Automated Quantitative Susceptibility and Morphometry MR Study: Feasibility and Interrelation Between Clinical Score, Lesion Load, Deep Grey Matter and Normal-Appearing White Matter in Multiple Sclerosis

Fully automated brain morphometry and susceptibility monitoring is feasible in MS patients. The lesion load, thalamus and NAWM susceptibility values and trophicity are interrelated and correlate with disability.

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Publication Details

Journal
Diagnostics
Published
2024-11-27
DOI
https://doi.org/10.3390/diagnostics14232669
Primary Topic
Multiple Sclerosis Research Studies
Type
article
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article

Automated Quantitative Susceptibility and Morphometry MR Study: Feasibility and Interrelation Between Clinical Score, Lesion Load, Deep Grey Matter and Normal-Appearing White Matter in Multiple Sclerosis

Tom Hilbert, Gibran Manasseh, Mário João Fartaria, Vincent Dunet et al.
Diagnostics
Multiple Sclerosis Research Studies
article

Automated Quantitative Susceptibility and Morphometry MR Study: Feasibility and Interrelation Between Clinical Score, Lesion Load, Deep Grey Matter and Normal-Appearing White Matter in Multiple Sclerosis

Tom Hilbert, Gibran Manasseh, Mário João Fartaria, Vincent Dunet, Bénédicte Maréchal, Meritxell Bach Cuadra, Jérémy Deverdun, Tobias Kober
article en

Abstract

Fully automated brain morphometry and susceptibility monitoring is feasible in MS patients. The lesion load, thalamus and NAWM susceptibility values and trophicity are interrelated and correlate with disability.

DiagnosticsVol. 14(23)
Université de Montpellier (FR), Hôpital Gui de Chauliac (FR), Centre d'Imagerie BioMedicale (CH), Siemens (Switzerland) (CH), École Polytechnique Fédérale de Lausanne (CH), University of Lausanne (CH)
Openalex Percentile: Top 65%
Multiple Sclerosis Research Studies
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Automated Quantitative Susceptibility and Morphometry MR Study: Feasibility and Interrelation Between Clinical Score, Lesion Load, Deep Grey Matter and Normal-Appearing White Matter in Multiple Sclerosis — Tom Hilbert, Gibran Manasseh, et al. · Diagnostics (2024) | TGRS Research Map | TGRS