Advanced MRI Approaches for Evaluating Common Lower Extremity Injuries in Basketball Players: Current and Emerging Techniques.

Magnetic resonance imaging (MRI) can provide accurate and non-invasive diagnoses of lower extremity injuries in athletes. Sport-related injuries commonly occur in and around the knee and can affect the articular cartilage, patellar tendon, hamstring muscles, and bone. Sports medicine physicians utilize MRI to evaluate and diagnose injury, track recovery, estimate return to sport timelines, and assess the risk of recurrent injury.

Improving Data-Efficiency and Robustness of Medical Imaging Segmentation Using Inpainting-Based Self-Supervised Learning.

We systematically evaluate the training methodology and efficacy of two inpainting-based pretext tasks of context prediction and context restoration for medical image segmentation using self-supervised learning (SSL). Multiple versions of self-supervised U-Net models were trained to segment MRI and CT datasets, each using a different combination of design choices and pretext tasks to determine the effect of these design choices on segmentation performance. The optimal design choices were used to train SSL models that were then compared with baseline supervised models for computing clinically-relevant metrics in label-limited scenarios.

Generalizability of Deep Learning Segmentation Algorithms for Automated Assessment of Cartilage Morphology and MRI Relaxometry.

Background: Deep learning (DL)-based automatic segmentation models can expedite manual segmentation yet require resource-intensive fine-tuning before deployment on new datasets. The generalizability of DL methods to new datasets without fine-tuning is not well characterized.

Purpose: Evaluate the generalizability of DL-based models by deploying pretrained models on independent datasets varying by MR scanner, acquisition parameters, and subject population.

Open Source Software for Automatic Subregional Assessment of Knee Cartilage Degradation Using Quantitative T2 Relaxometry and Deep Learning.

Objective: We evaluated a fully automated femoral cartilage segmentation model for measuring T2 relaxation values and longitudinal changes using multi-echo spin-echo (MESE) magnetic resonance imaging (MRI). We open sourced this model and developed a web app available at https://kl.stanford.

Effects of the Competitive Season and Off-Season on Knee Articular Cartilage in Collegiate Basketball Players Using Quantitative MRI: A Multicenter Study.

Background: Injuries to the articular cartilage in the knee are common in jumping athletes, particularly high-level basketball players. Unfortunately, these are often diagnosed at a late stage of the disease process, after tissue loss has already occurred.

Purpose/hypothesis: To evaluate longitudinal changes in knee articular cartilage and knee function in National Collegiate Athletic Association (NCAA) basketball players and their evolution over the competitive season and off-season.

Rapid volumetric gagCEST imaging of knee articular cartilage at 3 T: evaluation of improved dynamic range and an osteoarthritic population.

Chemical exchange saturation transfer of glycosaminoglycans, gagCEST, is a quantitative MR technique that has potential for assessing cartilage proteoglycan content at field strengths of 7 T and higher. However, its utility at 3 T remains unclear. The objective of this work was to implement a rapid volumetric gagCEST sequence with higher gagCEST asymmetry at 3 T to evaluate its sensitivity to osteoarthritic changes in knee articular cartilage and in comparison with T and T measures.

Does Injection of Hyaluronic Acid Protect Against Early Cartilage Injury Seen After Marathon Running? A Randomized Controlled Trial Utilizing High-Field Magnetic Resonance Imaging.

Background: Previous studies have shown that runners demonstrate elevated T2 and T1ρ values on magnetic resonance imaging (MRI) after running a marathon, with the greatest changes in the patellofemoral and medial compartment, which can persist after 3 months of reduced activity. Additionally, marathon running has been shown to increase serum inflammatory markers. Hyaluronic acid (HA) purportedly improves viscoelasticity of synovial fluid, serving as a lubricant while also having chondroprotective and anti-inflammatory effects.

Assessing the Effectiveness of Evidence-Based Medicine in Practice: A Case Study of First-Time Anterior Shoulder Dislocations.

Background: The dissemination of evidence-based information into medical practice is essential to provide patients with optimal care and realize society's substantial investments in medical research. Effective information delivery and treatment utilization may lead to improvements in patient outcome, reductions in cost, and an overall lower burden on the health-care system. This study examines the dissemination of medical evidence following a first-time anterior shoulder dislocation (FTASD) and assesses the impact of potential dissemination strategies.