Non-Invasive Sensing of Active and Passive Joint Acoustic Emissions as a Biomarker of Periprosthetic Joint Effusions.

Abstract

Total joint arthroplasty (TJA) effectively treats end-stage hip and knee joint diseases, improving patients' quality of life. However, 1-2% of TJA patients develop prosthetic joint infections (PJI), which are challenging to diagnose and treat. This study investigates non-invasive active vibration and passive acoustic emission analyses for PJI monitoring. In this ex vivo study, periprosthetic joint effusions were simulated in seven cadaveric specimens with knee replacements by injecting saline and bacterial solutions into the joint space. Active sensing involved non-invasively stimulating the tibia with a miniature shaker, while passive sensing used manual stress to induce vibrations. Wideband, low-noise accelerometers captured the resulting vibrations, with spectral and temporal features extracted from the active and passive recordings, respectively. A qualitative analytical beam model of the knee-tibia system was developed to represent the fluid as structural changes at the boundary of the system. Both methods proved to be sensitive to the fluid in the joint space. Linear regression models were built using the most informative features, estimating fluid volume with Pearson's r of 0.79 and mean absolute errors of 11.1 mL (active) and 11.9 mL (passive). Trends in frequency and time signals were consistent between the experimental results and the analytical model. The results of this study demonstrated the utility of novel vibration-based techniques to monitor periprosthetic joint effusions. These non-invasive techniques can lead to wearable devices for joint health monitoring, enabling PJI detection and personalized treatment plans, potentially improving patient outcomes and reducing PJI-related healthcare costs.