Vincent B. Nessler

Total joint arthroplasty is among the most common surgical procedures performed worldwide, with frequency increasing due to demographic changes. Accelerating the diagnostic process using new techniques is crucial for effective therapy. This pilot study aims to test such innovative technology in the context of periprosthetic joint infection (PJI) using Scattered Light Integrating Collector (SLIC) technology. While we wish to evaluate whether SLIC can be used to reliably detect the status of infection within human tissue samples in the future, our current research focused on building its foundation by evaluating steps of sample preparation that allow for heightened growth depiction. It is, to our knowledge, the first study concerning the usage of solid human tissue samples using the SLIC device. Adult patients presenting with native or periprosthetic joint infections were included in this prospective study. Biopsies were obtained using sequential sampling, and bacterial density was optimized through titration series. Cryopreservation and agents influencing coagulation were investigated. Our study demonstrates that simple pretreatment could aid in detecting pathogen growth in infected tissue samples. Findings showed a clear advantage for no addition of agents affecting coagulation. Additionally, our protocols proved reliable after prolonged cryopreservation at −20 °C for up to 8 weeks, showing no significant difference compared to primary testing. AUC comparison showed comparable results for sample storage at −80 °C for up to 8 weeks. Similar outcomes were seen for samples ranging from 25 µL to 300 µL, with biological replicates displaying higher thresholds for larger volumes without significant differences. This study introduces a simple and quick diagnostic tool for detecting bacterial growth using tissue biopsies and develops an SOP for further research with this innovative technique. The suggested SOP enables SLIC to hint at an underlying bacterial infection within 5 h using joint tissue, offering a possible novel approach in diagnosing periprosthetic joint infections and septic arthritis. While not yet designed to compare sensitivity to other culture methods, it provides a solid basis for further clinical research.

Bacterial antibiotic resistance is an important challenge that the healthcare system is continually battling and a major problem in the treatment of musculoskeletal infections such as periprosthetic joint infections. Current methods to identify infectious microbes and define susceptibility to antibiotics require two to ten days from isolation to the establishment of an antibiogram. This slow process limits advances in antimicrobial drug discovery and, in the clinical context, delays the delivery of targeted treatments, with potentially devastating outcomes for patients. With this in mind, we strived to establish a quicker and more sensitive method to deliver antibiotic susceptibility profiles of clinically relevant microbes using Scattered Light Integrated Collector (SLIC) technology. We established antibiotic panels to obtain an approximate identification of a wide variety of microbes linked to periprosthetic joint infections and determine their susceptibility to antibiotics. We challenged microbes isolated from patients with our tailored antibiotic panels and found that SLIC detects perturbations in bacterial growth accurately and reproducibly within minutes of culture. Indeed, we could show that SLIC can be used to measure the dose-dependent inhibitory or bacteriolytic activity of broad classes of antibiotics. Our panel design enabled us to establish a profile similar to an antibiogram for the tested bacteria within 90 min. Our method can provide information on the class of bacteria tested and potential treatment avenues in parallel. Our proof-of-principle experiments using isolated clinical strains of bacteria demonstrate that SLIC, together with our specifically designed antibiotic panels, could be used to rapidly provide information on the identity of an infecting microbe, such as those associated with periprosthetic joint infections, and guide physicians to prescribe targeted antibiotic treatment early-on. The constant emergence of resistant strains of bacteria pushes the pharmaceutical industry to develop further effective drugs. Our optimized method could significantly accelerate this work by characterizing the efficacy of new classes of compounds against bacterial viability within minutes, a timeframe far shorter than the current standards.