Ex Vivo Differentiation of Cartilage Degeneration Severity and Subchondral Bone Using Vibroacoustic Signals from Instrument–Tissue Interaction

Abstract Osteoarthritis (OA) of the knee is characterized by cartilage matrix degeneration, which eventually leads to joint dysfunction and surgical replacement. Preoperative radiography, the standard for treatment decision-making, provides limited information on the extent of degeneration, emphasizing the need for quantitative intraoperative techniques. This study evaluates the potential of vibroacoustic signals generated from instrument-tissue-interactions to assess cartilage degeneration severity. 138 ex vivo cartilage specimens of varying degeneration severity, histologically graded using the OARSI score, were collected from 41 patients undergoing arthroplasty. The specimens were classified into three groups: healthy cartilage (OARSI ≤ 2.0), degenerated cartilage (OARSI ≥ 2.5), and subchondral bone. Vibroacoustic signals were captured during specimen palpation using a vibration measurement system affixed to a surgical probe. 26 characteristic signal features were extracted using Continuous-Wavelet-Transformation, and their discriminative power was assessed using Support Vector Machine and k- Nearest-Neighbor classifier. Results showed 93.1% - 100% accuracy in differentiating bone from cartilage. Healthy cartilage (OARSI ≤ 2.0) was identifiable with 79.4% - 84.0% sensitivity, while specificity for degenerated cartilage (OARSI ≥ 2.5) dropped to 62.2%, reflecting a limitation of the approach. The study demonstrates that vibroacoustic signals from instrument-tissue- interactions provide valuable supplementary information for intraoperative cartilage evaluation and may support decision-making in arthroplasty.