Objective: We aim to validate four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) peak velocity tracking methods for measuring the peak velocity of mitral inflow against Doppler... Show moreObjective: We aim to validate four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) peak velocity tracking methods for measuring the peak velocity of mitral inflow against Doppler echocardiography.Method: Fifty patients were recruited who had 4D flow CMR and Doppler Echocardiography. After transvalvular flow segmentation using established valve tracking methods, peak velocity was automatically derived using three-dimensional streamlines of transvalvular flow. In addition, a static-planar method was used at the tip of mitral valve to mimic Doppler technique.Results: Peak E-wave mitral inflow velocity was comparable between TTE and the novel 4D flow automated dynamic method (0.9 +/- 0.5 vs 0.94 +/- 0.6 m/s; p = 0.29) however there was a statistically significant difference when compared with the static planar method (0.85 +/- 0.5 m/s; p = 0.01). Median A-wave peak velocity was also comparable across TTE and the automated dynamic streamline (0.77 +/- 0.4 vs 0.76 +/- 0.4 m/s; p = 0.77). A significant difference was seen with the static planar method (0.68 +/- 0.5 m/s; p = 0.04). E/A ratio was comparable between TTE and both the automated dynamic and static planar method (1.1 +/- 0.7 vs 1.15 +/- 0.5 m/s; p = 0.74 and 1.15 +/- 0.5 m/s; p = 0.5 respectively). Both novel 4D flow methods showed good correlation with TTE for E-wave (dynamic method; r = 0.70; P < 0.001 and static-planar method; r = 0.67; P < 0.001) and A-wave velocity measurements (dynamic method; r = 0.83; P < 0.001 and static method; r = 0.71; P < 0.001). The automated dynamic method demonstrated excellent intra/inter-observer reproducibility for all parameters.Conclusion: Automated dynamic peak velocity tracing method using 4D flow CMR is comparable to Doppler echocardiography for mitral inflow assessment and has excellent reproducibility for clinical use. Show less
Objective: We aim to validate four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) peak velocity tracking methods for measuring the peak velocity of mitral inflow against Doppler... Show moreObjective: We aim to validate four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) peak velocity tracking methods for measuring the peak velocity of mitral inflow against Doppler echocardiography.Method: Fifty patients were recruited who had 4D flow CMR and Doppler Echocardiography. After transvalvular flow segmentation using established valve tracking methods, peak velocity was automatically derived using three-dimensional streamlines of transvalvular flow. In addition, a static-planar method was used at the tip of mitral valve to mimic Doppler technique.Results: Peak E-wave mitral inflow velocity was comparable between TTE and the novel 4D flow automated dynamic method (0.9 +/- 0.5 vs 0.94 +/- 0.6 m/s; p = 0.29) however there was a statistically significant difference when compared with the static planar method (0.85 +/- 0.5 m/s; p = 0.01). Median A-wave peak velocity was also comparable across TTE and the automated dynamic streamline (0.77 +/- 0.4 vs 0.76 +/- 0.4 m/s; p = 0.77). A significant difference was seen with the static planar method (0.68 +/- 0.5 m/s; p = 0.04). E/A ratio was comparable between TTE and both the automated dynamic and static planar method (1.1 +/- 0.7 vs 1.15 +/- 0.5 m/s; p = 0.74 and 1.15 +/- 0.5 m/s; p = 0.5 respectively). Both novel 4D flow methods showed good correlation with TTE for E-wave (dynamic method; r = 0.70; P < 0.001 and static-planar method; r = 0.67; P < 0.001) and A-wave velocity measurements (dynamic method; r = 0.83; P < 0.001 and static method; r = 0.71; P < 0.001). The automated dynamic method demonstrated excellent intra/inter-observer reproducibility for all parameters.Conclusion: Automated dynamic peak velocity tracing method using 4D flow CMR is comparable to Doppler echocardiography for mitral inflow assessment and has excellent reproducibility for clinical use. Show less
Aims Pulmonary arterial hypertension (PAH) is a rare but serious disease associated with high mortality if left untreated. This study aims to assess the prognostic cardiac magnetic resonance (CMR)... Show moreAims Pulmonary arterial hypertension (PAH) is a rare but serious disease associated with high mortality if left untreated. This study aims to assess the prognostic cardiac magnetic resonance (CMR) features in PAH using machine learning. Methods and results Seven hundred and twenty-three consecutive treatment-naive PAH patients were identified from the ASPIRE registry; 516 were included in the training, and 207 in the validation cohort. A multilinear principal component analysis (MPCA)-based machine learning approach was used to extract mortality and survival features throughout the cardiac cycle. The features were overlaid on the original imaging using thresholding and clustering of high- and low-risk of mortality prediction values. The 1-year mortality rate in the validation cohort was 10%. Univariable Cox regression analysis of the combined short-axis and four-chamber MPCA-based predictions was statistically significant (hazard ratios: 2.1, 95% CI: 1.3, 3.4, c-index = 0.70, P = 0.002). The MPCA features improved the 1-year mortality prediction of REVEAL from c-index = 0.71 to 0.76 (P ≤ 0.001). Abnormalities in the end-systolic interventricular septum and end-diastolic left ventricle indicated the highest risk of mortality.Conclusion: The MPCA-based machine learning is an explainable time-resolved approach that allows visualization of prognostic cardiac features throughout the cardiac cycle at the population level, making this approach transparent and clinically interpretable. In addition, the added prognostic value over the REVEAL risk score and CMR volumetric measurements allows for a more accurate prediction of 1-year mortality risk in PAH. Show less
