Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep
Federica Viola1, Mariana Bustamante2, Ann Bolger3
1Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Insights
This study compared automated and semi-automated 4D Flow CMR methods for assessing the E/A ratio in diastolic dysfunction. The deep learning-based automated method showed strong association with echocardiography and the fastest results.
Area of Science:
- Cardiovascular Imaging
- Medical Technology
- Diastolic Function Assessment
Background:
- Diastolic left ventricular (LV) dysfunction significantly impacts heart failure symptoms and prognosis.
- The E/A ratio, derived from transmitral flow velocities, is crucial for grading diastolic dysfunction, especially in patients with reduced LV systolic function.
- Doppler echocardiography is standard for diastolic function assessment, but cardiovascular magnetic resonance (CMR) is less established.
Purpose of the Study:
- To compare automated and semi-automated 4D Flow CMR techniques for assessing the E/A ratio against conventional echocardiography.
- To evaluate the performance of a deep learning-based automated method versus semi-automated approaches for 4D Flow CMR E/A ratio calculation.
- To determine the feasibility of using 4D Flow CMR for diastolic function assessment in patients with cardiovascular disease.
Main Methods:
- Ninety-seven subjects with chronic ischemic heart disease underwent both echocardiography and CMR.
- Three 4D Flow CMR methods were used: two semi-automated (MVvel, MVflow) measuring inflow at the mitral valve plane, and one fully automated (LVvel) using deep learning for LV segmentation.
- E/A ratios were computed using all three 4D Flow methods and compared to echocardiography-derived E/A ratios.
Main Results:
- All three 4D Flow CMR methods (MVvel, MVflow, LVvel) demonstrated strong associations with the echocardiography-derived E/A ratio (R² = 0.60, 0.58, 0.72).
- The automated LVvel method showed the strongest correlation (R² = 0.72) and fastest runtime (∼40 seconds).
- Semi-automated methods (MVvel, MVflow) showed very strong association with the LVvel method, suggesting their utility as alternatives.
Conclusions:
- The E/A ratio assessed by 4D Flow CMR, particularly the automated deep learning method, strongly correlates with Doppler echocardiography.
- These 4D Flow CMR methods can expand the utility of CMR in assessing diastolic dysfunction in cardiovascular disease patients.
- While absolute velocities may be underestimated, the E/A ratio derived from 4D Flow CMR is reliable, with the automated approach offering the best performance.
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).
Results:
MVvel, MVflow, and LVvel E/A ratios were strongly associated with echocardiographically derived E/A 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 a strong association (R2 = 0.26, 0.57).
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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