부산대학교 도서관

Multiparametric magnetic resonance imaging (MRI) can be used to characterize many cancer subtypes including ovarian cancer. Quantitative mapping of MRI relaxation values, such as $T_{1}$ and $T_{2}$ mapping, is promising for improving tumor assessment beyond conventional qualitative $T_{1}$ - and $T_{2}$ -weighted images. However, quantitative MRI relaxation mapping methods often involve long scan times due to sequentially measuring many parameters. Magnetic resonance fingerprinting (MRF) is a new method that enables fast quantitative MRI by exploiting the transient signals caused by the variation of pseudorandom sequence parameters. These transient signals are then matched to a simulated dictionary of $T_{1}$ and $T_{2}$ values to create quantitative maps. The ability of MRF to simultaneously measure multiple parameters, could represent a new approach to characterizing cancer and assessing treatment response. This feasibility study investigates MRF for simultaneous $T_{1}$ , $T_{2}$ , and relative proton density (rPD) mapping using ovarian cancer as a model system.