ArticlePloS one2025
Sensitivity of multi-parametric quantitative magnetic resonance imaging for multiple sclerosis pathology.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn recent years, quantitative magnetic resonance imaging (MRI) made progress towards clinical applicability mainly through advances in acceleration techniques. In patients with multiple sclerosis (MS), objective quantitative MRI-based characterization of subtle pathological alterations in lesions, perilesion (PL), as well as normal-appearing (NA) white matter (NAWM) and grey matter (NAGM) would revolutionize clinical assessment. While numerous quantitative techniques have been applied in studies of MS patients, their diagnostic significance especially for individual patients with relatively short disease duration is unclear. Therefore, we investigated the sensitivity of several quantitative MRI parameters to focal and diffuse MS pathology in a clinical feasibility study with a small sample size.
methodsIn 13 MS patients with a mean disease duration of 8 years and a mean EDSS of 1.1 as well as 14 healthy age-matched controls (HC), we acquired nine (semi-)quantitative magnetic resonance (MR) biomarkers, namely myelin water fraction (MWF), magnetization transfer (MT) saturation (MTsat), inhomogeneous MT ratio (ihMTR), quantitative longitudinal relaxation time (qT1), intrinsic (qT2) and effective (qT2*) quantitative transverse relaxation times, proton density (PD), quantitative susceptibility mapping (QSM), and the ratio between T1-weighted and T2-weighted images (T1w/T2w). Four volumes of interest were automatically defined (NA/HC grey matter (GM), NA/HC white matter (WM), lesion, and PL), and biomarker values were analyzed between groups and tissue types.
resultsFor all nine assessed biomarkers, mean values per patient were significantly different between lesion, PL, and NAWM (p < 0.05, FDR corrected). The lesion values of qT1, qT2, qT2 * , PD, and QSM were rather inhomogeneous. Furthermore, MWF, MTsat, and ihMTR were sensitive to diffuse WM pathology in MS with the largest absolute differences between NAWM and HCWM medians, albeit not statistically significant after correction for multiple testing. DISCUSSION: In our study, we successfully compared nine different quantitative MR parameters within the same subjects for tissue characterization of MS. Our study adds relevant aspects to the current debate on different sensitivities of various quantitative MR biomarkers to MS pathology. While all investigated MR biomarkers allowed characterizing lesions in individual patients, a separation of NAWM and HCWM could be most promising with the myelin-sensitive measures MWF, MTsat, and ihMTR.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.