Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis

Abstract

Osteoarthritis (OA) of the knee is a major source of disability that has no known treatment or cure. Morphological and compositional MRI is commonly used for assessing the bone and soft tissues in the knee to enhance the understanding of OA pathophysiology. However, it is challenging to extend these imaging methods and their subsequent analysis techniques to study large population cohorts due to slow and inefficient imaging acquisition and postprocessing tools. This can create a bottleneck in assessing early OA changes and evaluating the responses of novel therapeutics. The purpose of this review article is to highlight recent developments in tools for enhancing the efficiency of knee MRI methods useful to study OA. Advances in efficient MRI data acquisition and reconstruction tools for morphological and compositional imaging, efficient automated image analysis tools, and hardware improvements to further drive efficient imaging are discussed in this review. For each topic, we discuss the current challenges as well as potential future opportunities to alleviate these challenges. Level of Evidence 5 Technical Efficacy Stage 3

Ultrashort echo time Cones double echo steady state (UTE‐Cones‐DESS) for rapid morphological imaging of short T2 tissues

“…1 In DESS, an SSFP signal is separated into two components, free induction decay (FID)-like signal (S + ) and echo-like signal (S − ), by using an extended and unbalanced readout gradient between two consecutive RF pulses. 2 DESS has been widely used for clinical applications in musculoskeletal (MSK) [3][4][5][6][7][8][9][10] and neuroimaging [11][12][13][14][15][16] due to its flexible tissue contrast involving T 1 , T 2 , and diffusion weighting. In DESS imaging, fat signal commonly appears with high signal intensity due to its high T 2 over T 1 ratio, a signal which typically needs to be suppressed when attempting to image non-lipid tissues with specificity.…”

Improving Quantitative Magnetic Resonance Imaging Using Deep Learning

“…In particular, many pioneer works in MR image reconstruction showed that conventional reconstruction methods, including parallel imaging [31][32][33][34] and compressed sensing, 35,36 can provide decreased acquisition time while maintaining acceptable image quality at a low acceleration rate. [37][38][39][40][41][42] More recently, a few attempts were made to dramatically increase the acquisition speed of quantitative imaging using deep learning, and they showed that methods based on deep learning can yield better image quality in comparison with conventional state-of-the-art reconstruction methods.…”

Preoperative MRI of Articular Cartilage in the Knee: A Practical Approach

“…T2 mapping has been explored as a sensitive biomarker for evaluating early chondral degeneration. 21,22 Most MRI acquisition schemes for acquiring T2 relaxation time mapping measurements rely on multi-echo spin-echo MRI that requires long acquisition durations. 23 This need for separate time-consuming sequences for anatomical and quantitative imaging of cartilage has precluded the use of quantitative MRI in a diagnostic clinical setting, despite promising results in studies evaluating osteoarthritis progression.…”