Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls

IntroductionThis study investigates whether a multi-shell diffusion tensor imaging (DTI) protocol and its subsets can reliably distinguish healthy controls (HC) from patients with multiple sclerosis (MS) presenting with low Expanded Disability Status Scale (EDSS) scores and mild MRI findings.Methods...

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Main Authors: Artur Tadeusz Krzyzak, Julia Lasek, Agnieszka Slowik
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Neurology
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Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1618582/full
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author Artur Tadeusz Krzyzak
Artur Tadeusz Krzyzak
Julia Lasek
Julia Lasek
Agnieszka Slowik
author_facet Artur Tadeusz Krzyzak
Artur Tadeusz Krzyzak
Julia Lasek
Julia Lasek
Agnieszka Slowik
author_sort Artur Tadeusz Krzyzak
collection DOAJ
description IntroductionThis study investigates whether a multi-shell diffusion tensor imaging (DTI) protocol and its subsets can reliably distinguish healthy controls (HC) from patients with multiple sclerosis (MS) presenting with low Expanded Disability Status Scale (EDSS) scores and mild MRI findings.MethodsTo enhance accuracy, spatial systematic errors in diffusion measurements were corrected using the B-matrix Spatial Distribution method (BSD-DTI). We examined the discriminative potential of fractional anisotropy (FA) and mean diffusivity (MD) across three broad brain regions: whole brain (WB), white matter (WM), and gray matter (GM), using both the full protocol and its subsets. Additionally, we employed a more detailed classification strategy based on segmentation into 95 regions of interest (ROIs), analyzing FA, MD, axial diffusivity (AD), and radial diffusivity (RD) under a stringent statistical criterion.ResultsWhile the protocol and each subset showed a comparable ability to differentiate between HC and MS groups, substantial variability in metric values across protocols highlights the limited utility of directly comparing DTI metrics between acquisition schemes.DiscussionThe results emphasize the importance of accounting for spatial systematic errors when selecting optimal protocols for clinical and research applications.
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spelling doaj-art-bf37f9b0d789403395570b7eb9c5fc4f2025-08-20T02:46:13ZengFrontiers Media S.A.Frontiers in Neurology1664-22952025-07-011610.3389/fneur.2025.16185821618582Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controlsArtur Tadeusz Krzyzak0Artur Tadeusz Krzyzak1Julia Lasek2Julia Lasek3Agnieszka Slowik4AGH University of Krakow, Kraków, PolandThe LaTiS NMR - Tomography and Spectroscopy Laboratory, Kraków, PolandAGH University of Krakow, Kraków, PolandThe LaTiS NMR - Tomography and Spectroscopy Laboratory, Kraków, PolandDepartment of Neurology, Jagiellonian University Medical College, University Hospital in Krakow, Krakow, PolandIntroductionThis study investigates whether a multi-shell diffusion tensor imaging (DTI) protocol and its subsets can reliably distinguish healthy controls (HC) from patients with multiple sclerosis (MS) presenting with low Expanded Disability Status Scale (EDSS) scores and mild MRI findings.MethodsTo enhance accuracy, spatial systematic errors in diffusion measurements were corrected using the B-matrix Spatial Distribution method (BSD-DTI). We examined the discriminative potential of fractional anisotropy (FA) and mean diffusivity (MD) across three broad brain regions: whole brain (WB), white matter (WM), and gray matter (GM), using both the full protocol and its subsets. Additionally, we employed a more detailed classification strategy based on segmentation into 95 regions of interest (ROIs), analyzing FA, MD, axial diffusivity (AD), and radial diffusivity (RD) under a stringent statistical criterion.ResultsWhile the protocol and each subset showed a comparable ability to differentiate between HC and MS groups, substantial variability in metric values across protocols highlights the limited utility of directly comparing DTI metrics between acquisition schemes.DiscussionThe results emphasize the importance of accounting for spatial systematic errors when selecting optimal protocols for clinical and research applications.https://www.frontiersin.org/articles/10.3389/fneur.2025.1618582/fulldiffusion tensor imagingBSD-DTIspatial systematic errorsmultiple sclerosisclinical trail protocol
spellingShingle Artur Tadeusz Krzyzak
Artur Tadeusz Krzyzak
Julia Lasek
Julia Lasek
Agnieszka Slowik
Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls
Frontiers in Neurology
diffusion tensor imaging
BSD-DTI
spatial systematic errors
multiple sclerosis
clinical trail protocol
title Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls
title_full Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls
title_fullStr Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls
title_full_unstemmed Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls
title_short Diagnostic performance of a multi-shell DTI protocol and its subsets with B-matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls
title_sort diagnostic performance of a multi shell dti protocol and its subsets with b matrix spatial distribution correction in differentiating early multiple sclerosis patients from healthy controls
topic diffusion tensor imaging
BSD-DTI
spatial systematic errors
multiple sclerosis
clinical trail protocol
url https://www.frontiersin.org/articles/10.3389/fneur.2025.1618582/full
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