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Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study
OBJECTIVE: We performed a retrospective study to compare the accuracy of preoperative planning using three-dimensional AI-HIP software and traditional two-dimensional manual templating to predict the size and position of prostheses. The purpose of this study was to evaluate the accuracy of AI-HIP in...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8597071/ https://www.ncbi.nlm.nih.gov/pubmed/34775845 http://dx.doi.org/10.1177/03000605211058874 |
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author | Ding, Xuzhuang Zhang, Bingshi Li, Wenao Huo, Jia Liu, Sikai Wu, Tao Han, Yongtai |
author_facet | Ding, Xuzhuang Zhang, Bingshi Li, Wenao Huo, Jia Liu, Sikai Wu, Tao Han, Yongtai |
author_sort | Ding, Xuzhuang |
collection | PubMed |
description | OBJECTIVE: We performed a retrospective study to compare the accuracy of preoperative planning using three-dimensional AI-HIP software and traditional two-dimensional manual templating to predict the size and position of prostheses. The purpose of this study was to evaluate the accuracy of AI-HIP in preoperative planning for primary total hip arthroplasty. METHODS: In total, 316 hips treated from April 2019 to June 2020 were retrospectively reviewed. A typical preoperative planning process for patients was implemented to compare the accuracy of the two preoperative planning methods with respect to prosthetic size and position. Intraclass correlation coefficients (ICCs) were used to evaluate the homogeneity between the actual prosthetic size and position and the preoperative planning method. RESULTS: When AI-HIP software and manual templating were used for preoperative planning, the stem agreement was 87.7% and 58.9%, respectively, and the cup agreement was 94.0% and 65.2%, respectively. The results showed that when AI-HIP software was used, an extremely high level of consistency (ICC > 0.95) was achieved for the femoral stem size, cup size, and femoral osteotomy level (ICC = 0.972, 0.962, and 0.961, respectively). CONCLUSION: AI-HIP software showed excellent reliability for predicting the component size and implant position in primary total hip arthroplasty. |
format | Online Article Text |
id | pubmed-8597071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-85970712021-11-18 Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study Ding, Xuzhuang Zhang, Bingshi Li, Wenao Huo, Jia Liu, Sikai Wu, Tao Han, Yongtai J Int Med Res Retrospective Clinical Research Report OBJECTIVE: We performed a retrospective study to compare the accuracy of preoperative planning using three-dimensional AI-HIP software and traditional two-dimensional manual templating to predict the size and position of prostheses. The purpose of this study was to evaluate the accuracy of AI-HIP in preoperative planning for primary total hip arthroplasty. METHODS: In total, 316 hips treated from April 2019 to June 2020 were retrospectively reviewed. A typical preoperative planning process for patients was implemented to compare the accuracy of the two preoperative planning methods with respect to prosthetic size and position. Intraclass correlation coefficients (ICCs) were used to evaluate the homogeneity between the actual prosthetic size and position and the preoperative planning method. RESULTS: When AI-HIP software and manual templating were used for preoperative planning, the stem agreement was 87.7% and 58.9%, respectively, and the cup agreement was 94.0% and 65.2%, respectively. The results showed that when AI-HIP software was used, an extremely high level of consistency (ICC > 0.95) was achieved for the femoral stem size, cup size, and femoral osteotomy level (ICC = 0.972, 0.962, and 0.961, respectively). CONCLUSION: AI-HIP software showed excellent reliability for predicting the component size and implant position in primary total hip arthroplasty. SAGE Publications 2021-11-14 /pmc/articles/PMC8597071/ /pubmed/34775845 http://dx.doi.org/10.1177/03000605211058874 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Retrospective Clinical Research Report Ding, Xuzhuang Zhang, Bingshi Li, Wenao Huo, Jia Liu, Sikai Wu, Tao Han, Yongtai Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study |
title | Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study |
title_full | Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study |
title_fullStr | Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study |
title_full_unstemmed | Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study |
title_short | Value of preoperative three-dimensional planning software (AI-HIP) in primary total hip arthroplasty: a retrospective study |
title_sort | value of preoperative three-dimensional planning software (ai-hip) in primary total hip arthroplasty: a retrospective study |
topic | Retrospective Clinical Research Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8597071/ https://www.ncbi.nlm.nih.gov/pubmed/34775845 http://dx.doi.org/10.1177/03000605211058874 |
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