# Topography matching for osteochondral graft transplantation

> **NIH NIH R21** · RUSH UNIVERSITY MEDICAL CENTER · 2021 · $207,240

## Abstract

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.

## Key facts

- **NIH application ID:** 10196071
- **Project number:** 1R21AR079063-01
- **Recipient organization:** RUSH UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** NOZOMU INOUE
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $207,240
- **Award type:** 1
- **Project period:** 2021-05-07 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10196071

## Citation

> US National Institutes of Health, RePORTER application 10196071, Topography matching for osteochondral graft transplantation (1R21AR079063-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10196071. Licensed CC0.

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