
| ID | 69628 |
| フルテキストURL | |
| 著者 |
Okuda, Ryuichiro
Department of Orthopaedic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
Tetsunaga, Tomonori
Department of Musculoskeletal Health Promotion, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
ORCID
Kaken ID
Yamada, Kazuki
Department of Orthopaedic Surgery, Okayama University Hospital
Tetsunaga, Tomoko
Department of Sports Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University
Koura, Takashi
Department of Orthopaedic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
Inoue, Tomohiro
Department of Orthopaedic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
Masada, Yasutaka
Department of Orthopaedic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
Okazaki, Yuki
Department of Orthopaedic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
Ozaki, Toshifumi
Department of Orthopaedic Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
Kaken ID
publons
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| 抄録 | Background and Objective: The use of computed tomography (CT)-based navigation systems has been shown to improve surgical accuracy in total hip arthroplasty. However, there is limited literature available about the application of CT-based navigation systems in severe hip dysplasia. This study aimed to evaluate the accuracy of a CT-based navigation system in patients with severe hip dysplasia using three-dimensional (3D)-printed bone models. Methods: 3D-printed bone models were generated from CT data of patients with severe hip dysplasia (Crowe type II, 10 hips; type III, 10 hips; and type IV, 10 hips). The accuracy of automatic segmentation, success rate, point-matching accuracy across different registration methods, and deviation values at reference points after registration were assessed. Results: For the combined cohort of Crowe II, III, and IV cases (n = 30), the Dice Similarity Coefficient and Jaccard Index were 0.99 ± 0.01 and 0.98 ± 0.02, respectively. These values indicate a high level of segmentation accuracy. The “Matching with true and false acetabulum + iliac crest” method achieved a 100% success rate across all groups, with mean deviations of 0.08 ± 0.28 mm in the Crowe II group, 0.12 ± 0.33 mm in the Crowe III group, and 0.14 ± 0.50 mm in the Crowe IV group (p = 0.572). In the Crowe IV group, the anterior superior iliac spine deviation was significantly lower using the “Matching with true and false acetabulum + iliac crest” method compared to the “Matching with true and false acetabulum” method (0.28 ± 0.49 mm vs. 3.29 ± 2.56 mm, p < 0.05). Conclusions: This study demonstrated the high accuracy of automatic AI-based segmentation, with a Dice Similarity Coefficient of 0.99 ± 0.01 and a Jaccard Index of 0.98 ± 0.02 in the combined cohort of Crowe type II, III, and IV cases (n = 30). The matching success rate was 100%, with additional points on the iliac crest, which improved matching accuracy and reduced deviations, depending on the case.
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| キーワード | total hip arthroplasty
CT-based navigation
bone model
artificial intelligence
Ortoma Treatment Solution
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| 発行日 | 2025-05-24
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| 出版物タイトル |
Medicina
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| 巻 | 61巻
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| 号 | 6号
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| 出版者 | MDPI AG
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| 開始ページ | 973
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| ISSN | 1648-9144
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| 資料タイプ |
学術雑誌論文
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| 言語 |
英語
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| OAI-PMH Set |
岡山大学
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| 著作権者 | © 2025 by the authors.
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| 論文のバージョン | publisher
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| DOI | |
| Web of Science KeyUT | |
| 関連URL | isVersionOf https://doi.org/10.3390/medicina61060973
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| ライセンス | https://creativecommons.org/licenses/by/4.0/
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| Citation | Okuda, R.; Tetsunaga, T.; Yamada, K.; Tetsunaga, T.; Koura, T.; Inoue, T.; Masada, Y.; Okazaki, Y.; Ozaki, T. Accuracy Verification of a Computed Tomography-Based Navigation System for Total Hip Arthroplasty in Severe Hip Dysplasia: A Simulation Study Using 3D-Printed Bone Models of Crowe Types II, III, and IV. Medicina 2025, 61, 973. https://doi.org/10.3390/medicina61060973
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