3D Geometry Scanning and Structural Integrity Assessment to Advance Meniscus Allograft Transplantation
PURPOSE: Meniscal allograft transplantation can restore joint biomechanics and alleviate symptoms, but its clinical use is limited by the scarcity of size-matched, structurally intact grafts. Current two-dimensional sizing and subjective inspection in tissue banks fail to capture complex three-dimensional geometry and subtle surface defects, highlighting the need for an accurate, reliable, and practical solution for routine donor tissue evaluation. METHODS: We developed an integrated system combining optical 3D scanning with curvature-based analysis for 3D geometry capture and surface defect detection in meniscus allografts. System performance was validated in terms of scanner accuracy and tissue bank workflow feasibility. RESULTS: The system completes each scan within 2 versus ~ 60 min for micro-computed tomography (μCT). It demonstrated μCT-comparable accuracy (mean volume difference: 6.9%; surface deviation: 8.3%). Scanning through phosphate buffer saline (PBS)-immersed transparent bags yielded equivalent accuracy to scanning in air (mean volume difference: 7.2%; surface deviation: 12.5%). The workflow demonstrated high intra- and inter-operator reproducibility. Viability testing revealed PBS-preserved tissues maintained > 94% viability for 20 min, whereas air-exposed tissues dropped below 70% within 10 min. For defect assessment, curvature metrics reliably identified surface wear, longitudinal, and radial defects, with size measurements for wear and longitudinal tears showing equivalence (± 10% margin) to stereomicroscopy. CONCLUSION: This portable system enables accurate and rapid 3D scanning under tissue banking conditions and quantitative surface defect detection. It supports improved graft shape matching and surface defect screening, offering a practical and scalable solution for tissue banks and clinical settings, potentially extendable to other fibrocartilaginous and osteochondral tissues.
Authors
- Dustin Mueller (ORCID: https://orcid.org/0000-0002-6784-2611)
- Shuchun Sun (ORCID: https://orcid.org/0000-0002-7985-2745)
- Haiyang Ma
- Jian Chen (ORCID: https://orcid.org/0000-0002-6740-8401)
- Pan Ge
- William Michael Pullen
- William C Bridges
- Hai Yao
- Shangping Wang
- Jichao Zhao
Institutions
- Medical University of South Carolina (US)
- Clemson University (US)
Publication Details
- Journal
- Annals of Biomedical Engineering
- Published
- 2026-05-01
- DOI
- https://doi.org/10.1007/s10439-026-04162-1
- Primary Topic
- Knee injuries and reconstruction techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Clemson University
- National Institutes of Health