In this section
@article{York:2024:10.1007/s00402-024-05589-8,
author = {York, TJ and Szyszka, B and Brivio, A and Musbahi, O and Barrett, D and Cobb, JP and Jones, GG},
doi = {10.1007/s00402-024-05589-8},
journal = {Archives of Orthopaedic and Trauma Surgery},
pages = {4963--4968},
title = {A radiographic artificial intelligence tool to identify candidates suitable for partial knee arthroplasty},
url = {http://dx.doi.org/10.1007/s00402-024-05589-8},
volume = {144},
year = {2024}
}
TY - JOUR
AB - Introduction: Knee osteoarthritis is a prevalent condition frequently necessitating knee replacement surgery, with demand projected to rise substantially. Partial knee arthroplasty (PKA) offers advantages over total knee arthroplasty (TKA), yet its utilisation remains low despite guidance recommending consideration alongside TKA in shared decision making. Radiographic decision aids exist but are underutilised due to clinician time constraints.Materials and Methods: This research develops a novel radiographic artificial intelligence (AI) tool using a dataset of knee radiographs and a panel of expert orthopaedic surgeons' assessments. Six AI models were trained to identify PKA candidacy. Results: 4,967 labelled four-view radiograph series were included. Models achieved statistically significant accuracies above random assignment, with EfficientNet-ES demonstrating the highest performance (AUC 95%, F1 score 83% and accuracy 80%). Conclusions: The AI decision tool shows promise in identifying PKA candidates, potentially addressing underutilisation of this procedure. Its integration into clinical practice could enhance shared decision making and improve patient outcomes. Further validation and implementation studies are warranted to assess real-world utility and impact.
AU - York,TJ
AU - Szyszka,B
AU - Brivio,A
AU - Musbahi,O
AU - Barrett,D
AU - Cobb,JP
AU - Jones,GG
DO - 10.1007/s00402-024-05589-8
EP - 4968
PY - 2024///
SN - 0936-8051
SP - 4963
TI - A radiographic artificial intelligence tool to identify candidates suitable for partial knee arthroplasty
T2 - Archives of Orthopaedic and Trauma Surgery
UR - http://dx.doi.org/10.1007/s00402-024-05589-8
UR - https://link.springer.com/article/10.1007/s00402-024-05589-8
VL - 144
ER -