Quantifying Cervical Spinal Cord Pathology of Multiple Sclerosis Using Oscillating Gradient Spin-echo DWI

Motivation: Spinal cord MRI has both diagnostic and prognostic value for multiple sclerosis (MS) patients. Several quantitative MRI biomarkers show high sensitivity to characterize MS lesions but lack pathological specificity. Time-dependent DWI may reveal microstructural features and pathological variations in MS. Goal(s): To explore diffusion time-dependence in the cervical spinal cord and its potential to quantify pathology of MSApproach: Optimized oscillating gradient spin-echo (OGSE) DTI were performed for healthy volunteers (N=18) and MS patients (N=17). Results: Diffusivities show time-dependence in the dorsal-columns and lateral-funiculis of healthy controls. The increase of RD in MS lesions is larger than healthy WM when diffusion time decreases. Impact: The time-dependence of diffusivities in the cervical spinal cord of healthy volunteers and MS patients are observed using optimized OGSE DWI sequences on a clinical scanner. This may reveal further insight into the microstructural differences and pathological variations in MS.

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
2024-11-26
DOI
https://doi.org/10.58530/2024/0110
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantifying Cervical Spinal Cord Pathology of Multiple Sclerosis Using Oscillating Gradient Spin-echo DWI

Diwei Shi, Junzhong Xu, Xianchang Zhang, Yi Xiao 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
Advanced MRI Techniques and Applications
article

Quantifying Cervical Spinal Cord Pathology of Multiple Sclerosis Using Oscillating Gradient Spin-echo DWI

Diwei Shi, Junzhong Xu, Xianchang Zhang, Yi Xiao, Mangsuo Zhao, Yuqi Zhang, Sisi Li, Hua Guo, Yishi Wang, Fan Liu
article en

Abstract

Motivation: Spinal cord MRI has both diagnostic and prognostic value for multiple sclerosis (MS) patients. Several quantitative MRI biomarkers show high sensitivity to characterize MS lesions but lack pathological specificity. Time-dependent DWI may reveal microstructural features and pathological variations in MS. Goal(s): To explore diffusion time-dependence in the cervical spinal cord and its potential to quantify pathology of MSApproach: Optimized oscillating gradient spin-echo (OGSE) DTI were performed for healthy volunteers (N=18) and MS patients (N=17). Results: Diffusivities show time-dependence in the dorsal-columns and lateral-funiculis of healthy controls. The increase of RD in MS lesions is larger than healthy WM when diffusion time decreases. Impact: The time-dependence of diffusivities in the cervical spinal cord of healthy volunteers and MS patients are observed using optimized OGSE DWI sequences on a clinical scanner. This may reveal further insight into the microstructural differences and pathological variations in MS.

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
Good health and well-being
Openalex Percentile: Top 62%
Advanced MRI Techniques and Applications
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.