A Low Percentage of Patients Satisfy Typical Indications for Single-stage Exchange Arthroplasty for Chronic Periprosthetic Joint Infection.

BACKGROUND: Periprosthetic joint infection (PJI) is a leading cause of revision arthroplasty. Considerable controversy still exists whether single- or two-stage exchange is the better approach for patients with chronic PJI. Historically, single-stage exchange arthroplasty was thought to have an unacceptably high risk of reinfection compared with two-stage exchange but recent studies have demonstrated that this may not be the case. To be considered for single-stage exchange, patients should meet certain criteria including a preoperatively identified nonvirulent pathogen in an immunocompetent host with an uncompromised soft tissue envelope. It is unclear what proportion of patients with chronic PJI actually meet these criteria. Additionally, patients who meet the criteria for single-stage exchange are selected because, in principle, they may be more likely to be able to overcome the infection, but it is unknown what the reinfection risk is in patients undergoing two-stage exchange who might have met selection criteria for single-stage exchange. QUESTIONS/PURPOSES: (1) What percentage of patients with chronic PJI treated at our institution met the International Consensus Meeting criteria for single-stage exchange arthroplasty? (2) Is the risk of persistent or recurrent infection lower for patients treated with two-stage exchange who met International Consensus Meeting criteria for single-stage exchange than it is among those who did not meet those inclusion criteria? METHODS: Between 2012 and 2016, one referral center treated 120 patients with chronic PJI as determined by Musculoskeletal Infection Society (MSIS) criteria. During this time, we used single-stage exchange only rarely in patients with chronic PJI (3%; four of 120), and only in oncologic patients with mega-prosthesis implants; 7% (eight of 120) underwent other procedures (resection arthroplasty or arthrodesis). Of the remaining 108, 16% (17) were lost to follow-up; the remaining 91 were evaluated in this retrospective study. To answer our first question, we applied the International Consensus Meeting indications for single-stage exchange, which were a known nonvirulent preoperative organism, an immunocompetent host, and a healthy soft-tissue envelope without a sinus tract; we then calculated the percentage of patients who would have met those criteria. To answer our second question, we compared those who would and would not have met those criteria in terms of the proportion who were determined to be infection-free at 2 years using the MSIS criteria. RESULTS: Only 19% (20 of 108) of patients met the International Consensus Meeting criteria for single-stage exchange. With the numbers available, there was no difference between those who met and did not meet those criteria in terms of the proportion of patients who had persistent or recurrent infection 2 years after treatment (three of 15 versus 32% [24 of 76]; p = 0.38). CONCLUSIONS: We found that only a small proportion of patients who presented with chronic PJI to a referral center would have been suitable for single-stage direct exchange; with the numbers available, we found no difference in the reinfection risk after two-stage revision in those patients compared with those who would not have met those criteria. Consequently, it is possible that a small proportion of patients may benefit from single-stage exchange, but our small sample size may have missed important differences in reinfection risk, and so our findings on that question must be considered preliminary. Larger studies randomizing patients who meet single-stage criteria to either single- or two-stage exchange will better elucidate the true reinfection risk in this patient population. LEVEL OF EVIDENCE: Level III, therapeutic study.

T2 texture index of cartilage can predict early symptomatic OA progression: data from the osteoarthritis initiative.

OBJECTIVE: There is an interest in using Magnetic Resonance Imaging (MRI) to identify pre-radiographic changes in osteoarthritis (OA) and features that indicate risk for disease progression. The purpose of this study is to identify image features derived from MRI T2 maps that can accurately predict onset of OA symptoms in subjects at risk for incident knee OA. METHODS: Patients were selected from the Osteoarthritis Initiative (OAI) control cohort and incidence cohort and stratified based on the change in total Western Ontario and McMaster Universities Arthritis (WOMAC) score from baseline to 3-year follow-up (80 non-OA progression and 88 symptomatic OA progression patients). For each patient, a series of image texture features were measured from the baseline cartilage T2 map. A linear discriminant function and feature reduction method was then trained to quantify a texture metric, the T2 texture index of cartilage (TIC), based on 22 image features, to identify a composite marker of T2 heterogeneity. RESULTS: Statistically significant differences were seen in the baseline T2 TIC between the non-progression and symptomatic OA progression populations. The baseline T2 TIC differentiates subjects that develop worsening of their WOMAC score OA with an accuracy between 71% and 76%. The T2 TIC differences were predominantly localized to a dominant knee compartment that correlated with the mechanical axis of the knee. CONCLUSION: Baseline heterogeneity in cartilage T2 as measured with the T2 TIC index is able to differentiate and predict individuals that will develop worsening of their WOMAC score at 3-year follow-up.

Automated classification and visualization of fluorescent live cell microscopy images.

Robotic, high-throughput microscopy is a powerful tool for small molecule screening and classifying cell phenotype, proteomic and genomic data. An important hurdle in the field is the automated classification and visualization of results collected from a data set of tens of thousands of images. We present a method that approaches these problems from the perspective of flow cytometry with supporting open-source code. Image analysis software was created that allowed high-throughput microscopy data to be analysed in a similar manner as flow cytometry. Each cell on an image is considered an object and a series of gates similar to flow cytometry is used to classify and quantify the properties of cells including size and level of fluorescent intensity. This method is released with open-source software and code that demonstrates the method's implementation. Accuracy of the software was determined by measuring the levels of apoptosis in a primary murine myoblast cell line after exposure to staurosporine and comparing these results to flow cytometry.