Diagnostic Accuracy of Quantitative Multicontrast 5-Minute Knee MRI Using Prospective Artificial Intelligence Image Quality Enhancement.

BACKGROUND. Potential approaches for abbreviated knee MRI, including prospective acceleration with deep learning, have achieved limited clinical implementation. OBJECTIVE. The objective of this study was to evaluate the interreader agreement between conventional knee MRI and a 5-minute 3D quantitative double-echo steady-state (qDESS) sequence with automatic T2 mapping and deep learning super-resolutionaugmentation and to compare the diagnostic performance of the two methods regarding findings from arthroscopic surgery. METHODS. Fifty-one patients with knee pain underwent knee MRI that included an additional 3D qDESS sequence with automatic T2 mapping. Fourier interpolation was followed by prospective deep learning super resolution to enhance qDESS slice resolution twofold. A musculoskeletal radiologist and a radiology resident performed independent retrospective evaluations of articular cartilage, menisci, ligaments, bones, extensor mechanism, and synovium using conventional MRI. Following a 2-month washout period, readers reviewed qDESS images alone followed by qDESS with the automatic T2 maps. Interreader agreement between conventional MRI and qDESS was computed using percentage agreement and Cohen kappa. The sensitivity and specificity of conventional MRI, qDESS alone, and qDESS plus T2 mapping were compared with arthroscopic findings using exact McNemar tests. RESULTS. Conventional MRI and qDESS showed 92% agreement in evaluating all tissues. Kappa was 0.79 (95% CI, 0.76-0.81) across all imaging findings. In 43 patients who underwent arthroscopy, sensitivity and specificity were not significantly different (p = .23 to > .99) between conventional MRI (sensitivity, 58-93%; specificity, 27-87%) and qDESS alone (sensitivity, 54-90%; specificity, 23-91%) for cartilage, menisci, ligaments, and synovium. For grade 1 cartilage lesions, sensitivity and specificity were 33% and 56%, respectively, for conventional MRI; 23% and 53% for qDESS (p = .81); and 46% and 39% for qDESS with T2 mapping (p = .80). For grade 2A lesions, values were 27% and 53% for conventional MRI, 26% and 52% for qDESS (p = .02), and 58% and 40% for qDESS with T2 mapping (p < .001). CONCLUSION. The qDESS method prospectively augmented with deep learning showed strong interreader agreement with conventional knee MRI and near-equivalent diagnostic performance regarding arthroscopy. The ability of qDESS to automatically generate T2 maps increases sensitivity for cartilage abnormalities. CLINICAL IMPACT. Using prospective artificial intelligence to enhance qDESS image quality may facilitate an abbreviated knee MRI protocol while generating quantitative T2 maps.

Synovial Fluid Lubricant Properties are Transiently Deficient after Arthroscopic Articular Cartilage Defect Repair with Platelet-Enriched Fibrin Alone and with Mesenchymal Stem Cells.

BACKGROUND: Following various types of naturally-occurring traumatic injury to an articular joint, the lubricating ability of synovial fluid is impaired, with a correlated alteration in the concentration and/or structure of lubricant molecules, hyaluronan and proteoglycan-4. However, the effect of arthroscopic cartilage repair surgery on synovial fluid lubricant function and composition is unknown. HYPOTHESIS: Arthroscopic treatment of full-thickness chondral defects in horses with (1) platelet-enriched fibrin or (2) platelet-enriched fibrin+mesenchymal stem cells leads to equine synovial fluid with impaired lubricant function and hyaluronan and proteoglycan-4 composition. STUDY DESIGN: Controlled Laboratory Study. METHODS: Equine synovial fluid was aspirated from normal joints at a pre-injury state (0 days) and at 10 days and 3 months following fibrin or fibrin+mesenchymal stem cell repair of full thickness chondral defects. Equine synovial fluid samples were analyzed for friction-lowering boundary lubrication of normal articular cartilage (static and kinetic friction coefficients) and concentrations of hyaluronan and proteoglycan-4, as well as molecular weight distribution of hyaluronan. Experimental groups deficient in lubrication function were also tested for the ability of exogenous high-molecular weight hyaluronan to restore lubrication function. RESULTS: Lubrication and biochemical data varied with time after surgery but generally not between repair groups. Relative to pre-injury, kinetic friction was higher (+94%) at 10 days but returned to baseline levels at 3 months while static friction was not altered. Correspondingly, hyaluronan concentration was transiently lower (-64%) and shifted towards lower molecular weight forms, while proteoglycan-4 concentration was increased (+210%) in 10-day samples relative to pre-injury levels. Regression analysis revealed that kinetic friction decreased with increasing total and high molecular weight hyaluronan. Addition of high molecular weight hyaluronan to bring 10-day hyaluronan levels to 2.0mg/ml restored kinetic friction to pre-injury levels. CONCLUSION: Following arthroscopic surgery for cartilage defect repair, synovial fluid lubrication function is transiently impaired, in association with decreased hyaluronan concentration. This functional deficiency in synovial fluid lubrication can be counteracted in vitro by addition of high molecular weight hyaluronan. CLINICAL RELEVANCE: Synovial fluid lubrication is deficient shortly following arthroscopic cartilage repair surgery, and supplementation with high molecular weight hyaluronan may be beneficial.