Reduced dynamic changes in pulmonary artery compliance during isometric handgrip exercise in patients with heart failure.

Exercise intolerance is a debilitating symptom in heart failure (HF), adversely affecting both quality of life and long-term prognosis. Emerging evidence suggests that pulmonary artery (PA) compliance may be a contributing factor. This study aims to non-invasively assess PA compliance and its dynamic properties during isometric handgrip (HG) exercise in HF patients and healthy controls, using cardiovascular magnetic resonance (CMR). We prospectively enrolled 36 subjects, comprising 17 HF patients (NYHA class II and III) and 19 healthy controls. Participants performed an HG test, and we assessed changes in PA compliance and hemodynamic flow parameters using advanced CMR techniques. We also explored the relationship between CMR-derived PA compliance metrics and established clinical indicators, ensuring the validity of our findings through intra- and interobserver agreements. HF patients had significantly lower resting PA compliance compared to controls (28.9% vs. 50.1%, p < 0.01). During HG exercise, HF patients exhibited a dampened adaptability in PA compliance. Hemodynamic responses, including heart rate and blood pressure, were not significantly different between the groups. Further analyses revealed a significant correlation between changes in PA compliance and functional capacity, and an inverse relationship with NYHA class. Our study demonstrates a marked difference in PA vascular responses during HG exercise between HF patients and healthy controls. The compromised adaptability in PA compliance in HF patients is correlated with diminished functional capacity. These findings have significant clinical implications and may guide future interventional strategies in HF management.

Cardiac Health Assessment Using a Wearable Device Before and After Transcatheter Aortic Valve Implantation: Prospective Study.

Background: Due to aging of the population, the prevalence of aortic valve stenosis will increase drastically in upcoming years. Consequently, transcatheter aortic valve implantation (TAVI) procedures will also expand worldwide. Optimal selection of patients who benefit with improved symptoms and prognoses is key, since TAVI is not without its risks. Currently, we are not able to adequately predict functional outcomes after TAVI. Quality of life measurement tools and traditional functional assessment tests do not always agree and can depend on factors unrelated to heart disease. Activity tracking using wearable devices might provide a more comprehensive assessment. Objective: This study aimed to identify objective parameters (eg, change in heart rate) associated with improvement after TAVI for severe aortic stenosis from a wearable device. Methods: In total, 100 patients undergoing routine TAVI wore a Philips Health Watch device for 1 week before and after the procedure. Watch data were analyzed offline-before TAVI for 97 patients and after TAVI for 75 patients. Results: Parameters such as the total number of steps and activity time did not change, in contrast to improvements in the 6-minute walking test (6MWT) and physical limitation domain of the transformed WHOQOL-BREF questionnaire. Conclusions: These findings, in an older TAVI population, show that watch-based parameters, such as the number of steps, do not change after TAVI, unlike traditional 6MWT and QoL assessments. Basic wearable device parameters might be less appropriate for measuring treatment effects from TAVI.

Deep learning based assessment of hemodynamics in the coarctation of the aorta: comparison of bidirectional recurrent and convolutional neural networks.

The utilization of numerical methods, such as computational fluid dynamics (CFD), has been widely established for modeling patient-specific hemodynamics based on medical imaging data. Hemodynamics assessment plays a crucial role in treatment decisions for the coarctation of the aorta (CoA), a congenital heart disease, with the pressure drop (PD) being a crucial biomarker for CoA treatment decisions. However, implementing CFD methods in the clinical environment remains challenging due to their computational cost and the requirement for expert knowledge. This study proposes a deep learning approach to mitigate the computational need and produce fast results. Building upon a previous proof-of-concept study, we compared the effects of two different artificial neural network (ANN) architectures trained on data with different dimensionalities, both capable of predicting hemodynamic parameters in CoA patients: a one-dimensional bidirectional recurrent neural network (1D BRNN) and a three-dimensional convolutional neural network (3D CNN). The performance was evaluated by median point-wise root mean square error (RMSE) for pressures along the centerline in 18 test cases, which were not included in a training cohort. We found that the 3D CNN (median RMSE of 3.23 mmHg) outperforms the 1D BRNN (median RMSE of 4.25 mmHg). In contrast, the 1D BRNN is more precise in PD prediction, with a lower standard deviation of the error (±7.03 mmHg) compared to the 3D CNN (±8.91 mmHg). The differences between both ANNs are not statistically significant, suggesting that compressing the 3D aorta hemodynamics into a 1D centerline representation does not result in the loss of valuable information when training ANN models. Additionally, we evaluated the utility of the synthetic geometries of the aortas with CoA generated by using a statistical shape model (SSM), as well as the impact of aortic arch geometry (gothic arch shape) on the model's training. The results show that incorporating a synthetic cohort obtained through the SSM of the clinical cohort does not significantly increase the model's accuracy, indicating that the synthetic cohort generation might be oversimplified. Furthermore, our study reveals that selecting training cases based on aortic arch shape (gothic versus non-gothic) does not improve ANN performance for test cases sharing the same shape.

CT-based comparison of porcine, ovine, and human pulmonary arterial morphometry.

To facilitate pre-clinical animal and in-silico clinical trials for implantable pulmonary artery pressure sensors, understanding the respective species pulmonary arteries (PA) anatomy is important. Thus, morphological parameters describing PA of pigs and sheep, which are common animal models, were compared with humans. Retrospective computed tomography data of 41 domestic pigs (82.6 ± 18.8 kg), 14 sheep (49.1 ± 6.9 kg), and 49 patients (76.8 ± 18.2 kg) were used for reconstruction of the subject-specific PA anatomy. 3D surface geometries including main, left, and right PA as well as LPA and RPA side branches were manually reconstructed. Then, specific geometric parameters (length, diameters, taper, bifurcation angle, curvature, and cross-section enlargement) affecting device implantation and post-interventional device effect and efficacy were automatically calculated. For both animal models, significant differences to the human anatomy for most geometric parameters were found, even though the respective parameters' distributions also featured relevant overlap. Out of the two animal models, sheep seem to be better suitable for a preclinical study when considering only PA morphology. Reconstructed geometries are provided as open data for future studies. These findings support planning of preclinical studies and will help to evaluate the results of animal trials.

In-silico enhanced animal study of pulmonary artery pressure sensors: assessing hemodynamics using computational fluid dynamics.

To assess whether in-silico models can be used to predict the risk of thrombus formation in pulmonary artery pressure sensors (PAPS), a chronic animal study using pigs was conducted. Computed tomography (CT) data was acquired before and immediately after implantation, as well as one and three months after the implantation. Devices were implanted into 10 pigs, each one in the left and right pulmonary artery (PA), to reduce the required number of animal experiments. The implantation procedure aimed at facilitating optimal and non-optimal positioning of the devices to increase chances of thrombus formation. Eight devices were positioned non-optimally. Three devices were positioned in the main PA instead of the left and right PA. Pre-interventional PA geometries were reconstructed from the respective CT images, and the devices were virtually implanted at the exact sites and orientations indicated by the follow-up CT after one month. Transient intra-arterial hemodynamics were calculated using computational fluid dynamics. Volume flow rates were modelled specifically matching the animals body weights. Wall shear stresses (WSS) and oscillatory shear indices (OSI) before and after device implantation were compared. Simulations revealed no relevant changes in any investigated hemodynamic parameters due to device implantation. Even in cases, where devices were implanted in a non-optimal manner, no marked differences in hemodynamic parameters compared to devices implanted in an optimal position were found. Before implantation time and surface-averaged WSS was 2.35±0.47 Pa, whereas OSI was 0.08±0.17, respectively. Areas affected by low WSS magnitudes were 2.5±2.7 cm2, whereas the areas affected by high OSI were 18.1±6.3 cm2. After device implantation, WSS and OSI were 2.45±0.49 Pa and 0.08±0.16, respectively. Surface areas affected by low WSS and high OSI were 2.9±2.7 cm2, and 18.4±6.1 cm2, respectively. This in-silico study indicates that no clinically relevant differences in intra-arterial hemodynamics are occurring after device implantation, even at non-optimal positioning of the sensor. Simultaneously, no embolic events were observed, suggesting that the risk for thrombus formation after device implantation is low and independent of the sensor position.

Modelling blood flow in patients with heart valve disease using deep learning: A computationally efficient method to expand diagnostic capabilities in clinical routine.

Introduction: The computational modelling of blood flow is known to provide vital hemodynamic parameters for diagnosis and treatment-support for patients with valvular heart disease. However, most diagnosis/treatment-support solutions based on flow modelling proposed utilize time- and resource-intensive computational fluid dynamics (CFD) and are therefore difficult to implement into clinical practice. In contrast, deep learning (DL) algorithms provide results quickly with little need for computational power. Thus, modelling blood flow with DL instead of CFD may substantially enhances the usability of flow modelling-based diagnosis/treatment support in clinical routine. In this study, we propose a DL-based approach to compute pressure and wall-shear-stress (WSS) in the aorta and aortic valve of patients with aortic stenosis (AS). Methods: A total of 103 individual surface models of the aorta and aortic valve were constructed from computed tomography data of AS patients. Based on these surface models, a total of 267 patient-specific, steady-state CFD simulations of aortic flow under various flow rates were performed. Using this simulation data, an artificial neural network (ANN) was trained to compute spatially resolved pressure and WSS using a centerline-based representation. An unseen test subset of 23 cases was used to compare both methods. Results: ANN and CFD-based computations agreed well with a median relative difference between both methods of 6.0% for pressure and 4.9% for wall-shear-stress. Demonstrating the ability of DL to compute clinically relevant hemodynamic parameters for AS patients, this work presents a possible solution to facilitate the introduction of modelling-based treatment support into clinical practice.

Disease- and sex-specific differences in patients with heart valve disease: a proteome study.

Pressure overload in patients with aortic valve stenosis and volume overload in mitral valve regurgitation trigger specific forms of cardiac remodeling; however, little is known about similarities and differences in myocardial proteome regulation. We performed proteome profiling of 75 human left ventricular myocardial biopsies (aortic stenosis = 41, mitral regurgitation = 17, and controls = 17) using high-resolution tandem mass spectrometry next to clinical and hemodynamic parameter acquisition. In patients of both disease groups, proteins related to ECM and cytoskeleton were more abundant, whereas those related to energy metabolism and proteostasis were less abundant compared with controls. In addition, disease group-specific and sex-specific differences have been observed. Male patients with aortic stenosis showed more proteins related to fibrosis and less to energy metabolism, whereas female patients showed strong reduction in proteostasis-related proteins. Clinical imaging was in line with proteomic findings, showing elevation of fibrosis in both patient groups and sex differences. Disease- and sex-specific proteomic profiles provide insight into cardiac remodeling in patients with heart valve disease and might help improve the understanding of molecular mechanisms and the development of individualized treatment strategies.

Muscle sodium content in patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

BACKGROUND: Muscle fatigue and pain are key symptoms of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). Although the pathophysiology is not yet fully understood, there is ample evidence for hypoperfusion which may result in electrolyte imbalance and sodium overload in muscles. Therefore, the aim of this study was to assess levels of sodium content in muscles of patients with ME/CFS and to compare these to healthy controls. METHODS: Six female patients with ME/CFS and six age, BMI and sex matched controls underwent 23Na-MRI of the left lower leg using a clinical 3T MR scanner before and after 3 min of plantar flexion exercise. Sodium reference phantoms with solutions of 10, 20, 30 and 40 mmol/L NaCl were used for quantification. Muscle sodium content over 40 min was measured using a dedicated plugin in the open-source DICOM viewer Horos. Handgrip strength was measured and correlated with sodium content. RESULTS: Baseline tissue sodium content was higher in all 5 lower leg muscle compartments in ME/CFS compared to controls. Within the anterior extensor muscle compartment, the highest difference in baseline muscle sodium content between ME/CFS and controls was found (mean ± SD; 12.20 ± 1.66 mM in ME/CFS versus 9.38 ± 0.71 mM in controls, p = 0.0034). Directly after exercise, tissue sodium content increased in gastrocnemius and triceps surae muscles with + 30% in ME/CFS (p = 0.0005) and + 24% in controls (p = 0.0007) in the medial gastrocnemius muscle but not in the extensor muscles which were not exercised. Compared to baseline, the increase of sodium content in medial gastrocnemius muscle was stronger in ME/CFS than in controls with + 30% versus + 17% to baseline at 12 min (p = 0.0326) and + 29% versus + 16% to baseline at 15 min (p = 0.0265). Patients had reduced average handgrip strength which was associated with increased average muscle tissue sodium content (p = 0.0319, R2 = 0.3832). CONCLUSION: Muscle sodium content before and after exercise was higher in ME/CFS than in healthy controls. Furthermore, our findings indicate an inverse correlation between muscle sodium content and handgrip strength. These findings provide evidence that sodium overload may play a role in the pathophysiology of ME/CFS and may allow for potential therapeutic targeting.

3D modeling and printing for complex biventricular repair of double outlet right ventricle.

Background: Double outlet right ventricle (DORV) describes a group of congenital heart defects where pulmonary artery and aorta originate completely or predominantly from the right ventricle. The individual anatomy of DORV patients varies widely with multiple subtypes classified. Although the majority of morphologies is suitable for biventricular repair (BVR), complex DORV anatomy can render univentricular palliation (UVP) the only option. Thus, patient-specific decision-making is critical for optimal surgical treatment planning. The evolution of image processing and rapid prototyping techniques facilitate the generation of detailed virtual and physical 3D models of the patient-specific anatomy which can support this important decision process within the Heart Team. Materilas and methods: The individual cardiovascular anatomy of nine patients with complex DORV, in whom surgical decision-making was not straightforward, was reconstructed from either computed tomography or magnetic resonance imaging data. 3D reconstructions were used to characterize the morphologic details of DORV, such as size and location of the ventricular septal defect (VSD), atrioventricular valve size, ventricular volumes, relationship between the great arteries and their spatial relation to the VSD, outflow tract obstructions, coronary artery anatomy, etc. Additionally, physical models were generated. Virtual and physical models were used in the preoperative assessment to determine surgical treatment strategy, either BVR vs. UVP. Results: Median age at operation was 13.2 months (IQR: 9.6-24.0). The DORV transposition subtype was present in six patients, three patients had a DORV-ventricular septal defect subtype. Patient-specific reconstruction was feasible for all patients despite heterogeneous image quality. Complex BVR was feasible in 5/9 patients (55%). Reasons for unsuitability for BVR were AV valve chordae interfering with potential intraventricular baffle creation, ventricular hypoplasia and non-committed VSD morphology. Evaluation in particular of qualitative data from 3D models was considered to support comprehension of complex anatomy. Conclusion: Image-based 3D reconstruction of patient-specific intracardiac anatomy provides valuable additional information supporting decision-making processes and surgical planning in complex cardiac malformations. Further prospective studies are required to fully appreciate the benefits of 3D technology.

Myocardial extracellular volume is a non-invasive tissue marker of heart failure in patients with transposition of the great arteries and systemic right ventricle.

Background: Focal myocardial fibrosis in the systemic right ventricle (RV) is related to ventricular dysfunction and adverse outcome in patients with d-transposition of the great arteries (dTGA) post atrial redirection and those with congenitally corrected TGA (ccTGA). The role of diffuse fibrotic lesions in these conditions remains poorly understood. Our study aimed to investigate diffuse myocardial fibrosis by measuring extracellular volume (ECV) with cardiovascular magnetic resonance (CMR) and to explore correlations between ECV and clinical as well as functional markers of heart failure in patients with TGA and systemic RV. Methods: We prospectively included dTGA and ccTGA patients aged ≥14 years and compared them to healthy controls. Standardized CMR included modified Look-Locker Inversion recovery T1 mapping to quantify diffuse myocardial fibrosis in the systemic RV and the subpulmonary left ventricle (LV). The centerline of RV and LV myocardium was marked with a line of interest tool to determine native and post-contrast T1 for quantification of ECV. Results: In total, 13 patients (dTGA: n = 8, ccTGA: n = 5) with a median age of 30.3 years were enrolled. LV ECV was higher in patients than in controls [34% (30%-41%) vs. 26% (23%-27%), p < 0.001], with values increased above the upper limit of normal in 10/13 patients (77%). RV ECV tended to be higher in patients than in controls, albeit without statistical significance [29% (27%-32%) vs. 28% (26%-29%), p = 0.316]. Patients with elevated LV ECV had lower LV ejection fraction than those with normal ECV (52 ± 5% vs. 65 ± 4%, p = 0.007). Correlations with clinical parameters were not observed. LV ECV was significantly higher than RV ECV (p = 0.016) in the patient group. Conclusions: In this study, LV ECV was significantly increased in TGA patients compared to controls, and was associated with LV dysfunction. Our data suggest that ECV may serve as a non-invasive tissue marker of heart failure in TGA with systemic RV. Further research is necessary to evaluate the prognostic implications and the potential role of ECV in monitoring disease progression and guiding therapy, aiming to maintain LV function or train the LV for subaortic location in TGA patients from infancy to adulthood.

Serum dihydrotestosterone levels are associated with adverse myocardial remodeling in patients with severe aortic valve stenosis before and after aortic valve replacement.

Animal studies show a pivotal role of dihydrotestosterone (DHT) in pressure overload-induced myocardial hypertrophy and dysfunction. The aim of our study was to evaluate the role of DHT levels and myocardial hypertrophy and myocardial protein expression in patients with severe aortic valve stenosis (AS). Forty-three patients [median age 68 (41-80) yr] with severe AS and indication for surgical aortic valve replacement (SAVR) were prospectively enrolled. Cardiac magnetic resonance imaging including analysis of left ventricular muscle mass (LVM), fibrosis and function, and laboratory tests including serum DHT levels were performed before and after SAVR. During SAVR, left ventricular (LV) biopsies were performed for proteomic profiling. Serum DHT levels correlated positively with indexed LVM (LVMi, R = 0.64, P = 0.0001) and fibrosis (R = 0.49, P = 0.0065) and inversely with LV function (R = -0.42, P = 0.005) in patients with severe AS. DHT levels were associated with higher abundance of the hypertrophy (moesin, R = 0.52, P = 0.0083)- and fibrosis (vimentin, R = 0.41, P = 0.039)-associated proteins from LV myocardial biopsies. Higher serum DHT levels preoperatively were associated with reduced LV function (ejection fraction, R = -0.34, P = 0.035; circulatory efficiency, R = -0.46, P = 0.012; and global longitudinal strain, R = 0.49, P = 0.01) and increased fibrosis (R = 0.55, P = 0.0022) after SAVR. Serum DHT levels were associated with adverse myocardial remodeling and higher abundance in hypertrophy- and fibrosis-associated proteins in patients with severe AS. DHT may be a target to prevent or attenuate adverse myocardial remodeling in patients with pressure overload due to AS.NEW & NOTEWORTHY Serum dihydrotestosterone (DHT) levels correlated positively with the degree of hypertrophy, fibrosis, and dysfunction from cardiac magnetic resonance imaging in female and male patients with aortic valve stenosis. Left ventricular proteome profiling had been performed in this patient cohort and an association between serum DHT levels and the abundance of the hypertrophy-associated protein moesin and the fibrosis-associated protein vimentin was found.

Effect of transcatheter edge-to-edge repair device position on diastolic hemodynamic parameters: An echocardiography-based simulation study.

Background: Transcatheter edge-to-edge repair (TEER) has developed from innovative technology to an established treatment strategy of mitral regurgitation (MR). The risk of iatrogenic mitral stenosis after TEER is, however, a critical factor in the conflict of interest between maximal reduction of MR and minimal impairment of left ventricular filling. We aim to investigate systematically the impact of device position on the post treatment hemodynamic outcome by involving the patient-specific segmentation of the diseased mitral valve. Materials and methods: Transesophageal echocardiographic image data of ten patients with severe MR (age: 57 ± 8 years, 20% female) were segmented and virtually treated with TEER at three positions by using a position based dynamics approach. Pre- and post-interventional patient geometries were preprocessed for computational fluid dynamics (CFD) and simulated at peak-diastole with patient-specific blood flow boundary conditions. Simulations were performed with boundary conditions mimicking rest and stress. The simulation results were compared with clinical data acquired for a cohort of 21 symptomatic MR patients (age: 79 ± 6 years, 43% female) treated with TEER. Results: Virtual TEER reduces the mitral valve area (MVA) from 7.5 ± 1.6 to 2.6 ± 0.6 cm2. Central device positioning resulted in a 14% smaller MVA than eccentric device positions. Furthermore, residual MVA is better predictable for central than for eccentric device positions (R 2 = 0.81 vs. R 2 = 0.49). The MVA reduction led to significantly higher maximal diastolic velocities (pre: 0.9 ± 0.2 m/s, post: 2.0 ± 0.5 m/s) and pressure gradients (pre: 1.5 ± 0.6 mmHg, post: 16.3 ± 9 mmHg) in spite of a mean flow rate reduction by 23% due to reduced MR after the treatment. On average, velocities were 12% and pressure gradients were 25% higher with devices in central compared to lateral or medial positions. Conclusion: Virtual TEER treatment combined with CFD is a promising tool for predicting individual morphometric and hemodynamic outcomes. Such a tool can potentially be used to support clinical decision making, procedure planning, and risk estimation to prevent post-procedural iatrogenic mitral stenosis.

Virtual treatment planning in three patients with univentricular physiology using computational fluid dynamics-Pitfalls and strategies.

Background: Uneven hepatic venous blood flow distribution (HFD) to the pulmonary arteries is hypothesized to be responsible for the development of intrapulmonary arteriovenous malformations (PAVM) in patients with univentricular physiology. Thus, achieving uniform distribution of hepatic blood flow is considered favorable. However, no established method for the prediction of the post-interventional hemodynamics currently exists. Computational fluid dynamics (CFD) offers the possibility to quantify HFD in patient-specific anatomies before and after virtual treatment. In this study, we evaluated the potential benefit of CFD-assisted treatment planning. Materials and methods: Three patients with total cavopulmonary connection (TCPC) and PAVM underwent cardiovascular magnetic resonance imaging (CMR) and computed tomography imaging (CT). Based on this imaging data, the patient-specific anatomy was reconstructed. These patients were considered for surgery or catheter-based intervention aiming at hepatic blood flow re-routing. CFD simulations were then performed for the untreated state as well as for different surgical and interventional treatment options. These treatment options were applied as suggested by treating cardiologists and congenital heart surgeons with longstanding experience in interventional and surgical treatment of patients with univentricular physiology. HFD was quantified for all simulations to identify the most viable treatment decision regarding redistribution of hepatic blood flow. Results: For all three patients, the complex TCPC anatomy could be reconstructed. However, due to the presence of metallic stent implants, hybrid models generated from CT as well as CMR data were required. Numerical simulation of pre-interventional HFD agreed well with angiographic assessment and physiologic considerations. One treatment option resulting in improvement of HFD was identified for each patient. In one patient follow-up data after treatment was available. Here, the virtual treatment simulation and the CMR flow measurements differed by 15%. Conclusion: The combination of modern computational methods as well as imaging methods for assessment of patient-specific anatomy and flow might allow to optimize patient-specific therapy planning in patients with pronounced hepatic flow mismatch and PAVM. In this study, we demonstrate that these methods can also be applied in patients with complex univentricular physiology and extensive prior interventions. However, in those cases, hybrid approaches utilizing information of different image modalities may be required.

CT-Based Analysis of Left Ventricular Hemodynamics Using Statistical Shape Modeling and Computational Fluid Dynamics.

Background: Cardiac computed tomography (CCT) based computational fluid dynamics (CFD) allows to assess intracardiac flow features, which are hypothesized as an early predictor for heart diseases and may support treatment decisions. However, the understanding of intracardiac flow is challenging due to high variability in heart shapes and contractility. Using statistical shape modeling (SSM) in combination with CFD facilitates an intracardiac flow analysis. The aim of this study is to prove the usability of a new approach to describe various cohorts. Materials and Methods: CCT data of 125 patients (mean age: 60.6 ± 10.0 years, 16.8% woman) were used to generate SSMs representing aneurysmatic and non-aneurysmatic left ventricles (LVs). Using SSMs, seven group-averaged LV shapes and contraction fields were generated: four representing patients with and without aneurysms and with mild or severe mitral regurgitation (MR), and three distinguishing aneurysmatic patients with true, intermediate aneurysms, and globally hypokinetic LVs. End-diastolic LV volumes of the groups varied between 258 and 347 ml, whereas ejection fractions varied between 21 and 26%. MR degrees varied from 1.0 to 2.5. Prescribed motion CFD was used to simulate intracardiac flow, which was analyzed regarding large-scale flow features, kinetic energy, washout, and pressure gradients. Results: SSMs of aneurysmatic and non-aneurysmatic LVs were generated. Differences in shapes and contractility were found in the first three shape modes. Ninety percent of the cumulative shape variance is described with approximately 30 modes. A comparison of hemodynamics between all groups found shape-, contractility- and MR-dependent differences. Disturbed blood washout in the apex region was found in the aneurysmatic cases. With increasing MR, the diastolic jet becomes less coherent, whereas energy dissipation increases by decreasing kinetic energy. The poorest blood washout was found for the globally hypokinetic group, whereas the weakest blood washout in the apex region was found for the true aneurysm group. Conclusion: The proposed CCT-based analysis of hemodynamics combining CFD with SSM seems promising to facilitate the analysis of intracardiac flow, thus increasing the value of CCT for diagnostic and treatment decisions. With further enhancement of the computational approach, the methodology has the potential to be embedded in clinical routine workflows and support clinicians.

Hemodynamic Changes During Physiological and Pharmacological Stress Testing in Patients With Heart Failure: A Systematic Review and Meta-Analysis.

Although disease etiologies differ, heart failure patients with preserved and reduced ejection fraction (HFpEF and HFrEF, respectively) both present with clinical symptoms when under stress and impaired exercise capacity. The extent to which the adaptation of heart rate (HR), stroke volume (SV), and cardiac output (CO) under stress conditions is altered can be quantified by stress testing in conjunction with imaging methods and may help to detect the diminishment in a patient's condition early. The aim of this meta-analysis was to quantify hemodynamic changes during physiological and pharmacological stress testing in patients with HF. A systematic literature search (PROSPERO 2020:CRD42020161212) in MEDLINE was conducted to assess hemodynamic changes under dynamic and pharmacological stress testing at different stress intensities in HFpEF and HFrEF patients. Pooled mean changes were estimated using a random effects model. Altogether, 140 study arms with 7,248 exercise tests were analyzed. High-intensity dynamic stress testing represented 73% of these data (70 study arms with 5,318 exercise tests), where: HR increased by 45.69 bpm (95% CI 44.51-46.88; I 2 = 98.4%), SV by 13.49 ml (95% CI 6.87-20.10; I 2 = 68.5%), and CO by 3.41 L/min (95% CI 2.86-3.95; I 2 = 86.3%). No significant differences between HFrEF and HFpEF groups were found. Despite the limited availability of comparative studies, these reference values can help to estimate the expected hemodynamic responses in patients with HF. No differences in chronotropic reactions, changes in SV, or CO were found between HFrEF and HFpEF. When compared to healthy individuals, exercise tolerance, as well as associated HR and CO changes under moderate-high dynamic stress, was substantially impaired in both HF groups. This may contribute to a better disease understanding, future study planning, and patient-specific predictive models. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/], identifier [CRD42020161212].

CT-Based Simulation of Left Ventricular Hemodynamics: A Pilot Study in Mitral Regurgitation and Left Ventricle Aneurysm Patients.

Background: Cardiac CT (CCT) is well suited for a detailed analysis of heart structures due to its high spatial resolution, but in contrast to MRI and echocardiography, CCT does not allow an assessment of intracardiac flow. Computational fluid dynamics (CFD) can complement this shortcoming. It enables the computation of hemodynamics at a high spatio-temporal resolution based on medical images. The aim of this proposed study is to establish a CCT-based CFD methodology for the analysis of left ventricle (LV) hemodynamics and to assess the usability of the computational framework for clinical practice. Materials and Methods: The methodology is demonstrated by means of four cases selected from a cohort of 125 multiphase CCT examinations of heart failure patients. These cases represent subcohorts of patients with and without LV aneurysm and with severe and no mitral regurgitation (MR). All selected LVs are dilated and characterized by a reduced ejection fraction (EF). End-diastolic and end-systolic image data was used to reconstruct LV geometries with 2D valves as well as the ventricular movement. The intraventricular hemodynamics were computed with a prescribed-motion CFD approach and evaluated in terms of large-scale flow patterns, energetic behavior, and intraventricular washout. Results: In the MR patients, a disrupted E-wave jet, a fragmentary diastolic vortex formation and an increased specific energy dissipation in systole are observed. In all cases, regions with an impaired washout are visible. The results furthermore indicate that considering several cycles might provide a more detailed view of the washout process. The pre-processing times and computational expenses are in reach of clinical feasibility. Conclusion: The proposed CCT-based CFD method allows to compute patient-specific intraventricular hemodynamics and thus complements the informative value of CCT. The method can be applied to any CCT data of common quality and represents a fair balance between model accuracy and overall expenses. With further model enhancements, the computational framework has the potential to be embedded in clinical routine workflows, to support clinical decision making and treatment planning.

Detection and analysis of cerebral aneurysms based on X-ray rotational angiography - the CADA 2020 challenge.

The Cerebral Aneurysm Detection and Analysis (CADA) challenge was organized to support the development and benchmarking of algorithms for detecting, analyzing, 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. The segmentation quality was measured using the Jaccard index and a combination of different surface distance measures. 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 CADA challenge. The U-Net-based detection solutions presented by the community show similar accuracy compared to experts (F2 score 0.92), with a small number of missed aneurysms with diameters smaller than 3.5 mm. In addition, the delineation of these structures, based on U-Net variations, is excellent, with a Jaccard score of 0.92. The rupture risk estimation methods achieved an F2 score of 0.71. The performance of the detection and segmentation solutions is equivalent to that of human experts. The best results are obtained in rupture risk estimation by combining different image-based, morphological, and computational fluid dynamic parameters using machine learning methods. Furthermore, we evaluated the best methods pipeline, from detecting and delineating the vessel dilations to estimating the risk of rupture. The chain of these methods achieves an F2-score of 0.70, which is comparable to applying the risk prediction to the ground-truth delineation (0.71).

Skin Sodium Accumulates in Psoriasis and Reflects Disease Severity.

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.