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

Thomas H Keefe; Mary Catherine Minnig; Liubov Arbeeva; Marc Niethammer; Zhenlin Xu; Zhengyang Shen; Boqi Chen; Daniel B Nissman; Yvonne M Golightly; J S Marron; Amanda E Nelson

doi:10.1016/j.ocarto.2023.100334

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

Osteoarthr Cartil Open. 2023 Jan 24;5(1):100334. doi: 10.1016/j.ocarto.2023.100334. eCollection 2023 Mar.

Authors

Thomas H Keefe¹, Mary Catherine Minnig^{2

3}, Liubov Arbeeva², Marc Niethammer⁴, Zhenlin Xu⁴, Zhengyang Shen⁴, Boqi Chen⁴, Daniel B Nissman⁵, Yvonne M Golightly^{2

3

6}, J S Marron¹, Amanda E Nelson^{2

3}

Affiliations

¹ Statistics and Operations Research, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, North Carolina, USA.
² Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
³ Department of Epidemiology, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, North Carolina, USA.
⁴ Department of Computer Science, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, North Carolina, USA.
⁵ Department of Radiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA.
⁶ College of Allied Health Professions, University of Nebraska Medical Center, Omaha, NE 68198, USA.

Abstract

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.

Keywords: Knee osteoarthritis; Modes of variation; cartilage thickness.