MRI-based T1rho and T2 cartilage compositional imaging in osteoarthritis: what have we learned and what is needed to apply it clinically and in a trial setting?

Abstract

Cartilage MRI-based T_1rho and T₂ compositional measurements have been developed to characterize cartilage matrix quality and diagnose cartilage damage before irreversible defects are found, allowing intervention at an early, potentially reversible disease stage. Over the last 2 decades, this technology was investigated in numerous studies and was validated using specimen studies and arthroscopy; and longitudinal studies documented its ability to predict progression of degenerative disease and radiographic osteoarthritis (OA). While T_1rho and T₂ measurements have shown promise in early disease stages, several hurdles have been encountered to apply this technology clinically. These include (i) challenges with cartilage segmentation, (ii) long image acquisition times, (iii) a lack of standardization of imaging, and (iv) an absence of reference databases and definitions of abnormal cut-off values. Progress has been made by developing deep-learning based automatic cartilage segmentation and faster imaging methods, enabling the feasibility of T_1rho and T₂ imaging for clinical and scientific trial applications. Also, the Radiological Society of North America (RSNA) Quantitative Imaging Biomarker Alliance mechanism was used to establish standardized profiles for compositional T_1rho and T₂ imaging, and multi-center feasibility testing is work in progress. The last hurdles are the development of reference databases and establishing a definition of normal versus abnormal cartilage T_1rho and T₂ values. Finally, effective treatments for prevention and slowing progression of OA are required in order to establish T_1rho and T₂ as imaging biomarkers for initiating and monitoring therapies, analogous to the role of dual X-ray absorptiometry (DXA) bone mineral density measurements in the management of osteoporosis. KEY POINTS: • T_1rho and T₂ cartilage measurements have been validated in characterizing cartilage degenerative change using histology and arthroscopy as a reference. • They have also been shown to predict progression of cartilage degeneration and incidence of radiographic OA. • Advances have been made to facilitate clinical and trial application of T_1rho and T₂ by improved standardization of imaging and by establishing deep learning-based automatic cartilage segmentation. • Effective treatments with disease-modifying OA specific drugs may establish T_1rho and T₂ cartilage compositional measurements as biomarkers to initiate and monitor treatment.

Keywords: Biomarkers; Cartilage; MRI; Osteoarthritis; Quantitative imaging.