Health effects of lesion localization in multiple sclerosis

Spatial registration and confounding adjustment

Ani Eloyan, Haochang Shou, Russell T. Shinohara, Elizabeth M. Sweeney, Mary Beth Nebel, Jennifer L. Cuzzocreo, Peter Calabresi, Daniel S. Reich, Martin Lindquist, Ciprian M Crainiceanu

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article numbere107263
JournalPLoS One
Volume9
Issue number9
DOIs
StatePublished - Sep 18 2014

Fingerprint

sclerosis
lesions (animal)
Multiple Sclerosis
Health
Brain
Brain Diseases
Masks
Magnetic resonance imaging
Spatial distribution
Statistical Factor Analysis
brain
Population
adverse effects
spatial distribution
duration

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Health effects of lesion localization in multiple sclerosis : Spatial registration and confounding adjustment. / Eloyan, Ani; Shou, Haochang; Shinohara, Russell T.; Sweeney, Elizabeth M.; Nebel, Mary Beth; Cuzzocreo, Jennifer L.; Calabresi, Peter; Reich, Daniel S.; Lindquist, Martin; Crainiceanu, Ciprian M.

In: PLoS One, Vol. 9, No. 9, e107263, 18.09.2014.

Research output: Contribution to journalArticle

Eloyan, Ani ; Shou, Haochang ; Shinohara, Russell T. ; Sweeney, Elizabeth M. ; Nebel, Mary Beth ; Cuzzocreo, Jennifer L. ; Calabresi, Peter ; Reich, Daniel S. ; Lindquist, Martin ; Crainiceanu, Ciprian M. / Health effects of lesion localization in multiple sclerosis : Spatial registration and confounding adjustment. In: PLoS One. 2014 ; Vol. 9, No. 9.
@article{2d86b144f0ea4ebbada2aaab8bc93304,
title = "Health effects of lesion localization in multiple sclerosis: Spatial registration and confounding adjustment",
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.",
author = "Ani Eloyan and Haochang Shou and Shinohara, {Russell T.} and Sweeney, {Elizabeth M.} and Nebel, {Mary Beth} and Cuzzocreo, {Jennifer L.} and Peter Calabresi and Reich, {Daniel S.} and Martin Lindquist and Crainiceanu, {Ciprian M}",
year = "2014",
month = "9",
day = "18",
doi = "10.1371/journal.pone.0107263",
language = "English (US)",
volume = "9",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "9",

}

TY - JOUR

T1 - Health effects of lesion localization in multiple sclerosis

T2 - Spatial registration and confounding adjustment

AU - Eloyan, Ani

AU - Shou, Haochang

AU - Shinohara, Russell T.

AU - Sweeney, Elizabeth M.

AU - Nebel, Mary Beth

AU - Cuzzocreo, Jennifer L.

AU - Calabresi, Peter

AU - Reich, Daniel S.

AU - Lindquist, Martin

AU - Crainiceanu, Ciprian M

PY - 2014/9/18

Y1 - 2014/9/18

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84907212644&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84907212644&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0107263

DO - 10.1371/journal.pone.0107263

M3 - Article

VL - 9

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 9

M1 - e107263

ER -