  Retrospectively gated cine (retro-cine) MRI is the clinical standard for
cardiac functional analysis. Deep learning (DL) based methods have been
proposed for the reconstruction of highly undersampled MRI data and show
superior image quality and magnitude faster reconstruction time than CS-based
methods. Nevertheless, it remains unclear whether DL reconstruction is suitable
for cardiac function analysis. To address this question, in this study we
evaluate and compare the cardiac functional values (EDV, ESV and EF for LV and
RV, respectively) obtained from highly accelerated MRI acquisition using DL
based reconstruction algorithm (DL-cine) with values from CS-cine and
conventional retro-cine. To the best of our knowledge, this is the first work
to evaluate the cine MRI with deep learning reconstruction for cardiac function
analysis and compare it with other conventional methods. The cardiac functional
values obtained from cine MRI with deep learning reconstruction are consistent
with values from clinical standard retro-cine MRI.
