Many cardiovascular diseases lead to local increases in relative pressure, reflecting the higher costs of driving blood flow. The utility of this biomarker for stratifying the severity of disease has thus driven the development of methods to measure these relative pressures. While intravascular catheterisation remains the most direct measure, its invasiveness limits clinical application in many instances. Non-invasive Doppler ultrasound estimates have partially addressed this gap; however only provide relative pressure estimates for a range of constricted cardiovascular conditions. Here we introduce a non-invasive method that enables arbitrary interrogation of relative pressures throughout an imaged vascular structure, leveraging modern phase contrast magnetic resonance imaging, the virtual work-energy equations, and a virtual field to provide robust and accurate estimates. The versatility and accuracy of the method is verified in a set of complex patient-specific cardiovascular models, where relative pressures into previously inaccessible flow regions are assessed. The method is further validated within a cohort of congenital heart disease patients, providing a novel tool for probing relative pressures in-vivo.

Introduction: Atrial fibrillation (AF) is a widespread cardiac arrhythmia that commonly affects the left atrium (LA), causing it to quiver instead of contracting effectively. This behavior is triggered by abnormal electrical impulses at a specific site in the atrial wall. Catheter ablation (CA) treatment consists of isolating this driver site by burning the surrounding tissue to restore sinus rhythm (SR). However, evidence suggests that CA can concur to the formation of blood clots by promoting coagulation near the heat source and in regions with low flow velocity and blood stagnation. Methods: A patient-specific modeling workflow was created and applied to simulate thermal-fluid dynamics in two patients pre- and post-CA. Each model was personalized based on pre- and post-CA imaging datasets. The wall motion and anatomy were derived from SSFP Cine MRI data, while the trans-valvular flow was based on Doppler ultrasound data. The temperature distribution in the blood was modeled using a modified Pennes bioheat equation implemented in a finite-element based Navier-Stokes solver. Blood particles were also classified based on their residence time in the LA using a particle-tracking algorithm. Results: SR simulations showed multiple short-lived vortices with an average blood velocity of 0.2-0.22 m/s. In contrast, AF patients presented a slower vortex and stagnant flow in the LA appendage, with the average blood velocity reduced to 0.08–0.14 m/s. Restoration of SR also increased the blood kinetic energy and the viscous dissipation due to the presence of multiple vortices. Particle tracking showed a dramatic decrease in the percentage of blood remaining in the LA for longer than one cycle after CA (65.9 vs. 43.3% in patient A and 62.2 vs. 54.8% in patient B). Maximum temperatures of 76° and 58°C were observed when CA was performed near the appendage and in a pulmonary vein, respectively. Conclusion: This computational study presents novel models to elucidate relations between catheter temperature, patient-specific atrial anatomy and blood velocity, and predict how they change from SR to AF. The models can quantify blood flow in critical regions, including residence times and temperature distribution for different catheter positions, providing a basis for quantifying stroke risks.

Fatal cerebrovascular events are often caused by rupture of atherosclerotic plaques. However, rupture-prone plaques are often distinguished by their internal composition rather than degree of luminal narrowing, and conventional imaging techniques might thus fail to detect such culprit lesions. In this feasibility study, we investigate the potential of ultrasound shear wave elastography (SWE) to detect vulnerable carotid plaques, evaluating group velocity and frequency-dependent phase velocities as novel biomarkers for plaque vulnerability. In total, 27 carotid plaques from 20 patients were scanned by ultrasound SWE and magnetic resonance imaging (MRI). SWE output was quantified as group velocity and frequency-dependent phase velocities, respectively, with results correlated to intraplaque constituents identified by MRI. Overall, vulnerable lesions graded as American Heart Association (AHA) type VI showed significantly higher group and phase velocity compared to any other AHA type. A selection of correlations with intraplaque components could also be identified with group and phase velocity (lipid-rich necrotic core content, fibrous cap structure, intraplaque hemorrhage), complementing the clinical lesion classification. In conclusion, we demonstrate the ability to detect vulnerable carotid plaques using combined SWE, with group velocity and frequency-dependent phase velocity providing potentially complementary information on plaque characteristics. With such, the method represents a promising non-invasive approach for refined atherosclerotic risk prediction.

Intracardiac blood flow is driven by differences in relative pressure, and assessing these is critical in understanding cardiac disease. Non-invasive image-based methods exist to assess relative pressure, however, the complex flow and dynamically moving fluid domain of the intracardiac space limits assessment. Recently, we proposed a method, νWERP, utilizing an auxiliary virtual field to probe relative pressure through complex, and previously inaccessible flow domains. Here we present an extension of νWERP for intracardiac flow assessments, solving the virtual field over sub-domains to effectively handle the dynamically shifting flow domain. The extended νWERP is validated in an in-silico benchmark problem, as well as in a patient-specific simulation model of the left heart, proving accurate over ranges of realistic image resolutions and noise levels, as well as superior to alternative approaches. Lastly, the extended νWERP is applied on clinically acquired 4D Flow MRI data, exhibiting realistic ventricular relative pressure patterns, as well as indicating signs of diastolic dysfunction in an exemplifying patient case. Summarized, the extended νWERP approach represents a directly applicable implementation for intracardiac flow assessments.

Left ventricular outflow tract (LVOT) obstruction is a relatively common consequence of transcatheter mitral valve replacement (TMVR). Although LVOT obstruction is associated with heart failure and adverse remodelling, its effects upon left ventricular hemodynamics remain poorly characterised. This study uses validated computational models to identify the LVOT obstruction degree that causes significant changes in ventricular hemodynamics after TMVR. Seven TMVR patients underwent personalised flow simulations based on pre-procedural imaging data. Different virtual valve configurations were simulated in each case, for a total of 32 simulations, and the resulting obstruction degree was correlated with pressure gradients and flow residence times. These simulations identified a threshold LVOT obstruction degree of 35%, beyond which significant deterioration of systolic function was observed. The mean increase from baseline (pre-TMVR) in the peak systolic pressure gradient rose from 5.7% to 30.1% above this threshold value. The average blood volume staying inside the ventricle for more than two cycles also increased from 4.4% to 57.5% for obstruction degrees above 35%, while the flow entering and leaving the ventricle within one cycle decreased by 13.9%. These results demonstrate the unique ability of modelling to predict the hemodynamic consequences of TMVR and to assist in the clinical decision-making process.