Evidence map›Paper›PMID 40813936›Full record

ArticleGeroScience2025

Quantitative assessment of asymptomatic spinal cord compression using MRI: a multi-center study.

Ali F Khan, Sanaa Hameed, Alaa Baha, Fauziyya Muhammad, Grace Haynes, Amber Dastgir, Suresh K Gulla, Hakeem J Shakir, Michael L Rohan, Yasin Y Dhaher and 1 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in GeroScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ali F KhanDepartment of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA. ali-f-khan@ouhsc.edu.ORCID 0000-0002-9690-5474
Sanaa HameedDepartment of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Alaa BahaDepartment of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Fauziyya MuhammadDepartment of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Grace HaynesStephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA.
Amber DastgirDepartment of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Suresh K GullaDepartment of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Hakeem J ShakirDepartment of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Michael L RohanLaureate Institute for Brain Research, Tulsa, OK, USA.
Yasin Y DhaherUniversity of Texas Southwestern Medical Center, Dallas, TX, USA.
Zachary A SmithDepartment of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aging is associated with an increased risk of neurodegenerative conditions, including degenerative cervical myelopathy (DCM), a leading cause of neurological disability in older adults. Asymptomatic spinal cord compression (ASCC) represents a potential precursor to DCM, characterized by spinal cord compression in individuals without overt clinical symptoms. Early identification and quantification of ASCC are critical for preventing age-related neurological decline. However, a standardized quantitative definition of ASCC remains lacking. This study aimed to develop a quantitative approach to assess cervical ASCC using high-resolution magnetic resonance imaging (MRI). T2-weighted 3 T spine MRI scans from 248 healthy controls (HCs), 53 ASCC individuals, and 55 DCM patients from three datasets conforming to the spine generic protocol were analyzed. An automated pipeline utilizing the Spinal Cord Toolbox was used to compute the maximum spinal cord compression (MSCC) metric at each slice, with peak MSCC serving as a quantitative metric for spinal cord compression. ASCC was identified in 17.6% of participants, predominantly at the C4-C6 spinal levels. While ASCC was observed in younger individuals (median age = 36 years), its prevalence increased with age. DCM patients were significantly older (median age = 54 years), exhibiting greater peak MSCC (22.4%) than ASCC individuals (13.8%). These findings suggest that spinal cord compression may begin in midlife and progress with aging, potentially contributing to age-related neurological impairments. This study validates an automated MRI-based approach for detecting and quantifying spinal cord compression, enabling large-scale analysis in aging populations. Given that ASCC is more common in older adults, longitudinal studies are necessary to determine its progression and potential conversion to symptomatic DCM. The proposed quantitative method may aid in early detection and monitoring of spinal cord compression, informing clinical decision-making to mitigate neurological decline in aging individuals.

Indexed as

Magnetic Resonance ImagingSpinal Cord CompressionAdultAgedCervical VertebraeFemaleHumansMaleMiddle AgedAsymptomatic spinal cord compressionCervical spondylotic myelopathyDegenerative cervical myelopathyMagnetic resonance imagingSpinal Cord ToolboxSpine generic protocol

Identifiers

PMID40813936
PMCPMC12638620

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.