Hemodynamic Modeling of Biological Aortic Valve Replacement Using Preoperative Data Only

Objectives: Prediction of aortic hemodynamics after aortic valve replacement (AVR) could help optimize treatment planning and improve outcomes. This study aims to demonstrate an approach to predict postoperative maximum velocity, maximum pressure gradient, secondary flow degree (SFD), and normalized flow displacement (NFD) in patients receiving biological AVR. Methods: Virtual AVR was performed for 10 patients, who received actual AVR with a biological prosthesis. The virtual AVRs used only preoperative anatomical and 4D flow MRI data. Subsequently, computational fluid dynamics (CFD) simulations were performed and the abovementioned hemodynamic parameters compared between postoperative 4D flow MRI data and CFD results. Results: For maximum velocities and pressure gradients, postoperative 4D flow MRI data and CFD results were strongly correlated (R 2 = 0.75 and R-2 = 0.81) with low root mean square error (0.21 m/s and 3.8 mmHg). SFD and NFD were moderately and weakly correlated at R 2 = 0.44 and R 2 = 0.20, respectively. Flow visualization through streamlines indicates good qualitative agreement between 4D flow MRI data and CFD results in most cases. Conclusion: The approach presented here seems suitable to estimate postoperative maximum velocity and pressure gradient in patients receiving biological AVR, using only preoperative MRI data. The workflow can be performed in a reasonable time frame and offers a method to estimate postoperative valve prosthesis performance and to identify patients at risk of patient-prosthesis mismatch preoperatively. Novel parameters, such as SFD and NFD, appear to be more sensitive, and estimation seems harder. Further workflow optimization and validation of results seems warranted

The Effects of Intervention on Heart Power in Aortic Coarctation

Background In aortic coarctation, current guidelines recommend reducing pressure gradients that exceed given thresholds. From a physiological standpoint this should ideally improve the energy expenditure of the heart and thus prevent long term organ damage. Objectives The aim was to assess the effects of interventional treatment on external and internal heart power (EHP, IHP) in patients with aortic coarctation and to explore the correlation of these parameters to pressure gradients obtained from heart catheterization. Methods In a collective of 52 patients with aortic coarctation 25 patients received stenting and/or balloon angioplasty, and 20 patients underwent MRI before and after an interventional treatment procedure. EHP and IHP were computed based on catheterization and MRI measurements. Along with the power efficiency these were combined in a cardiac energy profile. Results By intervention, the catheter gradient was significantly reduced from 21.8±9.4 to 6.2±6.1mmHg (p<0.001). IHP was significantly reduced after intervention, from 8.03±5.2 to 4.37±2.13W (p < 0.001). EHP was 1.1±0.3 W before and 1.0±0.3W after intervention, p = 0.044. In patients initially presenting with IHP above 5W intervention resulted in a significant reduction in IHP from 10.99±4.74 W to 4.94±2.45W (p<0.001), and a subsequent increase in power efficiency from 14 to 26% (p = 0.005). No significant changes in IHP, EHP or power efficiency were observed in patients initially presenting with IHP < 5W. Conclusion It was demonstrated that interventional treatment of coarctation resulted in a decrease in IHP. Pressure gradients, as the most widespread clinical parameters in coarctation, did not show any correlation to changes in EHP or IHP. This raises the question of whether they should be the main focus in coarctation interventions. Only patients with high IHP of above 5W showed improvement in IHP and power efficiency after the treatment procedure. Trial Registration clinicaltrials.gov NCT0259194

Link to complete results of study presented at ESAO 2023

Once published, the complete results of the study presented at ESAO 2023 as "Hemodynamic Rupture Risk Parameters for Intracranial Aneurysms and Uncertainty" (Hellmeier F) will be linked to here.</p

Numerical investigation of the impact of branching vessel boundary conditions on aortic hemodynamics

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)

Reconstructed surfaces and measured valve velocities

The reconstructed surfaces and measured valve velocities of the healthy volunteer belonging to the following publication:L. Obermeier, J. Korte, K. Vellguth, F. Barbieri, F. Hellmeier, P. Berg, and L. Goubergrits, Inter-model and inter-modality analysis of left ventricular hemodynamics: Comparative study of two CFD approaches based on echocardiography and magnetic resonance imaging, GAMM-Mitteilungen. (2023), e202370004. https://doi.org/10.1002/gamm.202370004The dataset contains the geometries (as STL) of:the left ventricle, left atrium, aorta and both valves in end-diastolic statethe left ventricle as watertight surface mesh over the cardiac cycleFurthermore, the measured valve velocities are included.Data for both imaging modalities (transthoracic echocardiography, magnetic resonance imaging) are included.For further questions contact [email protected]</p

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): uncertainty quantification of geometric rupture risk parameters

Abstract Background Geometric parameters have been proposed for prediction of cerebral aneurysm rupture risk. Predicting the rupture risk for incidentally detected unruptured aneurysms could help clinicians in their treatment decision. However, assessment of geometric parameters depends on several factors, including the spatial resolution of the imaging modality used and the chosen reconstruction procedure. The aim of this study was to investigate the uncertainty of a variety of previously proposed geometric parameters for rupture risk assessment, caused by variability of reconstruction procedures. Materials 26 research groups provided segmentations and surface reconstructions of five cerebral aneurysms as part of the Multiple Aneurysms AnaTomy CHallenge (MATCH) 2018. 40 dimensional and non-dimensional geometric parameters, describing aneurysm size, neck size, and irregularity of aneurysm shape, were computed. The medians as well as the absolute and relative uncertainties of the parameters were calculated. Additionally, linear regression analysis was performed on the absolute uncertainties and the median parameter values. Results A large variability of relative uncertainties in the range between 3.9 and 179.8% was found. Linear regression analysis indicates that some parameters capture similar geometric aspects. The lowest uncertainties  80% were found for some curvature parameters. Conclusions Uncertainty analysis is essential on the road to clinical translation and use of rupture risk prediction models. Uncertainty quantification of geometric rupture risk parameters provided by this study may help support development of future rupture risk prediction models

Beyond Pressure Gradients: The Effects of Intervention on Heart Power in Aortic Coarctation

<div><p>Background</p><p>In aortic coarctation, current guidelines recommend reducing pressure gradients that exceed given thresholds. From a physiological standpoint this should ideally improve the energy expenditure of the heart and thus prevent long term organ damage.</p><p>Objectives</p><p>The aim was to assess the effects of interventional treatment on external and internal heart power (EHP, IHP) in patients with aortic coarctation and to explore the correlation of these parameters to pressure gradients obtained from heart catheterization.</p><p>Methods</p><p>In a collective of 52 patients with aortic coarctation 25 patients received stenting and/or balloon angioplasty, and 20 patients underwent MRI before and after an interventional treatment procedure. EHP and IHP were computed based on catheterization and MRI measurements. Along with the power efficiency these were combined in a cardiac energy profile.</p><p>Results</p><p>By intervention, the catheter gradient was significantly reduced from 21.8±9.4 to 6.2±6.1mmHg (p<0.001). IHP was significantly reduced after intervention, from 8.03±5.2 to 4.37±2.13W (p < 0.001). EHP was 1.1±0.3 W before and 1.0±0.3W after intervention, p = 0.044. In patients initially presenting with IHP above 5W intervention resulted in a significant reduction in IHP from 10.99±4.74 W to 4.94±2.45W (p<0.001), and a subsequent increase in power efficiency from 14 to 26% (p = 0.005). No significant changes in IHP, EHP or power efficiency were observed in patients initially presenting with IHP < 5W.</p><p>Conclusion</p><p>It was demonstrated that interventional treatment of coarctation resulted in a decrease in IHP. Pressure gradients, as the most widespread clinical parameters in coarctation, did not show any correlation to changes in EHP or IHP. This raises the question of whether they should be the main focus in coarctation interventions. Only patients with high IHP of above 5W showed improvement in IHP and power efficiency after the treatment procedure.</p><p>Trial Registration</p><p>clinicaltrials.gov <a href="https://clinicaltrials.gov/ct2/show/NCT02591940" target="_blank">NCT02591940</a></p></div

Study flow diagram.

<p>Flow of participants through the study.</p

Main results.

<p>(a) Internal heart power (IHP) before and after treatment divided into groups according to the initial IHP above and below 5 W (b) The change in IHP with treatment plotted against the change of catheter-measured pressure gradients in each patient (the start-point of each vector represents the state before treatment, whereas the end-point represents the state after treatment) (c) Power efficiency before and after treatment grouped according to the initial IHP. * statistically significant differences.</p