Tendons and ligaments are dense, fibrous connective tissues that facilitate transmission of loads from muscle to bone (tendon) or from bone to bone (ligament). These tissues are subjected to wear and tear from day-to-day mechanical usage leading to sprains, tendinopathies, or ruptures, each of which is a major source of musculoskeletal disability. Clinically, the diagnosis of tendon and ligament injury is based on a clinical examination as well as magnetic resonance imaging (MRI) of the relevant tissues. MRI is a reliable, non-invasive tool for detecting large and complete tears; however, conventional T1 and T2-weighted grayscale images exhibit poor contrast and a low signal-to-noise ratio which makes identification of low-grade injuries more challenging to delineate. Therefore, there exists a need for reliable, quantitative and more robust imaging approaches to assess tendon and ligament microstructure and integrity
One of these MR approaches is diffusion tensor imaging (DTI), an advanced MRI technique primarily used in neuroimaging applications. DTI assesses tissue microstructural organization by quantifying the 3D diffusion of water molecules within tissues. It relies on the basic diffusion principle that water molecules diffuse more readily along (i.e., parallel to), rather than across physical barriers (e.g., collagen fibers). Diffusion of water molecules can be quantified by the diffusion tensor in each voxel, whereby the magnitude and orientation of water diffusion can be computed throughout the tissue, thus revealing the fiber microstructure. The primary aims of the proposed studies are to demonstrate applicability and reliability of the DTI technique for tendons and ligaments, and determine the sensitivity of b-values to DTI derived parameters of tissue integrity.
The proposed studies will investigate the applicability and sensitivity of DTI to intact tendons and ligaments. The long term goal of these initial studies is to provide in depth quantitative as well as qualitative characterization of these tissues which can significantly advance our ability to accurately image intact, damaged, and healing tissues, further our understanding of the microstructural mechanisms of microtrauma and repair, and potentially improve clinical management of injuries.
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