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.

翻译：心功能分析的临床标准是磁共振成像(retro-cine)磁共振成像(DL)基础方法,用于重塑高过低采样的磁共振成像数据,并显示比CS型方法更优的图像质量和大度重建时间。然而,仍然不清楚DL重建是否适合心脏功能分析。为解决这一问题,我们在本研究中评估和比较利用以CS-cine和常规反转cine的值为根据DL重建算法(DL-cine)高速获取的心功能值(EDV、ESV和EF,分别为LV和RV),并用CS-cine和常规反转cine的值。根据我们的知识,这是评估Cine MRI的首项工作,为心脏功能分析进行深层学习重建,并将其与其他常规方法进行比较。从Cine MRI获得的心脏功能值与深层学习重建符合临床标准反转晶MRI值。