Evidence map›Paper›PMID 42397574›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2026

ISSLS Prize in Bioengineering Science 2026: Hidden in Plain Sight: Machine Learning-Assisted MRI Reveals Novel Vertebral Body Biomarkers of Chronic Low Back Pain in Humans.

Jeffrey C Y Ng, Nathan Armani, Xijun Sun, Sabina M Pinto, Dino Samartzis, Arnold Y L Wong

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Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2026. 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
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0citing papers in PubMed
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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

6 authors.

Jeffrey C Y NgDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
Nathan ArmaniFaculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada. narmani@ualberta.ca.
Xijun SunDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
Sabina M PintoSchool of Medical and Health Sciences, Tung Wah College, Hong Kong, China.
Dino SamartzisDepartment of Orthopedic Surgery, Rush University Medical Center, Chicago, USA.
Arnold Y L WongDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China. arnold.wong@polyu.edu.hk.

Funding

Hong Kong Polytechnic University 4-ZZU7
6 · The paper itself

Abstract

purposeTo identify signal and spatial biomarkers in the lumbar vertebrae of individuals with and without non-specific chronic low back pain (NSCLBP) using magnetic resonance imaging (MRI).

methodsThis case-control study recruited 68 individuals with NSCLBP and 62 age- and sex-matched asymptomatic controls. Mid-sagittal T

resultsThe mean signal intensity was significantly lower in individuals with NSCLBP compared to controls (p < 0.001), whereas the COV was significantly higher in individuals with NSCLBP (p < 0.0001). Both the SIWC and GC were displaced anteriorly in individuals with NSCLBP relative to controls (SIWC p = 0.002; GC p < 0.001).

conclusionTo our knowledge, this is the first study to identify unique vertebral signal and spatial MRI biomarkers in individuals with NSCLBP. Specifically, those with NSCLBP exhibited markedly lower mean signal intensity, greater signal-intensity heterogeneity, and anterior displacement of both structural mass and signal intensity within the lumbar vertebrae. These novel quantitative "vertebral body biomarker profile" (VBBP) phenotypes may provide additional insight into clinically relevant pain phenotypes and support improved patient selection for targeted therapeutics.

Indexed as

BioengineeringChronic PainLow Back PainLumbar VertebraeMachine LearningMagnetic Resonance ImagingVertebral BodyAdultBiomarkersCase-Control StudiesFemaleHumansMaleMiddle AgedBiomarkersBiomarkersLow back painT2 mappingVertebral body

Identifiers

PMID42397574

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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.