We demonstrate the clinical feasibility of high-resolution (HR) in-vivo mapping of proteoglycan water fraction (PgWF) in human knee cartilage by combining the mcDESPOT protocol for data acquisition and Bayesian Monte Carlo (BMC) analysis for data analysis. For all subjects, PgWF maps derived from low resolution datasets exhibited partial volume and magnetic susceptibility effects leading, respectively, to an overestimation and an underestimation of PgWF values in several cartilage regions. These issues were absent in HR PgWF maps. Further, BMC-mcDESPOT demonstrates high reproducibility and stability in the estimation of PgWF as compared to the conventional stochastic region contraction (SRC) algorithm.
This abstract and the presentation materials are available to members only; a login is required.