Session Q02: Focus Session: The Fluid Dynamics of Medical Imaging I

Image-based computational modeling of right ventricular flow dynamics in congenital heart disease with 4D flow validation

The evaluation of intracardiac blood flow dynamics is a powerful approach to improve the understanding and treatment of cardiovascular disease. Most adult studies today have focused on the left ventricle (LV), with important results of clinical significance. In contrast, investigation of the right ventricle (RV) is especially motivated by congenital heart disease (CHD) in the pediatric population, where long-term complications of RV failure may develop despite early life-saving interventions. However, investigations of intracardiac flow patterns in the RV have been limited by the complex multidirectional wall motion and flow patterns. Thus, there is still a large knowledge gap in whether RV flow patterns could be used to monitor RV function in CHD patients. A detailed quantification of local flow phenomena may clarify flow pathophysiology and guide therapy planning. To this aim, we will present a complete pipeline from cardiac magnetic resonance (CMR) images to RV kinematic reconstruction and direct numerical simulation of the flow within the RV and pulmonary arteries. This work describes the components of this pipeline and provides results for the validation of the computational framework against conventional 4D flow CMR.   

Wall Shear Stress Estimation for 4D Flow MRI using Navier-Stokes Equation Correction

This study introduces a novel wall shear stress (WSS) estimation method for 4D flow MRI. The method improves the WSS accuracy by using the reconstructed pressure gradient and the flow-physics constraints to correct velocity gradient estimation. The method was tested on synthetic 4D flow data of analytical Womersley flow and flow in cerebral aneurysms and applied to in vivo 4D flow data acquired in cerebral aneurysms and aortas. The proposed method's performance was compared to the state-of-the-art method based on smooth-spline fitting of velocity profile and the WSS calculated from uncorrected velocity gradient. The proposed method improved the WSS accuracy by as much as 100% for the Womersley flow and reduced the underestimation of mean WSS by 39% to 50% for the synthetic aneurysmal flow. The predicted mean WSS from the in vivo aneurysmal data using the proposed method was 31% to 50% higher than the other methods. The predicted aortic WSS using the proposed method was 3 to 6 times higher than the other methods and was consistent with previous CFD studies and the results from recently developed methods. The proposed method improves the accuracy of WSS estimation from 4D flow MRI, which can help predict blood vessel remodeling and progression of cardiovascular diseases.   

Computed Tomography Cluster-informed Subject-Specific Assessment of Airway Resistance and Particle Deposition in Post-COVID-19 Lungs

Patients who recovered from the severe acute respiratory syndrome coronavirus (SARS-CoV-2 or COVID-19) may have long-term symptoms, given the diagnosis long COVID or post-acute sequelae of COVID-19 (PASC). In this study, we employed a cluster-informed (or guided) strategy that utilized contrastive learning and K-means to identify post-COVID-19 clusters from computed tomography (CT) images, and applied a CT imaging-based subject-specific multi-scale whole-lung computational fluid and particle dynamics (CFPD) model to investigate fluid dynamics within clusters for assessment of disease risk or therapeutic response. 140 post-COVID-19 subjects and 105 healthy controls were analyzed. The average time between COVID-19 diagnosis and CT acquisition was 113 days. Two clusters were identified, characterized by small airways disease (cluster 1, C1) and fibrotic-like lung patterns (cluster 2, C2), respectively. C1 had increased lobar resistance during tidal breathing due to airway narrowing, while C2 exhibited decreased lobar resistance due to airway-associated interstitial lungs. Compared to healthy controls, the whole-lung deposition in C2 during tidal breathing was reduced by 2% (p < 0.05) for particles ranging from 0.01 to 10.0 μm.   

Assessment of Intracranial Pressure via Ocular Hemodynamics Using Transocular Ultrasound Localization Microscopy

Knowledge of intracranial pressure (ICP) is essential for making decisions of surgical interventions for hydrocephalus patients. Direct invasive ICP measurements are risky. Hence, we explore noninvasive methods, where ICP is inferred from ocular hemodynamics. Ultrafast ultrasound localization microscopy (450 fps) is used for tracking microbubbles in the ocular vasculature of hydrocephalic infant pig models. Data processing involves SVD filtering to remove tissue signals, spatio-temporal band-pass filtering in the frequency domain for noise removal, and application of blind deconvolution to localize the bubble center. A Kalman filter along with several criteria are utilized for bubble tracking, which in turn define the location of blood vessels and the flow velocity in them. Data are acquired in 8 parallel horizontal planes to address potential effects of eye motion, and three of them, which contain similar vasculature, are used for analysis. Results of five pigs indicate that both retinal microcirculation and retrobulbar vascular flow decrease with increasing ICP. Accounting for pulse pressure, the correlation coefficients are 0.91 and 0.80, respectively. Such high correlation between ICP and quasi-3D imaging of ocular hemodynamics could have significant clinical implications.

    

Characterization of left ventricle vortex ring decay in the growing heart

During early diastolic filling, the left ventricle (LV) relaxes, creating a pressure imbalance which drives blood flow from left atrium (LA) into the LV. The incoming flow pushes open the mitral valve (MV) and rolls-off the MV leaflets to create a vortex ring (VR). Characteristics of the VR, its formation, and decay, provide essential information on LV diastolic filling. Interaction of the VR with the LV walls and viscous losses causes energy loss and decay. Previous research suggests that decay grows with increasing confinement ratio between the VR diameter and LV diameter (D_LV /D_MV). However, prior studies have not considered how VR decay varies with age-related LV growth, critical for understanding early heart development and potentially aiding clinically diagnosing heart failure. We quantified VR decay rate and other related vortex properties across six age groups: newborn (0-2 months old m/o; n=8), infant (3-11 m/o; n=6), toddler (1–4 years old y/o; n=5), child (5-10 y/o; n=5), adolescent (11-18 y/o; n=8), and young adulthood (19-40 y/o; n=13). We will analyze how VR decay scales across varying age, testing whether age-related growth of the heart requires an increase in VR decay rate as LV confinement remains near constant.

    

Color Doppler Echocardiography Velocity Reconstruction using Data Fusion with 4D Flow MRI

Color Flow Imaging (CFI), an imaging modality that measures intracardiac blood velocity, is useful for detecting ailments including congenital birth defects and valvular diseases. One limitation of the velocity measurements with CFI is that it only provides a single component of the underlying velocity vector field on the imaging plane. Recently introduced reconstruction methods such as Vector Flow Mapping (VFM) and Doppler Vector Reconstruction (DoVeR) can estimate the underlying vector field, however, both methods have inherent limitations. We introduce an improved Doppler-Velocity-Reconstruction (i-DoVeR) method, which uses data fusion of CFI and 4D flow MRI to reconstruct the volumetric field of the underlying velocity vectors. This library-based sparse representation method yields more physically consistent and hemodynamically accurate measurements to state-of-the-art reconstruction methods. We demonstrate the method with 9 healthy volunteers who underwent 4D flow MRI and CFI for resolving flow in the right ventricle. We compare our new method against the conventional intraventricular vector flow mapping (iVFM), DoVeR and 4D flow MRI data, and report on its accuracy and robustness. 

    

Evaluation of Left Ventricular Flow Propagation Velocity from Multi-Dimensional Cardiac Imaging

We introduce a new method to evaluate the left ventricular (LV) diastolic flow propagation from cardiac flow imaging. The proposed method estimates the local and instantaneous flow propagation velocity (V_prop) by fitting the first order wave equation to the velocity gradients with weighted least-squares. The proposed method was validated using the synthetic vortex ring flow data. The V_prop estimated from multi-dimensional data has about 50% less error than the V_prop from one-dimensional data. The method was first applied to the velocity fields acquired with two-dimensional phase-contrast magnetic resonance imaging (pc-MRI) and 4D flow MRI and provided the spatial distribution and the temporal evolution of V_prop during the LV diastole. During early diastole, the timing of peak flow propagation coincides with the peak intraventricular pressure difference. The flow propagation towards the apex is mainly located at the front of the inflow jet and downstream of the vortex ring formed near mitral valve tips. The proposed method provides a more comprehensive investigation and potentially improves the evaluation of LV diastolic function.