Patterns of variation among baseline femoral and tibial cartilage thickness and clinical features: Data from the osteoarthritis initiative.

Objective: To employ novel methodologies to identify phenotypes in knee OA based on variation among three baseline data blocks: 1) femoral cartilage thickness, 2) tibial cartilage thickness, and 3) participant characteristics and clinical features. Methods: Baseline data were from 3321 Osteoarthritis Initiative (OAI) participants with available cartilage thickness maps (6265 knees) and 77 clinical features. Cartilage maps were obtained from 3D DESS MR images using a deep-learning based segmentation approach and an atlas-based analysis developed by our group. Angle-based Joint and Individual Variation Explained (AJIVE) was used to capture and quantify variation, both shared among multiple data blocks and individual to each block, and to determine statistical significance. Results: Three major modes of variation were shared across the three data blocks. Mode 1 reflected overall thicker cartilage among men, those with higher education, and greater knee forces; Mode 2 showed associations between worsening Kellgren-Lawrence Grade, medial cartilage thinning, and worsening symptoms; and Mode 3 contrasted lateral and medial-predominant cartilage loss associated with BMI and malalignment. Each data block also demonstrated individual, independent modes of variation consistent with the known discordance between symptoms and structure in knee OA and reflecting the importance of features such as physical function, symptoms, and comorbid conditions independent of structural damage. Conclusions: This exploratory analysis, combining the rich OAI dataset with novel methods for determining and visualizing cartilage thickness, reinforces known associations in knee OA while providing insights into the potential for data integration in knee OA phenotyping.

Statistical shape model of the talus bone morphology: A comparison between impinged and nonimpinged ankles.

Diagnosis of ankle impingement is performed primarily by clinical examination, whereas medical imaging is used for severity staging and treatment guidance. The association of impingement symptoms with regional three-dimensional (3D) bone shape variaties visible in medical images has not been systematically explored, nor do we know the type and magnitude of this relation. In this cross-sectional case-control study, we hypothesized that 3D talus bone shape could be used to quantitatively formulate the discriminating shape variations between ankles with impingement from ankles without impingement, and we aimed to characterize and quantify these variations. We used statistical shape modeling (SSM) methods to determine the most prevalent modes of shape variations that discriminate between the impinged and nonimpinged ankles. Results of the compactness and parallel analysis test on the statistical shape model identify 8 prominent shape modes of variations (MoVs) representing approximately 78% of the total 3D variations in the population of shapes, among which two modes captured discriminating features between impinged and nonimpinged ankles (p value of 0.023 and 0.042). Visual inspection confirms that these two shape modes, capturing abnormalities in the anterior and posterior parts of talus, represent the two main bony risk factors in anterior and posterior ankle impingement. In conclusion, in this research using SSM we have identified shape MoVs that were found to correlate significantly with bony ankle impingement. We also illustrated potential guidance from SSMs for surgical planning.