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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., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

This study focuses on identifying anatomical markers with predictive capacity for long-term myocardial infarction (MI) in focal coronary artery disease (CAD). Eighty future culprit lesions (FCL) and 108 non-culprit lesions (NCL) from 80 patients underwent 3D quantitative coronary angiography. The minimum lumen area (MLA), minimum lumen ratio (MLR), and vessel fractional flow reserve (vFFR) were evaluated. MLR was defined as the ratio between MLA and the cross-sectional area at the proximal lesion edge, with lower values indicating more abrupt luminal narrowing. Significant differences were observed between FCL and NCL in MLR (0.41 vs. 0.53, p < 0.001). MLR correlated inversely with translesional vFFR (r =  - 0.26, p = 0.0004) and was the strongest predictor of MI at 5 years (AUC = 0.75). Lesions with MLR < 0.40 had a fourfold increased MI incidence at 5 years. MLR is a robust predictor of future adverse coronary events., (© 2024. The Author(s).)

Background: Automated 4D flow MRI valvular flow quantification without time-consuming manual segmentation might improve workflow., Purpose: 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)., Study Type: Retrospective., Population: 27 c-AVSD patients (median, 23 years; interquartile range, 16-31 years) and 24 healthy volunteers (25 years; 12.5-36.5 years)., Field Strength/sequence: Whole-heart 4D flow MRI and cine steady-state free precession at 3T., Assessment: 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., Statistical Tests: 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., Results: 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)., Data Conclusion: 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., Level of Evidence: 3 TECHNICAL EFFICACY: Stage 3., (© 2024 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background and Aims: Coronary hemodynamics impact coronary plaque progression and destabilization. The aim of the present study was to establish the association between focal vs. diffuse intracoronary pressure gradients and wall shear stress (WSS) patterns with atherosclerotic plaque composition., Methods: Prospective, international, single-arm study of patients with chronic coronary syndromes and hemodynamic significant lesions (fractional flow reserve [FFR] ≤ 0.80). Motorized FFR pullback pressure gradient (PPG), optical coherence tomography (OCT), and time-average WSS (TAWSS) and topological shear variation index (TSVI) derived from three-dimensional angiography were obtained., Results: One hundred five vessels (median FFR 0.70 [Interquartile range (IQR) 0.56-0.77]) had combined PPG and WSS analyses. TSVI was correlated with PPG (r = 0.47, [95% Confidence Interval (95% CI) 0.30-0.65], p < 0.001). Vessels with a focal CAD (PPG above the median value of 0.67) had significantly higher TAWSS (14.8 [IQR 8.6-24.3] vs. 7.03 [4.8-11.7] Pa, p < 0.001) and TSVI (163.9 [117.6-249.2] vs. 76.8 [23.1-140.9] m -1 , p < 0.001). In the 51 vessels with baseline OCT, TSVI was associated with plaque rupture (OR 1.01 [1.00-1.02], p = 0.024), PPG with the extension of lipids (OR 7.78 [6.19-9.77], p = 0.003), with the presence of thin-cap fibroatheroma (OR 2.85 [1.11-7.83], p = 0.024) and plaque rupture (OR 4.94 [1.82 to 13.47], p = 0.002)., Conclusions: Focal and diffuse coronary artery disease, defined using coronary physiology, are associated with differential WSS profiles. Pullback pressure gradients and WSS profiles are associated with atherosclerotic plaque phenotypes. Focal disease (as identified by high PPG) and high TSVI are associated with high-risk plaque features., Clinical Trial Registration: https://clinicaltrials,gov/ct2/show/NCT03782688., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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., (© 2023. The Author(s).)

Wall shear stress (WSS) estimated in models reconstructed from intravascular imaging and 3-dimensional-quantitative coronary angiography (3D-QCA) data provides important prognostic information and enables identification of high-risk lesions. However, these analyses are time-consuming and require expertise, limiting WSS adoption in clinical practice. Recently, a novel software has been developed for real-time computation of time-averaged WSS (TAWSS) and multidirectional WSS distribution. This study aims to examine its inter-corelab reproducibility. Sixty lesions (20 coronary bifurcations) with a borderline negative fractional flow reserve were processed using the CAAS Workstation WSS prototype to estimate WSS and multi-directional WSS values. Analysis was performed by two corelabs and their estimations for the WSS in 3 mm segments across each reconstructed vessel was extracted and compared. In total 700 segments (256 located in bifurcated vessels) were included in the analysis. A high intra-class correlation was noted for all the 3D-QCA and TAWSS metrics between the estimations of the two corelabs irrespective of the presence (range: 0.90-0.92) or absence (range: 0.89-0.90) of a coronary bifurcation, while the ICC was good-moderate for the multidirectional WSS (range: 0.72-0.86). Lesion level analysis demonstrated a high agreement of the two corelabls for detecting lesions exposed to an unfavourable haemodynamic environment (WSS > 8.24 Pa, κ = 0.77) that had a high-risk morphology (area stenosis > 61.3%, κ = 0.71) and were prone to progress and cause events. The CAAS Workstation WSS enables reproducible 3D-QCA reconstruction and computation of WSS metrics. Further research is needed to explore its value in detecting high-risk lesions., (© 2023. The Author(s).)

Paravalvular leak (PVL) is a shortcoming that can erode the clinical benefits of transcatheter valve replacement (TAVR) and therefore a readily applicable method (aortography) to quantitate PVL objectively and accurately in the interventional suite is appealing to all operators. The ratio between the areas of the time-density curves in the aorta and left ventricular outflow tract (LVOT-AR) defines the regurgitation fraction (RF). This technique has been validated in a mock circulation; a single injection in diastole was further tested in porcine and ovine models. In the clinical setting, LVOT-AR was compared with trans-thoracic and trans-oesophageal echocardiography and cardiac magnetic resonance imaging. LVOT-AR > 17% discriminates mild from moderate aortic regurgitation on echocardiography and confers a poor prognosis in multiple registries, and justifies balloon post-dilatation. The LVOT-AR differentiates the individual performances of many old and novel devices and is being used in ongoing randomized trials and registries., Competing Interests: PWS reports personal fees from Philips/Volcano, SMT, Novartis, Xeltis, Merillife. PCR has no conflict of interest. Aben is an employee of Pie Medical Imaging. MC is employed by and holds shares of Xeltis BV CS is an employee of Philips Healthcare. MA-W reports other from Medtronic, other from Boston Scientific, outside the submitted work. NP is a consultant to Medtronic, Peijia, and MicroPort. RM is an employee of Boston Scientific. AR reports grants and personal fees from Boston Scientific, personal fees from Edwards Lifesciences, outside the submitted work. KK reports personal fees from Abbott, personal fees from Boston Scientific, personal fees from Edwards Lifesciences, personal fees from Medtronic, personal fees from Meril Life Sciences, outside the submitted work. NVR reports grants and personal fees from Abbott, grants from Philips, grants from Biotronik, and personal fees from Microport, outside the submitted work. Rudolph is a proctor, speaker’s honoraria of JenaValve. FJN reports personal fees from Amgen, personal fees from Boehringer Ingelheim, personal fees from Daiichi Sankyo, grants and personal fees from Pfizer, grants and personal fees from Biotronic, grants and personal fees from Edwards Lifesciences, grants from Medtronic, grants and personal fees from Bayer Healthcare, personal fees from Novartis, grants from GlaxoSmithKline, grants and personal fees from Boston Scientific, personal fees from Ferrer, outside the submitted work. IJA-S is a proctor for Medtronic, Boston Scientific and Meril Life. OS and YO report several institutional research grants, outside the submitted work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Abdelshafy, Serruys, Tsai, Revaiah, Grag, Aben, Schultz, Abdelghani, Tonino, Miyazaki, Rutten, Cox, Sahyoun, Teng, Tateishi, Abdel-Wahab, Piazza, Pighi, Modolo, van Mourik, Wykrzykowska, de Wintet, Lemos, de Brito, Kawashima, Søendergaard, Rosseel, Wang, Gao, Tao, Rück, Kim, van Royen, Terkelsen, Nissen, Adam, Rudolph, Wienemann, Torii, Neuman, Schoechlin, Chen, Elkoumy, Elzomor, Amat-Santos, Mylotte, Soliman and Onuma.)

Patients with intermediate anatomical degree of coronary artery stenosis require determination of its functional significance. Currently, the reference standard for determining the functional significance of a stenosis is invasive measurement of the fractional flow reserve (FFR), which is associated with high cost and patient burden. To address these drawbacks, FFR can be predicted non-invasively from a coronary CT angiography (CCTA) scan. Hence, we propose a deep learning method for predicting the invasively measured FFR of an artery using a CCTA scan. The study includes CCTA scans of 569 patients from three hospitals. As reference for the functional significance of stenosis, FFR was measured in 514 arteries in 369 patients, and in the remaining 200 patients, obstructive coronary artery disease was ruled out by Coronary Artery Disease-Reporting and Data System (CAD-RADS) category 0 or 1. For prediction, the coronary tree is first extracted and used to reconstruct an MPR for the artery at hand. Thereafter, the coronary artery is characterized by its lumen, its attenuation and the area of the coronary artery calcium in each artery cross-section extracted from the MPR using a CNN. Additionally, characteristics indicating the presence of bifurcations and information indicating whether the artery is a main branch or a side-branch of a main artery are derived from the coronary artery tree. All characteristics are fed to a second network that predicts the FFR value and classifies the presence of functionally significant stenosis. The final result is obtained by merging the two predictions. Performance of our method is evaluated on held out test sets from multiple centers and vendors. The method achieves an area under the receiver operating characteristics curve (AUC) of 0.78, outperforming other works that do not require manual correction of the segmentation of the artery. This demonstrates that our method may reduce the number of patients that unnecessarily undergo invasive measurements., Competing Interests: Author CC reports receiving institutional research grants from GE Healthcare, Siemens, Insight Lifetech, Coroventis Research, Medis Medical Imaging, Pie Medical Imaging, CathWorks, Boston Scientific, HeartFlow, Abbott Vascular, and consultancy fees from HeartFlow, Abbott Vascular, and Cryotherapeutics. Author II reports institutional research grants by Pie Medical Imaging, Dutch Technology Foundation with participation of Pie Medical Imaging and Philips Healthcare (DLMedIA P15-26). Author J-PA was employed by Pie Medical Imaging BV. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Hampe, van Velzen, Planken, Henriques, Collet, Aben, Voskuil, Leiner and Išgum.)

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 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., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: To validate the k-adaptive-t autocalibrating reconstruction for Cartesian sampling (kat-ARC), an exclusive sparse reconstruction technique for four-dimensional (4D) flow cardiac magnetic resonance (CMR) using conservation of mass principle applied to transvalvular flow., Methods: This observational retrospective study (2020/21-075) was approved by the local ethics committee at the University of East Anglia. Consent was waived. Thirty-five patients who had a clinical CMR scan were included. CMR protocol included cine and 4D flow using Kat-ARC acceleration factor 6. No respiratory navigation was applied. For validation, the agreement between mitral net flow (MNF) and the aortic net flow (ANF) was investigated. Additionally, we checked the agreement between peak aortic valve velocity derived by 4D flow and that derived by continuous-wave Doppler echocardiography in 20 patients., Results: The median age of our patient population was 63 years (interquartile range [IQR] 54-73), and 18/35 (51%) were male. Seventeen (49%) patients had mitral regurgitation, and seven (20%) patients had aortic regurgitation. Mean acquisition time was 8 ± 4 min. MNF and ANF were comparable: 60 mL (51-78) versus 63 mL (57-77), p = 0.310). There was an association between MNF and ANF (rho = 0.58, p < 0.001). Peak aortic valve velocity by Doppler and 4D flow were comparable (1.40 m/s, [1.30-1.75] versus 1.46 m/s [1.25-2.11], p = 0.602) and also correlated with each other (rho = 0.77, p < 0.001)., Conclusions: Kat-ARC accelerated 4D flow CMR quantified transvalvular flow in accordance with the conservation of mass principle and is primed for clinical translation., (© 2022. The Author(s) under exclusive licence to European Society of Radiology.)

Background: Wall shear stress (WSS) estimated in 3D-quantitative coronary angiography (QCA) models appears to provide useful prognostic information and identifies high-risk patients and lesions. However, conventional computational fluid dynamics (CFD) analysis is cumbersome limiting its application in the clinical arena. This report introduces a user-friendly software that allows real-time WSS computation and examines its reproducibility and accuracy in assessing WSS distribution against conventional CFD analysis., Methods: From a registry of 414 patients with borderline negative fractional flow reserve (0.81-0.85), 100 lesions were randomly selected. 3D-QCA and CFD analysis were performed using the conventional approach and the novel CAAS Workstation WSS software, and QCA as well as WSS estimations of the two approaches were compared. The reproducibility of the two methodologies was evaluated in a subgroup of 50 lesions., Results: A good agreement was noted between the conventional approach and the novel software for 3D-QCA metrics (ICC range: 0.73-0-93) and maximum WSS at the lesion site (ICC: 0.88). Both methodologies had a high reproducibility in assessing lesion severity (ICC range: 0.83-0.97 for the conventional approach; 0.84-0.96 for the CAAS Workstation WSS software) and WSS distribution (ICC: 0.85-0.89 and 0.83-0.87, respectively). Simulation time was significantly shorter using the CAAS Workstation WSS software compared to the conventional approach (4.13 ± 0.59 min vs 23.14 ± 2.56 min, p < 0.001)., Conclusion: CAAS Workstation WSS software is fast, reproducible, and accurate in assessing WSS distribution. Therefore, this software is expected to enable the broad use of WSS metrics in the clinical arena to identify high-risk lesions and vulnerable patients., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Objective: 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., Results: 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., (© 2022. The Author(s).)

Background and Aims: 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)., Methods and Results: 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)., Conclusions: 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., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In this study, we analyzed turbulent flows through a phantom (a 180[Formula: 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., (© 2021. The Author(s).)

Objectives: We aimed to compare the quantitative angiographic aortic regurgitation (AR) into the left ventricular out flow tract (LVOT-AR) of five different types of transcatheter self-expanding valves and to investigate the impact of the learning curve on post-TAVR AR., Background: Quantitative video densitometric aortography is an objective, accurate, and reproducible tool for assessment of AR following TAVR., Methods and Results: This retrospective academic core-lab analysis, analyzed 1150 consecutive cine aortograms performed immediately post-TAVR. Quantitative angiographic AR of post-procedural aortography in 181 consecutive patients, who underwent TAVR with the Venus A-valve in a single Chinese center, were compared to the results of Evolut Pro, Evolut R, CoreValve, (Medtronic, Dublin, Ireland) and Acurate Neo (Boston Scientific, Massachusetts, US) transcatheter heart valves (THVs), from a previously published pooled database. Among the 181 aortograms of patients treated with the Venus A-Valve, 113 (62.4%) were analyzable for quantitative assessment of AR. The mean LVOT-AR was 8.9% ± 10.0% with 14.2% of patients having moderate or severe AR in the Venus A-valve group. No significant difference in mean LVOT-AR was observed between Evolut Pro, Evolut R, Acurate Neo, and Venus A-valve. The incidence of LVOT-AR >17%, which correlates with echocardiographic derived ≥ moderate AR, with the Evolut Pro was lower than with the Venus A-valve (5.3% vs. 14.2%, p = 0.034), but was not different from the Evolut R (5.3% vs. 8.8%, p = 0.612), or the Acurate Neo (5.3% vs. 11.3% p = 0.16) systems. A landmark analysis after recruitment of the first half of patients treated with the Venus A valve (N = 56), showed a significantly lower mean LVOT-AR in the second half of the series (11.3% ± 11.9% vs. 6.5% ± 7.1%, p = 0.011). The incidence of LVOT-AR >17% in the latest 57 cases was also numerically lower (7.0% vs. 21.4%, p = 0.857) and compared favorably with the best in class of the self-expanding valves., Conclusion: The Venus A-valve has comparable mean LVOT-AR to other self-expanding valves but has a higher rate of moderate or severe AR than the Evolut Pro THV. However, after completion of a learning phase, results improved and compared favorably with the best in class of the commercially available self-expanding valves. These findings should be confirmed in prospective randomized comparisons of AR between different THVs., Competing Interests: Dr. Serruys reports personal fees from Merillife, Novartis, Philips/Volcano, SMT, Sinomedical Sciences Technology, Xeltis outside the submitted work. Dr. Mylotte is a consultant for Medtronic, Boston Scientific, and Microport. JP. Aben is employee of Pie Medical Imaging. All other authors have no conflicts of interest to declare., (Copyright: © 2021 The Author(s).)

Objectives: This study aimed to validate a dedicated software for quantitative videodensitometric angiographic assessment of mitral regurgitation (QMR)., Background: Quantitative videodensitometric aortography of aortic regurgitation using the time-density principle is a well-documented technique, but the angiographic assessment of mitral regurgitation (MR) remains at best semi-quantitative and operator dependent., Methods: Fourteen sheep underwent surgical mitral valve replacement using 2 different prostheses. Pre-sacrifice left ventriculograms were used to assess MR fraction (MRF) using QMR and MR volume (MRV). In an independent core lab, the CAAS QMR 0.1 was used for QMR analysis. In vitro MRF and MRV were assessed in a mock circulation at a comparable cardiac output to the in vivo one by thermodilution. The correlations and agreements of in vitro and in vivo MRF, MRV, and interobserver reproducibility for QMR analysis were assessed using the averaged cardiac cycles (CCs)., Results: In vivo derived MRF by QMR strongly correlated with in vitro derived MRF, regardless of the number of the CCs analyzed (best correlation: 3 CCs y = 0.446 + 0.994x; R = 0.784; p =0.002). The mean absolute difference between in vitro derived MRF and in vivo derived MRF from 3 CCs was 0.01 ± 4.2% on Bland-Altman analysis. In vitro MRV and in vivo MRV from 3 CCs were very strongly correlated (y = 0.196 + 1.255x; R = 0.839; p < 0.001). The mean absolute difference between in vitro MRV and in vivo MRV from 3 CCs was -1.4 ± 1.9 ml. There were very strong correlations of in vivo MRF between 2 independent analysts, regardless of the number of the CCs., Conclusions: In vivo MRF using the novel software is feasible, accurate, and highly reproducible. These promising results have led us to initiate the first human feasibility study comprising patients undergoing percutaneous mitral valve edge-to-edge repair., Competing Interests: Funding Support and Author Disclosures Dr. Serruys has received personal fees from Biosensors, Medtronic, Micel Technologies, Sinomedical Sciences Technology, St. Jude Medical, Philips/Volcano, Xeltis, and HeartFlow, outside the submitted work. Mr. Aben is an employee of Pie Medical Imaging. Dr. Mylotte has served as a consultant for Medtronic, Boston Scientific, and Microport. Dr. Cox and W. Brunnett are employees of Xeltis. Dr. Pibarot has received grants from Cardiac Phoenix, from Edwards Lifesciences, outside the submitted work. Dr. Soliman has received several institutional research grants outside the submitted work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: The aim of this study was to investigate the online assessment feasibility of aortography using videodensitometry in the catheterization laboratory during transcatheter aortic valve replacement (TAVR)., Background: Quantitative assessment of regurgitation after TAVR through aortography using videodensitometry is simple, reproducible, and validated in vitro, in vivo, in clinical trials, and in "real-world" patients. However, thus far the assessment has been done offline., Methods: This was a single center, prospective, proof-of-principle, feasibility study. One hundred consecutive patients with aortic stenosis and indications to undergo TAVR were enrolled. All final aortograms were analyzed immediately after acquisition in the catheterization laboratory and were also sent to an independent core laboratory for blinded offline assessment. The primary endpoint of the study was the feasibility of the online assessment of regurgitation (percentage of analyzable cases). The secondary endpoint was the reproducibility of results between the online assessment and the offline analysis by the core laboratory., Results: Patients' mean age was 81 ± 7 years, and 56% were men. The implanted valves were either SAPIEN 3 (97%) or SAPIEN 3 Ultra (3%). The primary endpoint of online feasibility of analysis was 92% (95% confidence interval [CI]: 86% to 97%) which was the same feasibility encountered by the core laboratory (92%; 95% CI: 86% to 97%). Reproducibility assessment showed a high correlation between online and core laboratory evaluations (R 2  = 0.87, p < 0.001), with an intraclass correlation coefficient of 0.962 (95% CI: 0.942 to 0.975; p < 0.001)., Conclusions: This study showed high feasibility of online quantitative assessment of regurgitation and high agreement between the online examiner and core laboratory. These results may pave the way for the application of videodensitometry in the catheterization laboratory after TAVR. (Online Videodensitometric Assessment of Aortic Regurgitation in the Cath-Lab [OVAL]; NCT04047082)., Competing Interests: Funding Support And Author Disclosures Dr. Modolo has received research grants from Biosensors and SMT, not related to the present work. Mr. Aben is an employee of Pie Medical Imaging. Mr. Slots is employed by the company that developed CAAS A-Valve. Dr. Sahyoun is a full-time employee of Philips Healthcare. Dr. Baan has received an unrestricted research grant from Edwards Lifesciences. Prof. Serruys has received personal fees from Abbott Laboratories, AstraZeneca, Biotronik, Cardialysis, GLG Research, Medtronic, Sino Medical Sciences Technology, Société Europa Digital Publishing, and Stentys. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

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 [standard 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 (Rvol INDIRECT ), semiautomated quantification of Rvol using valve tracking (Rvol VALVE ), and semiautomated quantification of Rvol using flow tracking (Rvol FLOW ). 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: Rvol FLOW was higher (median, 24.8 mL; interquartile range [IQR], 14.3-45.7 mL) than Rvol VALVE (median, 9.9 mL; IQR, 6.0-16.9 mL; P < .001). Both Rvol FLOW and Rvol VALVE differed significantly from Rvol INDIRECT (median, 19.1 mL; IQR, 4.1-47.5 mL; P = .03). Rvol FLOW agreed more with Rvol INDIRECT ( ŷ = 0.78 x + 12, r = 0.88) than with Rvol VALVE ( ŷ = 0.16 x + 8.1, r = 0.53). Bland-Altman analysis revealed underestimation of Rvol VALVE in severe MV regurgitation. Interobserver agreement was excellent for Rvol FLOW ( r = 0.95, coefficient of variation = 27%) and moderate for Rvol VALVE ( r = 0.72, coefficient of variation = 57%). Orthogonal regression demonstrated better intervalve consistency for flow tracking ( ŷ = 1.2 x - 13.4, r = 0.82) than for valve tracking ( ŷ = 2.7 x - 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. Supplemental material is available for this article. © RSNA, 2020., Competing Interests: Disclosures of Conflicts of Interest: C.P.S.B. Activities related to the present article: data analysis software was provided by Pie Medical Imaging. Activities not related to the present article: disclosed no relevant relationships. Other relationships: disclosed no relevant relationships. J.J.M.W. disclosed no relevant relationships. J.P.A. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: is employed by Pie Medical Imaging. Other relationships: institution has patent pending with Pie Medical Imaging. G.P.B. disclosed no relevant relationships. S.A.J.C. disclosed no relevant relationships. S.M.B. disclosed no relevant relationships. A.J.N. disclosed no relevant relationships. T.L. Activities related to the present article: disclosed no relevant relationships. Activities not related to the present article: institution receives payment for lectures including service on speakers bureaus from Philips Healthcare and Bayer Healthcare. Other relationships: disclosed no relevant relationships. P.v.O. disclosed no relevant relationships. R.N.P. disclosed no relevant relationships., (2020 by the Radiological Society of North America, Inc.)

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, r 2  = 0.94) with the NS-8 mL than with the NS-15 mL injection (y = 26.5 + 0.55x, P < 0.001, r 2  = 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., (© 2018 Wiley Periodicals, Inc.)

Purpose To compare four-dimensional flow MRI with automated valve tracking to manual valve tracking in patients with acquired or congenital heart disease and healthy volunteers. Materials and Methods In this retrospective study, data were collected from 114 patients and 46 volunteers who underwent four-dimensional flow MRI at 1.5 T or 3.0 T from 2006 through 2017. Among the 114 patients, 33 had acquired and 81 had congenital heart disease (median age, 17 years; interquartile range [IQR], 13-49 years), 51 (45%) were women, and 63 (55%) were men. Among the 46 volunteers (median age, 28 years; IQR, 22-36 years), there were 19 (41%) women and 27 (59%) men. Two orthogonal cine views of each valve were used for valve tracking. Wilcoxon signed-rank test was used to compare analysis times, net forward volumes (NFVs), and regurgitant fractions. Intra- and interobserver variability was tested by using intraclass correlation coefficients (ICCs). Results Analysis time was shorter for automated versus manual tracking (all patients, 14 minutes [IQR, 12-15 minutes] vs 25 minutes [IQR, 20-25 minutes]; P < .001). Although overall differences in NFV and regurgitant fraction were comparable between both methods, NFV variation over four valves was smaller for automated versus manual tracking (all patients, 4.9% [IQR, 3.3%-6.7%] vs 9.8% [IQR, 5.1%-14.7%], respectively; P < .001). Regurgitation severity was discordant for seven pulmonary valves, 22 mitral valves, and 21 tricuspid valves. Intra- and interobserver agreement for automated tracking was excellent for NFV assessment (intra- and interobserver, ICC ≥ 0.99) and strong to excellent for regurgitant fraction assessment (intraobserver, ICC ≥ 0.94; interobserver, ICC ≥ 0.89). Conclusion Automated valve tracking reduces analysis time and improves reliability of valvular flow quantification with four-dimensional flow MRI in patients with acquired or congenital heart disease and in healthy volunteers. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by François in this issue.

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.

Aims: Videodensitometric assessment of aortography provides a periprocedural quantitation of prosthetic valve regurgitation (PVR) after transcatheter aortic valve implantation. We sought to compare the videodensitometric parameters of PVR severity to the regurgitation fraction (RF) in a controlled in vitro setting., Methods and Results: In a mock circulation system, a transcatheter balloon-expandable valve inserted at the aortic valve position was gradually deformed to induce different grades of paravalvular leakage and the RF was measured with a transonic flow probe. Contrast aortography was performed and the following videodensitometric parameters were generated: left ventricle aortic regurgitation (LV-AR), LV outflow tract AR (LVOT-AR), quantitative regurgitation assessment (qRA) index, relative maximum density (relative max), and maximum upslope of the LV time-density curve. The correlation was substantial between videodensitometric parameters (LV-AR, LVOT-AR, qRA index, relative max, and maximum upslope) and RF (r2=0.96, 0.96, 0.93, 0.87, and 0.93; p<0.001 for all). LV-AR (region of interest [ROI]=entire LV) and LVOT-AR (ROI=LVOT) were not different (p=0.51) and were strongly correlated (r2=0.99) with a mean difference of 1.92% (95% limits of agreement: ±2.83). The correlations of LV-AR and LVOT-AR with RF were stronger when more than one cardiac cycle was included in the analysis (one cycle: r2=0.85 and r2=0.83; four cycles: r2=0.96 and r2=0.96, for LV-AR and LVOT-AR, respectively). Including more cycles beyond four did not improve accuracy., Conclusions: Quantitative assessment of PVR by videodensitometry of aortograms strongly correlates with the actual RF in a controlled in vitro setting. Accuracy is improved by including more than one cardiac cycle in the analysis.

Aims: In the minimalist transcatheter aortic valve implantation (TAVI) era, the usage of transoesophageal echocardiography has become restricted. Conversely, aortography has gained clinical ground in quantifying prosthetic valve regurgitation (PVR) during the procedure. In a mock circulation system, we sought to compare the contrast volume required and the accuracy of aortographic videodensitometric PVR assessment using a synchronised diastolic and standard (non-synchronised) injection aortography., Methods and Results: Synchronised diastolic injection triggered by the signal stemming from the mock circulation was compared with standard non-synchronised injection. A transcatheter heart valve was implanted and was deformed step by step by advancing a screw perpendicularly to the cage of the valve in order to create increasing PVR. Quantitative measurement of PVR was derived from time-density curves of both a reference area (aortic root) and a region of interest (left ventricle) developed by a videodensitometric software. The volume of contrast required for the synchronised diastolic injection was significantly less than in the non-synchronised injection (8.1 [7.9-8.5] ml vs. 19.4 [19.2-19.9] ml, p<0.001). The correlation between the two methods was substantial (Spearman's coefficient rho ranging from 0.991 to 0.968). Intraobserver intra-class correlation coefficient for both methods of injection was 0.999 (95% CI: 0.996-1.000) for the synchronised diastolic and 0.999 (95% CI: 0.996-1.000) for the non-synchronised injection group. The mean difference in the rating was 0.17% and limits of agreement were ±1.64% for both groups., Conclusions: A short synchronised diastolic injection enables contrast volume reduction during aortography without compromising the accuracy of the quantitative assessment of PVR using videodensitometry.

Bifurcation lesions represent one of the most challenging lesion subsets in interventional cardiology. The European Bifurcation Club (EBC) is an academic consortium whose goal has been to assess and recommend the appropriate strategies to manage bifurcation lesions. The quantitative coronary angiography (QCA) methods for the evaluation of bifurcation lesions have been subject to extensive research. Single-vessel QCA has been shown to be inaccurate for the assessment of bifurcation lesion dimensions. For this reason, dedicated bifurcation software has been developed and validated. These software packages apply the principles of fractal geometry to address the "step-down" in the bifurcation and to estimate vessel diameter accurately. This consensus update provides recommendations on the QCA analysis and reporting of bifurcation lesions based on the most recent scientific evidence from in vitro and in vivo studies and delineates future advances in the field of QCA dedicated bifurcation analysis.

Background: Placing the left ventricular (LV) lead at a site of late electrical activation remote from scar is desired to improve cardiac resynchronization therapy (CRT) response., Objective: The purpose of this study was to integrate coronary venous electroanatomic mapping (EAM) with delayed enhancement cardiac magnetic resonance (DE-CMR) enabling LV lead guidance to the latest activated vein remote from scar., Methods: Eighteen CRT candidates with focal scar on DE-CMR were prospectively included. DE-CMR images were semi-automatically analyzed. Coronary venous EAM was performed intraprocedurally and integrated with DE-CMR to guide LV lead placement in real time. Image integration accuracy and electrogram parameters were evaluated offline., Results: Integration of EAM and DE-CMR was achieved using 8.9 ± 2.8 anatomic landmarks and with accuracy of 4.7 ± 1.1 mm (mean ± SD). Maximal electrical delay ranged between 72 and 197ms (57%-113% of QRS duration) and was heterogeneously located among individuals. In 12 patients, the latest activated vein was located outside scar, and placing the LV lead in the latest activated vein remote from scar was accomplished in 10 patients and prohibited in 2 patients. In the other 6 patients, the latest activated vein was located in scar, and targeting alternative veins was considered. Unipolar voltages were on average lower in scar compared to nonscar (6.71 ± 3.45 mV vs 8.18 ± 4.02 mV [median ± interquartile range), P <.001) but correlated weakly with DE-CMR scar extent (R -0.161, P <.001) and varied widely among individual patients., Conclusion: Integration of coronary venous EAM with DE-CMR can be used during CRT implantation to guide LV lead placement to the latest activated vein remote from scar, possibly improving CRT., (Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

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., (© 2016 International Society for Magnetic Resonance in Medicine.)

Introduction: Wall shear stress (WSS) plays a key role in the onset and progression of atherosclerosis in human coronary arteries. Especially sites with low and oscillating WSS near bifurcations have a higher propensity to develop atherosclerosis. WSS computations in coronary bifurcations can be performed in angiography-based 3D reconstructions. It is essential to evaluate how reconstruction errors influence WSS computations in mildly-diseased coronary bifurcations. In mildly-diseased lesions WSS could potentially provide more insight in plaque progression., Materials Methods: Four Plexiglas phantom models of coronary bifurcations were imaged with bi-plane angiography. The lumens were segmented by two clinically experienced readers. Based on the segmentations 3D models were generated. This resulted in three models per phantom: one gold-standard from the phantom model itself, and one from each reader. Steady-state and transient simulations were performed with computational fluid dynamics to compute the WSS. A similarity index and a noninferiority test were used to compare the WSS in the phantoms and their reconstructions. The margin for this test was based on the resolution constraints of angiography., Results: The reconstruction errors were similar to previously reported data; in seven out of eight reconstructions less than 0.10 mm. WSS in the regions proximal and far distal of the stenosis showed a good agreement. However, the low WSS areas directly distal of the stenosis showed some disagreement between the phantoms and the readers. This was due to small deviations in the reconstruction of the stenosis that caused differences in the resulting jet, and consequently the size and location of the low WSS area., Discussion: This study showed that WSS can accurately be computed within angiography-based 3D reconstructions of coronary arteries with early stage atherosclerosis. Qualitatively, there was a good agreement between the phantoms and the readers. Quantitatively, the low WSS regions directly distal to the stenosis were sensitive to small reconstruction errors.

Single-vessel quantitative coronary angiography (QCA) software is inaccurate when used in bifurcation lesions due to the specific anatomical characteristics of bifurcations, including the natural step-down in diameters after every bifurcation. Dedicated bifurcation QCA software has been developed to overcome the limitations of single-vessel QCA in bifurcations. A phantom validation study has shown the superior accuracy of these bifurcation QCA algorithms compared to the single-vessel QCA software. These QCA software algorithms are currently highly recommended to assess bifurcation lesions.

Purpose: The authors aim to improve image guidance during percutaneous coronary interventions of chronic total occlusions (CTO) by providing information obtained from computed tomography angiography (CTA) to the cardiac interventionist. To this end, the authors investigate a method to register a 3D CTA model to biplane reconstructions., Methods: The authors developed a method for registering preoperative coronary CTA with intraoperative biplane x-ray angiography (XA) images via 3D models of the coronary arteries. The models are extracted from the CTA and biplane XA images, and are temporally aligned based on CTA reconstruction phase and XA ECG signals. Rigid spatial alignment is achieved with a robust probabilistic point set registration approach using Gaussian mixture models (GMMs). This approach is extended by including orientation in the Gaussian mixtures and by weighting bifurcation points. The method is evaluated on retrospectively acquired coronary CTA datasets of 23 CTO patients for which biplane XA images are available., Results: The Gaussian mixture model approach achieved a median registration accuracy of 1.7 mm. The extended GMM approach including orientation was not significantly different (P>0.1) but did improve robustness with regards to the initialization of the 3D models., Conclusions: The authors demonstrated that the GMM approach can effectively be applied to register CTA to biplane XA images for the purpose of improving image guidance in percutaneous coronary interventions.

Aims: We describe a new semi-automated method that measures aortic regurgitation (AR) on contrast aortography with the objectives of reducing the inter-observer variability and standardising image acquisition., Methods and Results: Aortograms from three participating centres were reviewed to generate the following quality criteria: entire left ventricle and aortic root in view, descending aorta or TOE probe not over-projected, breath hold, no table motion, and adequate contrast opacification of the aortic root. AR was visually graded (Sellers) and was quantified by measuring the area under time-contrast density curves in the aortic root (reference) and the left ventricle. Quality criteria were met in 44 retrospectively identified aortograms and in 22 (69%) of 32 prospectively collected aortograms. The visual AR grade (Sellers) was highly correlated with time-density measurements including relative area under the curve (RAUC) and qRA index (r=0.81 and 0.83, respectively, p<0.001). Inter-observer reproducibility of visual grading was moderate (kappa 0.47-0.60, p<0.001). Inter-observer measurement of RAUC and qRA index were highly correlated (r=0.98, p<0.001) and showed a high level of agreement., Conclusions: Quantification of aortic regurgitation by measurement of time-density changes on contrast aortography may improve the reproducibility of AR assessment in the catheter laboratory. Steps for standardised aortography acquisition are proposed.

Aims: Validation of new three-dimensional (3-D) bifurcation quantitative coronary angiography (QCA) software., Methods and Results: Cardiovascular Angiography Analysis System (CAAS 5v10) allows 3-D angiographic reconstructions based on two or more 2-D projection images. Measurements for minimal lumen diameter (MLD), reference vessel diameter (RVD), percent diameter stenosis (DS) and bifurcation angle (BA) were validated against precision manufactured phantom bifurcations. Length measurements were validated against angiographic measurement catheters inserted into a plexiglas bifurcation phantom. In 3-D reconstructions based on two 2-D images, acquired at variable rotation and angulation, accuracy and precision (mean difference ± SD) of the 11-segment model for MLD, RVD and DS were 0.013±0.131 mm, -0.052±0.039 mm and -1.08±5.13%, respectively; inter-observer variability was 0.141 mm, 0.058 mm and 5.42%, respectively. Adding the antero-posterior (optimal) projection to these basic reconstructions resulted in reduced variability (0.101 mm, 0.041 mm and 3.93% for MLD, RVD and DS, p<0.01 for all) and showed a trend towards improved precision (0.109 mm, 0.031 mm and 4.26%, respectively, p>0.05 for all). In basic reconstructions, accuracy and precision for BA was -1.3±5.0°, whereas inter-observer variability was 7.5°; respective measures for length were 0.15±0.26 mm and 0.54 mm. Adding the antero-posterior projection resulted in decreased precision (0.47 mm, p<0.01) and increased variability (1.03 mm, p<0.01) for length measurements; precision (5.4°) and variability (7.9°) for BA did not change significantly (p>0.30)., Conclusions: Advances in the methodology of 3-D reconstruction and quantitative analysis for bifurcation lesions translated into highly accurate, precise and reproducible measures of diameter, length and BA.

Aims: To validate a new two dimensional (2-D) bifurcation quantitative coronary angiography (QCA) software., Methods and Results: In the latest edition of the Cardiovascular Angiography Analysis System (CAAS 5.9; Pie Medical Imaging, Maastricht, The Netherlands) video-densitometric information is dynamically integrated into the edge-detection algorithm of 11- and 6-segment models to reduce overestimation of small diameters. Furthermore, automatic reference obstruction analysis was optimised. Values of the minimal lumen diameter (MLD), reference vessel diameter (RVD), percent diameter stenosis (DS) and bifurcation angle (BA) for the different bifurcation segment models were validated against precision manufactured plexiglass phantoms. In anteroposterior views, accuracy and precision (mean difference±SD) of 11- and 6-segment models for MLD were 0.013±0.082 mm vs. 0.003±0.100 mm, for RVD -0.030±0.047 mm vs. -0.029±0.045 mm and for DS -0.48±3.66% vs. -0.11±3.97%. In smaller vessel segments (true MLD <0.7 mm), MLD overestimation was reduced. Inter-observer variability for MLD, RVD and DS for either model was ≤0.052 mm, ≤0.043 mm and ≤2.24%, respectively. Agreement between models for MLD, RVD and DS was ±0.076 mm, ±0.021 mm and ±2.53%, respectively. Accuracy and precision for BA were -2.6±3.5°, and variability was ≤1.2°. Accuracy and precision for diameter-derived parameters were slightly decreased in projections with 30° rotation; BA precision dropped to 6.2°., Conclusions: MLD quantification is improved for true MLD <0.7 mm, resulting in highly accurate and precise diameter measurements over the entire range of phantom diameters. Automatic reference obstruction analysis provides highly accurate, precise and reproducible RVD and DS measurements.

Background: Quantitative coronary angiography (QCA) analysis for bifurcation lesions needs to be standardized., Objectives: In vitro validation of two models for bifurcation QCA segmental analysis., Methods: In the latest edition of the Cardiovascular angiography analysis system (CAAS 5v8, Pie Medical Imaging, Maastricht, The Netherlands) a 6-segment model for two-dimensional coronary bifurcation analysis was implemented next to the currently available 11-segment model. Both models were validated against 6 precision manufactured plexiglas phantoms, each of them mimicking a vessel with three successive bifurcation lesions with variable anatomy and Medina class. The phantoms were filled with 100% contrast agent and imaged with a biplane gantry. Images acquired in antero-posterior (AP) direction by either C-arm and at 30° right and left anterior oblique angulation were analyzed by two independent analysts, blinded to the actual dimensions. Manual correction of the contours was not allowed. Measurements for minimal lumen diameter (MLD), reference vessel diameter (RVD), percent diameter stenosis (DS) and bifurcation angle (BA) were compared with the true phantom dimensions., Results: In AP views the accuracy and precision (mean difference ± SD) of 11- and 6-segment model for MLD, RVD, and DS were 0.065 ± 0.128 mm vs. 0.058 ± 0.142 mm, -0.021 ± 0.032 mm vs. -0.022 ± 0.030 mm, and -2.45% ± 5.07% vs. -2.28% ± 5.29%, respectively. Phantom MLD values ≤ 0.7 mm were systematically overestimated; if excluded, MLD accuracy and precision became 0.015 ± 0.106 mm and 0.004 ± 0.125 mm for the 11- and 6-segment model, respectively. Accuracy and precision for BA were -2.2° ± 3.3°. Interobserver variability for MLD, RVD, DS, and BA for either model was ≤ 0.049 mm, ≤ 0.056 mm, ≤ 2.77%, and 1.6°, respectively. Agreement between models for MLD, RVD, and DS was ± 0.079 mm, ± 0.011 mm, and ± 2.07%. Accuracy and precision for diameter-derived parameters were slightly decreased in angulated projections; precision for BA measurements dropped to 6.1°., Conclusions: The results of both models are highly reproducible and for phantom MLD values >0.7 mm in excellent agreement with the true dimensions., (Copyright © 2011 Wiley-Liss, Inc.)

Heart failure accounts for over five million patients in the United States alone. Many of them present dyssynchronous left ventricular (LV) contraction, whose treatment by cardiac resynchronization therapy (CRT) is until now guided by electrocardiographic analysis. One third of the selected patients, however, does not respond to the therapy. Aiming at improving the response rate, recent studies showed the importance of left bundle branch block (LBBB) configurations. Therefore, in order to detect motion patterns that relate to LBBB, this paper presents a novel method for three-dimensional quantification of regional LV mechanical dyssynchrony. LV wall-motion analysis is performed on magnetic resonance imaging (MRI) cines segmented by commercial software. Mutual delays between endocardial wall motion in different LV regions are estimated by cross correlation followed by phase difference analysis in frequency domain, achieving unlimited time resolution. Rather than focusing on the systolic phase, the full cardiac cycle is used to estimate the contraction timing. The method was successfully validated against MRI tagging in five dogs before and after LBBB induction. Preliminary validation in humans with 10 LBBB patients and 7 healthy subjects showed the method feasibility and reproducibility, with sensitivity and specificity in LBBB detection equal to 95.1% and 99.4%, respectively.

Rationale and Objectives: We sought to evaluate the automatic detection of the papillary muscle and to determine its influence on quantitative left ventricular (LV) mass assessment., Materials and Methods: Twenty-eight Yorkshire-Landrace swine and 10 volunteers underwent cardiac magnetic resonance imaging (CMR) of the left ventricle. The variability in measurements of LV papillary muscles traced automatically and manually were compared to intra- and interobserver variabilities. CMR-derived LV mass with the papillary muscle included or excluded from LV mass measurements was compared to true mass at autopsy of the Yorkshire-Landrace swine., Results: Automatic LV papillary muscle mass from all subjects correlated well with manually derived LV papillary muscle mass measurements (r = 0.84) with no significant bias between both measurements (mean difference +/- SD, 0.0 +/- 1.5 g; P = .98). The variability in results related to the contour detection method used was not statistically significant different compared to intra- and interobserver variabilities (P = .08 and P = .97, respectively). LV mass measurements including the papillary muscle showed significantly less underestimation (-10.6 +/- 7.1 g) with the lowest percentage variability (6%) compared to measurements excluding the papillary muscles (mean underestimation, -15.1 +/- 7.4 g percentage variability, 7%)., Conclusion: The automatic algorithm for detecting the papillary muscle was accurate with variabilities comparable to intra- and interobserver variabilities. LV mass is determined most accurately when the papillary muscles are included in the LV mass measurements. Taken together, these observations warrant the inclusion of automatic contour detection of papillary muscle mass in studies that involve the determination of LV mass.

Aims: To develop a novel dedicated quantitative coronary analysis (QCA) for bifurcations., Method and Results: A dedicated software that has minimal user interaction so as to increase the QCA results reproducibility. The new CAAS 5 bifurcation software combines established algorithm for contour detection with novel ways to determine the lesion characteristics together with the angulation of the bifurcation., Conclusion: The paper describes how this methodology is accomplished and reported.

Objectives: To reduce interstudy variability using long-axis information for correcting short-axis (SA) contours at basal and apical level for left-ventricular analysis by magnetic resonance imaging., Materials and Methods: A total of 20 patients with documented heart failure and 20 volunteers underwent magnetic resonance imaging examination twice for measuring endocardial end-diastolic volume, endocardial end-systolic volume, mass, and ejection fraction. The boundary of the left ventricle, the mitral valve plane, and apex were marked manually on the 2- and 4-chamber long-axis images. Automatic epicardial and endocardial contour detection was performed on the SA images using the intersection of the outlines from the long axis as starting positions. The same observer compared the interstudy variability of this method with analysis that was based on the SA images only., Results: The interstudy variability decreased when information from the long axis was included; for end-systolic volume, 9.6% versus 4.7% (P = 0.00014); for end-diastolic volume, 4.9% versus 2.5% (P = 0.0011); for mass, 7.4% versus 5.0% (P = 0.11); and for ejection fraction 12.2% versus 5.6% (P = 0.0017), respectively., Conclusions: Identification of the mitral valve plane and apex on long-axis images to limit the extent of volume at the base and the apex of the heart reduces interstudy variability for left-ventricular functional assessment.

Purpose: To compare global functional parameters determined from a stack of cinematographic MR images of mouse heart by a manual segmentation and an automatic segmentation algorithm., Materials and Methods: The manual and automatic segmentation results of 22 mouse hearts were compared. The automatic segmentation was based on propagation of a minimum cost algorithm in polar space starting from manually drawn contours in one heart phase. Intra- and interobserver variability as well as validity of the automatic segmentation was determined. To test the reproducibility of the algorithm the variability was calculated from the intra- and interobserver input., Results: The mean time of segmentation for one dataset was around 10 minutes and approximately 2.5 hours for automatic and manual segmentation, respectively. There were no significant differences between the automatic and the manual segmentation except for the end systolic epicardial volume. The automatically derived volumes correlated well with the manually derived volumes (R(2) = 0.90); left ventricular mass with and without papillary muscle showed a correlation R(2) of 0.74 and 0.76, respectively. The manual intraobserver variability was superior to the interobserver variability and the variability of the automatic segmentation, while the manual interobserver variability was comparable to the variability of the automatic segmentation. The automatic segmentation algorithm reduced the bias of the intra- and interobserver variability., Conclusion: We conclude that automatic segmentation of the mouse heart provides a fast and valid alternative to manual segmentation of the mouse heart.

The purpose of this study was to evaluate an automatic boundary detection algorithm of the left ventricle on magnetic resonance (MR) short-axis images with the essential restriction of no manual corrections. The study comprised 13 patients (nine men, four women) and 12 healthy volunteers (11 men, one woman), and institutional review board approval and informed consent were obtained. The outline of the left ventricle was indicated manually on horizontal and vertical long-axis MR images. The calculated intersection points with the short-axis MR images were the basis of the automatic contour detection. Automatically derived volumes correlated highly with manually derived (short axis-based) volumes (R2 = 0.98); ejection fraction (EF) and mass showed a correlation of 0.95 and 0.93, respectively. Automatic contour detection reduced interobserver variability to 0.1 mL for endocardial end-diastolic and end-systolic volumes, 1.1 mL for epicardial end-diastolic and end-systolic volumes, 0.02% for EF, and 1.1 g for mass. Thus, the algorithm enabled highly reproducible left ventricular parameters to be obtained., (RSNA, 2006)