Diastolic Function Assessment with 4D Flow CMR Using Automatic Deep Learning EA Ratio Analysis

Background Diastolic left ventricular dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed left ventricular systolic function the EA ratio is the first step to defining the grade of diastolic dysfunction. Doppler echocardiography is the preferred imaging technique for diastolic function assessment, while CMR is less established as a method. Previous 4D Flow-based studies have looked at the EA ratio proximally to the mitral valve, requiring manual interaction. In this study we compare an automated, deep learning-based, and two semiautomated approaches for 4D Flow CMR-based EA ratio assessment to conventional, gold standard echo-based methods. Methods Ninety-seven subjects with chronic ischemic heart disease underwent a cardiac echo followed by an MRI investigation. 4D Flow-based EA ratio values were computed using three different approaches; two semi-automated, assessing the EA ratio by measuring the inflow velocity (MVvel) and the inflow volume (MVflow) at the mitral valve plane, and one fully automated, creating a full LV segmentation using a deep learning-based method within which the EA ratio could be assessed without constraint to the mitral plane (LVvel). Results MVvel, MVflow, and LVvel EA ratios were strongly associated with Echo EA ratio (R2= 0.60, 0.58, 0.72). LVvel peak E and A showed moderate association to Echo peak E and A, while MVvel values were weakly associated. MVvel and MVflow EA ratios were very strongly associated with LVvel (R2= 0.84, 0.86). MVvel peak E was moderately associated with LVvel, while peak A showed strong association (R2= 0.26, 0.57). Discussion and Conclusion Peak E, peak A and EA ratio are integral to the assessment of diastolic dysfunction and may expand the utility of CMR studies in patients with cardiovascular disease. While underestimation of absolute peak E and A velocities was noted, the EA ratio measured with all three 4D Flow methods was strongly associated with the gold standard Doppler echocardiography. The automatic, deep learning-based method performed best, with the most favorable runtime of ~40seconds. As both semiautomatic methods associated very strongly to LVvel, they could be employed as an alternative for estimation of EA ratio.