Improvement of the time-resolved 4DMRI image quality through super-resolution reconstruction using compressed sensing

Since the development of respiratory-correlated four-dimensional computed tomography (RC-4DCT) [1] and magnetic resonance imaging (RC-4DMRI) [2,3], patient-specific respiratory-induced tumor motion has been incorporated in radiotherapy for treating mobile tumors, such as lung, liver and pancreatic cancer. However, the RC-based snapshot 4D imaging only provides one breathing cycle, often contains severe binning motion artifacts, and may not represent tumor motion over 20-minute treatment, affecting treatment outcomes. Therefore, respiratory motion irregularities remain a challenge in radiotherapy. In this study, we report an improved time-resolved 4DMRI technique that captures multi-breath and can be used clinically and quantifies tumor motion irregularities.