Quantitative Magnetic Resonance Fingerprinting in Ovarian Tumors for T1 and T2 Mapping

Abstract

Multi-parametric magnetic resonance imaging (MRI) can be used to characterize many cancer subtypes including ovarian cancer. Quantitative mapping of MRI relaxation values, such as T1 and T2 mapping, is capable of improving tumor assessment beyond usual qualitative T1- and T2-weighted images. Though, quantitative MRI relaxation mapping methods frequently engage long scan times because of sequentially measuring many parameters. Magnetic resonance fingerprinting (MRF) is a new technique that creates fast quantitative MRI by exploiting the transient signals caused by the variation of the pseudorandom sequence parameters. These transient signals are now matched with simulated dictionary of T1 and T2 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 paper investigates the MRF for simultaneous T1, T2, and relative proton density mapping treating ovarian cancer as a model system.