Dual-Energy Computed Tomography Iodine Maps: Application in the Diagnosis of Periprosthetic Joint Infection in Total Hip Arthroplasty.

BACKGROUND: The challenge of early and rapid diagnosis of periprosthetic joint infection (PJI) remains important. This study aimed to assess the efficacy of dual-energy computed tomography (DECT) iodine maps for diagnosing PJI in total hip arthroplasty. METHODS: We prospectively enrolled 68 patients who had postoperative joint pain after hip arthroplasty. All patients underwent preoperative DECT iodine imaging to quantify iodine concentration (IC) in periprosthetic tissues during arterial and venous phases. The diagnostic efficacy of DECT iodine maps was evaluated by constructing receiver operating characteristic curves according to the Musculoskeletal Infection Society criteria. RESULTS: Compared with erythrocyte sedimentation rate (area under the curve [AUC] = 0.837), polymorphonuclear cell percentage (AUC = 0.703), and C-reactive protein (AUC = 0.837), periprosthetic tissue venous-phase IC (AUC = 0.970) and arterial-phase IC (AUC = 0.964) exhibited outstanding discriminative capability between PJI and aseptic failure. The PJI cut-off point was venous IC = 1.225 mg/mL, with a sensitivity of 92.31% and specificity of 90.48%; for arterial IC = 1.065 mg/mL, the sensitivity was 96.15% and specificity was 90.70%. CONCLUSIONS: This study demonstrates the great potential of DECT iodine maps for the diagnosis of PJI around hip arthroplasty, which helps to differentiate between periprosthetic infection and aseptic failure after hip arthroplasty.

Current Status and Perspectives of Diagnosis and Treatment of Periprosthetic Joint Infection.

Periprosthetic joint infection (PJI) is a catastrophic complication following joint replacement surgery, posing significant challenges to orthopedic surgeons. Due to the lack of a definitive diagnostic gold standard, timely treatment initiation is problematic, resulting in substantial economic burdens on patients and society. In this review, we thoroughly analyze the complexities of PJI and emphasize the importance of accurate diagnosis and effective treatment. The article specifically focuses on the advancements in diagnostic techniques, ranging from traditional pathogen culture to advanced molecular diagnostics, and discusses their role in enhancing diagnostic accuracy. Additionally, we review the latest surgical management strategies, including everything from debridement to revision surgeries. Our summary aims to provide practical information for the diagnosis and treatment of PJI and encourages further research to improve diagnostic accuracy and treatment outcomes.

Prospects and challenges for the application of tissue engineering technologies in the treatment of bone infections.

Osteomyelitis is a devastating disease caused by microbial infection in deep bone tissue. Its high recurrence rate and impaired restoration of bone deficiencies are major challenges in treatment. Microbes have evolved numerous mechanisms to effectively evade host intrinsic and adaptive immune attacks to persistently localize in the host, such as drug-resistant bacteria, biofilms, persister cells, intracellular bacteria, and small colony variants (SCVs). Moreover, microbial-mediated dysregulation of the bone immune microenvironment impedes the bone regeneration process, leading to impaired bone defect repair. Despite advances in surgical strategies and drug applications for the treatment of bone infections within the last decade, challenges remain in clinical management. The development and application of tissue engineering materials have provided new strategies for the treatment of bone infections, but a comprehensive review of their research progress is lacking. This review discusses the critical pathogenic mechanisms of microbes in the skeletal system and their immunomodulatory effects on bone regeneration, and highlights the prospects and challenges for the application of tissue engineering technologies in the treatment of bone infections. It will inform the development and translation of antimicrobial and bone repair tissue engineering materials for the management of bone infections.

Diagnostic and Predictive Efficacy of Synovial Fluid Versus Serum C-Reactive Protein Levels for Periprosthetic Joint Infection and Reimplantation Success.

BACKGROUND: A 2-stage exchange revision for periprosthetic joint infection (PJI) is associated with major risks for reinfection. Although serum markers are frequently used for diagnosis, their effectiveness remains debatable. Synovial fluid markers may offer a more accurate diagnosis of PJI; however, the importance of these biomarkers, notably synovial fluid C-reactive protein (syCRP), remains controversial, particularly in the context of reimplantation. The present study aimed to clarify these diagnostic uncertainties by evaluating the diagnostic efficacy of syCRP versus serum CRP (seCRP) levels in the context of PJI and recurring or persisting infections before reimplantation. METHODS: A total of 186 patients were enrolled and divided into 2 groups: aseptic revision (n = 112) and PJI revision (n = 74). Of the PJI group, 65 were categorized as success and 9 as failure, based on the presence of recurrent or persistent infection before reimplantation. The syCRP and seCRP levels and their changes were assessed preoperatively and in the first-stage and second-stage revisions. Additionally, receiver operating characteristic (ROC) curves and area under the ROC curves (AUCs) were analyzed. RESULTS: Both seCRP and syCRP levels were significantly elevated in the PJI group compared with the aseptic group (P < .001). The ROC curve analysis highlighted the enhanced diagnostic accuracy of syCRP for PJI, with an AUC of 0.93 versus 0.80 for seCRP. Furthermore, syCRP proved to be more reliable in predicting reimplantation success, exhibiting an AUC of 0.86 versus 0.63 for seCRP. In evaluating trends in CRP levels to determine reimplantation timing, changes in syCRP levels demonstrated superior diagnostic utility, exhibiting an AUC of 0.79 versus 0.63 for changes in seCRP levels. CONCLUSIONS: In assessing PJI and infections before reimplantation, syCRP may offer enhanced accuracy compared with seCRP. Nevertheless, variations in both syCRP and seCRP levels did not consistently predict the outcome of reimplantation.

PI3K-Akt signaling regulates BMP2-induced osteogenic differentiation of mesenchymal stem cells (MSCs): A transcriptomic landscape analysis.

Bone morphogenetic protein 2 (BMP2) effectively induced mesenchymal stem cells (MSCs) osteogenic differentiation hold great potential for bone tissue engineering. However, a global mechanistic view of BMP2-induced osteogenic differentiation of MSCs remains to be fully elucidated. Here, human umbilical cord-derived MSCs (UC-MSCs) were induced with BMP2, three days and five days later, total RNA were extracted and subjected to RNA-sequencing (RNA-Seq) followed with bioinformatic analysis. Osteogenic differentiation abilities were evaluated with Alkaline phosphatase (ALP) staining and osteogenic differentiation marker expression at both mRNA and protein levels. We identified that adenoviral vectors effectively transduced in UC-MSCs and expressed BMP2 in high efficiency. Both on day 3 and day 5, differentially expressed genes (DEGs) were highly enriched in PI3K-Akt signaling pathway. As for the common DEGs among total BMP2 group vs control group, BMP2 (day 3) versus control (day 3) and BMP2 (day 5) versus control (day 5), there were 105 DGEs and highly enriched in PI3K-Akt signaling pathway. Finally, we found that PI3K-Akt signaling inhibitor dramatically inhibited BMP2-iduced osteogenic differentiation of UC-MSCs. We firstly identified that PI3K-Akt signaling pathway plays a pivotal role in BMP2-induced osteogenic differentiation of MSCs, which may apply a new perspective for BMP2 based bone tissue engineering.

Development and validation of nomograms for predicting survival of elderly patients with stage I small-cell lung cancer.

There is a lack of predictive models to determine the prognosis of elderly patients diagnosed with Stage I small-cell lung cancer (SCLC). The purpose of this study was to establish a useful nomogram to predict cancer-specific survival (CSS) in the elderly patient population. Based on the Surveillance, Epidemiology, and End Results registry database, patients aged ≥ 65 years with pathological AJCC (American Joint Committee on Cancer) Stage I SCLC from 2004 to 2014 were identified. The CSS was evaluated by the Kaplan-Meier method. Patients were randomly split into training and validation sets. In the training cohort, univariate analysis and multivariate analysis using the Cox regression identified risk factors that affected CSS, and the results were utilized to construct a nomogram for prediction of the 1-, 3-, and 5-year CSS rates of elderly patients with Stage I SCLC. The effectiveness of the nomogram was validated internally and externally by the bootstrap method. The clinical practicability and accuracy of the nomogram were evaluated by the concordance index (C-index), calibration curve, receiver operating characteristic curve, and decision curve analysis. In total, we extracted 1,623 elderly patients with Stage I SCLC. The median CSS was 34 months, and the 5-year CSS was 41%. Multivariate analysis revealed that histologic type, tumor size, age, and AJCC Stage were significant predictors of CSS. A nomogram was constructed according to the results of multivariate COX analysis. The C-indices of the nomogram for training and validation sets were 0.68 and 0.62, indicating that the nomogram demonstrated a favorable level of discrimination. The calibration curves exhibited satisfactory agreement between the actual observation and nomogram prediction. The net benefit of the nomogram was better than the AJCC TNM staging. A practical nomogram to predict the CSS of elderly patients with Stage I SCLC is constructed. The predictive tool is helpful for patient counseling and treatment decision-making.