Justin M. Cardenas MD , Dan Gordon MD , Bradford S. Waddell MD , Kurt J. Kitziger MD , Paul C. Peters Jr. MD , Brian P. Gladnick MD
{"title":"使用透视辅助计算机导航进行全髋关节置换术,人工智能是否优于人类?","authors":"Justin M. Cardenas MD , Dan Gordon MD , Bradford S. Waddell MD , Kurt J. Kitziger MD , Paul C. Peters Jr. MD , Brian P. Gladnick MD","doi":"10.1016/j.artd.2024.101410","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Successful total hip arthroplasty (THA) relies on the correct implant position. THA accuracy can be improved with the use of intraoperative fluoroscopic-assisted computer navigation. Artificial intelligence (AI) software may enhance fluoroscopic navigation; however, the accuracy of the AI compared to human-controlled software in assessing acetabular component position and leg length discrepancy (LLD) has not been studied.</p></div><div><h3>Methods</h3><p>We analyzed 420 consecutive primary THAs performed by a single surgeon using fluoroscopic-assisted computer navigation software. The first cohort of 211 patients required inputs from a human technician (manual), while the second cohort of 209 patients used an automated version of the software controlled by AI. The intraoperative acetabular component placement (inclination and anteversion) and LLD were recorded and compared to the 2-week postoperative standing anterior-posterior pelvis radiograph.</p></div><div><h3>Results</h3><p>Ninety-four percent (199/211) of cups in the manual cohort and 95% (198/209) of cups in the AI cohort were within the Lewinnek “safe-zone” (<em>P</em> = 1.0). In the manual cohort, 69% (146/211) of THAs had a final LLD within ±2 mm of the intraoperatively navigated LLD (ie, ΔLLD ≤2 mm). In the AI cohort, 66% (137/209) of THAs had a final LLD within ±2 mm of the intraoperatively navigated LLD (<em>P</em> = .47). Ninety-nine percent (209/211) of hips in the manual cohort and 98% (205/209) of hips in the AI cohort had a final LLD within ±5 mm of the intraoperatively navigated LLD (<em>P</em> = .45).</p></div><div><h3>Conclusions</h3><p>Both AI and human-controlled versions of the same navigation platform were similarly accurate for navigating cup position within the Lewinnek “safe zone” and LLD accuracy.</p></div>","PeriodicalId":37940,"journal":{"name":"Arthroplasty Today","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352344124000955/pdfft?md5=6053fc47a34bc564e5b763ed90576bb0&pid=1-s2.0-S2352344124000955-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Does Artificial Intelligence Outperform Humans Using Fluoroscopic-Assisted Computer Navigation for Total Hip Arthroplasty?\",\"authors\":\"Justin M. Cardenas MD , Dan Gordon MD , Bradford S. Waddell MD , Kurt J. Kitziger MD , Paul C. Peters Jr. MD , Brian P. Gladnick MD\",\"doi\":\"10.1016/j.artd.2024.101410\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Successful total hip arthroplasty (THA) relies on the correct implant position. THA accuracy can be improved with the use of intraoperative fluoroscopic-assisted computer navigation. Artificial intelligence (AI) software may enhance fluoroscopic navigation; however, the accuracy of the AI compared to human-controlled software in assessing acetabular component position and leg length discrepancy (LLD) has not been studied.</p></div><div><h3>Methods</h3><p>We analyzed 420 consecutive primary THAs performed by a single surgeon using fluoroscopic-assisted computer navigation software. The first cohort of 211 patients required inputs from a human technician (manual), while the second cohort of 209 patients used an automated version of the software controlled by AI. The intraoperative acetabular component placement (inclination and anteversion) and LLD were recorded and compared to the 2-week postoperative standing anterior-posterior pelvis radiograph.</p></div><div><h3>Results</h3><p>Ninety-four percent (199/211) of cups in the manual cohort and 95% (198/209) of cups in the AI cohort were within the Lewinnek “safe-zone” (<em>P</em> = 1.0). In the manual cohort, 69% (146/211) of THAs had a final LLD within ±2 mm of the intraoperatively navigated LLD (ie, ΔLLD ≤2 mm). In the AI cohort, 66% (137/209) of THAs had a final LLD within ±2 mm of the intraoperatively navigated LLD (<em>P</em> = .47). 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Does Artificial Intelligence Outperform Humans Using Fluoroscopic-Assisted Computer Navigation for Total Hip Arthroplasty?
Background
Successful total hip arthroplasty (THA) relies on the correct implant position. THA accuracy can be improved with the use of intraoperative fluoroscopic-assisted computer navigation. Artificial intelligence (AI) software may enhance fluoroscopic navigation; however, the accuracy of the AI compared to human-controlled software in assessing acetabular component position and leg length discrepancy (LLD) has not been studied.
Methods
We analyzed 420 consecutive primary THAs performed by a single surgeon using fluoroscopic-assisted computer navigation software. The first cohort of 211 patients required inputs from a human technician (manual), while the second cohort of 209 patients used an automated version of the software controlled by AI. The intraoperative acetabular component placement (inclination and anteversion) and LLD were recorded and compared to the 2-week postoperative standing anterior-posterior pelvis radiograph.
Results
Ninety-four percent (199/211) of cups in the manual cohort and 95% (198/209) of cups in the AI cohort were within the Lewinnek “safe-zone” (P = 1.0). In the manual cohort, 69% (146/211) of THAs had a final LLD within ±2 mm of the intraoperatively navigated LLD (ie, ΔLLD ≤2 mm). In the AI cohort, 66% (137/209) of THAs had a final LLD within ±2 mm of the intraoperatively navigated LLD (P = .47). Ninety-nine percent (209/211) of hips in the manual cohort and 98% (205/209) of hips in the AI cohort had a final LLD within ±5 mm of the intraoperatively navigated LLD (P = .45).
Conclusions
Both AI and human-controlled versions of the same navigation platform were similarly accurate for navigating cup position within the Lewinnek “safe zone” and LLD accuracy.
期刊介绍:
Arthroplasty Today is a companion journal to the Journal of Arthroplasty. The journal Arthroplasty Today brings together the clinical and scientific foundations for joint replacement of the hip and knee in an open-access, online format. Arthroplasty Today solicits manuscripts of the highest quality from all areas of scientific endeavor that relate to joint replacement or the treatment of its complications, including those dealing with patient outcomes, economic and policy issues, prosthetic design, biomechanics, biomaterials, and biologic response to arthroplasty. The journal focuses on case reports. It is the purpose of Arthroplasty Today to present material to practicing orthopaedic surgeons that will keep them abreast of developments in the field, prove useful in the care of patients, and aid in understanding the scientific foundation of this subspecialty area of joint replacement. The international members of the Editorial Board provide a worldwide perspective for the journal''s area of interest. Their participation ensures that each issue of Arthroplasty Today provides the reader with timely, peer-reviewed articles of the highest quality.