Cardiac magnetic resonance using fused 3D cine and 4D flow sequences: validation of ventricular and blood flow measurements

Purpose: Current cardiovascular magnetic resonance (CMR) examinations require expert planning, multiple breath holds, and 2D imaging. To address this, we sought to develop and validate a comprehensive free -breathing 3D cine function and flow CMR examination using a steady-state free precession (SSFP) sequence to depict anatomy fused with a spatially registered phase contrast (PC) sequence for blood flow analysis.Methods: In a prospective study, 25 patients underwent a CMR examination which included a 3D cine SSFP sequence and a 3D cine PC (also known as 4D flow) sequence acquired during free-breathing and after the administration of a gadolinium-based contrast agent. Both 3D sequences covered the heart and mediastinum, and used retrospective vectorcardiogram gating (20 phases/beat interpolated to 30 phases/beat) and prospective respiratory motion compensation confining data acquisition to end-expiration. Cardiovascular measurements derived from the 3D cine SSFP and PC images were then compared with those from standard 2D imaging.Results: All 3D cine SSFP and PC acquisitions were completed successfully. The mean time for the 3D cine sequences including prescription was shorter than that for the corresponding 2D sequences (21 min vs. 36 min, P-value < 0.001). Left and right ventricular end-diastolic volumes and stroke volumes by 3D cine SSFP were slightly smaller than those from 2D cine SSFP (all biases <= 5%). The blood flow measurements from the 3D and 2D sequences had close agreement in the ascending aorta (bias -2.6%) but main pulmonary artery flow was lower with the 3D cine sequence (bias -11.2%).Conclusion: Compared to the conventional 2D cine approach, a comprehensive 3D cine function and flow examination was faster and yielded slightly lower left and right end-diastolic volumes, stroke volumes, and main pulmonary artery blood flow. This free-breathing 3D cine approach allows flexible post-examination data analysis and has the potential to make examinations more comfortable for patients and easier to perform for the operator.Cardiovascular Aspects of Radiolog

Deep learning-based prediction of intra-cardiac blood flow in long-axis cine magnetic resonance imaging

Purpose: We aimed to design and evaluate a deep learning-based method to automatically predict the time-varying in-plane blood flow velocity within the cardiac cavities in long-axis cine MRI, validated against 4D flow. Methods: A convolutional neural network (CNN) was implemented, taking cine MRI as the input and the in-plane velocity derived from the 4D flow acquisition as the ground truth. The method was evaluated using velocity vector end-point error (EPE) and angle error. Additionally, the E/A ratio and diastolic function classification derived from the predicted velocities were compared to those derived from 4D flow. Results: For intra-cardiac pixels with a velocity > 5 cm/s, our method achieved an EPE of 8.65 cm/s and angle error of 41.27 degrees. For pixels with a velocity > 25 cm/s, the angle error significantly degraded to 19.26 degrees. Although the averaged blood flow velocity prediction was under-estimated by 26.69%, the high correlation (PCC = 0.95) of global time-varying velocity and the visual evaluation demonstrate a good agreement between our prediction and 4D flow data. The E/A ratio was derived with minimal bias, but with considerable mean absolute error of 0.39 and wide limits of agreement. The diastolic function classification showed a high accuracy of 86.9%. Conclusion: Using a deep learning-based algorithm, intra-cardiac blood flow velocities can be predicted from long-axis cine MRI with high correlation with 4D flow derived velocities. Visualization of the derived velocities provides adjunct functional information and may potentially be used to derive the E/A ratio from conventional CMR exams.Radiolog

Non-contrast free-breathing whole-heart 3D cine cardiovascular magnetic resonance with a novel 3D radial leaf trajectory

Purpose: To develop and validate a non-contrast free-breathing whole-heart 3D cine steady-state free precession (SSFP) sequence with a novel 3D radial leaf trajectory.Methods: We used a respiratory navigator to trigger acquisition of 3D cine data at end-expiration to minimize respiratory motion in our 3D cine SSFP sequence. We developed a novel 3D radial leaf trajectory to reduce gradient jumps and associated eddy-current artifacts. We then reconstructed the 3D cine images with a resolution of 2.0mm3 using an iterative nonlinear optimization algorithm. Prospective validation was performed by comparing ventricular volumetric measurements from a conventional breath-hold 2D cine ventricular short-axis stack against the non-contrast free-breathing whole-heart 3D cine dataset in each patient (n = 13).Results: All 3D cine SSFP acquisitions were successful and mean scan time was 07:09 +/- 01:31 min. End-diastolic ventricular volumes for left ventricle (LV) and right ventricle (RV) measured from the 3D datasets were smaller than those from 2D (LV: 159.99 +/- 42.99 vs. 173.16 +/- 47.42; RV: 180.35 +/- 46.08 vs. 193.13 +/- 49.38; p-value = 0.190, bias<6%). The 3D cine data had a lower subjective image quality score.Conclusion: Our non-contrast free-breathing whole-heart 3D cine sequence with novel leaf trajectory was robust and yielded smaller ventricular end-diastolic volumes compared to 2D cine imaging. It has the potential to make examinations easier and more comfortable for patients