Proof of concept of meniscus reconstruction and tear simulation via subtractive segmentation and bi-planar MRI integration

ObjectiveTo develop and validate a high-fidelity magnetic resonance imaging (MRI)-based three-dimensional (3D) reconstruction of the meniscus for improved tears characterization and quantification. MethodsA subtractive segmentation algorithm for clinical MRI with bi-planar (coronal and sagittal) model integration was employed to reconstruct 3D meniscal models from patients with various tear patterns. Geometric accuracy was validated against physical measurements and histological findings (Safranin-O/Fast green staining) with surgical specimens from arthritic patients. Tear morphology, surgical outcome simulation, and longitudinal healing efficiency were quantitatively assessed. ResultsThe reconstruction models of menisci from osteoarthritis patients demonstrated high morphometric fidelity, accurately replicating native meniscal dimensions (e.g., length, width, rim height) and revealing subtle internal deformities resembling lipid or myeloid deposits. The model enabled 3D visualization and quantification of tear patterns, including discoid, horizontal, longitudinal, flap, and complex tears, and captured topographic changes such as erosions in gout. Premorbid architecture of a discoid medial meniscus with complex tears was virtually rebuilt, facilitating the distinction of reparable regions from zones requiring meniscectomy. Two-year follow-up reconstructions revealed progressive reduction in tear diastasis and surface-initiated healing after suture repair. ConclusionWe demonstrate for the first time that MRI-based meniscal reconstruction improves the detection, characterization, and management of meniscal tears, providing detailed morphometric and intrasubstance measurements beyond conventional imaging and arthroscopy. This approach supports the prediction of surgical outcomes and postoperative monitoring, underscoring its substantial potential for personalized management of meniscal injuries and osteoarthritis.