Evidence map›Paper›PMID 39366765›Full record

ArticleAJNR. American journal of neuroradiology2025

Super-Resolution in Clinically Available Spinal Cord MRIs Enables Automated Atrophy Analysis.

Blake E Dewey, Samuel W Remedios, Muraleetharan Sanjayan, Nicole Bou Rjeily, Alexandra Zambriczki Lee, Chelsea Wyche, Safiya Duncan, Jerry L Prince, Peter A Calabresi, Kathryn C Fitzgerald and 1 more

Abstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

11 authors.

Blake E DeweyFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland blake.dewey@jhu.edu.ORCID 0000-0003-4554-5058
Samuel W RemediosDepartment of Computer Science (S.W.R.), Johns Hopkins University, Baltimore, Maryland.ORCID 0000-0001-8634-8128
Muraleetharan SanjayanFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland.
Nicole Bou RjeilyFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland.
Alexandra Zambriczki LeeFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland.
Chelsea WycheFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland.
Safiya DuncanFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland.
Jerry L PrinceDepartment of Electrical and Computer Engineering (J.L.P.), Johns Hopkins University, Baltimore, Maryland.
Peter A CalabresiFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland.ORCID 0000-0002-7776-6472
Kathryn C FitzgeraldFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland.
Ellen M MowryFrom the Department of Neurology (B.E.D., M.S., N.B.R., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Johns Hopkins University, Baltimore, Maryland.

Funding

Imaging Neurodegeneration in Multiple SclerosisR01NS082347 · NINDS · JOHNS HOPKINS UNIVERSITY · PI PETER A CALABRESI, Shiv Saidha · 2013 to 2026
$7.0M
Home-based actigraphy to predict disability progression and enhance clinical trials in multiple sclerosisR01NR018851 · NINR · JOHNS HOPKINS UNIVERSITY · PI Ellen M. Mowry · 2020 to 2026
$4.2M
Circadian Rhythms and Sleep, Structural Neuroimaging and Depression in People with Multiple SclerosisK01MH121582 · NIMH · JOHNS HOPKINS UNIVERSITY · PI FITZGERALD, KATHRYN C. · 2019 to 2022
$675k
NIMH NIH HHS K01 MH121582NINDS NIH HHS R01 NS082347NINR NIH HHS R01 NR018851
6 · The paper itself

Abstract

background and purposeMeasurement of the mean upper cervical cord area (MUCCA) is an important biomarker in the study of neurodegeneration. However, dedicated high-resolution (HR) scans of the cervical spinal cord are rare in standard-of-care imaging due to timing and clinical usability. Most clinical cervical spinal cord imaging is sagittally acquired in 2D with thick slices and anisotropic voxels. As a solution, previous work describes HR T1-weighted brain imaging for measuring the upper cord area, but this is still not common in clinical care. MATERIALS AND

methodsWe propose using a zero-shot super-resolution technique, synthetic multi-orientation resolution enhancement (SMORE), already validated in the brain, to enhance the resolution of 2D-acquired scans for upper cord area calculations. To incorporate super-resolution in spinal cord analysis, we validate SMORE against HR research imaging and in a real-world longitudinal data analysis.

resultsSuper-resolved (SR) images reconstructed by using SMORE showed significantly greater similarity to the ground truth than low-resolution (LR) images across all tested resolutions (

conclusionsSuper-resolution is a valuable tool for enabling large-scale studies of cord atrophy, as LR images acquired in clinical practice are common and available.

Indexed as

Cervical CordImage EnhancementImage Interpretation, Computer-AssistedMagnetic Resonance ImagingSpinal CordAdultAgedAtrophyFemaleHumansMaleMiddle AgedReproducibility of Results

Identifiers

PMID39366765
PMCPMC11979833

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.