A new classification to characterize and predict treatment of acetabular bone defects.

Mattia LoppiniEdoardo GuazzoniFrancesco Manlio GambaroFrancesco La CameraEmanuela MorenghiGuido Grappiolo

Published in: Archives of orthopaedic and trauma surgery (2024)

The newly proposed classification was able to characterize the extent of acetabular bone defects and predict pre-operatively the appropriate surgical treatment strategy in 87.3% of cases. It showed a strong agreement among raters and an almost perfect agreement among different measurements at 1 month distance. This new tool could be used in the preoperative assessment to drive the use of secondary level image examinations and the type of surgical management.

Keyphrases

deep learning
machine learning
bone mineral density
total hip arthroplasty
total hip
soft tissue
bone loss
patients undergoing
postmenopausal women
total knee arthroplasty