Multiple-echo steady-state (MESS): Extending DESS for joint T2 mapping and chemical-shift corrected water-fat separation

Biomarkers of Cartilage Composition

Magnetic resonance imaging (MRI) has significantly advanced the understanding of osteoarthritis (OA) because it enables visualization of noncalcified tissues. Cartilage is avascular and nurtured by diffusion, so it has a very low turnover and limited capabilities of repair. Consequently, prevention of structural and detection of premorphological damage is key in maintaining cartilage health. The integrity of cartilage composition and ultrastructure determines its mechanical properties but is not accessible to morphological imaging. Therefore, various techniques of compositional MRI with and without use of intravenous contrast medium have been developed. Spin-spin relaxation time (T2) and spin-lattice relaxation time constant in rotating frame (T1rho) mapping, the most studied cartilage biomarkers, were included in the recent standardization effort by the Quantitative Imaging Biomarkers Alliance (QIBA) that aims to make compositional MRI of cartilage clinically feasible and comparable. Additional techniques that are less frequently used include ultrashort echo time with T2*, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), glycosaminoglycan concentration by chemical exchange-dependent saturation transfer (gagCEST), sodium imaging, and diffusion-weighted MRI.

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?

Cartilage MRI-based T1rho 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 T1rho 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 T1rho 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 T1rho 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 T1rho and T2 values. Finally, effective treatments for prevention and slowing progression of OA are required in order to establish T1rho 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: • T1rho 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 T1rho 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 T1rho and T2 cartilage compositional measurements as biomarkers to initiate and monitor treatment.

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications

Osteoarthritis (OA) is a widely occurring degenerative joint disease that is severely debilitating and causes significant socioeconomic burdens to society. Magnetic resonance imaging (MRI) is the preferred imaging modality for the morphological evaluation of cartilage due to its excellent soft tissue contrast and high spatial resolution. However, its utilization typically involves subjective qualitative assessment of cartilage. Compositional MRI, which refers to the quantitative characterization of cartilage using a variety of MRI methods, can provide important information regarding underlying compositional and ultrastructural changes that occur during early OA. Cartilage compositional MRI could serve as early imaging biomarkers for the objective evaluation of cartilage and help drive diagnostics, disease characterization, and response to novel therapies. This review will summarize current and ongoing state-of-the-art cartilage compositional MRI techniques and highlight emerging methods for cartilage compositional MRI including MR fingerprinting, compressed sensing, multiexponential relaxometry, improved and robust radio-frequency pulse sequences, and deep learning-based acquisition, reconstruction, and segmentation. The review will also briefly discuss the current challenges and future directions for adopting these emerging cartilage compositional MRI techniques for use in clinical practice and translational OA research studies. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Magnetic Resonance Imaging Versus Computed Tomography for Three-Dimensional Bone Imaging of Musculoskeletal Pathologies: A Review

Magnetic resonance imaging (MRI) is increasingly utilized as a radiation‐free alternative to computed tomography (CT) for the diagnosis and treatment planning of musculoskeletal pathologies. MR imaging of hard tissues such as cortical bone remains challenging due to their low proton density and short transverse relaxation times, rendering bone tissues as nonspecific low signal structures on MR images obtained from most sequences. Developments in MR image acquisition and post‐processing have opened the path for enhanced MR‐based bone visualization aiming to provide a CT‐like contrast and, as such, ease clinical interpretation. The purpose of this review is to provide an overview of studies comparing MR and CT imaging for diagnostic and treatment planning purposes in orthopedic care, with a special focus on selective bone visualization, bone segmentation, and three‐dimensional (3D) modeling. This review discusses conventional gradient‐echo derived techniques as well as dedicated short echo time acquisition techniques and post‐processing techniques, including the generation of synthetic CT, in the context of 3D and specific bone visualization. Based on the reviewed literature, it may be concluded that the recent developments in MRI‐based bone visualization are promising. MRI alone provides valuable information on both bone and soft tissues for a broad range of applications including diagnostics, 3D modeling, and treatment planning in multiple anatomical regions, including the skull, spine, shoulder, pelvis, and long bones.