Noninvasive Left Ventricle Pressure-Volume Loop Determination Method with Cardiac Magnetic Resonance Imaging and Carotid Tonometry Using a Physics-Informed Approach.

Left ventricular (LV) pressure-volume loop (PV-loop) is an important tool to quantify intrinsic left ventricular properties and ventricular-arterial coupling. A significant drawback of conventional PV-loop assessment is the need of invasive measurements which limits its widespread application. To tackle this issue, we developed a PV-loop determination method by using non-invasive measurements from arterial tonometry and cardiac magnetic resonance imaging. A physics-based optimization strategy was designed that adaptively identifies the optimal parameters to construct the PV-loop. We conducted comparative analysis in a convenience sample (N = 77) with heart failure (HF) (N = 23) patients and a control (N = 54) group to evaluate the sensitivity our PV-loop estimation algorithm. Significant and coherent differences between cohorts for the parameters derived using the PV-loop were observed. Our method captures the significant elevation of LV end diastolic pressure (p<0.001), and the decrease of the ventricular efficiency (p<0.0001) of the HF patients compared to the Control group. This method further captures the mechanistic changes of the LV by highlighting the significant differences of the smaller stroke work (p<0.0001), mean external power (p<0.05), and contractility (p<0.001) between these groups. The LV performance metrics align well with the previous clinical PV-loop observations of HF patients and our results demonstrate that the proposed PV-loop reconstruction method can be used to assess the ventricular functional changes associated with HF. Using this noninvasive method may significantly impact and facilitate the diagnosis and therapeutic management of HF.

Framework Development for Patient-Specific Compliant Aortic Dissection Phantom Model Fabrication: Magnetic Resonance Imaging Validation and Deep-Learning Segmentation.

Type B aortic dissection is a life-threatening medical emergency that can result in rupture of the aorta. Due to the complexity of patient-specific characteristics, only limited information on flow patterns in dissected aortas has been reported in the literature. Leveraging the medical imaging data for patient-specific in vitro modeling can complement the hemodynamic understanding of aortic dissections. We propose a new approach toward fully automated patient-specific type B aortic dissection model fabrication. Our framework uses a novel deep-learning-based segmentation for negative mold manufacturing. Deep-learning architectures were trained on a dataset of 15 unique computed tomography scans of dissection subjects and were blind-tested on 4 sets of scans, which were targeted for fabrication. Following segmentation, the three-dimensional models were created and printed using polyvinyl alcohol. These models were then coated with latex to create compliant patient-specific phantom models. The magnetic resonance imaging (MRI) structural images demonstrate the ability of the introduced manufacturing technique for creating intimal septum walls and tears based on patient-specific anatomy. The in vitro experiments show the fabricated phantoms generate physiologically-accurate pressure results. The deep-learning models also show high similarity metrics between manual segmentation and autosegmentation where Dice metric is as high as 0.86. The proposed deep-learning-based negative mold manufacturing method facilitates an inexpensive, reproducible, and physiologically-accurate patient-specific phantom model fabrication suitable for aortic dissection flow modeling.

Thermal and Postural Effects on Fluid Mixing and Irrigation Patterns for Intraventricular Hemorrhage Treatment.

Intraventricular hemorrhage is characterized by blood leaking into the cerebral ventricles and mixing with cerebrospinal fluid. A standard treatment method involves inserting a passive drainage catheter, known as an external ventricular drain (EVD), into the ventricle. EVDs have common adverse complications, including the occlusion of the catheter, that may lead to permanent neural damage or even mortality. In order to prevent such complications, a novel dual-lumen catheter (IRRAflow®) utilizing an active fluid exchange mechanism has been recently developed. However, the fluid dynamics of the exchange system have not been investigated. In this study, convective flow in a three-dimensional cerebral lateral ventricle with an inserted catheter is evaluated using an in-house lattice-Boltzmann-based fluid-solid interaction solver. Different treatment conditions are simulated, including injection temperature and patient position. Thermal and gravitational effects on medication distribution are studied using a dye simulator based on a recently-introduced (pseudo)spectral convection-diffusion equation solver. The effects of injection temperature and patient position on catheter performance are presented and discussed in terms of hematoma irrigation, vortical structures, mixing, and medication volume distribution. Results suggest that cold-temperature injections can increase catheter efficacy in terms of dye distribution and irrigation potential, both of which can be further guided by patient positioning.

The Rheology of the Carotid Sinus: A Path Toward Bioinspired Intervention.

The association between blood viscosity and pathological conditions involving a number of organ systems is well known. However, how the body measures and maintains appropriate blood viscosity is not well-described. The literature endorsing the function of the carotid sinus as a site of baroreception can be traced back to some of the earliest descriptions of digital pressure on the neck producing a drop in blood delivery to the brain. For the last 30 years, improved computational fluid dynamic (CFD) simulations of blood flow within the carotid sinus have demonstrated a more nuanced understanding of the changes in the region as it relates to changes in conventional metrics of cardiovascular function, including blood pressure. We suggest that the unique flow patterns within the carotid sinus may make it an ideal site to transduce flow data that can, in turn, enable real-time measurement of blood viscosity. The recent characterization of the PIEZO receptor family in the sinus vessel wall may provide a biological basis for this characterization. When coupled with other biomarkers of cardiovascular performance and descriptions of the blood rheology unique to the sinus region, this represents a novel venue for bioinspired design that may enable end-users to manipulate and optimize blood flow.

Numerical investigation of the effects of blood rheology and wall elasticity in abdominal aortic aneurysm under pulsatile flow conditions.

BACKGROUND: Previous studies on aneurysm modeling have focused on the blood rheology and vessel elasticity separately. The combined effects of blood shear thinning properties and wall elasticity need to be revealed. OBJECTIVE: To provide insights on how pulsatile hemodynamics vary with blood rheology and vessel elasticity for a developed abdominal aortic aneurysm (AAA). METHOD: An Arbitrary Lagrangian-Eulerian fluid-solid interaction method is adopted with the Newtonian and the shear thinning Carreau constitutive models for the fluid with the linearly elastic and the hyperelastic Yeoh models for the vessel. Finite element based numerical solver is used to simulate the blood flow in the AAA. RESULTS: Newtonian model overestimates the velocity values compared to the Carreau model and the difference in the velocity field increases as the shear rate decreases at the instances of the cardiac cycle. The rigid walled simulations display higher deviations in the velocity and wall shear stress with the fluid rheology. The risk indicators show that Newtonian assumption combined with the linearly elastic model may overlook degeneration risk of arterial tissue. CONCLUSIONS: Newtonian assumption for the blood as well as modelling the arterial wall as linearly elastic lead to significant differences in oscillatory hemodynamic properties with respect to the use of Carreau fluid together with hyperelastic vessel model, even in large vessel aneurysms.