Regional Aortic Wall Shear Stress Increases over Time in Patients with a Bicuspid Aortic Valve.

BACKGROUND: Aortic wall shear stress (WSS) is a known predictor of ascending aortic growth in patients with a bicuspid aortic valve (BAV). The aim of this study was to study regional WSS and changes over time in BAV patients. METHODS: BAV patients and age-matched healthy controls underwent 4D flow CMR. Regional, peak systolic ascending aortic WSS, aortic valve function, aortic stiffness measures and aortic dimensions were assessed. In BAV patients, 4D flow CMR was repeated after three years follow-up and both at baseline and follow-up computed tomography angiography (CTA) was acquired. Aortic growth (volume increase of ≥5%) was measured on CTA. Regional WSS differences within patients' aorta and WSS changes over time were analysed using linear mixed-effect models and were associated with clinical parameters. RESULTS: Thirty BAV patients (aged 34 years [IQR 25-41]) were included in the follow-up analysis. Additionally, another 16 BAV patients and 32 healthy controls (aged 33 years [IQR 28-48]) were included for other regional analyses. Magnitude, axial, and circumferential WSS increased over time (all p<0.001) irrespective of aortic growth. The percentage of regions exposed to a magnitude WSS >95th percentile of healthy controls increased from 21% (baseline 506/2400 regions) to 31% (follow-up 734/2400 regions) (p<0.001). WSS angle, a measure of helicity near the aortic wall, decreased during follow-up. Magnitude WSS changes over time were associated with systolic blood pressure, peak aortic valve velocity, aortic valve regurgitation fraction, aortic stiffness indexes, and normalized flow displacement (all p<0.05). CONCLUSIONS: An increase of regional WSS over time was observed in BAV patients, irrespective of aortic growth. The increasing WSSs comprising a larger area of the aorta warrants further research to investigate the possible predictive value for aortic dissection.

Evaluation of atrial septal defects with 4D flow MRI-multilevel and inter-reader reproducibility for quantification of shunt severity.

PURPOSE: With the hypothesis that 4D flow can be used in evaluation of cardiac shunts, we seek to evaluate the multilevel and interreader reproducibility of measurements of the blood flow, shunt fraction and shunt volume in patients with atrial septum defect (ASD) in practice at multiple clinical sites. MATERIALS AND METHODS: Four-dimensional flow MRI examinations were performed at four institutions across Europe and the US. Twenty-nine patients (mean age, 43 years; 11 male) were included in the study. Flow measurements were performed at three levels (valve, main artery and periphery) in both the pulmonary and systemic circulation by two independent readers and compared against stroke volumes from 4D flow anatomic data. Further, the shunt ratio (Qp/Qs) was calculated. Additionally, shunt volume was quantified at the atrial level by tracking the atrial septum. RESULTS: Measurements of the pulmonary blood flow at multiple levels correlate well whether measuring at the valve, main pulmonary artery or branch pulmonary arteries (r = 0.885-0.886). Measurements of the systemic blood flow show excellent correlation, whether measuring at the valve, ascending aorta or sum of flow from the superior vena cava (SVC) and descending aorta (r = 0.974-0.991). Intraclass agreement between the two observers for the flow measurements varies between 0.96 and 0.99. Compared with stroke volume, pulmonic flow is underestimated with 0.26 l/min at the main pulmonary artery level, and systemic flow is overestimated with 0.16 l/min at the ascending aorta level. Direct measurements of ASD flow are feasible in 20 of 29 (69%) patients. CONCLUSION: Blood flow and shunt quantification measured at multiple levels and performed by different readers are reproducible and consistent with 4D flow MRI.

Diagnostic value of transmural perfusion ratio derived from dynamic CT-based myocardial perfusion imaging for the detection of haemodynamically relevant coronary artery stenosis.

OBJECTIVES: To investigate the additional value of transmural perfusion ratio (TPR) in dynamic CT myocardial perfusion imaging for detection of haemodynamically significant coronary artery disease compared with fractional flow reserve (FFR). METHODS: Subjects with suspected or known coronary artery disease were prospectively included and underwent a CT-MPI examination. From the CT-MPI time-point data absolute myocardial blood flow (MBF) values were temporally resolved using a hybrid deconvolution model. An absolute MBF value was measured in the suspected perfusion defect. TPR was defined as the ratio between the subendocardial and subepicardial MBF. TPR and MBF results were compared with invasive FFR using a threshold of 0.80. RESULTS: Forty-three patients and 94 territories were analysed. The area under the receiver operator curve was larger for MBF (0.78) compared with TPR (0.65, P = 0.026). No significant differences were found in diagnostic classification between MBF and TPR with a territory-based accuracy of 77 % (67-86 %) for MBF compared with 70 % (60-81 %) for TPR. Combined MBF and TPR classification did not improve the diagnostic classification. CONCLUSIONS: Dynamic CT-MPI-based transmural perfusion ratio predicts haemodynamically significant coronary artery disease. However, diagnostic performance of dynamic CT-MPI-derived TPR is inferior to quantified MBF and has limited incremental value. KEY POINTS: • The transmural perfusion ratio from dynamic CT-MPI predicts functional obstructive coronary artery disease • Performance of the transmural perfusion ratio is inferior to quantified myocardial blood flow • The incremental value of the transmural perfusion ratio is limited.

Fractional flow reserve computed from noninvasive CT angiography data: diagnostic performance of an on-site clinician-operated computational fluid dynamics algorithm.

PURPOSE: To validate an on-site algorithm for computation of fractional flow reserve (FFR) from coronary computed tomographic (CT) angiography data against invasively measured FFR and to test its diagnostic performance as compared with that of coronary CT angiography. MATERIALS AND METHODS: The institutional review board provided a waiver for this retrospective study. From coronary CT angiography data in 106 patients, FFR was computed at a local workstation by using a computational fluid dynamics algorithm. Invasive FFR measurement was performed in 189 vessels (80 of which had an FFR ≤ 0.80); these measurements were regarded as the reference standard. The diagnostic characteristics of coronary CT angiography-derived computational FFR, coronary CT angiography, and quantitative coronary angiography were evaluated against those of invasively measured FFR by using C statistics. Sensitivity and specificity were compared by using a two-sided McNemar test. RESULTS: For computational FFR, sensitivity was 87.5% (95% confidence interval [CI]: 78.2%, 93.8%), specificity was 65.1% (95% CI: 55.4%, 74.0%), and accuracy was 74.6% (95% CI: 68.4%, 80.8%), as compared with the finding of lumen stenosis of 50% or greater at coronary CT angiography, for which sensitivity was 81.3% (95% CI: 71.0%, 89.1%), specificity was 37.6% (95% CI: 28.5%, 47.4%), and accuracy was 56.1% (95% CI: 49.0%, 63.2%). C statistics revealed a larger area under the receiver operating characteristic curve (AUC) for computational FFR (AUC, 0.83) than for coronary CT angiography (AUC, 0.64). For vessels with intermediate (25%-69%) stenosis, the sensitivity of computational FFR was 87.3% (95% CI: 76.5%, 94.3%) and the specificity was 59.3% (95% CI: 47.8%, 70.1%). CONCLUSION: With use of a reduced-order algorithm, computation of the FFR from coronary CT angiography data can be performed locally, at a regular workstation. The diagnostic accuracy of coronary CT angiography-derived computational FFR for the detection of functionally important coronary artery disease (CAD) was good and was incremental to that of coronary CT angiography within a population with a high prevalence of CAD.

Quantification of the myocardial area at risk using coronary CT angiography and Voronoi algorithm-based myocardial segmentation.

OBJECTIVES: The purpose of this study was to estimate the myocardial area at risk (MAAR) using coronary computed tomography angiography (CTA) and Voronoi algorithm-based myocardial segmentation in comparison with single-photon emission computed tomography (SPECT). METHODS: Thirty-four patients with coronary artery disease underwent 128-slice coronary CTA, stress/rest thallium-201 SPECT, and coronary angiography (CAG). CTA-based MAAR was defined as the sum of all CAG stenosis (>50%) related territories (the ratio of the left ventricular volume). Using automated quantification software (17-segment model, 5-point scale), SPECT-based MAAR was defined as the number of segments with a score above zero as compared to the total 17 segments by summed stress score (SSS), difference (SDS) score map, and comprehensive SPECT interpretation with either SSS or SDS best correlating CAG findings (SSS/SDS). Results were compared using Pearson's correlation coefficient. RESULTS: Forty-nine stenoses were observed in 102 major coronary territories. Mean value of CTA-based MAAR was 28.3 ± 14.0%. SSS-based, SDS-based, and SSS/SDS-based MAAR was 30.1 ± 6.1%, 20.1 ± 15.8%, and 26.8 ± 15.7%, respectively. CTA-based MAAR was significantly related to SPECT-based MAAR (r = 0.531 for SSS; r = 0.494 for SDS; r = 0.814 for SSS/SDS; P < 0.05 in each). CONCLUSIONS: CTA-based Voronoi algorithm myocardial segmentation reliably quantifies SPECT-based MAAR. KEY POINTS: • Voronoi algorithm allows for three-dimensional myocardial segmentation of coronary CT angiography • Stenosis-related CT myocardial territories correlate to SPECT based area at risk • CT angiography myocardial segmentation may assist in clinical decision-making.

Wall shear stress angle is associated with aortic growth in bicuspid aortic valve patients.

AIMS: Aortic wall shear stress (WSS) distributions in bicuspid aortic valve (BAV) patients have been associated with aortic dilatation, but prospective, longitudinal data are missing. This study assessed differences in aortic WSS distributions between BAV patients and healthy controls and determined the association of WSS with aortic growth in patients. METHODS AND RESULTS: Sixty subjects underwent four-dimensional (4D) flow cardiovascular magnetic resonance of the thoracic aorta (32 BAV patients and 28 healthy controls). Peak velocity, pulse wave velocity, aortic distensibility, peak systolic WSS (magnitude, axial, and circumferential), and WSS angle were assessed. WSS angle is defined as the angle between the WSSmagnitude and WSSaxial component. In BAV patients, three-year computed tomography angiography-based aortic volumetric growth was determined in the proximal and entire ascending aorta. WSSaxial was significantly lower in BAV patients compared with controls (0.93 vs. 0.72 Pa, P = 0.047) and WSScircumferential and WSS angle were significantly higher (0.29 vs. 0.64 Pa and 18° vs. 40°, both P < 0.001). Significant volumetric growth of the proximal ascending aorta occurred in BAV patients (from 49.1 to 52.5 cm3, P = 0.003). In multivariable analysis corrected for baseline aortic volume and diastolic blood pressure, WSS angle was the only parameter independently associated with proximal aortic growth (P = 0.031). In the entire ascending aorta, besides the WSS angle, the WSSmagnitude was also independently associated with growth. CONCLUSION: Increased WSScircumferential and especially WSS angle are typical in BAV patients. WSS angle was found to predict aortic growth. These findings highlight the potential role of WSS measurements in BAV patients to stratify patients at risk for aortic dilation.

Diagnostic Cardiovascular Magnetic Resonance Imaging Criteria in Noncompaction Cardiomyopathy and the Yield of Genetic Testing.

BACKGROUND: Noncompaction cardiomyopathy (NCCM) is characterized by a thickened myocardial wall with excessive trabeculations of the left ventricle, and ∼30% is explained by a (likely) pathogenic variant [(L)PV] in a cardiomyopathy gene. Diagnosing an (L)PV is important because it allows accurate identification of which relatives are at risk and helps predicting prognosis. The goal of this study was to assess which specific clinical and morphologic characteristics of the myocardium may predict an (L)PV and which of the cardiovascular magnetic resonance (CMR) diagnostic criteria for NCCM can best be used for that purpose. METHODS: Sixty-two patients with NCCM, diagnosed by means of echocardiographic Jenni criteria, underwent CMR imaging that was evaluated according the Petersen, Stacey, Jacquier, Captur, and Choi diagnostic CMR criteria for NCCM. Patients also underwent DNA testing and were stratified according to having an (L)PV. RESULTS: Thirty-three patients (53%) with NCCM had an (L)PV. The apical and mid-lateral segments were the dominant locations for meeting Petersen and/or Stacey criteria. Correlation between different CMR criteria varied from moderate to very strong. In multivariate binary logistic regression analysis with CMR and non-CMR parameters, independent positive predictors for an (L)PV were familial cardiomyopathy, trabecular mass, and meeting Petersen criteria in ≥ 2 out of 3 long-axis views, whereas left bundle branch block and hypertension were negative predictors. The receiver operating characteristic curve of this multivariate model had an area under the curve of 0.89 (95% confidence interval 0.82-0.97). CONCLUSIONS: CMR criteria together with family history help to distinguish those patients in whom an (L)PV can be identified, consequently leading to referral for genetic diagnostics and cascade screening.

Left ventricular global longitudinal strain in bicupsid aortic valve patients: head-to-head comparison between computed tomography, 4D flow cardiovascular magnetic resonance and speckle-tracking echocardiography.

Left ventricular global longitudinal strain (LVGLS) analysis is a sensitive measurement of myocardial deformation most often done using speckle-tracking transthoracic echocardiography (TTE). We propose a novel approach to measure LVGLS using feature-tracking software on the magnitude dataset of 4D flow cardiovascular magnetic resonance (CMR) and compare it to dynamic computed tomography (CT) and speckle tracking TTE derived measurements. In this prospective cohort study 59 consecutive adult patients with a bicuspid aortic valve (BAV) were included. The study protocol consisted of TTE, CT, and CMR on the same day. Image analysis was done using dedicated feature-tracking (4D flow CMR and CT) and speckle-tracking (TTE) software, on apical 2-, 3-, and 4-chamber long-axis multiplanar reconstructions (4D flow CMR and CT) or standard apical 2-, 3-, and 4-chamber acquisitions (TTE). CMR and CT GLS analysis was feasible in all patients. Good correlations were observed for GLS measured by CMR (- 21 ± 3%) and CT (- 20 ± 3%) versus TTE (- 20 ± 3%, Pearson's r: 0.67 and 0.65, p < 0.001). CMR also correlated well with CT (Pearson's r 0.62, p < 0.001). The inter-observer analysis showed moderate to good reproducibility of GLS measurement by CMR, CT and TTE (Pearsons's r: 0.51, 0.77, 0.70 respectively; p < 0.05). Additionally, ejection fraction (EF), end-diastolic and end-systolic volume measurements (EDV and ESV) correlated well between all modalities (Pearson's r > 0.61, p < 0.001). Feature-tracking GLS analysis is feasible using the magnitude images acquired with 4D flow CMR. GLS measurement by CMR correlates well with CT and speckle-tracking 2D TTE. GLS analysis on 4D flow CMR allows for an integrative approach, integrating flow and functional data in a single sequence. Not applicable, observational study.

Validation of 4D flow CMR against simultaneous invasive hemodynamic measurements: a swine study.

The purpose of this study was to compare invasively measured aorta flow with 2D phase contrast flow and 4D flow measurements by cardiovascular magnetic resonance (CMR) imaging in a large animal model. Nine swine (mean weight 63 ± 4 kg) were included in the study. 4D flow CMR exams were performed on a 1.5T MRI scanner. Flow measurements were performed on 4D flow images at the aortic valve level, in the ascending aorta, and main pulmonary artery. Simultaneously, flow was measured using an invasive flow probe, placed around the ascending aorta. Additionally, standard 2D phase contrast flow and 2D left ventricular (LV) volumetric data were used for comparison. The correlations of cardiac output (CO) between the invasive flow probe, and CMR modalities were strong to very strong. CO measured by 4D flow CMR correlated better with the CO measured by the invasive flow probe than 2D flow CMR flow and volumetric LV data (4D flow CMR: Spearman's rho = 0.86 at the aortic valve level and 0.90 at the ascending aorta level; 2D flow CMR: 0.67 at aortic valve level; LV measurements: 0.77). In addition, there tended to be a correlation between mean pulmonary artery flow and aorta flow with 4D flow (Spearman's rho = 0.65, P = 0.07), which was absent in measurements obtained with 2D flow CMR (Spearman's rho = 0.40, P = 0.33). This study shows that aorta flow can be accurately measured by 4D flow CMR compared to simultaneously measured invasive flow. This helps to further validate the quantitative reliability of this technique.

Intermodality variation of aortic dimensions: How, where and when to measure the ascending aorta.

BACKGROUND: No established reference-standard technique is available for ascending aortic diameter measurements. The aim of this study was to determine agreement between modalities and techniques. METHODS: In patients with aortic pathology transthoracic echocardiography, computed tomography angiography (CTA) and magnetic resonance angiography (MRA) were performed. Aortic diameters were measured at the sinus of Valsalva (SoV), sinotubular junction (STJ) and tubular ascending aorta (TAA) during mid-systole and end-diastole. In echocardiography both the inner edge-to-inner edge (I-I edge) and leading edge-to­leading edge (L-L edge) methods were applied, and the length of the aortic annulus to the most cranial visible part of the ascending aorta was measured. In CTA and MRA the I-I method was used. RESULTS: Fifty patients with bicuspid aortic valve (36 ±â€¯13 years, 26% female) and 50 Turner patients (35 ±â€¯13 years) were included. Comparison of all aortic measurements showed a mean difference of 5.4 ±â€¯2.7 mm for the SoV, 5.1 ±â€¯2.0 mm for the STJ and 4.8 ±â€¯2.1 mm for the TAA. The maximum difference was 18 mm. The best agreement was found between echocardiography L-L edge and CTA during mid-systole. CTA and MRA showed good agreement. A mean difference of 1.5 ±â€¯1.3 mm and 1.8 ±â€¯1.5 mm was demonstrated at the level of the STJ and TAA comparing mid-systolic with end-diastolic diameters. The visible length of the aorta increased on average 5.3 ±â€¯5.1 mmW during mid-systole. CONCLUSIONS: MRA and CTA showed best agreement with L-L edge method by echocardiography. In individual patients large differences in ascending aortic diameter were demonstrated, warranting measurement standardization. The use of CTA or MRA is advised at least once.

Transthoracic 3D echocardiographic left heart chamber quantification in patients with bicuspid aortic valve disease.

Integration of volumetric heart chamber quantification by 3D echocardiography into clinical practice has been hampered by several factors which a new fully automated algorithm (Left Heart Model, (LHM)) may help overcome. This study therefore aims to evaluate the feasibility and accuracy of the LHM software in quantifying left atrial and left ventricular volumes and left ventricular ejection fraction in a cohort of patients with a bicuspid aortic valve. Patients with a bicuspid aortic valve were prospectively included. All patients underwent 2D and 3D transthoracic echocardiography and computed tomography. Left atrial and ventricular volumes were obtained using the automated program, which did not require manual contour detection. For comparison manual and semi-automated measurements were performed using conventional 2D and 3D datasets. 53 patients were included, in four of those patients no 3D dataset could be acquired. Additionally, 12 patients were excluded based on poor imaging quality. Left ventricular end-diastolic and end-systolic volumes and ejection fraction calculated by the LHM correlated well with manual 2D and 3D measurements (Pearson's r between 0.43 and 0.97, p < 0.05). Left atrial volume (LAV) also correlated significantly although LHM did estimate larger LAV compared to both 2DE and 3DE (Pearson's r between 0.61 and 0.81, p < 0.01). The fully automated software works well in a real-world setting and helps to overcome some of the major hurdles in integrating 3D analysis into daily practice, as it is user-independent and highly reproducible in a group of patients with a clearly defined and well-studied valvular abnormality.

Partial anomalous pulmonary venous return in Turner syndrome.

PURPOSE: The aim of this study is to describe the prevalence, anatomy, associations and clinical impact of partial anomalous pulmonary venous return in patients with Turner syndrome. METHODS AND RESULTS: All Turner patients who presented at our Turner clinic, between January 2007 and October 2015 were included in this study and underwent ECG, echocardiography and advanced imaging such as cardiac magnetic resonance or computed tomography as part of their regular clinical workup. All imaging was re-evaluated and detailed anatomy was described. Partial anomalous pulmonary venous return was diagnosed in 24 (25%) out of 96 Turner patients included and 14 (58%) of these 24 partial anomalous pulmonary venous return had not been reported previously. Right atrial or ventricular dilatation was present in 11 (46%) of 24 partial anomalous pulmonary venous return patients. CONCLUSION: When studied with advanced imaging modalities and looked for with specific attention, PAPVR is found in 1 out of 4 Turner patients. Half of these patients had right atrial and/or ventricular dilatation. Evaluation of pulmonary venous return should be included in the standard protocol in all Turner patients.

Integrating CT Myocardial Perfusion and CT-FFR in the Work-Up of Coronary Artery Disease.

OBJECTIVES: The aim of this study was to investigate the individual and combined accuracy of dynamic computed tomography (CT) myocardial perfusion imaging (MPI) and computed tomography angiography (CTA) fractional flow reserve (FFR) for the identification of functionally relevant coronary artery disease (CAD). BACKGROUND: Coronary CTA has become an established diagnostic test for ruling out CAD, but it does not allow interpretation of the hemodynamic severity of stenotic lesions. Two recently introduced functional CT techniques are dynamic MPI and CTA FFR using computational fluid dynamics. METHODS: From 2 institutions, 74 patients (n = 62 men, mean age 61 years) planned for invasive angiography with invasive FFR measurement in 142 vessels underwent CTA imaging and dynamic CT MPI during adenosine vasodilation. A patient-specific myocardial blood flow index was calculated, normalized to remote myocardial global left ventricular blood flow. CTA FFR was computed using an on-site, clinician-operated application. Using binary regression, a single functional CT variable was created combining both CT MPI and CTA FFR. Finally, stepwise diagnostic work-up of CTA FFR with selective use of CT MPI was simulated. The diagnostic performance of CT MPI, CTA FFR, and CT MPI integrated with CTA FFR was evaluated using C statistics with invasive FFR, with a threshold of 0.80 as a reference. RESULTS: Sensitivity, specificity, and accuracy were 73% (95% confidence interval [CI]: 61% to 86%), 68% (95% CI: 56% to 80%), and 70% (95% CI: 62% to 79%) for CT MPI and 82% (95% CI: 72% to 92%), 60% (95% CI: 48% to 72%), and 70% (63% to 80%) for CTA FFR. For CT MPI integrated with CTA FFR, diagnostic accuracy was 79% (95% CI: 71% to 87%), with improvement of the area under the curve from 0.78 to 0.85 (p < 0.05). Accuracy of the stepwise approach was 77%. CONCLUSIONS: CT MPI and CTA FFR both identify functionally significant CAD, with comparable accuracy. Diagnostic performance can be improved by combining the techniques. A stepwise approach, reserving CT MPI for intermediate CTA FFR results, also improves diagnostic performance while omitting nearly one-half of the population from CT MPI examinations.

Coronary CT angiography derived fractional flow reserve: Methodology and evaluation of a point of care algorithm.

BACKGROUND: Recently several publications described the diagnostic value of coronary CT angiography (coronary CTA) derived fractional flow reserve (CTA-FFR). For a recently introduced on-site CTA-FFR application, detailed methodology and factors potentially affecting performance have not yet been described. OBJECTIVE: To provide a methodological background for an on-site CTA-FFR application and evaluate the effect of patient and acquisition characteristics. METHODS: The on-site CTA-FFR application utilized a reduced-order hybrid model applying pressure drop models within stenotic regions. In 116 patients and 203 vessels the diagnostic performance of CTA-FFR was investigated using invasive FFR measurements as a reference. The effect of several potentially relevant factors on CTA-FFR was investigated. RESULTS: 90 vessels (44%) had a hemodynamically relevant stenosis according to invasive FFR (threshold ≤0.80). The overall vessel-based sensitivity, specificity and accuracy of CTA-FFR were 88% (CI 95%:79-94%), 65% (55-73%) and 75% (69-81%). The specificity was significantly lower in the presence of misalignment artifacts (25%, CI: 6-57%). A non-significant reduction in specificity from 74% (60-85%) to 48% (26-70%) was found for higher coronary artery calcium scores. Left ventricular mass, diabetes mellitus and large vessel size increased the discrepancy between invasive FFR and CTA-FFR values. CONCLUSIONS: On-site calculation of CTA-FFR can identify hemodynamically significant CAD with an overall per-vessel accuracy of 75% in comparison to invasive FFR. The diagnostic performance of CTA-FFR is negatively affected by misalignment artifacts. CTA-FFR is potentially affected by left ventricular mass, diabetes mellitus and vessel size.

Qualitative grading of aortic regurgitation: a pilot study comparing CMR 4D flow and echocardiography.

Over the past 10 years there has been intense research in the development of volumetric visualization of intracardiac flow by cardiac magnetic resonance (CMR).This volumetric time resolved technique called CMR 4D flow imaging has several advantages over standard CMR. It offers anatomical, functional and flow information in a single free-breathing, ten-minute acquisition. However, the data obtained is large and its processing requires dedicated software. We evaluated a cloud-based application package that combines volumetric data correction and visualization of CMR 4D flow data, and assessed its accuracy for the detection and grading of aortic valve regurgitation using transthoracic echocardiography as reference. Between June 2014 and January 2015, patients planned for clinical CMR were consecutively approached to undergo the supplementary CMR 4D flow acquisition. Fifty four patients(median age 39 years, 32 males) were included. Detection and grading of the aortic valve regurgitation using CMR4D flow imaging were evaluated against transthoracic echocardiography. The agreement between 4D flow CMR and transthoracic echocardiography for grading of aortic valve regurgitation was good (j = 0.73). To identify relevant,more than mild aortic valve regurgitation, CMR 4D flow imaging had a sensitivity of 100 % and specificity of 98 %. Aortic regurgitation can be well visualized, in a similar manner as transthoracic echocardiography, when using CMR 4D flow imaging.

Cloud-processed 4D CMR flow imaging for pulmonary flow quantification.

OBJECTIVES: In this study, we evaluated a cloud-based platform for cardiac magnetic resonance (CMR) four-dimensional (4D) flow imaging, with fully integrated correction for eddy currents, Maxwell phase effects, and gradient field non-linearity, to quantify forward flow, regurgitation, and peak systolic velocity over the pulmonary artery. METHODS: We prospectively recruited 52 adult patients during one-year period from July 2014. The 4D flow and planar (2D) phase-contrast (PC) were acquired during same scanning session, but 4D flow was scanned after injection of a gadolinium-based contrast agent. Eddy-currents were semi-automatically corrected using the web-based software. Flow over pulmonary valve was measured and the 4D flow values were compared against the 2D PC ones. RESULTS: The mean forward flow was 92 (±30) ml/cycle measured with 4D flow and 86 (±29) ml/cycle measured with 2D PC, with a correlation of 0.82 and a mean difference of -6ml/cycle (-41-29). For the regurgitant fraction the correlation was 0.85 with a mean difference of -0.95% (-17-15). Mean peak systolic velocity measured with 4D flow was 92 (±49) cm/s and 108 (±56) cm/s with 2D PC, having a correlation of 0.93 and a mean difference of 16cm/s (-24-55). CONCLUSION: 4D flow imaging post-processed with an integrated cloud-based application accurately quantifies pulmonary flow. However, it may underestimate the peak systolic velocity.