Quantifying longitudinal tract profile differences in multiple sclerosis lesional tracts

Motivation: Region-of-interest analyses of quantitative MRI measures may overlook heterogeneity in tissue microstructure. Tract profiling shows greater detail but is difficult to quantify over time. Goal(s): Quantify differences in lesional tract profiles across two timepoints. Approach: Tract profiles associated with focal lesions of myelin water fraction (MWF) and fractional anisotropy (FA) were created in people with multiple sclerosis (MS) who were scanned at two timepoints twelve months apart. Two measures were proposed to quantify tract profile differences, and were correlated with expanded disability status scale (EDSS) scores. Results: The mean absolute difference in MWF between two timepoints along lesional MS tracts correlated with EDSS. Impact: Differences in lesional tract profiles of myelin water fraction and fractional anisotropy were quantified across two timepoints twelve months apart using two newly proposed measures in people with multiple sclerosis, and showed moderate correlations with clinical scores.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/3755
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantifying longitudinal tract profile differences in multiple sclerosis lesional tracts

Shannon Kolind, Poljanka Johnson, Anthony Traboulsee, Neale Wiley et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Medical Imaging and Analysis
article

Quantifying longitudinal tract profile differences in multiple sclerosis lesional tracts

Shannon Kolind, Poljanka Johnson, Anthony Traboulsee, Neale Wiley, Adrian Wu, Alex MacKay, Sharada Balaji, Irene Vavasour, Roger C. Tam, David Li, Jiwon Oh, Erin Gallinger
article en

Abstract

Motivation: Region-of-interest analyses of quantitative MRI measures may overlook heterogeneity in tissue microstructure. Tract profiling shows greater detail but is difficult to quantify over time. Goal(s): Quantify differences in lesional tract profiles across two timepoints. Approach: Tract profiles associated with focal lesions of myelin water fraction (MWF) and fractional anisotropy (FA) were created in people with multiple sclerosis (MS) who were scanned at two timepoints twelve months apart. Two measures were proposed to quantify tract profile differences, and were correlated with expanded disability status scale (EDSS) scores. Results: The mean absolute difference in MWF between two timepoints along lesional MS tracts correlated with EDSS. Impact: Differences in lesional tract profiles of myelin water fraction and fractional anisotropy were quantified across two timepoints twelve months apart using two newly proposed measures in people with multiple sclerosis, and showed moderate correlations with clinical scores.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 76%
Medical Imaging and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.