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Gradient distortions in MRI: Characterizing and correcting for their effects on SIENA-generated measures of brain volume change

Zografos Caramanos, Vladimir S. Fonov, Simon J. Francis, Sridar Narayanan, G. Bruce Pike, D. Louis Collins, Douglas L. Arnold
2010 NeuroImage  
We used a novel DUPLO-based phantom to develop a spherical-harmonics-based gradient distortion field that was used to (i) correct for observed Z-shift-associated gradient distortion effects on SIENA-generated  ...  We also found that, if not corrected for, the gradient distortion effects associated with such Z-shifts can significantly decrease the accuracy and precision of MRI-derived measures of whole-brain atrophynegative  ...  Ron Lopez, and Ms. Louise Marcotte, for their help in setting up the acquisition protocols and acquiring the MRI data; (iii) Mr.  ... 
doi:10.1016/j.neuroimage.2009.08.008 pmid:19682586 fatcat:v7pvo6qti5btfnyruktma7wte4

Radiotherapy planning using MRI

Maria A Schmidt, Geoffrey S Payne
2015 Physics in Medicine and Biology  
distortions in MRI: characterizing and correcting for their effects on SIENA-generated measures of brain volume change Neuroimage 49 1601-11 Chang H and Fitzpatrick J M 1992 A technique for accurate magnetic  ...  and susceptibility effects in MRI-simulation and measurement of spatial accuracy Int.  ...  The authors wish to thank Dr Vibeke Hansen, Dr Margaret Bidmead and staff in the departments of Radiotherapy and Radiology, in particular the following: Chris South (  ... 
doi:10.1088/0031-9155/60/22/r323 pmid:26509844 pmcid:PMC5137785 fatcat:i43hzqxdafhvtck2pblilloirq

Brain MRI atrophy quantification in MS

Maria A. Rocca, Marco Battaglini, Ralph H.B. Benedict, Nicola De Stefano, Jeroen J.G. Geurts, Roland G. Henry, Mark A. Horsfield, Mark Jenkinson, Elisabetta Pagani, Massimo Filippi
2016 Neurology  
Atrophy can be measured from brain MRI scans, and many technological improvements have been made over the last few years.  ...  Current methods provide sufficient precision for cohort studies, but are not adequate for confidently assessing changes in individual patients over the scale of months or a few years.  ...  should also be paid to correction of the effects of gradient distortion.  ... 
doi:10.1212/wnl.0000000000003542 pmid:27986875 pmcid:PMC5272969 fatcat:mujeaqh6kbfi7fc6czfrufd5tq

An automated algorithm for the computation of brain volume change from sequential MRIs using an iterative principal component analysis and its evaluation for the assessment of whole-brain atrophy rates in patients with probable Alzheimer's disease

Kewei Chen, Eric M Reiman, Gene E Alexander, Daniel Bandy, Rosemary Renaut, William R Crum, Nick C Fox, Martin N Rossor
2004 NeuroImage  
the disease-modifying effects of putative treatments, and investigating the course of other normal and pathological changes in brain morphology. D 2004 Elsevier Inc. All rights reserved.  ...  Acknowledgments This work was funded in part by the Arizona Alzheimer's Research Center, the National Institute of Mental Health (grant MH57899 to EMR), and the National Institute on Aging (Alzheimer's  ...  Lawrence Mayer and Dr. Richard Gerkin for their statistical advice.  ... 
doi:10.1016/j.neuroimage.2004.01.002 pmid:15110003 fatcat:evoe7bwl45bxln467gp5f5mpda

Progression of MRI markers in cerebral small vessel disease: Sample size considerations for clinical trials

Philip Benjamin, Eva Zeestraten, Christian Lambert, Irina Chis Ster, Owen A Williams, Andrew J Lawrence, Bhavini Patel, Andrew D MacKinnon, Thomas R Barrick, Hugh S Markus
2015 Journal of Cerebral Blood Flow and Metabolism  
We evaluated the change in brain volume, T2 white matter hyperintensity (WMH) volume, lacunes, and white matter damage on diffusion tensor imaging (DTI).  ...  Over 3 years, change was detectable in all MRI markers but not in cognitive measures. WMH volume and DTI parameters were most sensitive to change and therefore had the smallest sample size estimates.  ...  Acknowledgement The authors thank Dr Lalit Kalra and Dr Tony Rudd for help with recruitment. The authors also thank Dr Thomas Willis for assistance with neuropsychologic assessment.  ... 
doi:10.1038/jcbfm.2015.113 pmid:26036939 pmcid:PMC4758545 fatcat:hfon75emvfaiza5ottt5t6udne

Symmetric diffeomorphic modeling of longitudinal structural MRI

John Ashburner
2013 Frontiers in Neuroscience  
Emphasis is placed on achieving internal consistency and accounting for many of the mathematical subtleties that most implementations overlook.  ...  seen in MRI data.  ...  Longitudinal anatomical MRI provides a framework for characterizing many of the macroscopic brain changes in natural development and in response to disease or injury.  ... 
doi:10.3389/fnins.2012.00197 pmid:23386806 pmcid:PMC3564017 fatcat:u567p5nw7fgshmzohfpktxmfuy

Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease

François De Guio, Eric Jouvent, Geert Jan Biessels, Sandra E Black, Carol Brayne, Christopher Chen, Charlotte Cordonnier, Frank-Eric De Leeuw, Martin Dichgans, Fergus Doubal, Marco Duering, Carole Dufouil (+29 others)
2016 Journal of Cerebral Blood Flow and Metabolism  
Abstract (200 words) Brain imaging is essential for the diagnosis and characterization of cerebral small vessel disease (SVD).  ...  This review focuses on the main SVD-related markers on MRI including: white matter hyperintensities, lacunes, dilated perivascular spaces, microbleeds and brain volume.  ...  The authors declare no conflict of interest. Supplementary material for this paper can be found at http://jcbfm.sagepub.com/content/by/supplemental-data  ... 
doi:10.1177/0271678x16647396 pmid:27170700 pmcid:PMC4976752 fatcat:62yvvbsgorgnbnlgv6v3w3j3bu

Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis

H. Vrenken, M. Jenkinson, M. A. Horsfield, M. Battaglini, R. A. van Schijndel, E. Rostrup, J. J. G. Geurts, E. Fisher, A. Zijdenbos, J. Ashburner, D. H. Miller, M. Filippi (+5 others)
2012 Journal of Neurology  
Based on open issues in the field of MS research, and the current state of the art in magnetic resonance image analysis methods for assessing brain lesion load and atrophy, this paper makes recommendations  ...  Improved accuracy and sensitivity will reduce the numbers of patients required to detect a given treatment effect in a trial, and ultimately, will allow reliable characterization of individual patients  ...  In healthy subjects with a mean age of 56.5 years, Takao et al. [93] investigated the effect of scanner performance on whole-brain and local volume change measurement.  ... 
doi:10.1007/s00415-012-6762-5 pmid:23263472 pmcid:PMC3824277 fatcat:s727aflyjrcrpip7d3nuissbhq

The comorbidity and cognition in multiple sclerosis (CCOMS) neuroimaging protocol: Study rationale, MRI acquisition, and minimal image processing pipelines

Md Nasir Uddin, Teresa D. Figley, Jennifer Kornelsen, Erin L. Mazerolle, Carl A. Helmick, Christopher B. O'Grady, Salina Pirzada, Ronak Patel, Sean Carter, Kaihim Wong, Marco R. Essig, Lesley A. Graff (+6 others)
2022 Frontiers in Neuroimaging  
of brain structure and function, including changes over time.  ...  cognitive changes and their association with comorbidities among persons with multiple sclerosis (MS).  ...  Xiufeng Li (University of Minnesota) for sharing the multi-band pCASL sequence, Dr. Edward Auerbach and all  ... 
doi:10.3389/fnimg.2022.970385 fatcat:n7rmuikp4vfmhkuf4mjmnni674

The impact of customized head molds on motion and motion-related artifacts from structural and functional MRI scans in children [article]

Timothy Weng, Ruben Vela, Wade Weber, Manwitha Dodla, Anibal Solon Heinsfeld, Samuel Parker, Blake Simon, Damion Demeter, Tehila Nugiel, Lucy Whitmore, Kathryn Mills, Jessica Church (+2 others)
2021 medRxiv   pre-print
Although neuroimaging provides powerful tools for assessing brain structure and function, their utility for elucidating mechanisms underlying neuropsychiatric disorders is limited by their sensitivity  ...  As such there is a continued need to explore and evaluate novel methods for reducing head motion, and their applicability in these populations.  ...  Eddy currents generated by quickly switching diffusion gradients on and off will induce geometric distortions in the data that can be exacerbated by head motion.  ... 
doi:10.1101/2021.03.24.21253213 fatcat:pdxsjemktbflpomoroksudfixu

Evaluation of brain atrophy estimation algorithms using simulated ground-truth data

S. Sharma, V. Noblet, F. Rousseau, F. Heitz, L. Rumbach, J.-P. Armspach
2010 Medical Image Analysis  
A number of analysis tools have been developed for the estimation of brain atrophy using MRI.  ...  Using these gold standards, an evaluation of the performance of three standard brain atrophy estimation methods (SIENA, SIENAX and BSI-UCD), on the basis of their robustness to various sources of error  ...  We are thankful to Alsace Region and ARSEP for supporting this study. We also thank Dr. Evan Fletcher (University of California, Davis) for his support on the BSI-UCD software.  ... 
doi:10.1016/j.media.2010.02.002 pmid:20219411 fatcat:txytawsghjetrl6fojzfatz66u

Mapping Alzheimer's disease progression in 1309 MRI scans: Power estimates for different inter-scan intervals

Xue Hua, Suh Lee, Derrek P. Hibar, Igor Yanovsky, Alex D. Leow, Arthur W. Toga, Clifford R. Jack, Matt A. Bernstein, Eric M. Reiman, Danielle J. Harvey, John Kornak, Norbert Schuff (+3 others)
2010 NeuroImage  
Recently, automated brain mapping methods, such as tensor-based morphometry (TBM) of structural MRI, have outperformed cognitive measures in their precision and power to track disease progression, greatly  ...  In the largest TBM study to date, we studied how sample size estimates for tracking structural brain changes depend on the time interval between the scans (6-24 months).  ...  ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott, AstraZeneca AB, Bayer  ... 
doi:10.1016/j.neuroimage.2010.01.104 pmid:20139010 pmcid:PMC2846999 fatcat:6djsyuu7wfbrnlgkw2k4xtudae

Automated structural imaging analysis detects premanifest Huntington's disease neurodegeneration within 1 year

D.S. Adnan Majid, Diederick Stoffers, Sarah Sheldon, Samar Hamza, Wesley K. Thompson, Jody Goldstein, Jody Corey-Bloom, Adam R. Aron
2011 Movement Disorders  
We used the SIENA software tool (Structural Image Evaluation, using Normalization, of Atrophy) to yield overall Percentage Brain Volume Change (PBVC) and voxel-level changes in atrophy.  ...  Conclusions-Automated whole-brain analysis of structural MRI can reliably detect preHD disease progression over one year.  ...  We thank Anders Dale and Matt Erhart for technical assistance with image preprocessing.  ... 
doi:10.1002/mds.23656 pmid:21484871 pmcid:PMC3136652 fatcat:qc32qzsw3jfzjbu6jmyvcvjmva

Agreement of MSmetrix with established methods for measuring cross-sectional and longitudinal brain atrophy

Martijn D. Steenwijk, Houshang Amiri, Menno M. Schoonheim, Alexandra de Sitter, Frederik Barkhof, Petra J.W. Pouwels, Hugo Vrenken
2017 NeuroImage: Clinical  
The mean difference percentage brain volume change (PBVC) was lowest between longitudinal MSmetrix and SIENA (+ 0.16 ± 0.91%).  ...  In this subgroup, we additionally analyzed the whole-brain and GM volume change using the longitudinal pipeline of MSmetrix and compared the results with those of FreeSurfer (longitudinal pipeline) and  ...  Prior to measuring atrophy, all image data was anonymized, corrected for geometric distortions due to gradient non-linearities, and converted to nifti file format.  ... 
doi:10.1016/j.nicl.2017.06.034 pmid:28794970 pmcid:PMC5540882 fatcat:lsgvfselnjdg7dilkzc23yoibu

Predicting Alzheimer's disease by classifying 3D-Brain MRI images using SVM and other well-defined classifiers

S Matoug, A Abdel-Dayem, K Passi, W Gross, M Alqarni
2012 Journal of Physics, Conference Series  
Advanced medical imaging such as the volumetric MRI can detect changes in the size of brain regions due to the loss of the brain tissues.  ...  We discuss an automatic scheme that reads volumetric MRI, extracts the middle slices of the brain region, performs 2-dimensional (volume slices) and volumetric segmentation methods in order to segment  ...  of 3D MRI volumes.  ... 
doi:10.1088/1742-6596/341/1/012019 fatcat:niplou5avndppjjswtyeka2qfq
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