Carol Act Supplement to Data-driven optimization of therapy for heart failure

卡罗尔法案对数据驱动的心力衰竭治疗优化的补充

• 批准号: 10851206
• 负责人: Kenneth S Campbell
• 金额: $ 12.86万
• 依托单位: UNIVERSITY OF KENTUCKY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10851206
• 关键词: 3-Dimensional; Administrative Supplement; Algorithms; Aortic Valve Insufficiency; Baroreflex; Beds; Blood; Cardiac; Circulation; Clinical; Computer Models; Computer software; Data; Dilated Cardiomyopathy; Disease; Exercise; Filament; Goals; Growth; Heart; Heart Diseases; Heart Valve Diseases; Heart failure; Hypertension; Hypertrophic Cardiomyopathy; Laws; Left ventricular structure; Mitral Valve; Mitral Valve Insufficiency; Mitral Valve Prolapse; Mitral Valve Stenosis; Modeling; Mutation; Myocardial; Myosin ATPase; Parents; Patients; Pattern; Physiological; Postdoctoral Fellow; Pregnancy; Proteins; Qualifying; Relaxation; Research; Signal Transduction; Stenosis; Stress; Supervision; System; Techniques; Testing; Therapeutic; Therapeutic Intervention; Thinness; Time; Work; aortic valve; blood pump; clinical phenotype; clinically relevant; computer program; connectin; constriction; experience; parent grant; response; simulation; therapeutic evaluation; treatment optimization

ABSTRACT This proposal is submitted in response to NOT-HL-23-078 “Administrative supplements to encourage research in valvular heart disease” and seeks 12 months of additional support for HL163977, Data-driven optimization of therapy for heart failure. The parent R01 is active until 2026. The overarching goal of HL163977 is to develop a computer model of the heart that can be used to test therapeutic strategies and optimize treatments for patients who have heart failure. Aim 1 develops a system called MyoVent as a test-bed for implementing baroreflex control and myocardial growth. Aims 2 and 3 use the techniques developed with MyoVent and deploy them in a more sophisticated 3D framework called MyoFE to create patient-specific personalized models. The team has made rapid progress and Aim 1 is now mostly complete. The breakthrough was accomplished by developing algorithms that modulate concentric (wall thickening / thinning) and eccentric (chamber dilation / constriction) growth in response to physiologic signals. Specifically, the model assumes that hearts grow concentrically to stabilize the intracellular ATP concentration while eccentric growth is sensitive to the passive intracellular stress sensed by titin filaments. These growth laws reproduce the patterns of cardiac growth observed in clinically-relevant conditions including hypertension, exercise, and destabilization of the myosin super-relaxed state. This supplement will extend the simulations to valvular heart disease. The objective is focused. The team will test whether the growth laws predict the patterns of eccentric and concentric growth observed clinically in patients with mitral valve insufficiency (including mitral valve prolapse) and stenosis, and aortic valve insufficiency and stenosis. This will be accomplished in a single year by a highly-qualified and experienced post-doc who will work under the supervision of the contact PI.

抽象的 本提案是针对 NOT-HL-23-078“鼓励研究的行政补充”而提交的 瓣膜性心脏病”，并寻求对 HL163977 的 12 个月额外支持，数据驱动的优化 心力衰竭的治疗。母版 R01 的有效期至 2026 年。 HL163977 的总体目标是开发可用于测试的心脏计算机模型 治疗策略并优化心力衰竭患者的治疗。目标 1 开发一个系统 称为 MyoVent 作为实施压力反射控制和心肌生长的试验台。目标 2 和 3 使用 使用 MyoVent 开发的技术并将其部署在名为 MyoFE 的更复杂的 3D 框架中 创建针对患者的个性化模型。 该团队取得了快速进展，目标 1 目前已基本完成。这一突破是通过 开发调节同心（壁增厚/变薄）和偏心（腔室扩张/ 收缩）响应生理信号的生长。具体来说，该模型假设心脏生长 同心生长以稳定细胞内 ATP 浓度，而偏心生长则对被动敏感 肌联蛋白丝感知细胞内压力。这些生长规律再现了心脏生长的模式 在临床相关病症中观察到，包括高血压、运动和肌球蛋白不稳定 超级放松的状态。 该补充品将模拟扩展到瓣膜性心脏病。目标是集中的。团队将 测试生长规律是否预测临床上观察到的患者偏心和同心生长模式 患有二尖瓣关闭不全（包括二尖瓣脱垂）和狭窄，以及主动脉瓣关闭不全和 狭窄。这将由一位高素质且经验丰富的博士后在一年内完成，他将在 在联系人 PI 的监督下。

项目成果

An in silico study of the effects of left ventricular assist device on right ventricular function and inter-ventricular interaction.

左心室辅助装置对右心室功能和心室间相互作用影响的计算机研究。

• DOI: 10.1111/aor.14649
• 发表时间: 2023
• 期刊: Artificial organs
• 影响因子: 2.4
• 作者: Fan,Lei;Choy,JennyS;Lee,Sangjin;Campbell,KennethS;Wenk,JonathanF;Kassab,GhassanS;Burkhoff,Daniel;Lee,LikChuan
• 通讯作者: Lee,LikChuan