Evidence map›Paper›PMID 42421162›Full record

ArticleArthroplasty (London, England)2026

Accuracy of automated segmentation of gluteus and paraspinal muscles in patients with hip osteoarthritis using TotalSegmentator in 3Dslicer.

Hyonmin Choe, Shogo Yokota, Ryohei Iino, Koki Abe, Hironori Yamane, Yuta Hieda, Hiroyuki Ike, Ken Kumagai, Naomi Kobayashi, Yutaka Inaba

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Article in Arthroplasty (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Hyonmin ChoeDepartment of Orthopaedic Surgery, Yokohama City University, Yokohama, Kanagawa, 236-0004, Japan. hyonmin@hotmail.com.
Shogo YokotaYokohama City University School of Medicine, Yokohama, Kanagawa, 236-0004, Japan.
Ryohei IinoYokohama City University School of Medicine, Yokohama, Kanagawa, 236-0004, Japan.
Koki AbeDepartment of Orthopaedic Surgery, Yokohama City University, Yokohama, Kanagawa, 236-0004, Japan.
Hironori YamaneDepartment of Orthopaedic Surgery, Yokohama City University, Yokohama, Kanagawa, 236-0004, Japan.
Yuta HiedaDepartment of Orthopaedic Surgery, Yokohama City University, Yokohama, Kanagawa, 236-0004, Japan.
Hiroyuki IkeDepartment of Orthopaedic Surgery, Yokohama City University, Yokohama, Kanagawa, 236-0004, Japan.
Ken KumagaiDepartment of Orthopaedic Surgery, Yokohama City University Medical Center, Yokohama, Kanagawa, 232-0024, Japan.
Naomi KobayashiDepartment of Orthopaedic Surgery, Yokohama City University Medical Center, Yokohama, Kanagawa, 232-0024, Japan.
Yutaka InabaDepartment of Orthopaedic Surgery, Yokohama City University, Yokohama, Kanagawa, 236-0004, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMuscle atrophy is prevalent among patients with hip osteoarthritis, yet quantitative assessment of the peri-hip muscles remains challenging. Although computed tomography (CT) enables objective evaluation, manual segmentation is time-consuming and impractical for routine use. TotalSegmentator, an artificial intelligence-based extension of 3D Slicer, allows rapid automated muscle segmentation. The purpose of this study was to evaluate the accuracy, reproducibility, and clinical relevance of automated peri-hip muscle segmentation using TotalSegmentator in patients with hip osteoarthritis.

methodsThis retrospective cohort study included 53 female patients (106 hips) with bilateral hip osteoarthritis. Automated segmentation using TotalSegmentator was performed for the gluteus maximus, gluteus medius, and paraspinal muscles and compared with manual segmentation. Muscle volume and CT attenuation were analyzed. Agreement and intraobserver reproducibility were assessed using intraclass correlation coefficients (ICCs). Associations with patient demographics, spinopelvic alignment, and hip function, assessed using the modified Harris Hip Score (mHHS), were also examined in exploratory secondary analyses.

resultsTotalSegmentator demonstrated moderate to good reliability for muscle volume and CT attenuation compared with manual segmentation (ICCs 0.47-0.83), with strong correlations between methods (r = 0.79-0.96). Muscle volumes measured by TotalSegmentator were significantly smaller, whereas CT attenuation values were significantly higher than those obtained by manual segmentation. Intraobserver reproducibility was excellent, with ICCs of 1.00 for all muscles. Higher CT attenuation demonstrated a weak positive correlation with young age, better sagittal malalignment, and higher postoperative mHHS.

conclusionAutomated peri-hip muscle segmentation using TotalSegmentator provides rapid, accurate, and reproducible quantitative assessment of muscle volume and quality in patients with hip osteoarthritis.

Indexed as

3D SlicerArtificial intelligenceHipMusclesSegmentationTotalSegmentator

Identifiers

PMID42421162
PMCPMC13343625

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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.