Ultra-Fresh Osteochondral Allograft Transplantation Supported by Artificial Intelligence Algorithms - Case Report of a 14-Year-Old Patient

György H1,2*, Rudolf HL1,2, Zsófia E1 , Péter S4 , Endre S3 , János S4 , Tamás G1,2 and László H1,2

Uzsoki Hospital, Budapest, Hungary 2 Department of Traumatology, Semmelweis University, Hungary 3 Alfréd Rényi Institute of Mathematics, Hungary 4 MedInnoScan Research and Development Ltd., Budapest, Hungary

^*Correspondance to: Hangody György 

 PDF  Full Text DOI: 10.25107/2474-1647.3167

Abstract

Surgical treatment of cartilage surface lesions is similar to tumor surgery in many ways. Depending on the extent, depth, and nature of the lesion, different pathways can lead to a solution. In our case, we performed an ?ultra-fresh? osteochondral allograft transplantation due to an extensive osteochondral lesion in the lateral femur condyle of a 14-year-old patient. One of the main limitations of this process is to create a precisely sized and fitting graft, and thereby establishing the best congruence possible. In order to achieve this, MRI-based artificial intelligence algorithms were developed and this was used for donor-recipient matching. Postoperative follow-up of the patient was performed according to current international protocols. Although we do not have longterm experience with the use of artificial intelligence in this form, we believe that matching the most appropriate donor-recipient pairs during transplantation may affect the long-term outcomes of surgery

Keywords

Knee; Cartilage; Ultra-fresh osteochondral allografts; Artificial intelligence; Deep learning

Cite the article

György H, Rudolf HL, Zsófia E, Péter S, Endre S, János S, et al. Ultra-Fresh Osteochondral Allograft Transplantation Supported by Artificial Intelligence Algorithms - Case Report of a 14-YearOld Patient. Clin Surg. 2021; 6: 3167..