Evidence map›Paper›PMID 31588688›Full record

ArticleAnnals of clinical and translational neurology2019

Diffusion basis spectrum imaging for identifying pathologies in MS subtypes.

Afsaneh Shirani, Peng Sun, Kathryn Trinkaus, Dana C Perantie, Ajit George, Robert T Naismith, Robert E Schmidt, Sheng-Kwei Song, Anne H Cross

Abstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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

9 authors.

Afsaneh ShiraniThe John L. Trotter Multiple Sclerosis Center and Neuroimmunology Section, Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.ORCID 0000-0002-8866-6426
Peng SunDepartment of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri.
Kathryn TrinkausBiostatistics Shared Resource and Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri.
Dana C PerantieThe John L. Trotter Multiple Sclerosis Center and Neuroimmunology Section, Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.
Ajit GeorgeDepartment of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri.
Robert T NaismithThe John L. Trotter Multiple Sclerosis Center and Neuroimmunology Section, Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.
Robert E SchmidtDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri.
Sheng-Kwei SongDepartment of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri.
Anne H CrossThe John L. Trotter Multiple Sclerosis Center and Neuroimmunology Section, Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.ORCID 0000-0003-0829-7569

Funding

Validating diffusion MRI biomarkers of inflammation and axon pathologies in EAEP01NS059560 · NINDS · WASHINGTON UNIVERSITY · PI SONG, SHENG-KWEI · 2008 to 2018
$11.3M
PREDICTIVE VALUE OF DIFFUSION MRI IN CERVICAL SPONDYLOTIC MYELOPATHYR01NS047592 · NINDS · WASHINGTON UNIVERSITY · PI RAY, WILSON Z, SONG, SHENG-KWEI · 2005 to 2021
$5.8M
IMAGING OPTIC NERVE FUNCTION AND PATHOLOGYU01EY025500 · NEI · WASHINGTON UNIVERSITY · PI SONG, SHENG-KWEI · 2015 to 2019
$3.1M
NEI NIH HHS U01 EY025500NIH HHS P01 NS059560NINDS NIH HHS P01 NS059560NINDS NIH HHS R01 NS047592
6 · The paper itself

Abstract

Diffusion basis spectrum imaging (DBSI) combines discrete anisotropic diffusion tensors and the spectrum of isotropic diffusion tensors to model the underlying multiple sclerosis (MS) pathologies. We used clinical MS subtypes as a surrogate of underlying pathologies to assess DBSI as a biomarker of pathology in 55 individuals with MS. Restricted isotropic fraction (reflecting cellularity) and fiber fraction (representing apparent axonal density) were the most important DBSI metrics to classify MS using brain white matter lesions. These DBSI metrics outperformed lesion volume. When analyzing the normal-appearing corpus callosum, the most significant DBSI metrics were fiber fraction, radial diffusivity (reflecting myelination), and nonrestricted isotropic fraction (representing edema). This study provides preliminary evidence supporting the ability of DBSI as a potential noninvasive biomarker of MS neuropathology.

Indexed as

AdultBrainCross-Sectional StudiesDiffusion Tensor ImagingFemaleHumansMaleMiddle AgedMultiple SclerosisNeuroimaging

Identifiers

PMID31588688
PMCPMC6856605

What OpenQuestion holds

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Registered trials

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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.