Biology subjects

Figueroa, C. A.

Publications and source records attributed to Figueroa, C. A..

9 recordsLinked to original sources

bioRxiv2026

A translational porcine model to assess the graded impact of hemorrhage and aortic occlusion on cardiovascular hemodynamics and renal perfusion

Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) is a lifesaving intervention used to manage non-compressible torso hemorrhage by temporarily occluding the aorta to minimize blood loss and preserve perfusion to vital organs. Partial REBOA (p-REBOA) has been proposed to mitigate ischemic injury associated with full-REBOA (f-REBOA). However, implementation of p-REBOA clinically has been challenging due to our limited understanding of the acute hemodynamics with p-REBOA particularly in relation to cardiac, carotid, and renal perfusion. In this study we developed and utilized a novel porcine model to continuously measure cardiac, carotid, renal and systemic hemodynamic responses to varying degrees of hemorrhagic shock and aortic occlusion. Yorkshire pigs (N=54) underwent instrumentation for continuous hemodynamic monitoring and hemorrhage was induced for 30 minutes to achieve 10%, 20%, or 30% blood volume loss (n=18/group), followed by randomized treatments of either no occlusion, p-REBOA, or f-REBOA occlusion strategies (n=6/group) for 30 minutes. After occlusion, shed blood was re-transfused over 15 minutes, and REBOA balloons were deflated and removed. This was followed by a 3-hour automated resuscitation and critical care period. Renal and carotid perfusion decreased progressively with hemorrhage severity. Interestingly, 30 minutes of f-REBOA resulted in significant ischemia-reperfusion injury where renal perfusion was profoundly suppressed to 40% of baseline renal flow. On the other hand, p-REBOA yielded superior renal perfusion, while maintaining cardiac function and carotid perfusion. p-REBOA also required less fluid and vasopressors. This translational pig model offers new opportunities to assess acute cardiovascular hemodynamics during interventions for the management of hemorrhagic shock.

physiology↗

bioRxiv2026

Calibration of a Closed-loop Model of Porcine Aortic Hemodynamics during Hemorrhage

Uncontrolled hemorrhage remains a leading cause of traumatic death, driven by rapid physiological deterioration that is often difficult to detect during the compensated phase. While large-animal models provide critical insights into these dynamics, they are resource-intensive, motivating the need for efficient computational frameworks that can mechanistically interpret cardiovascular responses. We developed and calibrated a closed-loop zero-dimensional (0D) lumped-parameter model (LPM) using hemodynamic data from 43 anesthetized swine subjected to controlled hemorrhage (10%, 20%, or 30% of total blood volume). The computational framework, incorporates a dynamic heart model with a custom time-varying elastance function, a multi-compartment aorta, and distal Windkessel models representing vascular beds. The model was calibrated at discrete time snapshots throughout the 30-minute hemorrhage protocol to reproduce group-averaged experimental waveforms for aortic flow, regional organ flows, and systemic pressures. The calibrated model successfully reproduced experimental hemodynamic targets and waveform morphology across all hemorrhage severities. Analysis of the calibrated parameters revealed distinct physiological mechanisms driving hemodynamic adaptation during hemorrhage: a preferential increase in renal resistance compared to carotid resistance, indicating flow redistribution to vital organs, and a progressive mobilization of venous unstressed volume to sustain cardiac filling. Furthermore, the model captured the distinct shift toward preload limitation state for 30% hemorrhage group. This study establishes a physiologically interpretable in-silico framework capable of predicting both global and regional hemodynamic responses to acute blood loss, providing a validated foundation for future applications in trauma care and resuscitation modeling.

physiology↗

bioRxiv2025

A Microstructurally-Motivated Framework to Study Autoregulation in the Coronary Circulation

Coronary autoregulation maintains relatively constant myocardial flow over a wide range of perfusion pressures through myogenic, shear-dependent, and metabolic control mechanisms. Understanding this phenomenon is challenging due to the coupled nature of these mechanisms and their heterogeneous effects throughout the coronary tree. In this study we developed a novel microstructurally-motivated model of coronary autoregulation based on constrained mixture theory, with anatomical and structural parameters calibrated through a homeostatic optimization framework. Autoregulation was simulated at three myocardial depths (subepicardium, midwall, and subendocardium), with the calibrated model accurately reproducing baseline hemodynamics and autoregulatory responses. For changes in epicardial pressure, our model reproduced experimentally measured subendocardium-to-subepicardium flow ratios (ENDO/EPI) and changes in vessel diameter, demonstrating its predictive capability. Furthermore, we extended Womersleys theory to simulate phasic coronary hemodynamics with a time-varying intramyocardial pressure. This microstructurally-motivated framework provides a mechanistic foundation for investigating coronary autoregulation and long-term vascular growth and remodeling in pathphysiological conditions. SummaryO_LICoronary autoregulation is defined as the capability of the coronary circulation to maintain the blood supply to the heart over a range of perfusion pressures. This phenomenon is facilitated through intrinsic mechanisms that control the vascular resistance by regulating the mechanical function of smooth muscle cells. Understanding the mechanisms involved in coronary autoregulation is one of the most fundamental questions in coronary physiology. C_LIO_LIThis paper presents a structurally-motivated coronary autoregulation model that uses a nonlinear continuum mechanics approach to account for the morphometry and vessel wall composition in two coronary trees in the subepicardial and subendocardial layers. C_LIO_LIThe model is calibrated against diverse experimental data from literature and is used to study heterogeneous autoregulatory response in the coronary trees. This model drastically differs from previous models, which relied on lumped parameter model formulations, and is suited to the study of long-term pathophysiological growth and remodeling phenomena in coronary vessels. C_LI

physiology↗

bioRxiv2025

Baseline State for Pulmonary Vasculature with Pulmonary Arterial Hypertension: Effect of Geometric Remodeling and Metabolic Shift

Pulmonary arterial hypertension (PAH) is a complex disease characterized by chronically elevated pulmonary arterial pressure, with early onset and progression linked to structural, metabolic and morphological changes in the pulmonary vasculature. Understanding the interplay between hemodynamics and arterial wall mechanics is essential to capture the pathology of the distal vasculature in PAH. This study aims to develop a data-driven framework that establishes a baseline state of PAH vasculature, incorporating key features of arterial wall constituents, geometry, and their interaction with PAH-specific hemodynamics. The model also explores changes in the metabolic energy costs of the arterial vasculature and hypothesize the most plausible metabolic costs based on PAH arterial wall energy consumption. Illustrative examples of symmetrically bifurcating arterial trees are used to establish baseline characteristics of PAH-affected pulmonary arteries. We establish the baseline state for PAH vasculature and compared it with healthy homeostatic vasculature in terms of arterial mechanics, morphometry, and pulsatile hemodynamics. This framework provides a representative computational model for advanced studies on PAH treatments and lays the groundwork for future pathophysiological modeling of the disease.

systems biology↗

bioRxiv2021

Cerebrovascular super-resolution 4D Flow MRI - using deep learning to non-invasively quantify velocity, flow, and relative pressure

The development of cerebrovascular disease is tightly coupled to changes in cerebrovascular hemodynamics, with altered flow and relative pressure indicative of the onset, development, and acute manifestation of pathology. Image-based monitoring of cerebrovascular hemodynamics is, however, complicated by the narrow and tortuous vasculature, where accurate output directly depends on sufficient spatial resolution. To address this, we present a method combining dedicated deep learning and state-of-the-art 4D Flow MRI to generate super-resolution full-field images with coupled quantification of relative pressure using a physics-driven image processing approach. The method is trained and validated in a patient-specific in-silico cohort, showing good accuracy in estimating velocity (relative error: 12.0 {+/-} 0.1%, mean absolute error (MAE): 0.07 {+/-} 0.06 m/s at peak velocity), flow (relative error: 6.6 {+/-} 4.7%, root mean square error (RMSE): 0.5 {+/-} 0.1 mL/s at peak flow), and with maintained recovery of relative pressure through the circle of Willis (relative error: 11.0 {+/-} 7.3%, RMSE: 0.3 {+/-} 0.2 mmHg). Furthermore, the method is applied to an in-vivo volunteer cohort, effectively generating data at <0.5mm resolution and showing potential in reducing low-resolution bias in relative pressure estimation. Our approach presents a promising method to non-invasively quantify cerebrovascular hemodynamics, applicable to dedicated clinical cohorts in the future.

bioengineering↗

bioRxiv2021

Multiscale model of the physiological control of myocardial perfusion to delineate putative metabolic feedback mechanisms

Coronary blood flow is tightly regulated to ensure that myocardial oxygen delivery meets local metabolic demand via the concurrent action of myogenic, neural, and metabolic mechanisms. While several competing hypotheses exist, the specific nature of the local metabolic mechanism(s) remains poorly defined. To gain insights into the viability of putative metabolic feedback mechanisms and into the coordinated action of parallel regulatory mechanisms, we applied a multi-scale modeling framework to analyze experimental data on coronary pressure, flow, and myocardial oxygen delivery in the porcine heart in vivo. The modeling framework integrates a previously established lumped-parameter model of myocardial perfusion used to account for transmural hemodynamic variations and a simple vessel mechanics model used to simulate the vascular tone in each of three myocardial layers. Vascular tone in the resistance vessel mechanics model is governed by input stimuli from the myogenic, metabolic, and autonomic control mechanisms. Seven competing formulations of the metabolic feedback mechanism are implemented in the modeling framework, and associated model simulations are compared to experimental data on coronary pressures and flows under a range of experimental conditions designed to interrogate the governing control mechanisms. Analysis identifies a maximally likely metabolic mechanism among the seven tested models, in which production of a metabolic signaling factor is proportional to MVO2 and delivery proportional to flow. Finally, the identified model is validated based on comparisons of simulations to data on the myocardial perfusion response to conscious exercise that were not used for model identification.

physiology↗

bioRxiv2021

A combined computational fluid dynamics and MRI Arterial Spin Labeling modeling strategy to quantify patient-specific cerebral hemodynamics in cerebrovascular occlusive disease

Cerebral hemodynamics in the presence of cerebrovascular occlusive disease (CVOD) are influenced by the anatomy of the intracranial arteries, the degree of stenosis, the patency of collateral pathways, and the condition of the cerebral microvasculature. Accurate characterization of cerebral hemodynamics is a challenging problem. In this work, we present a strategy to quantify cerebral hemodynamics using computational fluid dynamics (CFD) in combination with arterial spin labeling MRI (ASL). First, we calibrated patient-specific CFD outflow boundary conditions using ASL-derived flow splits in the Circle of Willis. Following, we validated the calibrated CFD model by evaluating the fractional blood supply from the main neck arteries to the vascular territories using Lagrangian particle tracking and comparing the results against vessel-selective ASL (VS-ASL). Finally, cerebral hemodynamics were assessed in two patients with CVOD and a healthy control subject. We demonstrated that the calibrated CFD model accurately reproduced the fractional blood supply to the vascular territories, as obtained from VS-ASL. The two patients revealed significant differences in pressure drop over the stenosis, collateral flow, and resistance of the distal vasculature, despite similar degrees of clinical stenosis severity. Our results demonstrated the advantages of a patient-specific CFD analysis for assessing the hemodynamic impact of stenosis.

bioengineering↗

bioRxiv2020

CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation

In this work, we describe the CRIMSON (CardiovasculaR Integrated Modelling and SimulatiON) software environment. CRIMSON provides a powerful, customizable and user-friendly system for performing three-dimensional and reduced-order computational haemodynamics studies via a pipeline which involves: 1) segmenting vascular structures from medical images; 2) constructing analytic arterial and venous geometric models; 3) performing finite element mesh generation; 4) designing, and 5) applying boundary conditions; 6) running incompressible Navier-Stokes simulations of blood flow with fluid-structure interaction capabilities; and 7) post-processing and visualizing the results, including velocity, pressure and wall shear stress fields. A key aim of CRIMSON is to create a software environment that makes powerful computational haemodynamics tools accessible to a wide audience, including clinicians and students, both within our research laboratories and throughout the community. The overall philosophy is to leverage best-in-class open source standards for medical image processing, parallel flow computation, geometric solid modelling, data assimilation, and mesh generation. It is actively used by researchers in Europe, North and South America, Asia, and Australia. It has been applied to numerous clinical problems; we illustrate applications of CRIMSON to real-world problems using examples ranging from pre-operative surgical planning to medical device design optimization. CRIMSON binaries for Microsoft Windows 10, documentation and example input files are freely available for download from www.crimson.software, and the source code with compilation instructions is available on GitHub https://github.com/carthurs/CRIMSONFlowsolver (CRIMSON Flowsolver) under the GPL v3.0 license, and https://github.com/carthurs/CRIMSONGUI (CRIMSON GUI), under the AGPL v3.0 license. Support is available on the CRIMSON Google Groups forum, located at https://groups.google.com/forum/#!forum/crimson-users.

bioengineering↗

bioRxiv2020

A Constrained Mixture Theory Model to Study Autoregulation in the Coronary Circulation

Coronary autoregulation is a short-term response manifested by a relatively constant flow over a wide range of perfusion pressures for a given metabolic state. This phenomenon is thought to be facilitated through a combination of mechanisms, including myogenic, shear dependent, and metabolic controls. The study of coronary autoregulation is challenging due to the coupled nature of the mechanisms and their differential effects through the coronary tree. In this paper, we developed a novel framework to study coronary autoregulation based on the constrained mixture theory. This structurally-motivated autoregulation model required calibration of anatomical and structural parameters of coronary trees via a homeostatic optimization approach using extensive literature data. Autoregulation was then simulated for two different coronary trees: subepicardial and subendocardial. The structurally calibrated model reproduced available baseline hemodynamics and autoregulation data for each coronary tree. The autoregulation analysis showed that the diameter of the intermediate and small arterioles varies the most in response to changes in perfusion pressure. Finally, we demonstrated the utility of the model in two application examples: 1) response to drops in epicardial pressure, and 2) response to drug infusion in the coronary arteries. The proposed structurally-motivated model could be extended to study long-term growth and remodeling in the coronary circulation in response to hypertension, atherosclerosis, etc. Key pointsO_LICoronary autoregulation is defined as the capability of the coronary circulation to maintain the blood supply to the heart over a range of perfusion pressures. This phenomenon is facilitated through intrinsic mechanisms that control the vascular resistance by regulating the mechanical function of smooth muscle cells. Understanding the mechanisms involved in coronary autoregulation is one of the most fundamental questions in coronary physiology. C_LIO_LIThis paper presents a structurally-motivated coronary autoregulation model that uses a nonlinear continuum mechanics approach to account for the morphometry and vessel wall composition in two coronary trees in the subepicardial and subendocardial layers. C_LIO_LIThe model is calibrated against diverse experimental data from literature and is used to study heterogeneous autoregulatory response in the coronary trees. This model drastically differs from previous models, which relied on lumped parameter model formulations, and is suited to the study of long-term pathophysiological growth and remodeling phenomena in coronary vessels. C_LI

physiology↗