep 23: 181-193.e7
MeSH Terms: Deep Learning, Humans, Image Interpretation, Computer-Assisted, Lymphocytes, Tumor-Infiltrating, Neoplasms
Show Abstract · Added October 30, 2019
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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Exact Topological Inference for Paired Brain Networks Persistent Homology.
Chung MK, Vilalta-Gil V, Lee H, Rathouz PJ, Lahey BB, Zald DH
(2017) Inf Process Med Imaging 2017: 299-310
MeSH Terms: Algorithms, Brain, Brain Mapping, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity
Show Abstract · Added March 21, 2018
We present a novel framework for characterizing paired brain networks using techniques in hyper-networks, sparse learning and persistent homology. The framework is general enough for dealing with any type of paired images such as twins, multimodal and longitudinal images. The exact nonparametric statistical inference procedure is derived on testing monotonic graph theory features that do not rely on time consuming permutation tests. The proposed method computes the exact probability in quadratic time while the permutation tests require exponential time. As illustrations, we apply the method to simulated networks and a twin fMRI study. In case of the latter, we determine the statistical significance of the heritability index of the large-scale reward network where every voxel is a network node.
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9 MeSH Terms
Pool size ratio of the substantia nigra in Parkinson's disease derived from two different quantitative magnetization transfer approaches.
Trujillo P, Summers PE, Smith AK, Smith SA, Mainardi LT, Cerutti S, Claassen DO, Costa A
(2017) Neuroradiology 59: 1251-1263
MeSH Terms: Aged, Biomarkers, Case-Control Studies, Female, Humans, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Male, Middle Aged, Parkinson Disease, Sensitivity and Specificity, Substantia Nigra
Show Abstract · Added March 30, 2020
PURPOSE - We sought to measure quantitative magnetization transfer (qMT) properties of the substantia nigra pars compacta (SNc) in patients with Parkinson's disease (PD) and healthy controls (HCs) using a full qMT analysis and determine whether a rapid single-point measurement yields equivalent results for pool size ratio (PSR).
METHODS - Sixteen different MT-prepared MRI scans were obtained at 3 T from 16 PD patients and eight HCs, along with B1, B0, and relaxation time maps. Maps of PSR, free and macromolecular pool transverse relaxation times ([Formula: see text], [Formula: see text]) and rate of MT exchange between pools (k ) were generated using a full qMT model. PSR maps were also generated using a single-point qMT model requiring just two MT-prepared images. qMT parameter values of the SNc, red nucleus, cerebral crus, and gray matter were compared between groups and methods.
RESULTS - PSR of the SNc was the only qMT parameter to differ significantly between groups (p < 0.05). PSR measured via single-point analysis was less variable than with the full MT model, provided slightly better differentiation of PD patients from HCs (area under curve 0.77 vs. 0.75) with sensitivity of 0.75 and specificity of 0.87, and was better than transverse relaxation time in distinguishing PD patients from HCs (area under curve 0.71, sensitivity 0.87, and specificity 0.50).
CONCLUSION - The increased PSR observed in the SNc of PD patients may provide a novel biomarker of PD, possibly associated with an increased macromolecular content. Single-point PSR mapping with reduced variability and shorter scan times relative to the full qMT model appears clinically feasible.
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