Purpose
To compare cine and tagged magnetic resonance imaging (MRI) for left ventricular dyssynchrony assessment in left bundle branch block (LBBB), using the time‐to‐peak contraction timing, and a ...novel approach based on cross‐correlation.
Materials and Methods
We evaluated a canine model dataset (n = 10) before (pre‐LBBB) and after induction of isolated LBBB (post‐LBBB). Multislice short‐axis tagged and cine MRI images were acquired using a 1.5 T scanner. We computed contraction time maps by cross‐correlation, based on the timing of radial wall motion and of circumferential strain. Finally, we estimated dyssynchrony as the standard deviation of the contraction time over the different regions of the myocardium.
Results
Induction of LBBB resulted in a significant increase in dyssynchrony (cine: 13.0 ± 3.9 msec for pre‐LBBB, and 26.4 ± 5.0 msec for post‐LBBB, P = 0.005; tagged: 17.1 ± 5.0 msec at for pre‐LBBB, and 27.9 ± 9.8 msec for post‐LBBB, P = 0.007). Dyssynchrony assessed by cine and tagged MRI were in agreement (r = 0.73, P = 0.0003); differences were in the order of time difference between successive frames of 20 msec (bias: –2.9 msec; limit of agreement: 10.1 msec). Contraction time maps were derived; agreement was found in the contraction patterns derived from cine and tagged MRI (mean difference in contraction time per segment: 3.6 ± 13.7 msec).
Conclusion
This study shows that the proposed method is able to quantify dyssynchrony after induced LBBB in an animal model. Cine‐assessed dyssynchrony agreed with tagged‐derived dyssynchrony, in terms of magnitude and spatial direction. J. MAGN. RESON. IMAGING 2016;44:956–963.
Ultrasound speckle tracking is frequently used to quantify myocardial strain, and magnetic resonance imaging (MRI) feature tracking is rapidly gaining interest. Our aim is to validate cardiac MRI ...feature tracking by comparing it with the gold standard method (i.e., MRI tagging) in healthy subjects and patients. Furthermore, we aim to perform an indirect validation by comparing ultrasound speckle tracking with MRI feature tracking. Forty-two subjects (17 formerly preeclamptic women, three healthy women, and 22 left bundle branch block patients of both sexes) received 3-T cardiac MRI and echocardiography. Cine and tagged MRI, and B-mode ultrasound images, were acquired. Intrapatient global and segmental left ventricular circumferential (MRI tagging vs. MRI feature tracking) and longitudinal (MRI feature tracking vs. ultrasound speckle tracking) peak strain and time to peak strain were compared between the three techniques. Intraclass correlation coefficient (ICC) (< 0.50 = poor, 0.50-0.75 = moderate, > 0.75-0.90 = good, > 0.90 = excellent) and Bland-Altman analysis were used to assess correlation and bias; p less than 0.05 indicates a significant ICC or bias. Global peak strain parameters showed moderate-to-good correlations between methods (ICC = 0.71-0.83, p < 0.01) with no significant biases. Global time to peak strain parameters showed moderate-to-good correlations (ICC = 0.56-0.82, p < 0.01) with no significant biases. Segmental peak strains showed significant biases in all parameters and moderate-to-good correlation (ICC = 0.62-0.77, p < 0.01), except for lateral longitudinal peak strain (ICC = 0.23, p = 0.22). Segmental time to peak strain parameters showed moderate-to-good correlation (ICC = 0.58-0.74, p < 0.01) with no significant biases. MRI feature tracking is a valid method to examine myocardial strain, but there is bias in absolute segmental strain values between imaging techniques. MRI feature tracking shows adequate comparability with ultrasound speckle tracking.
Automated 4D flow MRI valvular flow quantification without time-consuming manual segmentation might improve workflow.
Compare automated valve segmentation (AS) to manual (MS), and manually corrected ...automated segmentation (AMS), in corrected atrioventricular septum defect (c-AVSD) patients and healthy volunteers, for assessing net forward volume (NFV) and regurgitation fraction (RF).
Retrospective.
27 c-AVSD patients (median, 23 years; interquartile range, 16-31 years) and 24 healthy volunteers (25 years; 12.5-36.5 years).
Whole-heart 4D flow MRI and cine steady-state free precession at 3T.
After automatic valve tracking, valve annuli were segmented on time-resolved reformatted trans-valvular velocity images by AS, MS, and AMS. NFV was calculated for all valves, and RF for right and left atrioventricular valves (RAVV and LAVV). NFV variation (standard deviation divided by mean NFV) and NFV differences (NFV difference of a valve vs. mean NFV of other valves) expressed internal NFV consistency.
Comparisons between methods were assessed by Wilcoxon signed-rank tests, and intra/interobserver variability by intraclass correlation coefficients (ICCs). P < 0.05 was considered statistically significant, with multiple testing correction.
AMS mean analysis time was significantly shorter compared with MS (5.3 ± 1.6 minutes vs. 9.1 ± 2.5 minutes). MS NFV variation (6.0%) was significantly smaller compared with AMS (6.3%), and AS (8.2%). Median NFV difference of RAVV, LAVV, PV, and AoV between segmentation methods ranged from -0.7-1.0 mL, -0.5-2.8 mL, -1.1-3.6 mL, and - 3.1--2.1 mL, respectively. Median RAVV and LAVV RF, between 7.1%-7.5% and 3.8%-4.3%, respectively, were not significantly different between methods. Intraobserver/interobserver agreement for AMS and MS was strong-to-excellent for NFV and RF (ICC ≥0.88).
MS demonstrates strongest internal consistency, followed closely by AMS, and AS. Automated segmentation, with or without manual correction, can be considered for 4D flow MRI valvular flow quantification.
3 TECHNICAL EFFICACY: Stage 3.
Objectives
To evaluate the in vivo feasibility of aortography with one accurately timed diastolic low‐volume contrast injection for quantitative assessment of aortic regurgitation (AR) post ...transcatheter aortic valve replacement (TAVR).
Background
With the rise of a minimalistic approach for TAVR, aortography (re)emerges as a pragmatic tool for AR assessment. In a mock circulation system, we have validated the accuracy of a single diastolic injection triggered by electrocardiogram (ECG) with low‐contrast volume.
Methods
Two‐phase experiment: first, a series of aortograms were performed in a porcine model, with 8 mL of contrast using the synchronized (SYNC) and the conventional non‐synchronized (NS) injections. In a second phase, we developed a model of AR by inserting partially unsheathed Wallstents of 6–10 mm of diameter across the pig's aortic valve, performing SYNC injections with 8 mL of contrast and NS injections with 8 mL and 15 mL (rate: 20 mL/sec). Respective accuracies of SYNC vs. NS were assessed using Passing‐Bablock regression. An angiography core laboratory performed quantitative AR assessment with videodensitometry (VD‐AR).
Results
The SYNC injections produced higher opacification of the aortic root compared with NS injections (P = 0.04 for density). In the second phase, a regression line for predicting VD‐AR based on the SYNC injection resulted in a lower intercept and a slope closer to the line of identity (y = 11.9 + 0.79x, P < 0.001, r2 = 0.94) with the NS‐8 mL than with the NS‐15 mL injection (y = 26.5 + 0.55x, P < 0.001, r2 = 0.81).
Conclusion
Synchronized diastolic injection with low contrast volume produced denser images in the aortic root and more accurate than the conventional injection; thus, may be an appealing alternative for assessment of AR post TAVR.
In this study, we analyzed turbulent flows through a phantom (a 180Formula: see text bend with narrowing) at peak systole and a patient-specific coarctation of the aorta (CoA), with a pulsating flow, ...using magnetic resonance imaging (MRI) and computational fluid dynamics (CFD). For MRI, a 4D-flow MRI is performed using a 3T scanner. For CFD, the standard Formula: see text, shear stress transport Formula: see text, and Reynolds stress (RSM) models are applied. A good agreement between measured and simulated velocity is obtained for the phantom, especially for CFD with RSM. The wall shear stress (WSS) shows significant differences between CFD and MRI in absolute values, due to the limited near-wall resolution of MRI. However, normalized WSS shows qualitatively very similar distributions of the local values between MRI and CFD. Finally, a direct comparison between in vivo 4D-flow MRI and CFD with the RSM turbulence model is performed in the CoA. MRI can properly identify regions with locally elevated or suppressed WSS. If the exact values of the WSS are necessary, CFD is the preferred method. For future applications, we recommend the use of the combined MRI/CFD method for analysis and evaluation of the local flow patterns and WSS in the aorta.
The purpose of this study was to evaluate a semi-automatic right ventricle segmentation method on short-axis cardiac cine MR images which segment all right ventricle contours in a cardiac phase using ...one seed contour. Twenty-eight consecutive short-axis, four-chamber, and tricuspid valve view cardiac cine MRI examinations of healthy volunteers were used. Two independent observers performed the manual and automatic segmentations of the right ventricles. Analyses were based on the ventricular volume and ejection fraction of the right heart chamber. Reproducibility of the manual and semi-automatic segmentations was assessed using intra- and inter-observer variability. Validity of the semi-automatic segmentations was analyzed with reference to the manual segmentations. The inter- and intra-observer variability of manual segmentations were between 0.8 and 3.2%. The semi-automatic segmentations were highly correlated with the manual segmentations (
R
2
0.79–0.98), with median difference of 0.9–4.8% and of 3.3% for volume and ejection fraction parameters, respectively. In comparison to the manual segmentation, the semi-automatic segmentation produced contours with median dice metrics of 0.95 and 0.87 and median Hausdorff distance of 5.05 and 7.35 mm for contours at end-diastolic and end-systolic phases, respectively. The inter- and intra-observer variability of the semi-automatic segmentations were lower than observed in the manual segmentations. Both manual and semi-automatic segmentations performed better at the end-diastolic phase than at the end-systolic phase. The investigated semi-automatic segmentation method managed to produce a valid and reproducible alternative to manual right ventricle segmentation.
Wall shear stress (WSS) has been associated with atherogenesis and plaque progression. The present study assessed the value of WSS analysis derived from conventional coronary angiography to detect ...lesions culprit for future myocardial infarction (MI).
Three-dimensional quantitative coronary angiography (3DQCA), was used to calculate WSS and pressure drop in 80 patients. WSS descriptors were compared between 80 lesions culprit of future MI and 108 non-culprit lesions (controls). Endothelium-blood flow interaction was assessed by computational fluid dynamics (10.8 ± 1.41 min per vessel). Median time between baseline angiography and MI was 25.9 (21.9–29.8) months. Mean patient age was 70.3 ± 12.7. Clinical presentation was STEMI in 35% and NSTEMI in 65%. Culprit lesions showed higher percent area stenosis (%AS), translesional vFFR difference (ΔvFFR), time-averaged WSS (TAWSS) and topological shear variation index (TSVI) compared to non-culprit lesions (p < 0.05 for all). TSVI was superior to TAWSS in predicting MI (AUC-TSVI = 0.77, 95%CI 0.71–0.84 vs. AUC-TAWSS = 0.61, 95%CI 0.53–0.69, p < 0.001). The addition of TSVI increased predictive and reclassification abilities compared to a model based on %AS and ΔvFFR (NRI = 1.04, p < 0.001, IDI = 0.22, p < 0.001).
A 3DQCA-based WSS analysis was feasible and can identify lesions culprit for future MI. The combination of area stenoses, pressure gradients and WSS predicted the occurrence of MI. TSVI, a novel WSS descriptor, showed strong predictive capacity to detect lesions prone to cause MI.
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•Lesions culprit of future myocardial infarction (MI) had higher area stenosis, pressure gradient, time-averaged wall shear stress (TAWSS) and topological shear variation index (TSVI).•A three-dimensional quantitative coronary angiography (3DQCA)-based software provided in few minutes reliable WSS simulations.•The WSS topological skeleton feature TSVI showed strong predictive capacity for MI.
The present study establishes a link between blood flow energy transformations in coronary atherosclerotic lesions and clinical outcomes. The predictive capacity for future myocardial infarction (MI) ...was compared with that of established quantitative coronary angiography (QCA)-derived predictors. Angiography-based computational fluid dynamics (CFD) simulations were performed on 80 human coronary lesions culprit of MI within 5 years and 108 non-culprit lesions for future MI. Blood flow energy transformations were assessed in the converging flow segment of the lesion as ratios of kinetic and rotational energy values (KER and RER, respectively) at the QCA-identified minimum lumen area and proximal lesion sections. The anatomical and functional lesion severity were evaluated with QCA to derive percentage area stenosis (%AS), vessel fractional flow reserve (vFFR), and translesional vFFR (ΔvFFR). Wall shear stress profiles were investigated in terms of topological shear variation index (TSVI). KER and RER predicted MI at 5 years (AUC = 0.73, 95% CI 0.65–0.80, and AUC = 0.76, 95% CI 0.70–0.83, respectively;
p
< 0.0001 for both). The predictive capacity for future MI of KER and RER was significantly stronger than vFFR (
p
= 0.0391 and
p
= 0.0045, respectively). RER predictive capacity was significantly stronger than %AS and ΔvFFR (
p
= 0.0041 and
p
= 0.0059, respectively). The predictive capacity for future MI of KER and RER did not differ significantly from TSVI. Blood flow kinetic and rotational energy transformations were significant predictors for MI at 5 years (
p
< 0.0001). The findings of this study support the hypothesis of a biomechanical contribution to the process of plaque destabilization/rupture leading to MI.
Doppler echocardiographic aortic valve peak velocity and peak pressure gradient assessment across the aortic valve (AV) is the mainstay for diagnosing aortic stenosis. Four-dimensional flow ...cardiovascular magnetic resonance (4D flow CMR) is emerging as a valuable diagnostic tool for estimating the peak pressure drop across the aortic valve, but assessment remains cumbersome. We aimed to validate a novel semi-automated pipeline 4D flow CMR method of assessing peak aortic value pressure gradient (AVPG) using the commercially available software solution, CAAS MR Solutions, against invasive angiographic methods.
We enrolled 11 patients with severe AS on echocardiography from the EurValve programme. All patients had pre-intervention doppler echocardiography, invasive cardiac catheterisation with peak pressure drop assessment across the AV and 4D flow CMR. The peak AVPG was 51.9 ± 35.2 mmHg using the invasive pressure drop method and 52.2 ± 29.2 mmHg for the 4D flow CMR method (semi-automated pipeline), with good correlation between the two methods (r = 0.70, p = 0.017). Assessment of AVPG by 4D flow CMR using the novel semi-automated pipeline method shows excellent agreement to invasive assessment when compared to doppler-based methods and advocate for its use as complementary to echocardiography.
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