Advances in morphological and quantitative musculoskeletal MRI [electronic resource]

Over 1.5 million knee MRI scans are performed in the US annually for reasons ranging from acute knee injuries to researching diseases such as osteoarthritis. MRI can offer high-resolution imaging with excellent soft-tissue contrast and is often a tool of choice of interrogating various pathologies in musculoskeletal system. More recently, there has been a large emphasis on utilizing MRI in order to generate imaging-based biomarkers to track spatial and longitudinal changes in tissues. Using such biomarkers has potential for understanding and describing the pathophysiology of complex diseases such as Osteoarthritis. Despite the excellent image quality and potential biomarkers of disease activity that MRI can generate, it is still challenging to acquire all these features in rapid MRI protocols. High-resolution sequences are usually needed to evaluate fine structures typically observed in musculoskeletal systems. High signal from tissues is usually needed to accurately characterize quantitative biomarkers. At the same time, there is a growing need for rapid imaging methods in order to maximize patient throughput while minimizing patient discomfort. In MRI however, signal, resolution, and imaging time are properties of scans that are challenging to optimize simultaneously. In this work, I will describe how the already-available double-echo steady-state (DESS) sequence was optimized to generate quantitative morphological and biochemical biomarkers for cartilage and meniscus, in only a 5-minute acquisition. Conventional imaging methods used in large clinical studies typically require around 25 minutes of imaging time to generate such biomarkers. The validity of these biomarkers was compared to time-consuming methods and the reliability was evaluated using repeated acquisitions. Both the accuracy and the precision of this rapid DESS method was high enough to be confidently used in clinical studies in order to be able to track small longitudinal changes. This thesis also describes how the same DESS sequence can also be used for routine clinical knee MRI. The contrasts and the resolution that the DESS sequence offers can be used to diagnose internal knee derangement and its corresponding signs in tissues such as the cartilage, meniscus, tendon, ligaments, bone, and synovium. In additional to the morphological image contrasts, this study also probed the utility of having automatic quantitative T2 measurements available during diagnostic review also. Accuracy of the 5-minute DESS method against that of the routine knee MRI protocol was compared, where the DESS results were very promising. This thesis also studied the diagnostic accuracy of pairing one sequence from the conventional imaging protocol with DESS, in order to create an abridged two-sequence protocol. Such protocols have great potential for being able to transition from 30+ minute clinical protocols to protocols that last 5-7 minutes. While the 5-minute DESS sequence was able to interrogate several musculoskeletal tissues, there are still several tissues known as short-T2 tissues that generate very minimal signal using conventional Cartesian MRI sequences. In order to be able to image such tissues and to be able to quantify some of their underlying properties, we developed the Ultrashort Echo Time DESS (UTEDESS) sequence. This method permits imaging with a very high signal to noise ratio. This high signal with UTEDESS can be used to perform morphological and quantitative imaging of the menisci, tendons, and ligaments - all tissues that are very challenging to image with routine sequences. UTEDESS also provides the ability to image with isotropic resolutions in short scan times so that the images can be retrospectively re-sampled in arbitrary planes in order to maximize the diagnostic efficiency of the method. Overall, all the advances described in this thesis have the potential to accelerate the current paradigm of musculoskeletal imaging methods while being able to generate additional data which could be used in both - diagnostic and research settings.

Keywords: Bioengineering.
Advisor: Hargreaves Brian Andrew primary advisor. Thesis advisor
Gold Garry E.
Pelc Norbert J. advisor. Thesis advisor