The prevalence of femoroacetabular impingement anatomy in Division 1 aquatic athletes who tread water

Abstract Femoroacetabular impingement (FAI) is a disorder that causes hip pain and disability in young patients, particularly athletes. Increased stress on the hip during development has been associated with increased risk of cam morphology. The specific forces involved are unclear, but may be due to continued rotational motion, like the eggbeater kick. The goal of this prospective cohort study was to use magnetic resonance imaging (MRI) to identify the prevalence of FAI anatomy in athletes who tread water and compare it to the literature on other sports. With university IRB approval, 20 Division 1 water polo players and synchronized swimmers (15 female, 5 male), ages 18–23 years (mean age 20.7 ± 1.4), completed the 33-item International Hip Outcome Tool and underwent non-contrast MRI scans of both hips using a 3 Tesla scanner. Recruitment was based on sport, with both symptomatic and asymptomatic individuals included. Cam and pincer morphology were identified. The Wilcoxon Signed-Rank/Rank Sum tests were used to assess outcomes. Seventy per cent (14/20) of subjects reported pain in their hips yet only 15% (3/20) sought clinical evaluation. Cam morphology was present in 67.5% (27/40) of hips, while 22.5% (9/40) demonstrated pincer morphology. The prevalence of cam morphology in water polo players and synchronized swimmers is greater than that reported for the general population and at a similar level as some other sports. From a clinical perspective, acknowledgment of the high prevalence of cam morphology in water polo players and synchronized swimmers should be considered when these athletes present with hip pain

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femoral, tibial, patellar) cartilage and meniscus segmentations was standardized. Challenge submissions and a majority-vote ensemble were evaluated using Dice score, average symmetric surface distance, volumetric overlap error, and coefficient of variation on a hold-out test set. Similarities in network segmentations were evaluated using pairwise Dice correlations. Articular cartilage thickness was computed per-scan and longitudinally. Correlation between thickness error and segmentation metrics was measured using Pearson's coefficient. Two empirical upper bounds for ensemble performance were computed using combinations of model outputs that consolidated true positives and true negatives. Results: Six teams (T1-T6) submitted entries for the challenge. No significant differences were observed across all segmentation metrics for all tissues (p=1.0) among the four top-performing networks (T2, T3, T4, T6). Dice correlations between network pairs were high (>0.85). Per-scan thickness errors were negligible among T1-T4 (p=0.99) and longitudinal changes showed minimal bias (<0.03mm). Low correlations (<0.41) were observed between segmentation metrics and thickness error. The majority-vote ensemble was comparable to top performing networks (p=1.0). Empirical upper bound performances were similar for both combinations (p=1.0). Conclusion: Diverse networks learned to segment the knee similarly where high segmentation accuracy did not correlate to cartilage thickness accuracy. Voting ensembles did not outperform individual networks but may help regularize individual models.Comment: Submitted to Radiology: Artificial Intelligence; Fixed typo

Recommendations for defining preventable HIV-related mortality for public health monitoring in the era of Getting to Zero: an expert consensus

Getting to Zero is a commonly cited strategic aim to reduce mortality due to both HIV and avoidable deaths among people with HIV. However, no clear definitions are attached to these aims with regard to what constitutes HIV-related or preventable mortality, and their ambition is limited. This Position Paper presents consensus recommendations to define preventable HIV-related mortality for a pragmatic approach to public health monitoring by use of national HIV surveillance data. These recommendations were informed by a comprehensive literature review and agreed by 42 international experts, including clinicians, public health professionals, researchers, commissioners, and community representatives. By applying the recommendations to 2019 national HIV surveillance data from the UK, we show that 30% of deaths among people with HIV were HIV-related or possibly HIV-related, and at least 63% of these deaths were preventable or potentially preventable. The application of these recommendations by health authorities will ensure consistent monitoring of HIV elimination targets and allow for the identification of inequalities and areas for intervention

pyKNEEr: An image analysis workflow for open and reproducible research on femoral knee cartilage.

Transparent research in musculoskeletal imaging is fundamental to reliably investigate diseases such as knee osteoarthritis (OA), a chronic disease impairing femoral knee cartilage. To study cartilage degeneration, researchers have developed algorithms to segment femoral knee cartilage from magnetic resonance (MR) images and to measure cartilage morphology and relaxometry. The majority of these algorithms are not publicly available or require advanced programming skills to be compiled and run. However, to accelerate discoveries and findings, it is crucial to have open and reproducible workflows. We present pyKNEEr, a framework for open and reproducible research on femoral knee cartilage from MR images. pyKNEEr is written in python, uses Jupyter notebook as a user interface, and is available on GitHub with a GNU GPLv3 license. It is composed of three modules: 1) image preprocessing to standardize spatial and intensity characteristics; 2) femoral knee cartilage segmentation for intersubject, multimodal, and longitudinal acquisitions; and 3) analysis of cartilage morphology and relaxometry. Each module contains one or more Jupyter notebooks with narrative, code, visualizations, and dependencies to reproduce computational environments. pyKNEEr facilitates transparent image-based research of femoral knee cartilage because of its ease of installation and use, and its versatility for publication and sharing among researchers. Finally, due to its modular structure, pyKNEEr favors code extension and algorithm comparison. We tested our reproducible workflows with experiments that also constitute an example of transparent research with pyKNEEr, and we compared pyKNEEr performances to existing algorithms in literature review visualizations. We provide links to executed notebooks and executable environments for immediate reproducibility of our findings

Potential of PET-MRI for imaging of non-oncologic musculoskeletal disease

Early detection of musculoskeletal disease leads to improved therapies and patient outcomes, and would benefit greatly from imaging at the cellular and molecular level. As it becomes clear that assessment of multiple tissues and functional processes are often necessary to study the complex pathogenesis of musculoskeletal disorders, the role of multi-modality molecular imaging becomes increasingly important. New positron emission tomography-magnetic resonance imaging (PET-MRI) systems offer to combine high-resolution MRI with simultaneous molecular information from PET to study the multifaceted processes involved in numerous musculoskeletal disorders. In this article, we aim to outline the potential clinical utility of hybrid PET-MRI to these non-oncologic musculoskeletal diseases. We summarize current applications of PET molecular imaging in osteoarthritis (OA), rheumatoid arthritis (RA), metabolic bone diseases and neuropathic peripheral pain. Advanced MRI approaches that reveal biochemical and functional information offer complementary assessment in soft tissues. Additionally, we discuss technical considerations for hybrid PET-MR imaging including MR attenuation correction, workflow, radiation dose, and quantification

Approach to MR Imaging of the Elbow and Wrist Technical Aspects and Innovation

Wrist and elbow MR imaging technology is advancing at a dramatic rate. Wrist and elbow MR imaging is performed at medium and higher field strengths with more specialized surface coils and more variable pulse sequences and postprocessing techniques. High field imaging and improved coils lead to an increased signal-to-noise ratio and increased variety of soft tissue contrast options. Three-dimensional imaging is improving in terms of usability and artifacts. Some of these advances have challenges in wrist and elbow imaging, such as postoperative patient imaging, cartilage mapping, and molecular imaging. This review considers technical advances in hardware and software and their clinical applications

Cross‐relaxation imaging of human articular cartilage

In this paper, cross-relaxation imaging (CRI) is applied to human ex vivo knee cartilage, and correlations of the CRI parameters with macromolecular content in articular cartilage are reported. We show that, unlike the more commonly used magnetization transfer ratio (MTR), the bound pool fraction (BPF), the cross-relaxation rate (k) and the longitudinal relaxation time (T(1)) vary with depth and can therefore provide insight into the differences between the top and bottom layers of articular cartilage. Our CRI model is more sensitive to macromolecular content in the top layers of cartilage, with BPF showing moderate correlations with proteoglycan content, and k and T(1) exhibiting moderate correlations with collagen