Key result
Automated deep learning 4D Flow CMR correlates strongly with Doppler echocardiography for E/A ratio.
Why the study?
CMR is less established than Doppler echocardiography for diastolic function assessment, and prior 4D Flow CMR E/A ratio evaluations required manual interaction.
Does 4D Flow CMR-based E/A ratio assessment accurately measure diastolic function compared to Doppler echocardiography in patients with suspected chronic ischemic heart disease?
Cross-Sectional (n=97)
Blinded analysis
No
Does 4D Flow CMR-based E/A ratio assessment accurately measure diastolic function compared to Doppler echocardiography in patients with suspected chronic ischemic heart disease?
Automated deep learning-based 4D Flow CMR provides a fast and accurate alternative to echocardiography for assessing the E/A ratio in evaluating diastolic function.
May support rapid automated E/A assessment via 4D Flow CMR; hypothesis-generating and requires prospective validation before clinical use.
BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and the peak late (A) transmitral flow velocity, is the first step to defining the grade of diastolic dysfunction. Doppler echocardiography (echo) is the preferred imaging technique for diastolic function assessment, while cardiovascular magnetic resonance (CMR) is less established as a method. Previous four-dimensional (4D) Flow-based studies have looked at the E/A ratio proximal to the mitral valve, requiring manual interaction. In this study, we compare an automated, deep learning-based and two semi-automated approaches for 4D Flow CMR-based E/A ratio assessment to conventional, gold-standard echo-based methods. METHODS: Ninety-seven subjects with chronic ischemic heart disease underwent a cardiac echo followed by CMR investigation. 4D Flow-based E/A ratio values were computed using three different approaches; two semi-automated, assessing the E/A 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 with which the E/A ratio could be assessed without constraint to the mitral plane (LVvel). CONCLUSION: Peak E, peak A, and E/A 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 E/A 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 ∼40 seconds. As both semi-automatic methods associated very strongly to LVvel, they could be employed as an alternative for estimation of E/A ratio.
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Viola et al. (2024) conducted a cross-sectional in Chronic ischemic heart disease (n=97). 4D Flow CMR-based E/A ratio assessment (automated deep learning method) vs. Doppler echocardiography was evaluated on Association of E/A ratio between 4D Flow CMR methods and Doppler echocardiography (R2 = 0.72). The automatic, deep learning-based 4D Flow CMR method for assessing the E/A ratio was strongly associated with gold standard Doppler echocardiography (R2 = 0.72) and had a runtime of ~40 seconds.
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