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PLoS One. 2014 Sep 18;9(9):e107263. doi: 10.1371/journal.pone.0107263. eCollection 2014.

Health effects of lesion localization in multiple sclerosis: spatial registration and confounding adjustment.

Author information

1
Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America.
2
Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
3
Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America; Translational Neurology Unit, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America.
4
Laboratory for Neurocognitive and Imaging Research, Kennedy Krieger Institute, Baltimore, Maryland, United States of America; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
5
Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
6
Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
7
Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States of America; Translational Neurology Unit, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, United States of America; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America; Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.

Abstract

Brain lesion localization in multiple sclerosis (MS) is thought to be associated with the type and severity of adverse health effects. However, several factors hinder statistical analyses of such associations using large MRI datasets: 1) spatial registration algorithms developed for healthy individuals may be less effective on diseased brains and lead to different spatial distributions of lesions; 2) interpretation of results requires the careful selection of confounders; and 3) most approaches have focused on voxel-wise regression approaches. In this paper, we evaluated the performance of five registration algorithms and observed that conclusions regarding lesion localization can vary substantially with the choice of registration algorithm. Methods for dealing with confounding factors due to differences in disease duration and local lesion volume are introduced. Voxel-wise regression is then extended by the introduction of a metric that measures the distance between a patient-specific lesion mask and the population prevalence map.

PMID:
25233361
PMCID:
PMC4169434
DOI:
10.1371/journal.pone.0107263
[Indexed for MEDLINE]
Free PMC Article

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