BackgroundLV diastolic vortex formation has been suggested to critically contribute to efficient blood pumping function, while altered vortex formation has been associated with LV pathologies. Therefore, quantitative characterization of vortex flow might provide a novel objective tool for evaluating LV function. The objectives of this study were 1) assess feasibility of vortex flow analysis during both early and late diastolic filling in vivo in normal subjects using 4D Flow cardiovascular magnetic resonance (CMR) with retrospective cardiac gating and 3D vortex core analysis 2) establish normal quantitative parameters characterizing 3D LV vortex flow during both early and late ventricular filling in normal subjects.MethodsWith full ethical approval, twenty-four healthy volunteers (mean age: 20±10 years) underwent whole-heart 4D Flow CMR. The Lambda2-method was used to extract 3D LV vortex ring cores from the blood flow velocity field during early (E) and late (A) diastolic filling. The 3D location of the center of vortex ring core was characterized using cylindrical cardiac coordinates (Circumferential, Longitudinal (L), Radial (R)). Comparison between E and A filling was done with a paired T-test. The orientation of the vortex ring core was measured and the ring shape was quantified by the circularity index (CI). Finally, the Spearman’s correlation between the shapes of mitral inflow pattern and formed vortex ring cores was tested.ResultsDistinct E- and A-vortex ring cores were observed with centers of A-vortex rings significantly closer to the mitral valve annulus (E-vortex L=0.19±0.04 versus A-vortex L=0.15±0.05; p=0.0001), closer to the ventricle’s long-axis (E-vortex: R=0.27±0.07, A-vortex: R=0.20±0.09, p=0.048) and more elliptical in shape (E-vortex: CI=0.79±0.09, A-vortex: CI=0.57±0.06; <0.001) compared to E-vortex. The circumferential location and orientation relative to LV long-axis for both E- and A-vortex ring cores were similar. Good to strong correlation was found between vortex shape and mitral inflow shape through both the annulus (r=0.66) and leaflet tips (r=0.83).ConclusionsQuantitative characterization and comparison of 3D vortex rings in LV inflow during both early and late diastolic phases is feasible in normal subjects using retrospectively-gated 4D Flow CMR, with distinct differences between early and late diastolic vortex rings.Electronic supplementary materialThe online version of this article (doi:10.1186/s12968-014-0078-9) contains supplementary material, which is available to authorized users.

PurposeTo evaluate viscous energy loss and the association with three‐dimensional (3D) vortex ring formation in left ventricular (LV) blood flow during diastolic filling.Theory and MethodsThirty healthy volunteers were compared with 32 patients with corrected atrioventricular septal defect as unnatural mitral valve morphology and inflow are common in these patients. 4DFlow MRI was acquired from which 3D vortex ring formation was identified in LV blood flow at peak early (E)‐filling and late (A)‐filling and characterized by its presence/absence, orientation, and position from the lateral wall. Viscous energy loss was computed over E‐filling, A‐filling, and complete diastole using the Navier‐Stokes energy equations.ResultsCompared with healthy volunteers, viscous energy loss was significantly elevated in patients with disturbed vortex ring formation as characterized by a significantly inclined orientation and/or position closer to the lateral wall. Highest viscous energy loss was found in patients without a ring‐shaped vortex during E‐filling (on average more than double compared with patients with ring‐shape vortex, P < 0.003). Altered A‐filling vortex ring formation was associated with significant increase in total viscous energy loss over diastole even in the presence of normal E‐filling vortex ring.ConclusionAltered vortex ring formation during LV filling is associated with increased viscous energy loss. Magn Reson Med 77:794–805, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

BackgroundMyocardial infarction (MI) leads to complex changes in left ventricular (LV) haemodynamics that are linked to clinical outcomes. We hypothesize that LV blood flow kinetic energy (KE) is altered in MI and is associated with LV function and infarct characteristics. This study aimed to investigate the intra-cavity LV blood flow KE in controls and MI patients, using cardiovascular magnetic resonance (CMR) four-dimensional (4D) flow assessment.MethodsForty-eight patients with MI (acute-22; chronic-26) and 20 age/gender-matched healthy controls underwent CMR which included cines and whole-heart 4D flow. Patients also received late gadolinium enhancement imaging for infarct assessment. LV blood flow KE parameters were indexed to LV end-diastolic volume and include: averaged LV, minimal, systolic, diastolic, peak E-wave and peak A-wave KEiEDV. In addition, we investigated the in-plane proportion of LV KE (%) and the time difference (TD) to peak E-wave KE propagation from base to mid-ventricle was computed. Association of LV blood flow KE parameters to LV function and infarct size were investigated in all groups.ResultsLV KEiEDV was higher in controls than in MI patients (8.5 ± 3 μJ/ml versus 6.5 ± 3 μJ/ml, P = 0.02). Additionally, systolic, minimal and diastolic peak E-wave KEiEDV were lower in MI (P < 0.05). In logistic-regression analysis, systolic KEiEDV (Beta = − 0.24, P < 0.01) demonstrated the strongest association with the presence of MI. In multiple-regression analysis, infarct size was most strongly associated with in-plane KE (r = 0.5, Beta = 1.1, P < 0.01). In patients with preserved LV ejection fraction (EF), minimal and in-plane KEiEDV were reduced (P < 0.05) and time difference to peak E-wave KE propagation during diastole increased (P < 0.05) when compared to controls with normal EF.ConclusionsReduction in LV systolic function results in reduction in systolic flow KEiEDV. Infarct size is independently associated with the proportion of in-plane LV KE. Degree of LV impairment is associated with TD of peak E-wave KE. In patient with preserved EF post MI, LV blood flow KE mapping demonstrated significant changes in the in-plane KE, the minimal KEiEDV and the TD. These three blood flow KE parameters may offer novel methods to identify and describe this patient population.Electronic supplementary materialThe online version of this article (10.1186/s12968-018-0483-6) contains supplementary material, which is available to authorized users.

Purpose To generate fully automated and fast 4D‐flow MRI‐based 3D segmentations of the aorta using deep learning for reproducible quantification of aortic flow, peak velocity, and dimensions. Methods A total of 1018 subjects with aortic 4D‐flow MRI (528 with bicuspid aortic valve, 376 with tricuspid aortic valve and aortic dilation, 114 healthy controls) comprised the data set. A convolutional neural network was trained to generate 3D aortic segmentations from 4D‐flow data. Manual segmentations served as the ground truth (N = 499 training, N = 101 validation, N = 418 testing). Dice scores, Hausdorff distance, and average symmetrical surface distance were calculated to assess performance. Aortic flow, peak velocity, and lumen dimensions were quantified at the ascending, arch, and descending aorta and compared using Bland‐Altman analysis. Interobserver variability of manual analysis was assessed on a subset of 40. Results Convolutional neural network segmentation required 0.438 ± 0.355 seconds versus 630 ± 254 seconds for manual analysis and demonstrated excellent performance with a median Dice score of 0.951 (0.930‐0.966), Hausdorff distance of 2.80 (2.13‐4.35), and average symmetrical surface distance of 0.176 (0.119‐0.290). Excellent agreement was found for flow, peak velocity, and dimensions with low bias and limits of agreement less than 10% difference versus manual analysis. For aortic volume, limits of agreement were moderate within 16.3%. Interobserver variability (median Dice score: 0.950; Hausdorff distance: 2.45; and average symmetrical surface distance: 0.145) and convolutional neural network–based analysis (median Dice score: 0.953‐0.959; Hausdorff distance: 2.24‐2.91; and average symmetrical surface distance: 0.145‐1.98 to observers) demonstrated similar reproducibility. Conclusions Deep learning enabled fast and automated 3D aortic segmentation from 4D‐flow MRI, demonstrating its potential for efficient clinical workflows. Future studies should investigate its utility for other vasculature and multivendor applications.

PurposeTo validate three widely‐used acceleration methods in four‐dimensional (4D) flow cardiac MR; segmented 4D‐spoiled‐gradient‐echo (4D‐SPGR), 4D‐echo‐planar‐imaging (4D‐EPI), and 4D‐k‐t Broad‐use Linear Acquisition Speed‐up Technique (4D‐k‐t BLAST).Materials and MethodsAcceleration methods were investigated in static/pulsatile phantoms and 25 volunteers on 1.5 Tesla MR systems. In phantoms, flow was quantified by 2D phase‐contrast (PC), the three 4D flow methods and the time‐beaker flow measurements. The later was used as the reference method. Peak velocity and flow assessment was done by means of all sequences. For peak velocity assessment 2D PC was used as the reference method. For flow assessment, consistency between mitral inflow and aortic outflow was investigated for all pulse‐sequences. Visual grading of image quality/artifacts was performed on a four‐point‐scale (0 = no artifacts; 3 = nonevaluable).ResultsFor the pulsatile phantom experiments, the mean error for 2D PC = 1.0 ± 1.1%, 4D‐SPGR = 4.9 ± 1.3%, 4D‐EPI = 7.6 ± 1.3% and 4D‐k‐t BLAST = 4.4 ± 1.9%. In vivo, acquisition time was shortest for 4D‐EPI (4D‐EPI = 8 ± 2 min versus 4D‐SPGR = 9 ± 3 min, P < 0.05 and 4D‐k‐t BLAST = 9 ± 3 min, P = 0.29). 4D‐EPI and 4D‐k‐t BLAST had minimal artifacts, while for 4D‐SPGR, 40% of aortic valve/mitral valve (AV/MV) assessments scored 3 (nonevaluable). Peak velocity assessment using 4D‐EPI demonstrated best correlation to 2D PC (AV:r = 0.78, P < 0.001; MV:r = 0.71, P < 0.001). Coefficient of variability (CV) for net forward flow (NFF) volume was least for 4D‐EPI (7%) (2D PC:11%, 4D‐SPGR: 29%, 4D‐k‐t BLAST: 30%, respectively).ConclusionIn phantom, all 4D flow techniques demonstrated mean error of less than 8%. 4D‐EPI demonstrated the least susceptibility to artifacts, good image quality, modest agreement with the current reference standard for peak intra‐cardiac velocities and the highest consistency of intra‐cardiac flow quantifications. Level of Evidence: 1 Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2018;47:272–281.