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Supplemental Digital Content is available in the text., Background: Many heart diseases can result in reduced pumping capacity of the heart muscle. A mismatch between ATP demand and ATP production of cardiomyocytes is one of the possible causes. Assessment of the relation between myocardial ATP production (MVATP) and cardiac workload is important for better understanding disease development and choice of nutritional or pharmacologic treatment strategies. Because there is no method for measuring MVATP in vivo, the use of physiology-based metabolic models in conjunction with protein abundance data is an attractive approach. METHOD: We developed a comprehensive kinetic model of cardiac energy metabolism (CARDIOKIN1) that recapitulates numerous experimental findings on cardiac metabolism obtained with isolated cardiomyocytes, perfused animal hearts, and in vivo studies with humans. We used the model to assess the energy status of the left ventricle of healthy participants and patients with aortic stenosis and mitral valve insufficiency. Maximal enzyme activities were individually scaled by means of protein abundances in left ventricle tissue samples. The energy status of the left ventricle was quantified by the ATP consumption at rest (MVATP[rest]), at maximal workload (MVATP[max]), and by the myocardial ATP production reserve, representing the span between MVATP(rest) and MVATP(max). Results: Compared with controls, in both groups of patients, MVATP(rest) was increased and MVATP(max) was decreased, resulting in a decreased myocardial ATP production reserve, although all patients had preserved ejection fraction. The variance of the energetic status was high, ranging from decreased to normal values. In both patient groups, the energetic status was tightly associated with mechanic energy demand. A decrease of MVATP(max) was associated with a decrease of the cardiac output, indicating that cardiac functionality and energetic performance of the ventricle are closely coupled. Conclusions: Our analysis suggests that the ATP-producing capacity of the left ventricle of patients with valvular dysfunction is generally diminished and correlates positively with mechanical energy demand and cardiac output. However, large differences exist in the energetic state of the myocardium even in patients with similar clinical or image-based markers of hypertrophy and pump function. Registration: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03172338 and NCT04068740.

Background In adult cardiomyopathy (CM), diffuse myocardial fibrosis is associated with adverse clinical outcome. However, its relevance in pediatric patients remains relatively unknown. The study aimed to evaluate myocardial extracellular volume (ECV) reflecting diffuse myocardial fibrosis with cardiovascular magnetic resonance (CMR) T1 mapping, and to analyze correlations with clinical and functional data in children and adolescents with different CM phenotypes. Methods Patients with primary dilated (DCM), hypertrophic (HCM) or left ventricular non-compaction CM (LVNC) were prospectively enrolled and compared with healthy controls. Study participants underwent standardized CMR with modified Look-Locker Inversion recovery (MOLLI) T1 mapping. Results In total, 33 patients (median age 12.0 years; DCM: n = 10, HCM: n = 13; LVNC: n = 10) and 7 controls (14.5 years) were included. DCM: ECV was higher than in controls (38.1 ± 7.5% vs. 27.2 ± 3.6%; p = 0.014). Patients with elevated ECV were younger than those with normal values (p = 0.044). ECV correlated with N-terminal pro brain natriuretic peptide (r = 0.66, p = 0.038), left ventricular ejection fraction (r = −0.63, p = 0.053), and stroke volume of left (r = −0.75, p = 0.013) and right ventricle (r = −0.67, p = 0.033). During a median follow-up of 25.3 months, 3 patients underwent heart transplantation (HTx), and 2 were listed for HTx. All 5 patients had elevated ECV. HCM/LVNC: ECV was within normal range in HCM (25.5 ± 4.5%) and LVNC (29.6 ± 4.2), and was not related with clinical and/or functional parameters. Conclusions Our results indicate an increased burden of diffuse myocardial fibrosis in relation with younger age in pediatric DCM. ECV was associated with clinical and biventricular functional markers of heart failure in DCM.

Modeling of hemodynamics and artificial intelligence have great potential to support clinical diagnosis and decision making. While hemodynamics modeling is extremely time- and resource-consuming, machine learning (ML) typically requires large training data that are often unavailable. The aim of this study was to develop and evaluate a novel methodology generating a large database of synthetic cases with characteristics similar to clinical cohorts of patients with coarctation of the aorta (CoA), a congenital heart disease associated with abnormal hemodynamics. Synthetic data allows use of ML approaches to investigate aortic morphometric pathology and its influence on hemodynamics. Magnetic resonance imaging data (154 patients as well as of healthy subjects) of aortic shape and flow were used to statistically characterize the clinical cohort. The methodology generating the synthetic cohort combined statistical shape modeling of aortic morphometry and aorta inlet flow fields and numerical flow simulations. Hierarchical clustering and non-linear regression analysis were successfully used to investigate the relationship between morphometry and hemodynamics and to demonstrate credibility of the synthetic cohort by comparison with a clinical cohort. A database of 2652 synthetic cases with realistic shape and hemodynamic properties was generated. Three shape clusters and respective differences in hemodynamics were identified. The novel model predicts the CoA pressure gradient with a root mean square error of 4.6 mmHg. In conclusion, synthetic data for anatomy and hemodynamics is a suitable means to address the lack of large datasets and provide a powerful basis for ML to gain new insights into cardiovascular diseases.

The transvalvular pressure gradient (TPG) is commonly estimated using the Bernoulli equation. However, the method is known to be inaccurate. Therefore, an adjusted Bernoulli model for accurate TPG assessment was developed and evaluated. Numerical simulations were used to calculate TPGCFD in patient-specific geometries of aortic stenosis as ground truth. Geometries, aortic valve areas (AVA), and flow rates were derived from computed tomography scans. Simulations were divided in a training data set (135 cases) and a test data set (36 cases). The training data was used to fit an adjusted Bernoulli model as a function of AVA and flow rate. The model-predicted TPGModel was evaluated using the test data set and also compared against the common Bernoulli equation (TPGB). TPGB and TPGModel both correlated well with TPGCFD (r > 0.94), but significantly overestimated it. The average difference between TPGModel and TPGCFD was much lower: 3.3 mmHg vs. 17.3 mmHg between TPGB and TPGCFD. Also, the standard error of estimate was lower for the adjusted model: SEEModel = 5.3 mmHg vs. SEEB = 22.3 mmHg. The adjusted model's performance was more accurate than that of the conventional Bernoulli equation. The model might help to improve non-invasive assessment of TPG. Graphical abstract Processing pipeline for the definition of an adjusted Bernoulli model for the assessment of transvalvular pressure gradient. Using CT image data, the patient specific geometry of the stenosed AVs were reconstructed. Using this segmentation, the AVA as well as the volume flow rate was calculated and used for model definition. This novel model was compared against classical approaches on a test data set, which was not used for the model definition.

Increased risk of cardiovascular complications during and post‐COVID‐19 infection is more and more recognized—including myocarditis, arrhythmias, and myocardial infarctions (MIs). The mechanisms leading to these complications are direct virus‐induced injuries, as well as potential thrombotic and inflammatory‐induced mechanisms. To the latter, inflammatory plaque instability and plaque rupture are discussed entities contributing to MI‐induced post‐COVID‐19 complications. Our case report describes the first time, when a temporary impairment of LVEF in the COVID‐19‐convalescence phase unmasks a silent MI due to coronary plaque rupture by using invasive (OCT) and non‐invasive (CMR) modalities. Myocardial infarction might be an important differential diagnosis to consider in deteriorating patients with COVID‐19, especially if dyspnoea persists after acute infection.

Background T1 mapping using modified Look-Locker inversion recovery (MOLLI) provides quantitative information on myocardial tissue composition. T1 results differ between sites due to variations in hardware and software equipment, limiting the comparability of results. The aim was to test if Z-scores can be used to compare the results of MOLLI T1 mapping from different cardiovascular magnetic resonance (CMR) platforms. Methods First, healthy subjects (n = 15) underwent 11 combinations of native short-axis T1 mapping (four CMR systems from two manufacturers at 1.5 T and 3 T, three MOLLI schemes). Mean and standard deviation (SD) of septal myocardial T1 were derived for each combination. T1 maps were transformed into Z-score maps based on mean and SD values using a prototype post-processing module. Second, Z-score mapping was applied to a validation sample of patients with cardiac amyloidosis at 1.5 T (n = 25) or 3 T (n = 13). Results In conventional T1 analysis, results were confounded by variations in field strength, MOLLI scheme, and manufacturer-specific system characteristics. Z-score-based analysis yielded consistent results without significant differences between any two of the combinations in part 1 of the study. In the validation sample, Z-score mapping differentiated between patients with cardiac amyloidosis and healthy subjects with the same diagnostic accuracy as standard T1 analysis regardless of field strength. Conclusions T1 analysis based on Z-score mapping provides consistent results without significant differences due to field strengths, CMR systems, or MOLLI variants, and detects cardiac amyloidosis with the same diagnostic accuracy as conventional T1 analysis. Z-score mapping provides a means to compare native T1 results acquired with MOLLI across different CMR platforms.

Objective Aortic distensibility (AD) represents a well-established parameter of aortic stiffness. It remains unclear, however, whether AD can be obtained with high reproducibility in standard 4-chamber cine CMR images of the descending aorta. This study investigated the intra- and inter-observer agreement of AD based on different angles of the aorta and provided a sample size calculation of AD for future trials. Methods Thirty-one patients underwent CMR. Angulation of the descending aorta was performed to obtain strictly transversal and orthogonal cross-sectional aortic areas. AD was obtained both area and diameter based. Results For area-based values, inter-observer agreement was highest for 4-chamber AD (ICC 0.97; 95% CI 0.93–99), followed by orthogonal AD (ICC 0.96; 95% CI 0.91–98) and transversal AD (ICC 0.93; 95% CI 0.80–97). For diameter-based values, agreement was also highest for 4-chamber AD (ICC 0.97; 95% CI 0.94–99), followed by orthogonal AD (ICC 0.96; 95% CI 0.92–98) and transversal AD (ICC 0.91; 95% CI 0.77–96). Bland–Altman plots confirmed a small variation among observers. Sample size calculation showed a sample size of 12 patients to detect a change in 4-chamber AD of 1 × 10−3 mmHg−1 with either the area or diameter approach. Conclusion AD measurements are highly reproducible and allow an accurate and rapid assessment of arterial compliance from standard 4-chamber cine CMR., Clinical Research in Cardiology, 109 (4)

OBJECTIVES Complex blood flow profiles in the aorta are known to contribute to vessel dilatation. We studied flow profiles in the aorta in patients with aortic valve disease before and after surgical aortic valve replacement (AVR). METHODS Thirty-four patients with aortic valve disease underwent 4-dimensional velocity-encoded magnetic resonance imaging before and after AVR (biological valve = 27, mechanical valve = 7). Seven healthy volunteers served as controls. Eccentricity (ES) and complex flow scores (CFS) were determined from the degree of helicity, vorticity and eccentricity of flow profiles in the aorta. Model-based therapy planning was used in 4 cases to improve in silico postoperative flow profiles by personalized adjustment of size, rotation and angulation of the valve as well as aorta diameter. RESULTS Patients with aortic valve disease showed more complex flow than controls [median ES 2.5 (interquartile range (IQR) 2.3–2.7) vs 1.0 (IQR 1.0–1.0), P CONCLUSIONS Abnormal flow profiles in the aorta more frequently persist after surgical AVR. Model-based therapy planning might have the potential to optimize treatment for best possible individual outcome. Clinical trial registration number clinicaltrials.gov NCT03172338, 1 June 2017, retrospectively registered; NCT02591940, 30 October 2015, retrospectively registered.

Context Pro-opiomelanocortin (POMC) and the melanocortin-4 receptor (MC4R) play a pivotal role in the leptin–melanocortin pathway. Mutations in these genes lead to monogenic types of obesity due to severe hyperphagia. In addition to dietary-induced obesity, a cardiac phenotype without hypertrophy has been identified in MC4R knockout mice. Objective We aimed to characterize cardiac morphology and function as well as tissue Na+ content in humans with mutations in POMC and MC4R genes. Methods A cohort of 42 patients (5 patients with bi-allelic POMC mutations, 6 heterozygous MC4R mutation carriers, 19 obese controls without known monogenic cause, and 12 normal weight controls) underwent cardiac magnetic resonance (CMR) imaging and 23Na-MRI. Results Monogenic obese patients with POMC or MC4R mutation respectively had a significantly lower left ventricular mass/body surface area (BSA) than nonmonogenic obese patients. Left ventricular end-diastolic volume/BSA was significantly lower in POMC- and MC4R-deficient patients than in nonmonogenic obese patients. Subcutaneous fat and skin Na+ content was significantly higher in POMC- and MC4R-deficient patients than in nonmonogenic obese patients. In these compartments, the water content was significantly higher in patients with POMC and MC4R mutation than in control groups. Conclusion Patients with POMC or MC4R mutations carriers had a lack of transition to hypertrophy, significantly lower cardiac muscle mass/BSA, and stored more Na+ within the subcutaneous fat tissue than nonmonogenic obese patients. The results point towards the role of the melanocortin pathway for cardiac function and tissue Na+ storage and the importance of including cardiologic assessments into the diagnostic work-up of these patients.

Background: Myocardial efficiency should be maintained stable under light-to-moderate stress conditions, but ischemia puts the myocardium at risk for impaired functionality. Additionally, the measurement of such efficiency typically requires invasive heart catheterization and exposure to ionizing radiation. In this work, we aimed to non-invasively assess myocardial power and the resulting efficiency during pharmacological stress testing and ischemia induction.Methods: In a cohort of n = 10 healthy Landrace pigs, dobutamine stress testing was performed, followed by verapamil-induced ischemia alongside cardiac magnetic resonance (CMR) imaging. External myocardial power, internal myocardial power, and myocardial efficiency were assessed non-invasively using geometrical and functional parameters from CMR volumetric as well as blood flow and pressure measurements.Results: External myocardial power significantly increased under dobutamine stress [2.3 (1.6–3.1) W/m2 vs. 1.3 (1.1–1.6) W/m2, p = 0.005] and significantly decreased under verapamil-induced ischemia [0.8 (0.5–0.9) W/m2, p = 0.005]. Internal myocardial power [baseline: 5.9 (4.6–8.5) W/m2] was not affected by dobutamine [7.5 (6.9–9.0) W/m2, p = 0.241] nor verapamil [5.8 (4.7–8.8) W/m2, p = 0.878]. Myocardial efficiency did not change from baseline to dobutamine [21% (15–27) vs. 31% (20–44), p = 0.059] but decreased significantly during verapamil-induced ischemia [10% (8–13), p = 0.005].Conclusion: In healthy Landrace pigs, dobutamine stress increased external myocardial power, whereas myocardial efficiency was maintained stable. On the contrary, verapamil-induced ischemia substantially decreased external myocardial power and myocardial efficiency. Non-invasive CMR was able to quantify these efficiency losses and might be useful for future clinical studies evaluating the effects of therapeutic interventions on myocardial energetics.

Aims: Aortic valve replacement (AVR) may result in reverse cardiac remodeling. We aimed to assess long-term changes in the myocardium following AVR by Cardiac Magnetic Resonance Imaging (CMR). Methods: We prospectively observed the long-term left ventricular (LV) function and structure of 27 patients with AVR [n = 19 with aortic stenosis (AS); n = 8 with aortic regurgitation (AR)] by CMR. Patients underwent CMR before, as well as 1, 5, and 10 years after AVR. We evaluated clinical parameters, LV volumes, mass, geometry, ejection fraction (EF), global myocardial longitudinal strain (MyoGLS), global myocardial circular strain (MyoGCS), hemodynamic forces (HemForces), and Late Gadolinium Enhancement (LGE). Results: The median of LVMI, EDVI, and ESVI decreased in both groups. Patients with AR had higher initial values of EDVI and ESVI and showed a more prominent initial reduction. In AS, MyoGLS improved already after 1 year and remained constant afterward, whereas, in AR no improvement of MyoGLS was found. MyoGCS remained unchanged in the AS group but deteriorated in the AR group over 10 years. Ejection fraction (EF) was higher in AS patients compared to AR 10 years post-AVR. Late gadolinium enhancement (LGE) could be found more frequently in AS patients. Conclusion: CMR was well suited to investigate myocardial changes over a 10-year follow up period in patients with aortic valve disease. Regarding the long-term functional changes following AVR, patients with AR seemed to benefit less from AVR compared to AS patients. Fibrosis was more common in AS, but this did not reflect functional evolution in these patients. Close monitoring seems indispensable to avoid irreversible structural damage of the heart and to perform AVR at an appropriate stage., Frontiers in Cardiovascular Medicine, 8, ISSN:2297-055X

Background: Pharmacological stress testing can help to uncover pathological hemodynamic conditions and is, therefore, used in the clinical routine to assess patients with structural heart diseases such as aortic coarctation with borderline indication for treatment. The aim of this study was to develop and test a reduced-order model predicting dobutamine stress induced pressure gradients across the coarctation. Methods: The reduced-order model was developed based on n=21 imaging data sets of patients with aortic coarctation and a meta-analysis of subjects undergoing dobutamine stress testing. Within an independent test cohort of n=21 patients with aortic coarctation, the results of the model were compared with dobutamine stress testing during catheterization. Results: In n=19 patients responding to dobutamine stress testing, pressure gradients across the coarctation during dobutamine stress increased from 15.7±5.1 to 33.6±10.3 mm Hg (paired t test, P P =0.021). Conclusions: The developed reduced-order model can instantly predict dobutamine-induced hemodynamic changes with accuracy equivalent to heart catheterization in patients with aortic coarctation. The method is easy to use, available as a web-based calculator, and provides a promising alternative to conventional stress testing in the clinical routine. Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT02591940.

Rupture of an intracranial aneurysm often results in subarachnoid hemorrhage, a life-threatening condition with high mortality and morbidity. The Cerebral Aneurysm Detection and Analysis (CADA) competition was organized to support the development and benchmarking of algorithms for the detection, analysis, and risk assessment of cerebral aneurysms in X-ray rotational angiography (3DRA) images. 109 anonymized 3DRA datasets were provided for training, and 22 additional datasets were used to test the algorithmic solutions. Cerebral aneurysm detection was assessed using the F2 score based on recall and precision, and the fit of the delivered bounding box was assessed using the distance to the aneurysm. Segmentation quality was measured using Jaccard and a combination of different surface distance measurements. Systematic errors were analyzed using volume correlation and bias. Rupture risk assessment was evaluated using the F2 score. 158 participants from 22 countries registered for the CADAchallenge. The detection solutions presented by the community are mostly accurate (F2 score 0.92) with a small number of missed aneurysms with diameters of 3.5 mm. In addition, the delineation of these structures is very good with a Jaccard score of 0.915. The rupture risk estimation methods achieved an F2 score of 0.7. The performance of the detection and segmentation solutions is equivalent to that of human experts. In rupture risk estimation, the best results are obtained by combining different image-based, morphological and computational fluid dynamic parameters using machine learning methods.

Subarachnoid hemorrhage, commonly caused by the rupture of cerebral aneurysms, is a life-threatening condition with high mortality and morbidity. With a death rate of roughly 40%, it is highly desirable to detect aneurysms early and decide about the appropriate rupture prevention strategy. Rotational X-ray angiography is a non-invasive imaging modality and enables diagnostics to detect cerebral aneurysms at an early stage.

Cardiovascular diseases are the top cause of death worldwide. Commonly, physicians screen suspected pathological patients with histological examinations and blood tests. Since these clinical parameters are frequently ambiguous, they are routinely extended by delayed-enhancement magnetic resonance imaging of the myocardium.

Intracranial aneurysms frequently cause subarachnoid hemorrhage—a life-threatening condition with a high mortality and morbidity rate. State-of-the-art methods combine demographic, clinical, morphological, and computational fluid dynamics parameters.

The importance of mitral valve therapies is rising due to an aging population. Visualization and quantification of the valve anatomy from image acquisitions is an essential component of surgical and interventional planning. The segmentation of the mitral valve from computed tomography (CT) acquisitions is challenging due to high variation in appearance and visibility across subjects. We present a novel semi-automatic approach to segment the open-state valve in 3D CT volumes that combines user-defined landmarks to an initial valve model which is automatically adapted to the image information, even if the image data provide only partial visibility of the valve. Context information and automatic view initialization are derived from segmentation of the left heart lumina, which incorporates topological, shape and regional information. The valve model is initialized with user-defined landmarks in views generated from the context segmentation and then adapted to the image data in an active surface approach guided by landmarks derived from sheetness analysis. The resulting model is refined by user landmarks. For evaluation, three clinicians segmented the open valve in 10 CT volumes of patients with mitral valve insufficiency. Despite notable differences in landmark definition, the resulting valve meshes were overall similar in appearance, with a mean surface distance of $$1.62 \pm 2.10$$ mm. Each volume could be segmented in 5–22 min. Our approach enables an expert user to easily segment the open mitral valve in CT data, even when image noise or low contrast limits the visibility of the valve.

Severe mitral valve regurgitation can either be treated by a replacement or a repair of the valve. The latter is recommended due to lower perioperative mortality and better long-term survival. On the other hand, recurrence rates after mitral valve repair are high compared to those after replacements and the repair intervention can cause induced mitral valve stenosis. So far, there are no methods to predict the hemodynamic outcome of a chosen treatment or to compare different treatment options in advance. To overcome this, diastolic mitral valve hemodynamics are simulated using computational fluid dynamics after different virtual treatments of the valve. The left ventricular geometry of one patient was reconstructed using trans-esophageal echocardiography and computed tomography data. Pre-op hemodynamics are simulated using a referenced wall model to avoid expansive modeling of wall motion. Subsequently, the flow structures are compared to in vivo measurements. After manipulating the patient-specific geometry in order to mimic a restrictive mitral annuloplasty as well as a MitraClip intervention, hemodynamics results are calculated. Good agreements exist between calculated pre-op hemodynamics and in vivo measurements. The virtual annuloplasty did not result in any remarkable change of hemodynamics. Neither the pressure drop nor the velocity field showed strong differences. In contrast, the virtual MitraClip intervention led to a complete change in blood flow structures as well as an elevated pressure drop across the valve. The presented approach allows fast simulation of the diastolic hemodynamic situation before and after treatment of a mitral valve insufficiency. However, this approach is limited to the early diastolic phase of the cardiac cycle and needs to be validated using a larger sample size.

Sodium can accumulate in the skin at concentrations exceeding serum levels. A high sodium environment can lead to pathogenic T helper 17 cell expansion. Psoriasis is a chronic inflammatory skin disease in which IL-17. producing T helper 17 cells play a crucial role. In an observational study, we measured skin sodium content in patients with psoriasis and in age-matched healthy controls by Sodium-23 magnetic resonance imaging. Patients with PASI > 5 showed significantly higher sodium and water content in the skin but not in other tissues than those with lower PASI or healthy controls. Skin sodium concentrations measured by Sodium-23 spectroscopy or by atomic absorption spectrometry in ashed-skin biopsies verified the findings with Sodium-23 magnetic resonance imaging. In vitro T helper 17 cell differentiation of naive CD4(+) cells from patients with psoriasis markedly induced IL-17A expression under increased sodium chloride concentrations. The imiquimod-induced psoriasis mouse model replicated the human findings. Extracellular tracer Chromium-51-EDTA measurements in imiquimod- and sham-treated skin showed similar extracellular volumes, rendering excessive water of intracellular origin. Chronic genetic IL-17A-driven psoriasis mouse models underlined the role of IL-17A in dermal sodium accumulation and inflammation. Our data describe skin sodium as a pathophysiological feature of psoriasis, which could open new avenues for its treatment.

Journal of Cardiovascular Magnetic Resonance, 20, ISSN:1097-6647, ISSN:1532-429X

Patient-specific models become increasingly important in cardiovascular research as they allow prediction of surgical procedures. While the left ventricular outflow profile is an essential boundary condition, it remains unknown before treatment takes place. To overcome this problem, hemodynamics after virtual valve replacement were calculated based on different inlet profiles at the left ventricular outflow tract: a generic plug profile and a profile derived from 4D-flow-MRI. Spatially averaged parameters within the aorta were not significantly altered using either profile. A generic profile might be sufficient for the prediction of hemodynamics, circumventing the problem of predicting change in patient-specific boundary conditions.

CFD has gained significant attention as a tool to model aortic hemodynamics. However, obtaining accurate patient-specific boundary conditions still poses a major challenge and represents a major source of uncertainties, which are difficult to quantify. This study presents an attempt to quantify these uncertainties by comparing 14 patient-specific simulations of the aorta (reference method), each exhibiting stenosis, against simulations using the same geometries without the branching vessels of the aortic arch (simplified method). Results were evaluated by comparing pressure drop along the aorta, secondary flow degree (SFD) and surface-averaged wall shear stress (WSS) for each patient. The comparison shows little difference in pressure drop between the two methods (simplified-reference) with the mean difference being 1.2 mmHg (standard deviation: 3.0 mmHg). SFD and WSS, however, show striking differences between the methods: SFD downstream of the stenosis is on average 61 % higher in the simplified cases, while WSS is on average 3.0 Pa lower in the simplified cases. Although unphysiological, the comparison of both methods gives an upper bound for the error introduced by uncertainties in branching vessel boundary conditions. For the pressure drop this error appears to be remarkably low, while being unacceptably high for SFD and WSS.

Modeling different treatment options before a procedure is performed is a promising approach for surgical decision making and patient care in heart valve disease. This study investigated the hemodynamic impact of different prostheses through patient-specific MRI-based CFD simulations. Ten time-resolved MRI data sets with and without velocity encoding were obtained to reconstruct the aorta and set hemodynamic boundary conditions for simulations. Aortic hemodynamics after virtual valve replacement with a biological and mechanical valve prosthesis were investigated. Wall shear stress (WSS), secondary flow degree (SFD), transvalvular pressure drop (TPD), turbulent kinetic energy (TKE), and normalized flow displacement (NFD) were evaluated to characterize valve-induced hemodynamics. The biological prostheses induced significantly higher WSS (medians: 9.3 vs. 8.6 Pa, P = 0.027) and SFD (means: 0.78 vs. 0.49, P = 0.002) in the ascending aorta, TPD (medians: 11.4 vs. 2.7 mm Hg, P = 0.002), TKE (means: 400 vs. 283 cm2 /s2 , P = 0.037), and NFD (means: 0.0994 vs. 0.0607, P = 0.020) than the mechanical prostheses. The differences between the prosthesis types showed great inter-patient variability, however. Given this variability, a patient-specific evaluation is warranted. In conclusion, MRI-based CFD offers an opportunity to assess the interactions between prosthesis and patient-specific boundary conditions, which may help in optimizing surgical decision making and providing additional guidance to clinicians.

Myocardial extracellular volume fraction (ECV) reflecting diffuse myocardial fibrosis can be measured with T1 mapping cardiovascular magnetic resonance (CMR) before and after the application of a gadolinium-based extracellular contrast agent. The equilibrium between blood and myocardium contrast concentration required for ECV measurements can be obtained with a primed contrast infusion (equilibrium contrast-CMR). We hypothesized that equilibrium can also be achieved with a single contrast bolus to accurately measure diffuse myocardial fibrosis in patients with congenital heart disease (CHD). Healthy controls (n = 17; median age 24.0 years) and patients with CHD (n = 19; 25.0 years) were prospectively enrolled. Using modified Look-Locker inversion recovery T1 mapping before, 15 min after bolus injection, and during constant infusion of gadolinium-DOTA, T1 values were obtained for blood pool and myocardium of the left ventricle (LV), the interventricular septum (IVS), and the right ventricle (RV) in a single midventricular plane in short axis or in transverse orientation. ECV of LV, IVS and RV by bolus-only and bolus-infusion correlated significantly in CHD patients (r = 0.94, 0.95, and 0.74; p

Cardiac diseases manifest in a multitude of interconnected changes in morphology and dynamics. Radiomics approaches are a promising technique to analyze such changes directly from image data. We propose novel features to specifically describe moving cardiac structures, and an interactive 4D visualization method to explore such data. Prototypical tests with an open data set containing different diseases show that our approach can be a fast and useful tool for the 4D analysis of heterogeneous cohort data.

Minimally invasive surgery is increasingly utilized for mitral valve repair and replacement. The intervention is performed with an endoscopic field of view on the arrested heart. Extracting the necessary information from the live endoscopic video stream is challenging due to the moving camera position, the high variability of defects, and occlusion of structures by instruments. During such minimally invasive interventions there is no time to segment regions of interest manually. We propose a real-time-capable deep-learning-based approach to detect and segment the relevant anatomical structures and instruments. For the universal deployment of the proposed solution, we evaluate them on pixel accuracy as well as distance measurements of the detected contours. The U-Net, Google’s DeepLab v3, and the Obelisk-Net models are cross-validated, with DeepLab showing superior results in pixel accuracy and distance measurements.

In aortic coarctation (CoA), clinical guidelines recommend treatment in the presence of a relevant pressure gradient [(1)][1]. Although reliable noninvasive measurement approaches would be crucial, the accuracy of currently available methods is limited and cardiac catheterization has remained a

Aortic valve replacement (AVR) does not usually restore physiological flow profiles. Complex flow profiles are associated with aorta dilatation, ventricle remodeling, aneurysms, and development of atherosclerosis. All these affect long-term morbidity and often require reoperations. In this pilot study, we aim to investigate an ability to optimize the real surgical AVR procedure toward flow profile associated with healthy persons. Four cases of surgical AVR (two with biological and two with mechanical valve prosthesis) with available post-treatment cardiac magnetic resonance imaging (MRI), including four-dimensional flow MRI and showing abnormal complex post-treatment hemodynamics, were investigated. All cases feature complex hemodynamic outcomes associated with valve-jet eccentricity and strong secondary flow characterized by helical flow and recirculation regions. A commercial computational fluid dynamics solver was used to simulate peak systolic hemodynamics of the real post-treatment outcome using patient-specific MRI measured boundary conditions. Then, an attempt to optimize hemodynamic outcome by modifying valve size and orientation as well as ascending aorta size reduction was made. Pressure drop, wall shear stress, secondary flow degree, helicity, maximal velocity, and turbulent kinetic energy were evaluated to characterize the AVR hemodynamic outcome. The proposed optimization strategy was successful in three of four cases investigated. Although no single parameter was identified as the sole predictor for a successful flow optimization, downsizing of the ascending aorta in combination with the valve orientation was the most effective optimization approach. Simulations promise to become an effective tool to predict hemodynamic outcome. The translation of these tools requires, however, studies with a larger cohort of patients followed by a prospective clinical validation study.

PURPOSE To introduce a scheme based on a recent technique in computational hemodynamics, known as the lattice Boltzmann methods (LBM), to noninvasively measure pressure gradients in patients with a coarctation of the aorta (CoA). To provide evidence on the accuracy of the proposed scheme, the computed pressure drop values are compared against those obtained using the reference standard method of catheterization. MATERIALS AND METHODS Pre- and posttreatment LBM-based pressure gradients for 12 patients with CoA were simulated for the time point of peak systole using the open source library OpenLB. Four-dimensional (4D) flow-sensitive phase-contrast MRI at 1.5 Tesla was used to acquire flow and to setup the simulation. The vascular geometry was reconstructed using 3D whole-heart MRI. Patients underwent pre- and postinterventional pressure catheterization as a reference standard. RESULTS There is a significant linear correlation between the pretreatment catheter pressure drops and those computed based on the LBM simulation, r=.85, P

Computational modelling has made significant progress towards clinical application in recent years. In addition to providing detailed diagnostic data, these methods have the potential to simulate patient-specific interventions and to predict their outcome. Our objective was to evaluate to which extent patient-specific modelling influences treatment decisions in coarctation of the aorta (CoA), a common congenital heart disease. We selected three cases with CoA, two of which had borderline indications for intervention according to current clinical guidelines. The third case was not indicated for intervention according to guidelines. For each case, we generated two separate datasets. First dataset included conventional diagnostic parameters (echocardiography and magnetic resonance imaging). In the second, we added modelled parameters (pressure fields). For the two cases with borderline indications for intervention, the second dataset also included pressure fields after virtual stenting simulations. All parameters were computed by modelling methods that were previously validated. In an online-administered, invitation-only survey, we randomized 178 paediatric cardiologists to view either conventional (control) or add-on modelling (experimental) datasets. Primary endpoint was the proportion of participants recommending different therapeutic options: (1) surgery or catheter lab (collectively, “intervention”) or (2) no intervention (follow-up with or without medication). Availability of data from computational predictive modelling influenced therapeutic decision making in two of three cases. There was a statistically significant association between group assignment and the recommendation of an intervention for one borderline case and one non-borderline case: 94.3% vs. 72.2% (RR: 1.31, 95% CI: 1.14–1.50, p = 0.00) and 18.8% vs. 5.1% (RR: 3.09, 95% CI: 1.17–8.18, p = 0.01) of participants in the experimental and control groups respectively recommended an intervention. For the remaining case, there was no difference between the experimental and control group and the majority of participants recommended intervention. In sub-group analyses, findings were not affected by the experience level of participating cardiologists. Despite existing clinical guidelines, the therapy recommendations of the participating physicians were heterogeneous. Validated patient-specific computational modelling has the potential to influence treatment decisions. Future studies in broader areas are needed to evaluate whether differences in decisions result in improved outcomes (Trial Registration: NCT02700737).

Purpose: While novel tools for segmentation of the mitral valve are often based on automatic image processing, they mostly require manual interaction by a proficient user. Those segmentations are essential for numerical support of mitral valve treatment using computational fluid dynamics, where the reconstructed geometry is incorporated into a simulation domain. To quantify the uncertainty and reliability of hemodynamic simulations, it is crucial to examine the influence of user-dependent variability in valve segmentation. Methods: Previously, the inter-user variability of landmarks in mitral valve segmentation was investigated. Here, the inter-user variability of geometric parameters of the mitral valve, projected orifice area (OA) and projected annulus area (AA), is investigated for 10 mitral valve geometries, each segmented by three users. Furthermore, the propagation of those variations into numerically calculated hemodynamics, i.e., the blood flow velocity, was investigated. Results: Among the three geometric valve parameters, AA was least user-dependent. Almost all deviations to the mean were below 10%. Larger variations were observed for OA. Variations observed for the numerically calculated hemodynamics were in the same order of magnitude as those of geometric parameters. No correlation between variation of geometric parameters and variation of calculated hemodynamic parameters was found. Conclusion: Errors introduced due to the user-dependency were of the same size as the variations of calculated hemodynamics. The variation was thereby of the same scale as deviations in clinical measurements of blood flow velocity using Doppler echocardiography. Since no correlation between geometric and hemodynamic uncertainty was found, further investigation of the complex relationship between anatomy, leaflet shape and flow is necessary.

A variety of arrhythmias following myocardial infarction are implicated with ectopic beats (EBs) resulting from spontaneous calcium (Ca2+) release (SCR) events. However, investigation of these arrhythmias is hampered by the lack of adequate techniques to assess with certainty abnormalities at the subcellular scale and arrhythmogenic events at the organ level. The aim of this study was to construct a multiscale computational model to investigate SCR-mediated ectopy within the infarcted human heart. To achieve this goal, an experimentally based phenomenological model of SCR events was integrated in the equations for Ca2+ cycling of an human ventricular action potential model. This augmented myocyte model was used in in-silico experiments with a postinfarction biventricular (BiV) model constructed based on magnetic resonance imaging data. The infarct scar and border zone (BZ) were segmented by thresholding the voxel intensity within the ventricular wall. These were then used to build a finite element mesh. Within the multiscale human BiV model we show that SCR-mediated DADs in cells interspersed with fibrosis in the infarcted BZ are capable of overcoming local source-sink mismatches to trigger an EB. The results presented here are the first to show that EBs resulting from abnormalities at the subcellular level can be studied using highly detailed human heart models.

Ectopic beats are known to be involved in the initiation of a variety of cardiac arrhythmias. Although their location may vary, ectopic excitations have been found to originate from infarct areas, regions of micro-fibrosis and other heterogeneous tissues. However, the underlying mechanisms that link ectopic foci to heterogeneous tissues have yet to be fully understood. In this work, we investigate the mechanism of micro-reentry that leads to the generation of ectopic beats near infarct areas using a patient-specific heart model. The patient-specific geometrical model of the heart, including scar and peri-infarct zones, is obtained through magnetic resonance imaging (MRI). The infarct region is composed of ischemic myocytes and non-conducting cells (fibrosis, for instance). Electrophysiology is captured using an established cardiac myocyte model of the human ventricle modified to describe ischemia. The simulation results clearly reveal that ectopic beats emerge from micro-reentries that are sustained by the heterogeneous structure of the infarct regions. Because microscopic information about the heterogeneous structure of the infarct regions is not available, Monte-Carlo simulations are used to identify the probabilities of an infarct region to behave as an ectopic focus for different levels of ischemia and different percentages of non-conducting cells. From the proposed model, it is observed that ectopic beats are generated when a percentage of non-conducting cells is near a topological metric known as the percolation threshold. Although the mechanism for micro-reentries was proposed half a century ago to be a source of ectopic beats or premature ventricular contractions during myocardial infarction, the present study is the first to reproduce this mechanism in-silico using patient-specific data.

Pulmonary hypertension is associated with diverse cardiac, pulmonary, and systemic diseases in neonates, infants, and older children and contributes to significant morbidity and mortality. However, current approaches to caring for pediatric patients with pulmonary hypertension have been limited by the lack of consensus guidelines from experts in the field. In a joint effort from the American Heart Association and American Thoracic Society, a panel of experienced clinicians and clinician-scientists was assembled to review the current literature and to make recommendations on the diagnosis, evaluation, and treatment of pediatric pulmonary hypertension. This publication presents the results of extensive literature reviews, discussions, and formal scoring of recommendations for the care of children with pulmonary hypertension.

Purpose: The coarctation of the aorta (CoA), a local narrowing of the aortic arch, accounts for 7 % of all congenital heart defects. Stenting is a recommended therapy to reduce the pressure gradient. This procedure is associated with complications such as the development of adverse flow conditions. A computer-aided treatment planning based on flow simulations can help to predict possible complications. The virtual stent planning is an important, intermediate step in the treatment planning pipeline. We present a novel approach that automatically suggests a stent setup and provides a set of intuitive parameters that allow for an interactive adaption of the suggested stent placement and induced deformation. Methods: A high-quality mesh and a centerline are automatically generated. The stent-induced deformation is realized through a deformation of the centerline and a vertex displacement with respect to the deformed centerline and additional stent parameters. The parameterization is automatically derived from the underlying data and can be optionally altered through a condensed set of clinically sound parameters. Results: The automatic deformation can be generated in about 25 s on a consumer system. The interactive adaption can be performed in real time. Compared with manual expert reconstructions of the stented vessel section, the mean difference of vessel path and diameter is below 1 mm. Conclusion: Our approach enables a medical user to easily generate a plausibly deformed vessel mesh which is necessary as input for a simulation-based treatment planning of CoA.

Background The role of intracardiac blood flow behavior within the context of manifestation and interventional success in patients with mitral regurgitation is unknown to date. The present study aims to assess left ventricular blood flow behavior characterized by kinetic energy (KE) in patients with mitral regurgitation before and after mitral valve surgery. Methods Patients with mitral regurgitation (mean age 56 ± 9 years) and the necessity for mitral valve repair (n = 6) or biological valve replacement (n = 4) received cardiac magnetic resonance before and after surgery and were compared with a group of healthy volunteers (n = 7; mean age 27 ± 7 years). Volumetric data and KE of the left ventricle were obtained for all subjects. KE normalized and nonnormalized to volume was calculated from four-dimensional flow magnetic resonance imaging. Mean KE and KE peaks (systolic, early-diastolic and late diastolic), and end-systolic phase duration were considered. Results End-diastolic, end-systolic and stroke volume were significantly higher in patients with mitral regurgitation than in healthy volunteers (P = 0.00, 0.01, and 0.00, respectively) and decreased significantly after surgery (P = 0.00, 0.01, and 0.00, respectively). A significant postoperative decrease of mean KE, systolic and early-diastolic KE peaks was observed (P = 0.01, 0.02, and 0.01, respectively). Late-diastolic KE peak remained high in postoperative patients (P = 0.58). Conclusion Intracardiac blood flow as characterized by measurements of KE is altered in patients with mitral regurgitation. Physiological flow conditions appear to not fully be restored with mitral valve surgery. J. Magn. Reson. Imaging 2015.

The large amount of clinical signals in intensive care units can easily overwhelm health-care personnel and can lead to treatment delays, suboptimal care, or clinical errors. The aim of this study was to apply deep machine learning methods to predict severe complications during critical care in real time after cardiothoracic surgery.We used deep learning methods (recurrent neural networks) to predict several severe complications (mortality, renal failure with a need for renal replacement therapy, and postoperative bleeding leading to operative revision) in post cardiosurgical care in real time. Adult patients who underwent major open heart surgery from Jan 1, 2000, to Dec 31, 2016, in a German tertiary care centre for cardiovascular diseases formed the main derivation dataset. We measured the accuracy and timeliness of the deep learning model's forecasts and compared predictive quality to that of established standard-of-care clinical reference tools (clinical rule for postoperative bleeding, Simplified Acute Physiology Score II for mortality, and the Kidney Disease: Improving Global Outcomes staging criteria for acute renal failure) using positive predictive value (PPV), negative predictive value, sensitivity, specificity, area under the curve (AUC), and the FOf 47 559 intensive care admissions (corresponding to 42 007 patients), we included 11 492 (corresponding to 9269 patients). The deep learning models yielded accurate predictions with the following PPV and sensitivity scores: PPV 0·90 and sensitivity 0·85 for mortality, 0·87 and 0·94 for renal failure, and 0·84 and 0·74 for bleeding. The predictions significantly outperformed the standard clinical reference tools, improving the absolute complication prediction AUC by 0·29 (95% CI 0·23-0·35) for bleeding, by 0·24 (0·19-0·29) for mortality, and by 0·24 (0·13-0·35) for renal failure (p0·0001 for all three analyses). The deep learning methods showed accurate predictions immediately after patient admission to the intensive care unit. We also observed an increase in performance in our validation cohort when the machine learning approach was tested against clinical reference tools, with absolute improvements in AUC of 0·09 (95% CI 0·03-0·15; p=0·0026) for bleeding, of 0·18 (0·07-0·29; p=0·0013) for mortality, and of 0·25 (0·18-0·32; p0·0001) for renal failure.The observed improvements in prediction for all three investigated clinical outcomes have the potential to improve critical care. These findings are noteworthy in that they use routinely collected clinical data exclusively, without the need for any manual processing. The deep machine learning method showed AUC scores that significantly surpass those of clinical reference tools, especially soon after admission. Taken together, these properties are encouraging for prospective deployment in critical care settings to direct the staff's attention towards patients who are most at risk.No specific funding.

BackgroundWe sought to assess left ventricular regional function in patients with and without left ventricular wall scar tissue in the long term after repair of an anomalous origin of the left coronary artery from the pulmonary artery.MethodsA total of 20 patients aged 12.8±7.4 years were assessed 10 (0.5–17) years after the repair of an anomalous origin of the left coronary artery from the pulmonary artery; of them, 10 (50%) patients showed left ventricular wall scar tissue on current cardiac MRI. Left ventricular regional function was assessed by two-dimensional speckle-tracking echocardiography in 10 patients with scar tissue and 10 patients without scar tissue and in 10 age-matched controls.ResultsIn patients with scar tissue, MRI-derived left ventricular ejection fraction was significantly reduced compared with that in patients without scar tissue (51 versus 61%, pConclusionsRegional left ventricular function is reduced even in patients without left ventricular wall scar tissue late after successful repair of an anomalous origin of the left coronary artery from the pulmonary artery. This highlights the need for meticulous lifelong follow-up in all patients with a repaired anomalous origin of the left coronary artery from the pulmonary artery.

Objective We investigated a full energetic profile of pressure and volume loaded right ventricle (RV) in porcine models by evaluating kinetic energy (KE), stroke power, power output and power loss across pulmonary valves with stenosis (PS) or with regurgitation (PR). Methods Fifteen pigs (6 PS and 6 PR, 3 unoperated controls) were studied. Phase-contrast 4D-flow MRI was performed in models of PS and PR at baseline and at 10–12 weeks, in conjunction with cardiac catheterization. Phase contrast velocities over 1 cardiac cycle were registered with a dynamic mask of the RV segmented from cine images. Mean KE and KE curve profiles were measured, normalized for RV volumes and compared between groups. Right heart catheterization pressures were used to calculate RV stroke power and power output, from which pulmonary valve power loss and RV power output ratio were calculated, and compared between groups. Results PS and PR groups had similar KE pre procedure but significant changes in KE post procedure. The PR group had higher RV power output ratio and KE (72.1% ± 11.4%; 20.6 ± 6.1) than PS group (25.6% ± 4.7%; 13.8 ± 5.0) post procedure. Volume loaded RV from PR had higher KE and power output ratio compared to pressure load from PS. Conclusions In porcine models of PS and PR, the RV presents altered systolic and diastolic energetic profiles. Pulmonary valve efficiency appeared to decrease in the medium term with somatic growth, with increased power loss in all groups studied, and greatly within the PS group.