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.

摘要 本提案是为响应NOT-HL-23-078《鼓励研究的行政补充文件》而提交的 在心脏瓣膜病中的应用”，并寻求对HL 163977的12个月额外支持， 治疗心力衰竭父R 01将在2026年之前一直处于活动状态。 HL 163977的总体目标是开发一个心脏的计算机模型，可用于测试 治疗策略和优化心力衰竭患者的治疗。Aim 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 MyoVent开发的技术，并将其部署在一个更复杂的3D框架中，称为MyoFE， 创建患者特定的个性化模型。 该团队取得了快速进展，目标1现已基本完成。这一突破是由 开发调节同心（壁增厚/变薄）和偏心（腔室扩张/收缩）的算法。 收缩）响应生理信号的生长。具体来说，该模型假设心脏会生长， 同心地稳定细胞内ATP浓度，而离心生长对被动 肌联蛋白丝感受细胞内应激。这些生长规律再现了心脏生长的模式 在临床相关疾病中观察到，包括高血压、运动和肌球蛋白不稳定 超放松状态 这一补充将扩大模拟心脏瓣膜病。目标是集中的。该团队将 测试生长规律是否能预测临床上观察到的偏心和同心生长模式 二尖瓣关闭不全（包括二尖瓣脱垂）和狭窄，主动脉瓣关闭不全， 狭窄。这将在一年内完成由一个高素质和经验丰富的博士后谁将工作 在联系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