Project Summary/Abstract The overall goal of the proposed project is to translate topography matching algorithms for osteochondral allograft transplantation to clinical practice. Focal chondral defects of the knee are prevalent and are a significant source of pain and morbidity in the young, active population. Successful osteochondral allograft transplantation is dependent on the congruity, preparation, size, and fixation of the graft. Irregularities in cartilage thickness between the donor and recipient site may lead to abnormal stresses and compromised function. Evaluation and understanding of osseous and chondral surface topography can be also useful in graft selection during surgical procedures in osteochondral graft transplantation. However, evaluation of topography can be cumbersome and expensive with conventional CT and/or MR imaging. Newer imaging technologies are emerging, including 3D scanning with a quick smartphone scan. 3D image acquisition through this method is simple, fast, and inexpensive and our pilot study supports its use as an alternative to CT scanning and could be used during surgery and allograft preparation. Accurate implementation of the topographic matching for graft transplantation requires appropriate instrumentation. We have demonstrated accuracy and efficacy of novel 3D patient-specific instrumentation systems using 3D printed devices for total shoulder arthroplasty and our proposed techniques for allograft transplantation procedures will share the same working principles. The proposed project will utilize these novel technologies in order to translate the topography matching technique for osteochondral transplantation from in silico to clinical practice. Topography matching for osteochondral graft transplantation planned using 3D computer models will be implemented on cadaveric specimens and validated by comparing in silico transplanted model with the real cadaveric transplanted model as a gold standard (Aim 1). Accuracy of the new 3D imaging technique using the smartphone, which will be a key technique in a clinical setting, will be validated by comparing with laser scanning as a gold standard (Aim 2). Accurate topography matching of graft transplantation established in the proposed project can improve treatment outcomes for focal chondral defects of the knee in young patients through increased stability of the graft and decreased cartilage degeneration in the graft and surrounding/opposing cartilage, in turn, reducing the risk for future osteoarthritis onset. The technique and knowledge obtained by the project can also be applied to other surgical procedures involving 3D surface geometry evaluation.