A Novel computational approach to optimize Fontan and improve surgical predictability

一种优化 Fontan 并提高手术可预测性的新型计算方法

• 批准号: 10346020
• 负责人: Vijay Govindarajan
• 金额: $ 62.75万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10346020
• 关键词: Adult; Affect; Algorithms; Anatomy; Aneurysm; Arteriovenous malformation; Assessment tool; Biochemistry; Blood; Blood Circulation; Blood Platelets; Blood coagulation; Blood flow; Caliber; Cardiac; Cardiac Surgery procedures; Caring; Childhood; Clinical; Coagulation Process; Collection; Complex; Consumption; Coupled; Custom; Data; Deposition; Distal; Engineering; Environment; Equilibrium; Evaluation; Failure; Family suidae; Fibrin; Flare; Fontan Procedure; Gases; Geometry; Heart; Hematologist; Hepatic; Image; In Vitro; Intervention; Lead; Liquid substance; Liver; Lung; Magnetic Resonance Imaging; Manuals; Methodology; Methods; Modeling; Monitor; Morbidity - disease rate; Operative Surgical Procedures; Organ; Outcome; Palliative Care; Pathway interactions; Patients; Physiology; Play; Polytetrafluoroethylene; Postoperative Period; Proteins; Protocols documentation; Research; Risk; Role; Route; Shapes; Single ventricle congenital heart disease; Surgeon; Techniques; Thrombin; Thrombosis; Thrombus; Time; Validation; Variant; Venous; Ventricular; Work; aortic arch; base; biochemical model; blood pump; clinical application; cohort; comparative; computerized tools; congenital heart disorder; design; hemodynamics; improved; in silico; in vitro Model; insight; kidney dysfunction; mortality; multidisciplinary; novel; palliative; pressure; prevent; prospective; reconstruction; repaired; success; surgery outcome; thrombotic; tool; virtual; virtual surgery

An efficient hemodynamics with minimal thrombosis risk post-surgery is essential for short- and long-term success of a cardiac surgery. Achieving this is a challenge in cardiac surgery that involves the design of a complex flow pathway. Aortic arch reconstruction, aneurysm repair, Fontan surgeries are a few examples. The Fontan surgical procedure is the most effective palliative treatment for patients with single ventricle defects (SVD). SVD refers to a collection of congenital heart diseases where one of the lower ventricular chambers of the heart remains underdeveloped. Fontan procedure involves re-routing of deoxygenated blood from upper and lower body to flow directly to lungs allowing the single functioning ventricle to pump blood for systemic circulation. Though lifesaving, the Fontan physiology creates a non-natural pathway for venous return of the blood to the lungs thus producing a non-physiological blood flow. A successful Fontan procedure should involve 1) well-balanced overall and hepatic venous flow return to lungs to prevent pulmonary arteriovenous malformations (PAVMs) that can lead to poor gas exchange, 2) minimal energy loss, and 3) minimal thrombosis (blood clot) risk. Complications such as PAVMs and thrombosis post-surgery can result in a Fontan failure. To improve Fontan surgical planning, its efficacy and predictability, we propose to develop an automated image-based computational fluid dynamics (CFD) workflow capable of optimizing and predicting all the above determinants for a successful Fontan physiology. CFD models have been developed in the past to assess energy loss and hepatic venous flow distribution, but an automated computational tool for rapidly optimizing the patients' Fontan physiology in terms of factors affecting success does not exist. To fill this gap, we will integrate our existing patient-specific Fontan surgical planning protocol to predict energy loss and hepatic venous flow distribution with 1) a shape optimization algorithm and 2) our validated model of blood coagulation to provide a computational tool to virtually improve the planned Fontan physiology for optimal hepatic and overall venous return to lungs, minimal energy loss and thrombotic potential and quantitatively predict thrombosis risk. We will completely automate our workflow with custom scripts to minimize errors and user intervention. Our biochemical model of blood coagulation has all the components representing platelet and fibrin deposition and is 2-way coupled with blood flow. The continuum-based approach of this model allows it to be used in large geometries. After rigorous validation of our surgical optimization workflow using MRI-based patient specific in-vitro models, we will perform virtual surgeries using our tool and retrospective patient data to establish clinical applicability. Our tool could potentially be 1) included in the current surgical planning workflow to perform virtual surgeries using patient pre-op data to improve and predict surgical outcomes, and 2) used to evaluate risk of clotting post- Fontan so that patients can be selectively monitored. Our long-term objective is to provide a prospective surgical planning tool for Fontan and then extend it other surgeries where such optimization can improve surgical efficacy.

术后血栓形成风险最小的有效血流动力学对于短期和长期治疗至关重要。 心脏手术的成功实现这一点是心脏外科的一个挑战，涉及到设计一个 复杂的流动路径。主动脉弓重建，动脉瘤修复，Fontan手术是几个例子。 Fontan手术是单心室患者最有效的姑息治疗方法 缺陷（SVD）。SVD是指一组先天性心脏病，其中一个下心室 心脏仍然发育不全Fontan手术涉及脱氧血液的改道 从上半身和下半身直接流向肺部，允许单个功能心室泵送血液， 体循环虽然可以挽救生命，但Fontan生理学为静脉回流创造了一个非自然的途径 因此产生了非生理性的血流。一个成功的丰唐手术应该 涉及1）总体和肝静脉血流平衡良好，回流至肺部，以防止肺动静脉 可能导致气体交换不良的畸形（PAVM），2）最小能量损失，3）最小血栓形成 （血凝块）风险。术后并发症（如PAVM和血栓形成）可能导致Fontan失败。 为了改善Fontan手术计划，其有效性和可预测性，我们建议开发一种自动化的 基于图像的计算流体动力学（CFD）工作流程，能够优化和预测上述所有内容 成功的丰唐生理学的决定因素。过去已经开发了CFD模型来评估能量 损失和肝静脉流量分布，而是一种自动计算工具，用于快速优化患者的 丰唐生理学方面影响成功的因素并不存在。为了填补这一空白，我们将整合我们的 现有患者特定Fontan手术计划方案，用于预测能量损失和肝静脉血流 分布与1）形状优化算法和2）我们的血液凝固的验证模型，以提供一个 一种计算工具，用于虚拟改善计划的Fontan生理学，以实现最佳的肝脏和整体静脉 返回肺部，最小的能量损失和血栓形成潜力，并定量预测血栓形成风险。我们将 使用自定义脚本完全自动化我们的工作流程，以最大限度地减少错误和用户干预。我们的生化 血液凝固模型具有代表血小板和纤维蛋白沉积的所有成分，并且是双向的 再加上血流该模型基于连续体的方法使其能够用于大型几何形状。 在使用基于MRI的患者特异性体外模型对我们的手术优化工作流程进行严格验证后， 我们将使用我们的工具和回顾性患者数据进行虚拟手术，以建立临床适用性。 我们的工具有可能1）包含在当前的手术计划工作流程中，以执行虚拟手术 使用患者术前数据改善和预测手术结局，2）用于评估术后凝血风险， Fontan，以便有选择地监测患者。我们的长期目标是提供一种有前景的外科手术 Fontan计划工具，然后将其扩展到其他手术，其中这种优化可以提高手术疗效。