Ventricular-vascular interaction is central in the adaptation to cardiovascular disease. However, cardiomyopathy patients are predominantly monitored using cardiac biomarkers. The aim of this study is therefore to explore aortic function in dilated cardiomyopathy (DCM). Fourteen idiopathic DCM patients and 16 controls underwent cardiac magnetic resonance imaging, with aortic relative pressure derived using physics-based image processing and a virtual cohort utilized to assess the impact of cardiovascular properties on aortic behaviour. Subjects with reduced left ventricular systolic function had significantly reduced aortic relative pressure, increased aortic stiffness, and significantly delayed time-to-pressure peak duration. From the virtual cohort, aortic stiffness and aortic volumetric size were identified as key determinants of aortic relative pressure. As such, this study shows how advanced flow imaging and aortic hemodynamic evaluation could provide novel insights into the manifestation of DCM, with signs of both altered aortic structure and function derived in DCM using our proposed imaging protocol.

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.

In this work, we present an efficient methodology for multigrid tomographic image reconstruction from non-truncated projection data. By partitioning the reconstruction domain and adapting the forward and backward operators, an image can be reconstructed accurately within multiple domains of varying discretisation or regularisation. We demonstrate the efficacy of the multigrid reconstruction principle using simulated data for quantitative assessment and experimental measurements from a μ-CT scanner for a clinically relevant use case scenario. A major advantage of using multiple reconstruction grids is the possibility to drastically reduce the number of unknowns in the inverse problem, and thereby the associated computational cost. This cost reduction helps to enlarge the class of available algorithms in applications with strict limitations on computation time or resources, and it enables full system resolution reconstruction of subregions that would otherwise be infeasible for the full field of view. The numerical experiments, along with a brief error analysis, show that the expected artefacts from coarse discretisation outside the region of interest become noticeable only for large differences in discretisation between subregions.

Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, νWERP, utilizing the concept of virtual work-energy to accurately probe relative pressure through complex branching vasculature. Here, we present an extension of this approach for turbulent flows: νWERP-t. We present a theoretical method derivation based on flow covariance, quantifying the impact of flow fluctuations on relative pressure. νWERP-t is tested on a set of in-vitro stenotic flow phantoms with data acquired by 4D flow MRI with six-directional flow encoding, as well as on a patient-specific in-silico model of an acute aortic dissection. Over all tests νWERP-t shows improved accuracy over alternative energy-based approaches, with excellent recovery of estimated relative pressures. In particular, the use of a guaranteed divergence-free virtual field improves accuracy in cases where turbulent flows skew the apparent divergence of the acquired field. With the original νWERP allowing for assessment of relative pressure into previously inaccessible vasculatures, the extended νWERP-t further enlarges the method's clinical scope, underlining its potential as a novel tool for assessing relative pressure in-vivo.

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.

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.

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 degrees and 58 degrees 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.

Ultrasound elastography has shown potential for improved plaque risk stratification. However, no clear consensus exists on what output metric to use, or what imaging parameters would render optimal plaque differentiation. For this reason we developed a combined ex vivo and in vitro setup, in which the ability to differentiate phantom plaques of varying stiffness was evaluated as a function of plaque geometry, push location, imaging plane, and analysed wave speed metric. The results indicate that group velocity or phase velocity >= 1 kHz showed the highest ability to significantly differentiate plaques of different stiffness, successfully classifying a majority of the 24 analysed plaque geometries, respectively. The ability to differentiate plaques was also better in the longitudinal views than in the transverse view. Group velocity as well as phase velocities <1 kHz showed a systematic underestimation of plaque stiffness, stemming from the confined plaque geometries, however, despite this group velocity analysis showed lowest deviation in estimated plaque stiffness (0.1 m s(-1) compared to 0.2 m s(-1) for phase velocity analysis). SWE results were also invariant to SWE push location, albeit apparent differences in signal-to-noise ratio (SNR) and generated plaque particle velocity. With that, the study has reinforced the potential of SWE for successful plaque differentiation; however the results also highlight the importance of choosing optimal imaging settings and using an appropriate wave speed metric when attempting to differentiate different plaque groups.

Echocardiography is the most commonly used image modality in cardiology, assessing several aspects of cardiac viability. The importance of cardiac hemodynamics and 4D blood flow motion has recently been highlighted, however such assessment is still difficult using routine echo-imaging. Instead, combining imaging with computational fluid dynamics (CFD)-simulations has proven valuable, but only a few models have been applied clinically. In the following, patient-specific CFD-simulations from transthoracic dobutamin stress echocardiography have been used to analyze the left ventricular 4D blood flow in three subjects: two with normal and one with reduced left ventricular function. At each stress level, 4D-images were acquired using a GE Vivid E9 (4VD, 1.7MHz/3.3MHz) and velocity fields simulated using a presented pathway involving endocardial segmentation, valve position identification, and solution of the incompressible Navier-Stokes equation. Flow components defined as direct flow, delayed ejection flow, retained inflow, and residual volume were calculated by particle tracing using 4th-order Runge-Kutta integration. Additionally, systolic and diastolic average velocity fields were generated. Results indicated no major changes in average velocity fields for any of the subjects. For the two subjects with normal left ventricular function, increased direct flow, decreased delayed ejection flow, constant retained inflow, and a considerable drop in residual volume was seen at increasing stress. Contrary, for the subject with reduced left ventricular function, the delayed ejection flow increased whilst the retained inflow decreased at increasing stress levels. This feasibility study represents one of the first clinical applications of an echo-based patient-specific CFD-model at elevated stress levels, and highlights the potential of using echo-based models to capture highly transient flow events, as well as the ability of using simulation tools to study clinically complex phenomena. With larger patient studies planned for the future, and with the possibility of adding more anatomical features into the model framework, the current work demonstrates the potential of patient-specific CFD-models as a tool for quantifying 4D blood flow in the heart.

The combination of medical imaging with computational fluid dynamics (CFD) has enabled the study of 3D blood flow on a patient-specificlevel. However, with models based on gated high-resolution data, the study of transient flows, and any model implementation into routine cardiac care, is challenging. The present paper presents a novel pathway for patient-specific CFD modelling of the left ventricle (LV), using 4D transthoracic echocardiography (TTE) as input modality. To evaluate the clinical usability, two sub-studies were performed. First, a robustness evaluation was performed where repeated models with alternating input variables were generated for 6 subjects and changes in simulated output quantified. Second, a validation study was carried out where the pathway accuracy was evaluated against pulsed-wave Doppler (100 subjects), and 2D through-plane phase-contrast magnetic resonance imaging measurements over 7 intraventricular planes (6 subjects). The robustness evaluation indicated a model deviation of <12%, with highest regional and temporal deviations at apical segments and at peak systole, respectively. The validation study showed an error of < 11% (velocities < 10 cm/s) for all subjects, with no significant regional or temporal differences observed. With the patient-specific pathway shown to provide robust output with high accuracy, and with the pathway dependent only on 4DTTE, the method has a high potential to be used within future clinical studies on 3D intraventricular flowpatterns. To this, future model developments in the form of e.g. anatomically accurate LV valves may further enhance the clinical value of the simulations.