Accurate diagnosis of periprosthetic joint infections (PJI) is one of the most widely researched areas in modern orthopedic endoprosthesis. However, our understanding of the immunological basis of this severe complication is still limited. In this study, we developed a flow cytometric approach to precisely characterize the immune cell composition in periprosthetic joints. Using high-dimensional multi-parametric data, we defined, for the first time, the local immune cell populations of artificial joints. We identified significant differences in the cellular distribution between infected and non-infected samples, and revealed that myeloid-derived suppressor cells (MDSCs) act as potential regulators of infiltrating immune cells in PJI. Further, we developed an algorithm to predict septic and aseptic samples with high sensitivity and specificity, that may serve as an indispensable addition to the current criteria of the Musculoskeletal Infection Society. This study describes a novel approach to flow cytometrically analyze the immune cell infiltrate of joint fluid that not only improves our understanding of the pathophysiology of PJI, but also enables the development of a novel screening tool to predict infection status. Our data further suggest that pharmacological targeting of MDSCs represents a novel strategy for addressing PJI.

Extracellular vesicles (EVs) comprise an as yet insufficiently investigated intercellular communication pathway in the field of revision total joint arthroplasty (RTJA). This study examined whether periprosthetic joint synovial fluid contains EVs, developed a protocol for their isolation and characterized them with respect to quantity, size, surface markers as well as documented their differences between aseptic implant failure (AIF) and periprosthetic joint infection (PJI). EV isolation was accomplished using ultracentrifugation, electron microscopy (EM) and nanoparticle tracking analysis evaluated EV presence as well as particle size and quantity. EV surface markers were studied by a bead-based multiplex analysis. Using our protocol, EM confirmed the presence of EVs in periprosthetic joint synovial fluid. Higher EV particle concentrations and decreased particle sizes were apparent for PJI. Multiplex analysis confirmed EV-typical surface epitopes and revealed upregulated CD44 and HLA-DR/DP/DQ for AIF, as well as increased CD40 and CD105. Our protocol achieved isolation of EVs from periprosthetic joint synovial fluid, confirmed by EM and multiplex analysis. Characterization was documented with respect to size, concentration and epitope surface signature. Our results indicate various differences between PJI and AIF EVs. This pilot study enables new research approaches and rising diagnostic opportunities in the field of RTJA.

The role and diagnostic value of the synovial complement system in patients with low-grade periprosthetic joint infection (PJI) are unclear. We sought to evaluate, for the first time, the usefulness of synovial complement factors in these patients by measuring the individual synovial fluid levels of complement factors (C1q, C3b/iC3b, C4b, C5, C5a, C9, factor B, factor D, factor H, factor I, properdin, and mannose-binding lectin [MBL]). The patients (n = 74) were classified into septic (n = 28) and aseptic (n = 46). Receiver-operator characteristic curves and a multiple regression model to determine the feasibility of a combination of the tested cytokines to determine the infection status were calculated. The synovial fluid levels of C1q, C3b/C3i, C4b, C5, C5a, MBL, and properdin were significantly elevated in the PJI group. The best sensitivity and specificity was found for C1q. The multiple regression models revealed that the combination of C1q, C3b/C3i, C4b, C5, C5a, and MBL was associated with the best sensitivity (83.3%) and specificity (79.2%) for a cutoff value of 0.62 (likelihood ratio: 4.0; area under the curve: 0.853). Nevertheless, only a combined model showed acceptable results. The expression patterns of the complement factors suggested that PJI activates all three pathways of the complement system.

Introduction: The complex field of femoral defects in revision hip arthroplasty displays a lack of standardized, intuitive pre- and intraoperative assessment. To address this issue, the femoral defect classification (FDC) is introduced to offer a reliable, reproducible and an intuitive classification system with a clear therapeutic guideline. Materials and methods: The FDC is based on the integrity of the main femoral segments which determine function and structural support. It focuses on the femoral neck, the metaphysis consisting of the greater and lesser trochanter, and the femoral diaphysis. The four main categories determine the location of the defect while subcategories a, b and c are being used to classify the extent of damage in each location. In total, 218 preoperative radiographs were retrospectively graded according to FDC and compared to intraoperatively encountered bone defects. To account for inter-rater and intra-rater agreement, 5 different observers evaluated 80 randomized cases at different points in time. Results: A Cohens kappa of 0.832 ± 0.028 could be evaluated, accounting for excellent agreement between preoperative radiographs and intraoperative findings. To account for inter-rater reliability, 80 patients have been evaluated by 5 different observers. Testing for inter-rater reliability, a Fleiss Kappa of 0.688 could be evaluated falling into the good agreement range. When testing for intra-rater reliability, Cohens Kappa of each of the 5 raters has been analyzed and the mean was evaluated at 0.856 accounting for excellent agreement. Conclusion: The FDC is a reliable and reproducible classification system. It combines intuitive use and structured design and allows for consistent preoperative planning and intraoperative guidance. A therapeutic algorithm has been created according to current literature and expert opinion. Due to the combination of the FDC with the recently introduced Acetabular Defect Classification (ADC) a structured approach to the entire field of hip revision arthroplasty is now available.

Introduction: Acetabular defect recognition and classification remains a challenging field of practice for orthopedic surgeons. Recently, the Acetabular Defect Classification (ADC) has been introduced to provide a reliable, reproducible and intuitive classification system. In order to improve ease of use and efficiency of the ADC, a browser-based application has been created. We hypothesized that the ADC application can improve rating performance of non-specialists (medical students) to achieve good inter- and intra-rater agreement and will compare favorable to the results of specialists (experienced surgeons) without the help of the application. Materials and methods: The ADC is based on the integrity of the acetabular rim and the supporting structures. It consists of four main types of defects ascending in severity. These defects are further subdivided in A–C, narrowing down defect location. 80 randomized radiographs were graded according to ADC by three non-specialists (medical students) with help of the ADC application and by three specialists (orthopedic surgeons) without help of the application to evaluate the difference in inter-rater agreement between groups. To account for intra-rater agreement, the rating process was repeated after a reasonable wash-out period. Results: Inter-rater and intra-rater agreement within the non-specialist group rated lower when compared to the specialist group while still falling into the good agreement range. The student group presented with k values of 0.61 for inter-rater agreement and 0.68 for intra-rater agreement, while the surgeon group displayed k values of 0.72 for inter-rater agreement and 0.83 for intra-rater agreement. Conclusion: The app-guided assessment of acetabular defects offers a promising innovative approach to simplify complex situations. It makes the challenging field of acetabular revision arthroplasty more approachable especially for less experienced surgeons and offers insight and guidance in the planning stage as well as intra-operative setting.