Synthesis of Double Inversion Recovery-like Images for Superior Contrast and Multiple Sclerosis Lesion Visibility

Motivation: Double Inversion Recovery (DIR) can enhance lesion detection, particularly in multiple sclerosis (MS) where juxtacortical and infratentorialplaques are challenging to detect with conventional techniques. Goal(s): This study evaluates DIR-like images(Syn-DIR) generated from T1 and T2 FLAIR for brain structure and lesion visibility Approach: The study evaluates 30 subjects to assess quantitative segmentation, volumetric consistency, and lesion-to-white-matter contrast. A second longitudinal study cohort assessed 20 additional subjects scanned at two time points to evaluate performance consistency over time. Results: Syn-DIR demonstrated high structural agreement to the reference set and showed significantly higher lesion-to-white matter contrast, with stable gray-to-white-matter contrast across time points. Impact: Syn-DIR provides superior lesion visibility and consistent brain structure representation. The strong agreement in quantitative lesion and regional brain volumes demonstrates its robustness for clinical and research applications.

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/10.58530/2025/3587
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

Synthesis of Double Inversion Recovery-like Images for Superior Contrast and Multiple Sclerosis Lesion Visibility

Xiang Lei, Lawrence Tanenbaum, Ajit Shankaranarayanan, Craig B. Arnold 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
Brain Tumor Detection and Classification
article

Synthesis of Double Inversion Recovery-like Images for Superior Contrast and Multiple Sclerosis Lesion Visibility

Xiang Lei, Lawrence Tanenbaum, Ajit Shankaranarayanan, Craig B. Arnold, Suzie Bash, Long Wang, Zechen Zhou
article en

Abstract

Motivation: Double Inversion Recovery (DIR) can enhance lesion detection, particularly in multiple sclerosis (MS) where juxtacortical and infratentorialplaques are challenging to detect with conventional techniques. Goal(s): This study evaluates DIR-like images(Syn-DIR) generated from T1 and T2 FLAIR for brain structure and lesion visibility Approach: The study evaluates 30 subjects to assess quantitative segmentation, volumetric consistency, and lesion-to-white-matter contrast. A second longitudinal study cohort assessed 20 additional subjects scanned at two time points to evaluate performance consistency over time. Results: Syn-DIR demonstrated high structural agreement to the reference set and showed significantly higher lesion-to-white matter contrast, with stable gray-to-white-matter contrast across time points. Impact: Syn-DIR provides superior lesion visibility and consistent brain structure representation. The strong agreement in quantitative lesion and regional brain volumes demonstrates its robustness for clinical and research applications.

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 68%
Brain Tumor Detection and Classification
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Synthesis of Double Inversion Recovery-like Images for Superior Contrast and Multiple Sclerosis Lesion Visibility — Xiang Lei, Lawrence Tanenbaum, 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 (2025) | TGRS Research Map | TGRS