Evidence map›Paper›PMID 40059265›Full record

ArticleEJNMMI physics2025

Automated segmentation of the sacro-iliac joints, posterior spinal joints and discovertebral units on low-dose computed tomography for Na[

Wouter R P van der Heijden, Floris H P van Velden, Robert Hemke, Tom C Doorschodt, Ronald Boellaard, Conny J van der Laken, Gerben J C Zwezerijnen

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Article in EJNMMI physics, 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

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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. Na[EJNMMI research · 2025
    Article
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Wouter R P van der HeijdenDepartment of Clinical Immunology and Rheumatology, Amsterdam UMC, Meibergdreef 9, Amsterdam, The Netherlands. w.r.p.vanderheijden@amsterdamumc.nl.ORCID http://orcid.org/0009-0007-0453-8157
Floris H P van VeldenDepartment of Radiology, Leiden University Medical Center, Albinusdreef 2, Leiden, The Netherlands.ORCID http://orcid.org/0000-0003-2859-2119
Robert HemkeDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, De Boelelaan 1117, Amsterdam, The Netherlands.ORCID http://orcid.org/0000-0002-0826-302X
Tom C DoorschodtDepartment of Radiology and Nuclear Medicine, OLVG, Oosterparkstraat 9, Amsterdam, The Netherlands.ORCID http://orcid.org/0009-0007-0307-4143
Ronald BoellaardDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, De Boelelaan 1117, Amsterdam, The Netherlands.ORCID http://orcid.org/0000-0002-0313-5686
Conny J van der LakenDepartment of Clinical Immunology and Rheumatology, Amsterdam UMC, Meibergdreef 9, Amsterdam, The Netherlands.ORCID http://orcid.org/0000-0002-9865-6213
Gerben J C ZwezerijnenDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, De Boelelaan 1117, Amsterdam, The Netherlands.ORCID http://orcid.org/0000-0002-9571-9362

Funding

ReumaNederland NSP22-1-302
6 · The paper itself

Abstract

purposeSpondyloarthritis (SpA) is a chronic inflammatory rheumatic disease which involves the axial skeleton. Quantitative sodium fluoride-18 (Na[

methodsTwo segmentation methods were developed using Na[

resultsThe morphological method achieved significantly better DSC (0.82 (0.73-0.88) vs. 0.74 (0.68-0.79); p < 0.001) for all DVUs combined compared to the atlas-based method. The atlas-based method outperformed the morphological method for the posterior joints with a median error distance of 4.00 mm (4.00-5.66) vs. 5.66 mm (4.00-8.00) (p < 0.001). For lesion detection, the atlas-based segmentations were more successful than the morphological method, with the most accurate metric being the maximum standardized uptake value (SUVmax) of the lesional Na[

conclusionWe present the first methods for detailed automatic segmentation of the posterior spinal joints, DVUs and SIJs on LDCT. The atlas-based method is the most appropriate, reaching high segmentation performance and lesion detection accuracy. More research on the PET-based lesion segmentation is required, to develop a pipeline for fully automated lesional Na[

Indexed as

Artificial intelligence-based segmentationAutomated lesion detectionPET quantificationRheumatic diseaseSpinal bone formation

Identifiers

PMID40059265
PMCPMC11891110

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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.