A Fluid-Solid-Growth Solver for Cardiovascular Modeling.

We implement full, three-dimensional constrained mixture theory for vascular growth and remodeling into a finite element fluid-structure interaction (FSI) solver. The resulting "fluid-solid-growth" (FSG) solver allows long term, patient-specific predictions of changing hemodynamics, vessel wall morphology, tissue composition, and material properties. This extension from short term (FSI) to long term (FSG) simulations increases clinical relevance by enabling mechanobioloigcally-dependent studies of disease progression in complex domains.

Tissue engineered vascular grafts are resistant to the formation of dystrophic calcification.

Advancements in congenital heart surgery have heightened the importance of durable biomaterials for adult survivors. Dystrophic calcification poses a significant risk to the long-term viability of prosthetic biomaterials in these procedures. Herein, we describe the natural history of calcification in the most frequently used vascular conduits, expanded polytetrafluoroethylene grafts. Through a retrospective clinical study and an ovine model, we compare the degree of calcification between tissue-engineered vascular grafts and polytetrafluoroethylene grafts. Results indicate superior durability in tissue-engineered vascular grafts, displaying reduced late-term calcification in both clinical studies (p < 0.001) and animal models (p < 0.0001). Further assessments of graft compliance reveal that tissue-engineered vascular grafts maintain greater compliance (p < 0.0001) and distensibility (p < 0.001) than polytetrafluoroethylene grafts. These properties improve graft hemodynamic performance, as validated through computational fluid dynamics simulations. We demonstrate the promise of tissue engineered vascular grafts, remaining compliant and distensible while resisting long-term calcification, to enhance the long-term success of congenital heart surgeries.

Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease.

Physics-based computational models of the cardiovascular system are increasingly used to simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and diseased states. While predictive models using computational fluid dynamics (CFD) originated primarily for use in surgical planning, their application now extends well beyond this purpose. In this review, we describe an increasingly wide range of modeling applications aimed at uncovering fundamental mechanisms of disease progression and development, performing model-guided design, and generating testable hypotheses to drive targeted experiments. Increasingly, models are incorporating multiple physical processes spanning a wide range of time and length scales in the heart and vasculature. With these expanded capabilities, clinical adoption of patient-specific modeling in congenital and acquired cardiovascular disease is also increasing, impacting clinical care and treatment decisions in complex congenital heart disease, coronary artery disease, vascular surgery, pulmonary artery disease, and medical device design. In support of these efforts, we discuss recent advances in modeling methodology, which are most impactful when driven by clinical needs. We describe pivotal recent developments in image processing, fluid-structure interaction, modeling under uncertainty, and reduced order modeling to enable simulations in clinically relevant timeframes. In all these areas, we argue that traditional CFD alone is insufficient to tackle increasingly complex clinical and biological problems across scales and systems. Rather, CFD should be coupled with appropriate multiscale biological, physical, and physiological models needed to produce comprehensive, impactful models of mechanobiological systems and complex clinical scenarios. With this perspective, we finally outline open problems and future challenges in the field.

A matched-pair case control study identifying hemodynamic predictors of cerebral aneurysm growth using computational fluid dynamics.

Introduction: Initiation and progression of cerebral aneurysms is known to be driven by complex interactions between biological and hemodynamic factors, but the hemodynamic mechanism which drives aneurysm growth is unclear. We employed robust modeling and computational methods, including temporal and spatial convergence studies, to study hemodynamic characteristics of cerebral aneurysms and identify differences in these characteristics between growing and stable aneurysms. Methods: Eleven pairs of growing and non-growing cerebral aneurysms, matched in both size and location, were modeled from MRA and CTA images, then simulated using computational fluid dynamics (CFD). Key hemodynamic characteristics, including wall shear stress (WSS), oscillatory shear index (OSI), and portion of the aneurysm under low shear, were evaluated. Statistical analysis was then performed using paired Wilcoxon rank sum tests. Results: The portion of the aneurysm dome under 70% of the parent artery mean wall shear stress was higher in growing aneurysms than in stable aneurysms and had the highest significance among the tested metrics (p = 0.08). Other metrics of area under low shear had similar levels of significance. Discussion: These results align with previously observed hemodynamic trends in cerebral aneurysms, indicating a promising direction for future study of low shear area and aneurysm growth. We also found that mesh resolution significantly affected simulated WSS in cerebral aneurysms. This establishes that robust computational modeling methods are necessary for high fidelity results. Together, this work demonstrates that complex hemodynamics are at play within cerebral aneurysms, and robust modeling and simulation methods are needed to further study this topic.

Patient-specific changes in aortic hemodynamics is associated with thrombotic risk after fenestrated endovascular aneurysm repair with large diameter endografts.

Background: The durability of fenestrated endovascular aneurysm repair (fEVAR) has been threatened by thrombotic complications. In the present study, we used patient-specific computational fluid dynamic (CFD) simulation to investigate the effect of the endograft diameter on hemodynamics after fEVAR and explore the hypothesis that diameter-dependent alterations in aortic hemodynamics can predict for thrombotic events. Methods: A single-institutional retrospective study was performed of patients who had undergone fEVAR for juxtarenal aortic aneurysms. The patients were stratified into large diameter (34-36 mm) and small diameter (24-26 mm) endograft groups. Patient-specific CFD simulations were performed using three-dimensional paravisceral aortic models created from computed tomographic images with allometrically scaled boundary conditions. Aortic time-averaged wall shear stress (TAWSS) and residence time (RT) were computed and correlated with future thrombotic complications (eg, renal stent occlusion, development of significant intraluminal graft thrombus). Results: A total of 36 patients (14 with a small endograft and 22 with a large endograft) were included in the present study. The patients treated with large endografts had experienced a higher incidence of thrombotic complications compared with small endografts (45.5% vs 7.1%; P = .016). Large endografts were associated with a lower postoperative aortic TAWSS (1.45 ± 0.76 dynes/cm2 vs 3.16 ± 1.24 dynes/cm2; P < .001) and longer aortic RT (0.78 ± 0.30 second vs 0.34 ± 0.08 second; P < .001). In the large endograft group, a reduction >0.39 dynes/cm2 in aortic TAWSS demonstrated discriminatory power for thrombotic complications (area under the receiver operating characteristic curve, 0.77). An increased aortic RT of ≥0.05 second had similar accuracy for predicting thrombotic complications (area under the receiver operating characteristic curve, 0.78). The odds of thrombotic complications were significantly higher if patients had met the hemodynamic threshold changes in aortic TAWSS (odds ratio, 7.0; 95% confidence interval, 1.1-45.9) and RT (odds ratio, 8.0; 95% confidence interval, 1.13-56.8). Conclusions: Patient-specific CFD simulation of fEVAR in juxtarenal aortic aneurysms demonstrated significant endograft diameter-dependent differences in aortic hemodynamics. A postoperative reduction in TAWSS and an increased RT correlated with future thrombotic events after large-diameter endograft implantation. Patient-specific simulation of hemodynamics provides a novel method for thrombotic risk stratification after fEVAR.

Biodegradable external wrapping promotes favorable adaptation in an ovine vein graft model.

Vein grafts, the most commonly used conduits in multi-vessel coronary artery bypass grafting surgery, have high intermediate- and long-term failure rates. The abrupt and marked increase in hemodynamic loads on the vein graft is a known contributor to failure. Recent computational modeling suggests that veins can more successfully adapt to an increase in mechanical load if the rate of loading is gradual. Applying an external wrap or support at the time of surgery is one way to reduce the transmural load, and this approach has improved performance relative to an unsupported vein graft in several animal studies. Yet, a clinical trial in humans has shown benefits and drawbacks, and mechanisms by which an external wrap affects vein graft adaptation remain unknown. This study aims to elucidate such mechanisms using a multimodal experimental and computational data collection pipeline. We quantify morphometry using magnetic resonance imaging, mechanics using biaxial testing, hemodynamics using computational fluid dynamics, structure using histology, and transcriptional changes using bulk RNA-sequencing in an ovine carotid-jugular interposition vein graft model, without and with an external biodegradable wrap that allows loads to increase gradually. We show that a biodegradable external wrap promotes luminal uniformity, physiological wall shear stress, and a consistent vein graft phenotype, namely, it prevents over-distension, over-thickening, intimal hyperplasia, and inflammation, and it preserves mechanotransduction. These mechanobiological insights into vein graft adaptation in the presence of an external support can inform computational growth and remodeling models of external support and facilitate design and manufacturing of next-generation external wrapping devices. STATEMENT OF SIGNIFICANCE: External mechanical support is emerging as a promising technology to prevent vein graft failure following coronary bypass graft surgery. While variants of this technology are currently under investigation in clinical trials, the fundamental mechanisms of adaptation remain poorly understood. We employ an ovine carotid-jugular interposition vein graft model, with and without an external biodegradable wrap to provide mechanical support, and probe vein graft adaptation using a multimodal experimental and computational data collection pipeline. We quantify morphometry using magnetic resonance imaging, mechanics using biaxial testing, fluid flow using computational fluid dynamics, vascular composition and structure using histology, and transcriptional changes using bulk RNA sequencing. We show that the wrap mitigates vein graft failure by promoting multiple adaptive mechanisms (across biological scales).

Tissue engineered vascular grafts transform into autologous neovessels capable of native function and growth.

Background: Tissue-engineered vascular grafts (TEVGs) have the potential to advance the surgical management of infants and children requiring congenital heart surgery by creating functional vascular conduits with growth capacity. Methods: Herein, we used an integrative computational-experimental approach to elucidate the natural history of neovessel formation in a large animal preclinical model; combining an in vitro accelerated degradation study with mechanical testing, large animal implantation studies with in vivo imaging and histology, and data-informed computational growth and remodeling models. Results: Our findings demonstrate that the structural integrity of the polymeric scaffold is lost over the first 26 weeks in vivo, while polymeric fragments persist for up to 52 weeks. Our models predict that early neotissue accumulation is driven primarily by inflammatory processes in response to the implanted polymeric scaffold, but that turnover becomes progressively mechano-mediated as the scaffold degrades. Using a lamb model, we confirm that early neotissue formation results primarily from the foreign body reaction induced by the scaffold, resulting in an early period of dynamic remodeling characterized by transient TEVG narrowing. As the scaffold degrades, mechano-mediated neotissue remodeling becomes dominant around 26 weeks. After the scaffold degrades completely, the resulting neovessel undergoes growth and remodeling that mimicks native vessel behavior, including biological growth capacity, further supported by fluid-structure interaction simulations providing detailed hemodynamic and wall stress information. Conclusions: These findings provide insights into TEVG remodeling, and have important implications for clinical use and future development of TEVGs for children with congenital heart disease.

Hemodynamic performance of tissue-engineered vascular grafts in Fontan patients.

In the field of congenital heart surgery, tissue-engineered vascular grafts (TEVGs) are a promising alternative to traditionally used synthetic grafts. Our group has pioneered the use of TEVGs as a conduit between the inferior vena cava and the pulmonary arteries in the Fontan operation. The natural history of graft remodeling and its effect on hemodynamic performance has not been well characterized. In this study, we provide a detailed analysis of the first U.S. clinical trial evaluating TEVGs in the treatment of congenital heart disease. We show two distinct phases of graft remodeling: an early phase distinguished by rapid changes in graft geometry and a second phase of sustained growth and decreased graft stiffness. Using clinically informed and patient-specific computational fluid dynamics (CFD) simulations, we demonstrate how changes to TEVG geometry, thickness, and stiffness affect patient hemodynamics. We show that metrics of patient hemodynamics remain within normal ranges despite clinically observed levels of graft narrowing. These insights strengthen the continued clinical evaluation of this technology while supporting recent indications that reversible graft narrowing can be well tolerated, thus suggesting caution before intervening clinically.

Patient-derived models link re-entrant driver localization in atrial fibrillation to fibrosis spatial pattern.

AIMS: The mechanisms underlying persistent atrial fibrillation (AF) in patients with atrial fibrosis are poorly understood. The goal of this study was to use patient-derived atrial models to test the hypothesis that AF re-entrant drivers (RDs) persist only in regions with specific fibrosis patterns. METHODS AND RESULTS: Twenty patients with persistent AF (PsAF) underwent late gadolinium-enhanced MRI to detect the presence of atrial fibrosis. Segmented images were used to construct personalized 3D models of the fibrotic atria with biophysically realistic atrial electrophysiology. In each model, rapid pacing was applied to induce AF. AF dynamics were analysed and RDs were identified using phase mapping. Fibrosis patterns in RD regions were characterized by computing maps of fibrosis density (FD) and entropy (FE). AF was inducible in 13/20 models and perpetuated by few RDs (2.7 ± 1.5) that were spatially confined (trajectory of phase singularities: 7.6 ± 2.3 mm). Compared with the remaining atrial tissue, regions where RDs persisted had higher FE (IQR: 0.42-0.60 vs. 0.00-0.40, P < 0.05) and FD (IQR: 0.59-0.77 vs. 0.00-0.33, P < 0.05). Machine learning classified RD and non-RD regions based on FD and FE and identified a subset of fibrotic boundary zones present in 13.8 ± 4.9% of atrial tissue where 83.5 ± 2.4% of all RD phase singularities were located. CONCLUSION: Patient-derived models demonstrate that AF in fibrotic substrates is perpetuated by RDs persisting in fibrosis boundary zones characterized by specific regional fibrosis metrics (high FE and FD). These results provide new insights into the mechanisms that sustain PsAF and could pave the way for personalized, MRI-based management of PsAF.

Feasibility of using patient-specific models and the "minimum cut" algorithm to predict optimal ablation targets for left atrial flutter.

BACKGROUND: Left atrial flutter (LAFL) occurs in patients after atrial fibrillation ablation. Identification of optimal ablation targets to terminate LAFL remains challenging. OBJECTIVE: The purpose of this study was to use patient-specific models to simulate LAFL and predict optimal ablation targets using a novel approach based on flow network theory. METHODS: Late gadolinium-enhanced cardiac magnetic resonance scans from 10 patients with LAFL were used to construct atrial models incorporating fibrosis by investigators blinded to procedural findings. Rapid pacing was applied in silico to induce LAFL. In each LAFL, we represented reentrant wave propagation as an electric flow network and identified the "minimum cut" (MC), which was the smallest amount of tissue that separated the flow into 2 discontinuous components. In silico ablation was applied at MCs, and targets were compared to those that terminated LAFL during catheter ablation. RESULTS: Patient-specific atrial models were successfully generated from patient scans. LAFL was induced in 7 of 10 models. Ablation of MCs terminated LAFL in 4 models and produced new, slower LAFL morphologies in the other 3. For the latter cases, flow analysis was repeated to identify MCs of emergent LAFLs. Ablation of these MCs terminated emergent LAFLs. The MC-based ablation lesions in simulations were similar in length and location to ablation targets that terminated LAFL during catheter ablation for these 7 patients. CONCLUSION: Personalized atrial simulations can predict ablation targets for LAFL. These simulations provide a powerful tool for planning ablation procedures and may reduce procedural times and complications.