Novel Technologies in Periprosthetic Joint Infection: Emerging Diagnostics

Abstract

Periprosthetic joint infection (PJI) is one of the most challenging complications following total joint arthroplasty, contributing to high morbidity, increased health care costs, and frequent implant failures. The current diagnostic methods, including synovial fluid analysis and microbiological cultures, are limited by their sensitivity and specificity, particularly in culture-negative infections. As a result, there is a growing need for novel diagnostic technologies that can provide rapid and reliable detection of PJI. This review explores emerging diagnostic strategies, including real-time intra-articular pH monitoring via X-ray-based sensors, urinary peptide biomarkers, molecular and immune cell profiling, and advanced synovial fluid assays. Implantable pH sensors and X-ray-excited luminescence chemical imaging allow noninvasive monitoring of synovial environment changes, enabling earlier infection detection. Urinary peptide biomarkers provide a novel, noninvasive approach, reflecting systemic inflammatory responses associated with PJI. Multiomic techniques, including transcriptomic, proteomic, and immune cell profiling, offer deeper insights into host-pathogen interactions, distinguishing PJI from aseptic failures with high accuracy. Among synovial fluid biomarkers, calprotectin has gained major attention due to its rapid detection capabilities via a lateral flow assay. As a proinflammatory protein released by neutrophils and macrophages, synovial calprotectin demonstrates high sensitivity and specificity in differentiating PJI from aseptic failures, making it an effective point-of-care diagnostic tool. Recent studies have validated its clinical utility in intraoperative and outpatient settings, with strong diagnostic performance comparable to established criteria. The integration of these novel diagnostic technologies has the potential to revolutionize PJI detection, reducing diagnostic delays and unnecessary invasive procedures. However, further large-scale clinical validation is required to establish these innovations as standard-of-care tools, ultimately improving patient outcomes and prosthetic longevity. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.