Fully quantitative mapping of abnormal aortic velocity and wall shear stress direction in patients with bicuspid aortic valves and repaired coarctation using 4D flow cardiovascular magnetic resonance

Background: Helices and vortices in thoracic aortic blood flow measured with 4D flow cardiovascular magnetic resonance (CMR) have been associated with aortic dilation and aneurysms. Current approaches are semi-quantitative or when fully quantitative based on 2D plane placement. In this study, we present a fully quantitative and three-dimensional approach to map and quantify abnormal velocity and wall shear stress (WSS) at peak systole in patients with a bicuspid aortic valve (BAV) of which 52% had a repaired coarctation. Methods: 4D flow CMR was performed in 48 patients with BAV and in 25 healthy subjects at a spatiotemporal resolution of 2.5 × 2.5 × 2.5mm3/ ~ 42 ms and TE/TR/FA of 2.1 ms/3.4 ms/8° with k-t Principal Component Analysis factor R = 8. A 3D average of velocity and WSS direction was created for the normal subjects. Comparing BAV patient data with the 3D average map and selecting voxels deviating between 60° and 120° and > 120° yielded 3D maps and volume (in cm3) and surface (in cm2) quantification of abnormally directed velocity and WSS, respectively. Linear regression with Bonferroni corrected significance of P 120° correlated moderately with the vorticity scores (R ~ 0.50, P 120° did not correlate with quantitative vorticity. For abnormal velocity and WSS deviating between 60° and 120°, moderate correlations were found with aortic diameters (R = 0.50–0.70). For abnormal velocity and WSS deviating > 120°, additional moderate correlations were found with age and with peak velocity (stenosis severity) and a weak correlation with gender. Ensemble maps showed that more than 60% of the patients had abnormally directed velocity and WSS. Additionally, abnormally directed velocity and WSS was higher in the proximal descending aorta in the patients with repaired coarctation than in the patients where coarctation was never present. Conclusion: The possibility to reveal directional abnormalities of velocity and WSS in 3D provides a new tool for hemodynamic characterization in BAV disease

Advanced cardiac MRI techniques for evaluation of left-sided valvular heart disease

The most common types of left-sided valvular heart disease (VHD) in the Western world are aortic valve stenosis, aortic valve regurgitation, and mitral valve regurgitation. Comprehensive clinical evaluation entails both hemodynamic analysis and structural as well as functional characterization of the left ventricle. Cardiac magnetic resonance imaging (MRI) is an established diagnostic modality for assessment of left-sided VHD and is progressively gaining ground in modern-day clinical practice. Detailed flow visualization and quantification of flow-related biomarkers in VHD can be obtained using 4D flow MRI, an imaging technique capable of measuring blood flow in three orthogonal directions over time. In addition, recent MRI sequences enable myocardial tissue characterization and strain analysis. In this review we discuss the emerging potential of state-of-the-art MRI including 4D flow MRI, tissue mapping, and strain quantification for the diagnosis and prognosis of left-sided VHD. Level of Evidence: 1. Technical Efficacy Stage: 1. J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:318–329

Advanced cardiac MRI techniques for evaluation of left-sided valvular heart disease

The most common types of left-sided valvular heart disease (VHD) in the Western world are aortic valve stenosis, aortic valve regurgitation, and mitral valve regurgitation. Comprehensive clinical evaluation entails both hemodynamic analysis and structural as well as functional characterization of the left ventricle. Cardiac magnetic resonance imaging (MRI) is an established diagnostic modality for assessment of left-sided VHD and is progressively gaining ground in modern-day clinical practice. Detailed flow visualization and quantification of flow-related biomarkers in VHD can be obtained using 4D flow MRI, an imaging technique capable of measuring blood flow in three orthogonal directions over time. In addition, recent MRI sequences enable myocardial tissue characterization and strain analysis. In this review we discuss the emerging potential of state-of-the-art MRI including 4D flow MRI, tissue mapping, and strain quantification for the diagnosis and prognosis of left-sided VHD. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:318-329

Quantification of mitral valve regurgitation from 4d flow mri using semiautomated flow tracking

Purpose: To compare the accuracy of semiautomated flow tracking with that of semiautomated valve tracking in the quantification of mitral valve (MV) regurgitation from clinical four-dimensional (4D) flow MRI data obtained in patients with mild, moderate, or severe MV regurgitation. Materials and Methods: The 4D flow MRI data were retrospectively collected from 30 patients (21 men; mean age, 61 years ± 10 [stan-dard deviation]) who underwent 4D flow MRI from 2006 to 2016. Ten patients had mild MV regurgitation, nine had moderate MV regurgitation, and 11 had severe MV regurgitation, as diagnosed by using semiquantitative echocardiography. The regurgitant volume (Rvol) across the MV was obtained using three methods: indirect quantification of Rvol (RvolINDIRECT ), semiautomated quantification of Rvol using valve tracking (RvolVALVE ), and semiautomated quantification of Rvol using flow tracking (RvolFLOW ). A second observer repeated the measurements. Aortic valve flow was quantified as well to test for intervalve consistency. The Wilcoxon signed rank test, orthogonal regression, Bland-Altman analysis, and coefficients of variation were used to assess agreement among measurements and between observers. Results: RvolFLOW was higher (median, 24.8 mL; interquartile range [IQR], 14.3–45.7 mL) than RvolVALVE (median, 9.9 mL; IQR, 6.0–16.9 mL; P < .001). Both RvolFLOW and RvolVALVE differed significantly from RvolINDIRECT (median, 19.1 mL; IQR, 4.1–47.5 mL; P = .03). RvolFLOW agreed more with RvolINDIRECT (ŷ = 0.78x + 12, r = 0.88) than with RvolVALVE (ŷ = 0.16x + 8.1, r = 0.53). Bland-Altman analysis revealed underestimation of RvolVALVE in severe MV regurgitation. Interobserver agreement was excellent for RvolFLOW (r = 0.95, coefficient of variation = 27%) and moderate for RvolVALVE (r = 0.72, coefficient of variation = 57%). Orthogonal regression demonstrated better intervalve consistency for flow tracking (ŷ = 1.2x-13.4, r = 0.82) than for valve tracking (ŷ = 2.7x-92.4, r = 0.67). Conclusion: Flow tracking enables more accurate 4D flow MRI–derived MV regurgitation quantification than valve tracking in terms of agreement with indirect quantification and intervalve consistency, particularly in severe MV regurgitation

Quantification of mitral valve regurgitation from 4d flow mri using semiautomated flow tracking

Purpose: To compare the accuracy of semiautomated flow tracking with that of semiautomated valve tracking in the quantification of mitral valve (MV) regurgitation from clinical four-dimensional (4D) flow MRI data obtained in patients with mild, moderate, or severe MV regurgitation. Materials and Methods: The 4D flow MRI data were retrospectively collected from 30 patients (21 men; mean age, 61 years ± 10 [stan-dard deviation]) who underwent 4D flow MRI from 2006 to 2016. Ten patients had mild MV regurgitation, nine had moderate MV regurgitation, and 11 had severe MV regurgitation, as diagnosed by using semiquantitative echocardiography. The regurgitant volume (Rvol) across the MV was obtained using three methods: indirect quantification of Rvol (RvolINDIRECT ), semiautomated quantification of Rvol using valve tracking (RvolVALVE ), and semiautomated quantification of Rvol using flow tracking (RvolFLOW ). A second observer repeated the measurements. Aortic valve flow was quantified as well to test for intervalve consistency. The Wilcoxon signed rank test, orthogonal regression, Bland-Altman analysis, and coefficients of variation were used to assess agreement among measurements and between observers. Results: RvolFLOW was higher (median, 24.8 mL; interquartile range [IQR], 14.3–45.7 mL) than RvolVALVE (median, 9.9 mL; IQR, 6.0–16.9 mL; P < .001). Both RvolFLOW and RvolVALVE differed significantly from RvolINDIRECT (median, 19.1 mL; IQR, 4.1–47.5 mL; P = .03). RvolFLOW agreed more with RvolINDIRECT (ŷ = 0.78x + 12, r = 0.88) than with RvolVALVE (ŷ = 0.16x + 8.1, r = 0.53). Bland-Altman analysis revealed underestimation of RvolVALVE in severe MV regurgitation. Interobserver agreement was excellent for RvolFLOW (r = 0.95, coefficient of variation = 27%) and moderate for RvolVALVE (r = 0.72, coefficient of variation = 57%). Orthogonal regression demonstrated better intervalve consistency for flow tracking (ŷ = 1.2x-13.4, r = 0.82) than for valve tracking (ŷ = 2.7x-92.4, r = 0.67). Conclusion: Flow tracking enables more accurate 4D flow MRI–derived MV regurgitation quantification than valve tracking in terms of agreement with indirect quantification and intervalve consistency, particularly in severe MV regurgitation

Whole-Heart 4D Flow MRI for Evaluation of Normal and Regurgitant Valvular Flow: A Quantitative Comparison Between Pseudo-Spiral Sampling and EPI Readout

Background: Pseudo-spiral Cartesian sampling with compressed sensing reconstruction has facilitated highly accelerated 4D flow magnetic resonance imaging (MRI) in various cardiovascular structures. However, unlike echo planar imaging (EPI)-accelerated 4D flow MRI, it has not been validated in whole-heart applications. Hypothesis: Pseudo-spiral 4D flow MRI (PROUD [PROspective Undersampling in multiple Dimensions]) is comparable to EPI in robustness of valvular flow measurements and remains comparable as the undersampling factor is increased and scan time reduced. Study Type: Prospective. Population: Twelve healthy subjects and eight patients with valvular regurgitation. Field Strength/Sequence: 3.0 T; PROUD and EPI 4D flow sequences, 2D flow and balanced steady-state free precession sequences. Assessment: Valvular blood flow was quantified using valve tracking. PROUD- and EPI-based measurements of aortic (AV) and pulmonary (PV) flow volumes and left and right ventricular stroke volumes were tested for agreement with 2D MRI-based measurements. PROUD reconstructions with undersampling factors (R) of 9, 14, 28, and 56 were tested for intervalve consistency (per valve, compared to the other valves) and preservation of peak velocities and E/A ratios. Statistical Tests: We used repeated measures ANOVA, Bland-Altman, Wilcoxon signed rank, and intraclass correlation coefficients. P < 0.05 was considered statistically significant. Results: PROUD and EPI intervalve consistencies were not significantly different both in healthy subjects (valve-averaged mean difference [limits of agreement width]: 3.2 ± 0.8 [8.7 ± 1.1] mL/beat for PROUD, 5.5 ± 2.9 [13.7 ± 2.3] mL/beat for EPI, P = 0.07) and in patients with valvular regurgitation (2.3 ± 1.2 [15.3 ± 5.9] mL/beat for PROUD, 0.6 ± 0.6 [19.3 ± 2.9] mL/beat for EPI, P = 0.47). Agreement between EPI and PROUD was higher than between 4D flow (EPI or PROUD) and 2D MRI for forward flow, stroke volumes, and regurgitant volumes. Up to R = 28 in healthy subjects and R = 14 in patients with valvular regurgitation, PROUD intervalve consistency remained comparable to that of EPI. Peak velocities and E/A ratios were preserved up to R = 9. Conclusion: PROUD is comparable to EPI in terms of intervalve consistency and may be used with higher undersampling factors to shorten scan times further. Level of Evidence: 1. Technical Efficacy Stage: 2

Retrospective Camera-Based Respiratory Gating in Clinical Whole-Heart 4D Flow MRI

Background: Respiratory gating is generally recommended in 4D flow MRI of the heart to avoid blurring and motion artifacts. Recently, a novel automated contact-less camera-based respiratory motion sensor has been introduced. Purpose: To compare camera-based respiratory gating (CAM) with liver-lung-navigator-based gating (NAV) and no gating (NO) for whole-heart 4D flow MRI. Study Type: Retrospective. Subjects: Thirty two patients with a spectrum of cardiovascular diseases. Field Strength/Sequence: A 3T, 3D-cine spoiled-gradient-echo-T1-weighted-sequence with flow-encoding in three spatial directions. Assessment: Respiratory phases were derived and compared against each other by cross-correlation. Three radiologists/cardiologist scored images reconstructed with camera-based, navigator-based, and no respiratory gating with a 4-point Likert scale (qualitative analysis). Quantitative image quality analysis, in form of signal-to-noise ratio (SNR) and liver-lung-edge (LLE) for sharpness and quantitative flow analysis of the valves were performed semi-automatically. Statistical Tests: One-way repeated measured analysis of variance (ANOVA) with Wilks's lambda testing and follow-up pairwise comparisons. Significance level of P ≤ 0.05. Krippendorff's-alpha-test for inter-rater reliability. Results: The respiratory signal analysis revealed that CAM and NAV phases were highly correlated (C = 0.93 ± 0.09, P 0.05). Pairwise comparisons showed that reconstructions without respiratory gating were different in flow measurements to either CAM or NAV or both, but no differences were found between CAM and NAV reconstructions. Data Conclusion: Camera-based respiratory gating performed as well as conventional liver-lung-navigator-based respiratory gating. Quantitative image quality analysis showed that both techniques were equivalent and superior to no-gating-reconstructions. Quantitative flow analysis revealed local flow differences (tricuspid/pulmonary valves) in images of no-gating-reconstructions, but no differences were found between images reconstructed with camera-based and navigator-based respiratory gating. Level of Evidence: 3. Technical Efficacy: Stage 2

Retrospective Camera-Based Respiratory Gating in Clinical Whole-Heart 4D Flow MRI

Background: Respiratory gating is generally recommended in 4D flow MRI of the heart to avoid blurring and motion artifacts. Recently, a novel automated contact-less camera-based respiratory motion sensor has been introduced. Purpose: To compare camera-based respiratory gating (CAM) with liver-lung-navigator-based gating (NAV) and no gating (NO) for whole-heart 4D flow MRI. Study Type: Retrospective. Subjects: Thirty two patients with a spectrum of cardiovascular diseases. Field Strength/Sequence: A 3T, 3D-cine spoiled-gradient-echo-T1-weighted-sequence with flow-encoding in three spatial directions. Assessment: Respiratory phases were derived and compared against each other by cross-correlation. Three radiologists/cardiologist scored images reconstructed with camera-based, navigator-based, and no respiratory gating with a 4-point Likert scale (qualitative analysis). Quantitative image quality analysis, in form of signal-to-noise ratio (SNR) and liver-lung-edge (LLE) for sharpness and quantitative flow analysis of the valves were performed semi-automatically. Statistical Tests: One-way repeated measured analysis of variance (ANOVA) with Wilks's lambda testing and follow-up pairwise comparisons. Significance level of P ≤ 0.05. Krippendorff's-alpha-test for inter-rater reliability. Results: The respiratory signal analysis revealed that CAM and NAV phases were highly correlated (C = 0.93 ± 0.09, P &lt; 0.01). Image scoring showed poor inter-rater reliability and no significant differences were observed (P ≥ 0.16). The image quality comparison showed that NAV and CAM were superior to NO with higher SNR (P = 0.02) and smaller LLE (P &lt; 0.01). The quantitative flow analysis showed significant differences between the three respiratory-gated reconstructions in the tricuspid and pulmonary valves (P ≤ 0.05), but not in the mitral and aortic valves (P &gt; 0.05). Pairwise comparisons showed that reconstructions without respiratory gating were different in flow measurements to either CAM or NAV or both, but no differences were found between CAM and NAV reconstructions. Data Conclusion: Camera-based respiratory gating performed as well as conventional liver-lung-navigator-based respiratory gating. Quantitative image quality analysis showed that both techniques were equivalent and superior to no-gating-reconstructions. Quantitative flow analysis revealed local flow differences (tricuspid/pulmonary valves) in images of no-gating-reconstructions, but no differences were found between images reconstructed with camera-based and navigator-based respiratory gating. Level of Evidence: 3. Technical Efficacy: Stage 2.ImPhys/Medical Imagin

Coronary Flow Assessment Using Accelerated 4D Flow MRI With Respiratory Motion Correction

Magnetic resonance imaging (MRI) can potentially be used for non-invasive screening of patients with stable angina pectoris to identify probable obstructive coronary artery disease. MRI-based coronary blood flow quantification has to date only been performed in a 2D fashion, limiting its clinical applicability. In this study, we propose a framework for coronary blood flow quantification using accelerated 4D flow MRI with respiratory motion correction and compressed sensing image reconstruction. We investigate its feasibility and repeatability in healthy subjects at rest. Fourteen healthy subjects received 8 times-accelerated 4D flow MRI covering the left coronary artery (LCA) with an isotropic spatial resolution of 1.0 mm3. Respiratory motion correction was performed based on 1) lung-liver navigator signal, 2) real-time monitoring of foot-head motion of the liver and LCA by a separate acquisition, and 3) rigid image registration to correct for anterior-posterior motion. Time-averaged diastolic LCA flow was determined, as well as time-averaged diastolic maximal velocity (VMAX) and diastolic peak velocity (VPEAK). 2D flow MRI scans of the LCA were acquired for reference. Scan-rescan repeatability and agreement between 4D flow MRI and 2D flow MRI were assessed in terms of concordance correlation coefficient (CCC) and coefficient of variation (CV). The protocol resulted in good visibility of the LCA in 11 out of 14 subjects (six female, five male, aged 28 ± 4 years). The other 3 subjects were excluded from analysis. Time-averaged diastolic LCA flow measured by 4D flow MRI was 1.30 ± 0.39 ml/s and demonstrated good scan-rescan repeatability (CCC/CV = 0.79/20.4%). Time-averaged diastolic VMAX (17.2 ± 3.0 cm/s) and diastolic VPEAK (24.4 ± 6.5 cm/s) demonstrated moderate repeatability (CCC/CV = 0.52/19.0% and 0.68/23.0%, respectively). 4D flow- and 2D flow-based diastolic LCA flow agreed well (CCC/CV = 0.75/20.1%). Agreement between 4D flow MRI and 2D flow MRI was moderate for both diastolic VMAX and VPEAK (CCC/CV = 0.68/20.3% and 0.53/27.0%, respectively). In conclusion, the proposed framework of accelerated 4D flow MRI equipped with respiratory motion correction and compressed sensing image reconstruction enables repeatable diastolic LCA flow quantification that agrees well with 2D flow MRI

Clinical intra-cardiac 4D flow CMR: acquisition, analysis, and clinical applications

Identification of flow patterns within the heart has long been recognized as a potential contribution to the understanding of physiological and pathophysiological processes of cardiovascular diseases. Although the pulsatile flow itself is multi-dimensional and multi-directional, current available non-invasive imaging modalities in clinical practice provide calculation of flow in only 1-direction and lack 3-dimensional volumetric velocity information. Four-dimensional flow cardiovascular magnetic resonance imaging (4D flow CMR) has emerged as a novel tool that enables comprehensive and critical assessment of flow through encoding velocity in all 3 directions in a volume of interest resolved over time. Following technical developments, 4D flow CMR is not only capable of visualization and quantification of conventional flow parameters such as mean/peak velocity and stroke volume but also provides new hemodynamic parameters such as kinetic energy. As a result, 4D flow CMR is being extensively exploited in clinical research aiming to improve understanding of the impact of cardiovascular disease on flow and vice versa. Of note, the analysis of 4D flow data is still complex and accurate analysis tools that deliver comparable quantification of 4D flow values are a necessity for a more widespread adoption in clinic. In this article, the acquisition and analysis processes are summarized and clinical applications of 4D flow CMR on the heart including conventional and novel hemodynamic parameters are discussed. Finally, clinical potential of other emerging intra-cardiac 4D flow imaging modalities is explored and a near-future perspective on 4D flow CMR is provided