Toward a Multi-Scale Computational Model of Arterial Adaptation in Hypertension: Verification of a Multi-Cell Agent Based Model

Agent-based models (ABMs) represent a novel approach to study and simulate complex mechano chemo-biological responses at the cellular level. Such models have been used to simulate a variety of emergent responses in the vasculature, including angiogenesis and vasculogenesis. Although not used previously to study large vessel adaptations, we submit that ABMs will prove equally useful in such studies when combined with well-established continuum models to form multi-scale models of tissue-level phenomena. In order to couple agent-based and continuum models, however, there is a need to ensure that each model faithfully represents the best data available at the relevant scale and that there is consistency between models under baseline conditions. Toward this end, we describe the development and verification of an ABM of endothelial and smooth muscle cell responses to mechanical stimuli in a large artery. A refined rule-set is proposed based on a broad literature search, a new scoring system for assigning confidence in the rules, and a parameter sensitivity study. To illustrate the utility of these new methods for rule selection, as well as the consistency achieved with continuum-level models, we simulate the behavior of a mouse aorta during homeostasis and in response to both transient and sustained increases in pressure. The simulated responses depend on the altered cellular production of seven key mitogenic, synthetic, and proteolytic biomolecules, which in turn control the turnover of intramural cells and extracellular matrix. These events are responsible for gross changes in vessel wall morphology. This new ABM is shown to be appropriately stable under homeostatic conditions, insensitive to transient elevations in blood pressure, and responsive to increased intramural wall stress in hypertension

Differential Progressive Remodeling of Coronary and Cerebral Arteries and Arterioles in an Aortic Coarctation Model of Hypertension

Objectives: Effects of hypertension on arteries and arterioles often manifest first as a thickened wall, with associated changes in passive material properties (e.g., stiffness) or function (e.g., cellular phenotype, synthesis and removal rates, and vasomotor responsiveness). Less is known, however, regarding the relative evolution of such changes in vessels from different vascular beds. Methods: We used an aortic coarctation model of hypertension in the mini-pig to elucidate spatiotemporal changes in geometry and wall composition (including layer-specific thicknesses as well as presence of collagen, elastin, smooth muscle, endothelial, macrophage, and hematopoietic cells) in three different arterial beds, specifically aortic, cerebral, and coronary, and vasodilator function in two different arteriolar beds, the cerebral and coronary. Results: Marked geometric and structural changes occurred in the thoracic aorta and left anterior descending coronary artery within 2 weeks of the establishment of hypertension and continued to increase over the 8-week study period. In contrast, no significant changes were observed in the middle cerebral arteries from the same animals. Consistent with these differential findings at the arterial level, we also found a diminished nitric oxide-mediated dilation to adenosine at 8 weeks of hypertension in coronary arterioles, but not cerebral arterioles. Conclusion: These findings, coupled with the observation that temporal changes in wall constituents and the presence of macrophages differed significantly between the thoracic aorta and coronary arteries, confirm a strong differential progressive remodeling within different vascular beds. Taken together, these results suggest a spatiotemporal progression of vascular remodeling, beginning first in large elastic arteries and delayed in distal vessels

Rare solid and cystic presentation of hemangiopericytoma/ solitary fibrous tumor: A case report

Hemangiopericytoma/Solitary Fibrous Tumor (HPC/SFT) is a rare fibroblastic sarcoma characterized by hyper-vasculature and STAT6 trans-nuclear localization. Cystic HPC/SFT is extremely rare. Due to the scarcity of cystic HPC/SFT cases, diagnostic and treatment guidelines are not well established. To our knowledge, we present the first case of cystic HPC/SFT observed in the liver. In addition, the patient had over 6 years of recurrent hypervascular solid HPC/SFT in the brain, bone, leptomeninges, liver and lung prior to developing a cystic HPC/SFT. Briefly, a 37-year-old Caucasian female with a history of HPC/SFT presented with several enlarging cystic hepatic lesions on surveillance MRI. The cystic/nonenhancing nature of these liver metastases were confirmed by contrast-enhanced ultrasound. Due to diagnostic uncertainty, two of these hepatic cysts were removed laparoscopically and pathology confirmed cystic HPC/SFT with a high MIB-1 index. Previously, in 2014, the patient was diagnosed with solid intracranial grade III pseudopapillary mesenchymal HPC/SFT in the posterior fossa and underwent subtotal resection followed by external beam radiation. In 2017, she had recurrent intracranial, vertebral, and intraspinal intradural extramedullary HPC/SFTs followed by surgery, proton therapy, and SRS radiotherapy. In 2019, after an uneventful pregnancy and birth, routine surveillance revealed metastases in the liver requiring an extended right hepatectomy. In 2020-2021 two solid hypervascular hepatic HPC/SFT were found and treated with microwave ablation. Shortly afterwards, several rapidly growing hepatic cystic HPC/SFT lesions developed. Of note, she has not taken any systemic therapy, indicating the cystic tumors are from metastases rather than cystic degradation as a sequela of therapy. Overall, this case highlights that cystic metastasis are a potential clinical manifestation of solid HPC/SFT. Moreover, cystic HPC/SFT can co-exist with the more typical primary solid hypervascular HPC/SFTs in the same patient. Lastly, in this case cystic HPC/SFT had a higher growth rate and propensity to metastasize as compared to the solid equivalent.Peer reviewe

An agent-based model of leukocyte transendothelial migration during atherogenesis.

A vast amount of work has been dedicated to the effects of hemodynamics and cytokines on leukocyte adhesion and trans-endothelial migration (TEM) and subsequent accumulation of leukocyte-derived foam cells in the artery wall. However, a comprehensive mechanobiological model to capture these spatiotemporal events and predict the growth and remodeling of an atherosclerotic artery is still lacking. Here, we present a multiscale model of leukocyte TEM and plaque evolution in the left anterior descending (LAD) coronary artery. The approach integrates cellular behaviors via agent-based modeling (ABM) and hemodynamic effects via computational fluid dynamics (CFD). In this computational framework, the ABM implements the diffusion kinetics of key biological proteins, namely Low Density Lipoprotein (LDL), Tissue Necrosis Factor alpha (TNF-α), Interlukin-10 (IL-10) and Interlukin-1 beta (IL-1β), to predict chemotactic driven leukocyte migration into and within the artery wall. The ABM also considers wall shear stress (WSS) dependent leukocyte TEM and compensatory arterial remodeling obeying Glagov's phenomenon. Interestingly, using fully developed steady blood flow does not result in a representative number of leukocyte TEM as compared to pulsatile flow, whereas passing WSS at peak systole of the pulsatile flow waveform does. Moreover, using the model, we have found leukocyte TEM increases monotonically with decreases in luminal volume. At critical plaque shapes the WSS changes rapidly resulting in sudden increases in leukocyte TEM suggesting lumen volumes that will give rise to rapid plaque growth rates if left untreated. Overall this multi-scale and multi-physics approach appropriately captures and integrates the spatiotemporal events occurring at the cellular level in order to predict leukocyte transmigration and plaque evolution

Multiphysics model showing the handshaking between the ABM and CFD.

<p>The coordinates of the inner arterial layer from ABM (left) is sent to COMSOL to perform CFD analysis (right). The instantaneous WSS from CFD is sent back to ABM and influences leukocyte TEM.</p

List of rules used in the ABM.

<p>List of rules used in the ABM.</p

When the degree of stenosis was below 8%, the level of leukocyte TEM was constant over an average change in lumen volume of 107±5 patches, followed by a rapid increase in TEM over the next 28±17 patches.

<p>(A) Scatter plot displaying leukocyte TEM and severity of stenosis as a function of luminal volume (patches). (B) Bar plot indicating the change in lumen volume after which a significant increase in leukocyte TEM was observed. (Mean ± SD, *p < 0.05). (C) Longitudinal cross sections of the ABM at ‘a’, ‘b’, and ‘c’ points from 5A, illustrating where the initial inward growth occurred. ACs, ECs, and leukocytes in the plaque are indicated in red, green and yellow, respectively. Black represents the new ECs added in the lumen. Inlet flow is at the bottom of each subfigure. (D) Subplot showing the number of patches (from ABM) with WSS < 1.2 Pa at specific plaque shapes (i.e., lumen volumes) corresponding to ‘a’, ‘b’, and ‘c’ points from 5A. Overlaid color contour plots of the WSS (from CFD) over the plaque at each point. The number of patches of low WSS (blue region) are almost constant (13 and 15 respectively) corresponding to nearly constant TEM. Then, the number of patches having low WSS increases (83) as does TEM. Inlet flow is at the left of each subfigure in (D).</p

Eccentric plaque growth and remodeling prediction.

<p>Longitudinal (left) and corresponding transverse (right) views of an evolving artery where ECs, ACs and leukocytes are represented by green, red and yellow respectively. A) Initially the artery is impregnated with 15 leukocytes. B) At 6 months the plaque area is 40% of the lumen area and will start growing inside lumen according to Glagov’s phenomenon. C) At 7 months the plaque has grown inward and outward, changing the luminal geometry.</p

Different types of leukocytes present in the plaque as it evolves.

<p>Before the plaque reduces the caliber of the lumen, as indicated by the vertical dashed red line, TEM is only due to endothelial activation by cytokines. Initially neutrophils constitute the majority of the plaque volume, followed by monocytes and monocyte-derived cells and then neutrophils again. When the plaque starts growing inside the lumen (vertical dashed line) leukocyte TEM is largely influenced by blood flow. With time the severity of stenosis increases and so does the region of low WSS. Therefore, the rate of leukocyte TEM is greater for all cells. Among these cells, the concentration of neutrophils (62%) in blood is higher than monocytes and lymphocytes (5.3% and 30% respectively). Also neutrophils adhere on the EC surface with WSS < 1.2 Pa whereas the monocytes and lymphocytes adhere with WSS < 1 Pa and < 0.4 Pa respectively. Thus there is a rapid increase of neutrophils immediately after 6 months whereas the rate for lymphocyte increases after several days when the plaque is bigger and WSS < 0.4 Pa.</p

Initial ABM parameters.

<p>Initial ABM parameters.</p