Blood flow modeling reveals improved collateral artery performance during the regenerative period in mammalian hearts

Collateral arteries are a vessel subtype that bridges two artery branches, forming a natural bypass that can deliver blood flow downstream of an occlusion. These bridges in the human heart are associated with better outcomes during coronary artery disease. We recently found that their rapid development in neonates supports heart regeneration, while the non-regenerative adult heart displays slow and minimal collateralization. Thus, inducing robust collateral artery networks could serve as viable treatment for cardiac ischemia, but reaching this goal requires more knowledge on their developmental mechanisms and functional capabilities. Here, we use whole-organ imaging and 3D computational fluid dynamics (CFD) modeling to identify the spatial architecture of and predict blood flow through collaterals in neonate and adult hearts. We found that neonate collaterals are more numerous, larger in diameter, and, even when similar in size/number, are predicted to more effectively re-perfuse an occluded coronary network when compared to adults. CFD analysis revealed that collaterals perform better in neonates because of decreased differential pressures along their coronary artery tree. Furthermore, testing of various collateral configurations indicated that larger, more proximal collaterals are more beneficial than many smaller ones, identifying a target architecture for therapeutic interventions. Morphometric analysis revealed how the coronary artery network expands during postnatal growth. Vessel diameters do not scale with cardiac muscle growth. Instead, the coronary tree expands solely by adding additional branches of a set length, a burst of which occurs during murine puberty. Finally, we compared mouse structural and functional data to human hearts. Surprisingly, fetal human hearts possessed a very large number of small, but mature, smooth muscle cell covered collaterals while angiogram data indicated adult patients with chronic coronary occlusions contained at least two. Comparing size ratios with modeled mouse data suggested low re-perfusion capabilities of the embryonic collaterals but higher functional benefits of those in diseased adults. Our unique interdisciplinary approach allowed us to quantify the functional significance of collateral arteries during heart regeneration and repair–a critical step towards realizing their therapeutic potential.

Mathematical Modeling of Blood Flow to Evaluate the Hemodynamic Significance of Peripheral Vascular Lesions

Background: Evaluating the severity of peripheral artery lesions is challenging. Image-based blood flow modeling from peripheral Computed Tomographic Angiography (pCTA) may provide a non-invasive method to determine the hemodynamic significance of lesions. This pilot study evaluates the performance of pCTA-based blood flow modeling in diagnosing functionally significant peripheral lesions in comparison with Digital Subtraction Angiography (DSA). Methods: Ten patients undergoing DSA and pCTA were included. The peripheral arteries were divided into 8 segments per extremity and stenosis severity was graded by visual estimation from DSA. Each segment was graded 0 to IV (normal, mildly-stenotic, moderately-stenotic, severely-stenotic, occluded) or non-evaluable. Independent from DSA review, a Resting Pressure Drop (RPD) and an Exercise Pressure Drop (ExPD) for each segment was calculated from pCTA-based blood flow modeling. A functionally significant (FS) lesion was defined as grade III or IV by DSA and RPD > 5 mmHg from pCTA-based modeling. Analysis was repeated with an ExPD > 20 mmHg. Sensitivity, specificity and accuracy were calculated for RPD > 5 mmHg and ExPD > 20 mmHg using DSA as the standard. Results: Mean age was 52±16 years, 4 patients were male, 8 patients presented with critical limb ischemia, mean ankle brachial index was 0.60±0.29, and 66 arterial segments were available for both assessment methods. Twenty-two segments had FS lesions by DSA. Using an RPD > 5 mmHg, sensitivity was 80%, specificity was 85% and accuracy was 79%. Using an ExPD > 20 mmHg, sensitivity was 84%, specificity was 89% and accuracy was 88%. Conclusion: Use of a resting pressure drop > 5 mmHg and an exercise pressure drop > 20 mmHg, measured by blood flow modeling from CT angiography, can accurately identify functionally significant stenosis in patients with peripheral vascular disease. This information motivates the need for a larger-scale prospective imaging trial to further validate this novel non-invasive approach.

Blood flow modeling reveals improved collateral artery performance during mammalian heart regeneration

Collateral arteries are a vessel subtype that bridges two artery branches, forming a natural bypass that can deliver blood flow downstream of an occlusion. These bridges in the human heart are associated with better outcomes during coronary artery disease. We recently found that their rapid development in neonates supports heart regeneration, while the non-regenerative adult heart displays slow and minimal collateralization. Thus, inducing robust collateral artery networks could serve as viable treatment for cardiac ischemia, but reaching this goal requires more knowledge on their developmental mechanisms and functional capabilities. Here, we use whole-organ imaging and 3D computational fluid dynamics (CFD) modeling to identify the spatial architecture of and predict blood flow through collaterals in neonate and adult hearts. We found that neonate collaterals are more numerous, larger in diameter, and, even when similar in size/number, are predicted to more effectively re-perfuse an occluded coronary network when compared to adults. CFD analysis revealed that collaterals perform better in neonates because of decreased differential pressures along their coronary artery tree. Furthermore, testing of various collateral configurations indicated that larger, more proximal collaterals are more beneficial than many smaller ones, identifying a target architecture for therapeutic interventions. Morphometric analysis revealed how the coronary artery network expands during postnatal growth. Vessel diameters do not scale with cardiac muscle growth. Instead, the coronary tree expands solely by adding additional branches of a set length, a burst of which occurs during murine puberty. Finally, we compared mouse structural and functional data to human hearts. Surprisingly, fetal human hearts possessed a very large number of small, but mature, smooth muscle cell covered collaterals while angiogram data indicated adult patients with chronic coronary occlusions contained at least two. Comparing size ratios with modeled mouse data suggested low re-perfusion capabilities of the embryonic collaterals but higher functional benefits of those in diseased adults. Our unique interdisciplinary approach allowed us to quantify the functional significance of collateral arteries during heart regeneration and repair–a critical step towards realizing their therapeutic potential.

A Novel Mathematical Framework for the Venous Valve Leaflet Morphology Extracted From In-Vitro Images Using Machine Learning Assisted Stereological Analysis

It has been suggested that stasis (stagnant zones over a period of time, dependent on other factors such as age, or underlying medical conditions, such as cancer or covid19) in the valve pockets may increase the risk of clots due to stasis in combination with other factors increases the risk of Deep Venous Thrombosis (DVT) formation, blood stasis may also result in a decrease in the anticoagulants factors that prevent clots from forming, and if the vein wall is damaged this further increases the risk of clot formation. We propose a proactive framework to predict DVT vulnerability, track progression and provide patient care checkpoints is of clear benefit. The framework is based on leading-edge cloud computing technologies and promises to offer user-friendly Software- & Platform-as-a-Service (SaaS/PaaS) solutions via novel machine learning (ML) algorithm and high fidelity blood flow modeling through the venous network under various valve configurations. In this work, we will present the progress made towards the leaflet morphology extraction from in-vitro images using ML assisted stereological analysis for obtaining a sufficiently accurate representation of morphology. Ultimately, the workflow can be tailored to specific patients. The extracted valve is used to identify red-flag stagnant zones by a detailed, physics-based computational study of the blood flow through the leaflet models.

Cerebral arterial architectonics and CFD simulation in mice with type 1 diabetes mellitus of different duration

Type 1 diabetes is a chronic autoimmune disease that affects tens of millions of people. Diabetes mellitus is one of the strongest factors in the development of cerebrovascular diseases. In this study we used NOD.CB17 Prkdcscid mice and the pharmacological model of type 1 diabetes mellitus of different duration to study changes in the cerebral vasculature. We used two combined approaches using magnetic resonance angiography both steady and transient CFD blood flow modeling. We identified the influence of type 1 diabetes on the architectonics and hemodynamics of the large blood vessels of the brain as the disease progresses. For the first time, we detected a statistically significant change in angioarchitectonics (the angles between the vessels of the circle of Willis, cross-sections areas of vessels) and hemodynamic (maximum blood flow rate, hydraulic resistance) in animals with diabetes duration of 2 months, that is manifested by the development of asymmetry of cerebral blood flow. The result shows the negative effect of diabetes on cerebral circulation as well as the practicability of CFD modeling. This may be of extensive interest, in pharmacological and preclinical studies.

Blood Flow Modeling in Coronary Arteries: A Review

Atherosclerosis is one of the main causes of cardiovascular events, namely, myocardium infarction and cerebral stroke, responsible for a great number of deaths every year worldwide. This pathology is caused by the progressive accumulation of low-density lipoproteins, cholesterol, and other substances on the arterial wall, narrowing its lumen. To date, many hemodynamic studies have been conducted experimentally and/or numerically; however, this disease is not yet fully understood. For this reason, the research of this pathology is still ongoing, mainly, resorting to computational methods. These have been increasingly used in biomedical research of atherosclerosis because of their high-performance hardware and software. Taking into account the attempts that have been made in computational techniques to simulate realistic conditions of blood flow in both diseased and healthy arteries, the present review aims to give an overview of the most recent numerical studies focused on coronary arteries, by addressing the blood viscosity models, and applied physiological flow conditions. In general, regardless of the boundary conditions, numerical studies have been contributed to a better understanding of the development of this disease, its diagnosis, and its treatment.

Abstract 16856: Mathematical Modeling of Blood Flow to Evaluate the Hemodynamic Significance of Peripheral Vascular Lesions

Introduction: Evaluating the severity of lesions in peripheral arteries is challenging. Image-based blood flow modeling from peripheral computed tomographic angiography (pCTA) may provide a non-invasive method to determine the hemodynamic significance of lesions. The objective of this study was to evaluate the diagnostic performance of a trans-lesion pressure drop computed from pCTA-based blood flow modeling in the peripheral arteries. Methods: Ten patients undergoing digital subtraction angiography (DSA) and pCTA were included. The peripheral arteries were divided into 8 segments per extremity and stenosis severity was visually graded by DSA as non-stenosed (grade 0), mild (grade I), moderate (grade II), severe (grade III), occluded (grade IV) or non-evaluable. A functionally significant lesion was defined as grade III or IV by DSA. Independent from the DSA review, a resting pressure gradient (rPG) and exercise PG (ExPG) for each segment was calculated from pCTA-based blood flow modeling (Figure), and a functionally significant lesion was defined as having an rPG > 5 mm Hg or an ExPG > 20 mm Hg. Results: Mean age was 52±16 years, 4 patients (40%) were male, 8 patients (80%) presented with critical limb ischemia, mean ankle brachial index was 0.60±0.29 and 66 arterial segments were available for both assessment methods. Twenty-two segments had functionally significant lesions by DSA. For rPG, sensitivity was 80%, specificity was 85% and accuracy was 79% with DSA as the standard; for ExPG, sensitivity was 84%, specificity was 89% and accuracy was 88%. Conclusions: Use of a resting pressure gradient > 5 mm Hg and an exercise pressure gradient > 20 mm Hg measured by peripheral computed tomography-based blood flow modeling accurately identifies functionally significant stenosis in patients with advanced peripheral vascular disease. These results support a prospective imaging trial to further validate this novel approach.