Purpose: This study aims to develop a novel time-resolved magnetic resonance fingerprinting (TR-MRF) technique for respiratory motion imaging applications.
Materials and methods: The TR-MRF technique consists of repeated MRF acquisitions using an unbalanced steady-state free precession sequence with spiral-in-spiral-out trajectory. Time-resolved magnetic resonance fingerprinting was first tested via computer simulation using a four-dimensional (4D) extended cardiac-torso (XCAT) phantom for both regular and irregular breathing profiles, and was tested in three healthy volunteers. Parametric TR-MRF maps at different respiratory phases were subsequently estimated using our TR-MRF sorting and reconstruction techniques. The resulting TR-MRF maps were evaluated using a set of metrices related to radiotherapy applications, including absolute difference in motion amplitude, error in the amplitude of diaphragm motion (ADM), tumor volume error (TVE), signal-to-noise ratio (SNR), and tumor contrast.
Results: TR-MRF maps with regular and irregular breathing were successfully generated in XCAT phantom. Numerical simulations showed that the TVE were 1.6 ± 2.7% and 1.3 ± 2.2%, the average absolute differences in tumor motion amplitude were 0.3 ± 0.7 mm and 0.3 ± 0.6 mm, and the ADM were 4.1 ± 0.9% and 3.5 ± 0.9% for irregular and regular breathing, respectively. The SNR of the T1 and T2 maps of the liver and the tumor were generally higher for regular breathing compared to irregular breathing, whereas tumor-to-liver contrast is similar between the two breathing patterns. The proposed technique was successfully implemented on the healthy volunteers.
Conclusion: We have successfully demonstrated in both digital phantom and healthy subjects a novel TR-MRF technique capable of imaging respiratory motions with simultaneous quantification of MR multiparametric maps.
Keywords: liver cancer; multiparametric MRI; radiotherapy.
© 2020 American Association of Physicists in Medicine.