Evidence map›Paper›PMID 34402140›Full record

ArticleEuropean journal of neurology2022

Lesion features on magnetic resonance imaging discriminate multiple sclerosis patients.

Sandra M Hurtado Rúa, Ulrike W Kaunzner, Sneha Pandya, Elizabeth Sweeney, Ceren Tozlu, Amy Kuceyeski, Thanh D Nguyen, Susan A Gauthier

Abstract read
In one paragraph

Article in European journal of neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sandra M Hurtado RúaDepartment of Mathematics and Statistics, Cleveland State University, Cleveland, Ohio, USA.
Ulrike W KaunznerDepartment of Neurology, Weill Cornell Medicine, New York City, New York, USA.
Sneha PandyaDepartment of Radiology, Weill Cornell Medicine, New York City, New York, USA.
Elizabeth SweeneyDepartment of Population Health Sciences, Weill Cornell Medicine, New York City, New York, USA.
Ceren TozluDepartment of Radiology, Weill Cornell Medicine, New York City, New York, USA.
Amy KuceyeskiDepartment of Radiology, Weill Cornell Medicine, New York City, New York, USA.
Thanh D NguyenDepartment of Radiology, Weill Cornell Medicine, New York City, New York, USA.
Susan A GauthierDepartment of Neurology, Weill Cornell Medicine, New York City, New York, USA.ORCID 0000-0002-4015-1781

Funding

Disparities in COVID Disease Severity and Outcomes in New York CityUL1TR002384 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI JULIANNE L IMPERATO-MCGINLEY · 2017 to 2026
$86.2M
Identifying mechanisms of tissue injury in MS lesions: a multi-modality imaging approachR01NS104283 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI GAUTHIER, SUSAN A · 2018 to 2022
$2.2M
Quantifying the role of the connectome in resiliency to multiple sclerosisR21NS104634 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI KUCEYESKI, AMY FRANCES · 2017 to 2018
$466k
NCATS NIH HHS UL1 TR002384NINDS NIH HHS R01 NS104283NINDS NIH HHS R21 NS104634
6 · The paper itself

Abstract

backgroundMagnetic resonance imaging (MRI) provides insight into various pathological processes in multiple sclerosis (MS) and may provide insight into patterns of damage among patients.

objectiveWe sought to determine if MRI features have clinical discriminative power among a cohort of MS patients.

methodsNinety-six relapsing remitting and seven progressive MS patients underwent myelin water fraction (MWF) imaging and conventional MRI for cortical thickness and thalamic volume. Patients were clustered based on lesion level MRI features using an agglomerative hierarchical clustering algorithm based on principal component analysis (PCA).

resultsOne hundred and three patients with 1689 MS lesions were analyzed. PCA on MRI features demonstrated that lesion MWF and volume distributions (characterized by 25th, 50th, and 75th percentiles) accounted for 87% of the total variability based on four principal components. The best hierarchical cluster confirmed two distinct patient clusters. The clustering features in order of importance were lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, total lesion volume, cortical thickness, and thalamic volume (all p values <0.01368). The clusters were associated with patient Expanded Disability Status Scale (EDSS) (n = 103, p = 0.0338) at baseline and at 5 years (n = 72, p = 0.0337).

conclusionsThese results demonstrate that individual MRI features can identify two patient clusters driven by lesion-based values, and our unique approach is an analysis blinded to clinical variables. The two distinct clusters exhibit MWF differences, most likely representing individual remyelination capabilities among different patient groups. These findings support the concept of patient-specific pathophysiological processes and may guide future therapeutic approaches.

Indexed as

Multiple SclerosisMultiple Sclerosis, Chronic ProgressiveMultiple Sclerosis, Relapsing-RemittingBrainHumansMagnetic Resonance ImagingMyelin Sheathcluster analysislesionMRImultiple sclerosismyelin water fraction

Identifiers

PMID34402140
PMCPMC8727028

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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.