Evidence map›Paper›PMID 41598315›Full record

ArticleLife (Basel, Switzerland)2026

AI-Powered Lateral DEXA Morphometry for Integrated Evaluation of Thoracic Kyphosis and Bone Density Assessment in Patients with Axial Spondyloarthritis.

Elena Bischoff, Stoyanka Vladeva, Xenofon Baraliakos, Nikola Kirilov

Abstract read
In one paragraph

Article in Life (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Elena BischoffDepartment of Health Care, Faculty of Medicine, Trakia University, 6000 Stara Zagora, Bulgaria.ORCID 0000-0003-1632-2920
Stoyanka VladevaDepartment of Health Care, Faculty of Medicine, Trakia University, 6000 Stara Zagora, Bulgaria.
Xenofon BaraliakosRheumazentrum Ruhrgebiet Herne, Ruhr-Universität Bochum, 44649 Herne, Germany.
Nikola KirilovInstitute of Medical Informatics, Heidelberg University Hospital, 69118 Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Axial spondyloarthritis (axSpA) is a chronic inflammatory disorder causing structural spinal damage and pathological thoracic kyphosis. Accurate quantification of spinal curvature is crucial for monitoring disease progression and guiding treatment. Conventional Cobb angle measurement on radiographs or DEXA images is widely used but is time-consuming and prone to inter-observer variability. This study evaluates an automated deep learning-based approach using a You Only Look Once (YOLO) model for vertebral detection on lateral morphometric DEXA scans and estimation of thoracic kyphosis angles. A dataset of 512 annotated DEXA images, including 182 from axSpA patients, was used to train and test the model. Kyphosis angles were computed by fitting a circle through detected vertebral centroids (Th4-Th12) and calculating the corresponding curvature angle. Model-predicted angles demonstrated strong agreement with physician-measured Cobb angles (r = 0.92,

Indexed as

axial spondyloarthritisCobb angledeep learningDEXAkyphosismorphometric analysisvertebra detectionYOLO

Identifiers

PMID41598315
PMCPMC12843375

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.