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International Consortium for Multimodality Phenotyping in Adults with Non-compaction

国际非致密化成人多模态表型联盟

基本信息

批准号：
10218265
负责人：
Koen Nieman
金额：
$ 73.33万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-16 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10218265
关键词：
3-Dimensional Adult Adverse event Anticoagulation Architecture Arrhythmia Artificial Intelligence Awareness Behavior Benign Cardiac Cardiomyopathies Cessation of life Clinic Clinical Complex Computers DNA Sequence Alteration Data Data Analyses Defibrillators Detection Diagnosis Diagnostic Diagnostic Imaging Diagnostic Procedure Disease Echocardiography Event Family member Foundations Fractals Genetic Genetic Structures Goals Guidelines Health Heart failure Histologic Image Image Analysis Imaging Techniques Individual International Intervention Joints Knowledge Lead Left ventricular non-compaction Life Machine Learning Magnetic Resonance Imaging Measures Medical Genetics Mission Modeling Multimodal Imaging Mutation Myocardial Myocardial tissue Myocardium Nature Non-compaction cardiomyopathy Organism Outcome Pathologic Patient Care Patients Pattern Pennsylvania Performance Phenotype Physiological Population Predictive Value Preventive care Preventive measure Preventive therapy Public Health Research Resolution Risk Risk Factors Savings Stroke Structure Sudden Death Techniques United States National Institutes of Health Universities Ventricular Arrhythmia accurate diagnosis adjudicate adjudication adverse event risk analytical method base clinically relevant cohort deep learning density disability embolic stroke genetic pedigree heart imaging high risk imaging genetics implantation improved improved outcome innovation multimodality novel outcome prediction patient subsets predictive modeling preventive intervention prognostic value prospective radiomics research clinical testing risk prediction risk prediction model risk stratification sudden cardiac death thrombogenesis young adult

项目摘要

Summary Non-compaction cardiomyopathy (NCCM) is a heterogeneous, poorly understood disorder characterized by a prominent inner layer of loose myocardial tissue. Patients with NCCM are at increased risk of heart failure, stroke, severe rhythm irregularities and death. Current imaging techniques cannot differentiate pathological from benign hypertrabeculation. In addition, current echo/MRI-based criteria of NCCM lead to over-diagnosis of NCCM, provide no prognostic value, and lead to implantation of defibrillators (ICD) and the use of anticoagulation without a positive benefit in many otherwise healthy individuals with non-compacted myocardium. For a growing population diagnosed with NCCM there is an urgent need for better risk stratification to appropriately allocate (or safely withhold) these impactful preventive measures. Our international consortium combines expertise in myocardial disease, cardiac imaging and advanced computer analytics from 5 centers dedicated to the care of patients with cardiomyopathies, and has the ultimate goal to improve care of patients with non-compaction cardiomyopathy. We hypothesize that comprehensive analysis of clinical, genetic, structural and functional information will improve risk stratification. In addition, we hypothesize that detailed structural analysis will allow for differentiation of pathological and benign patterns of non-compaction. In a large cohort of adult patients with suspected NCCM we will perform in-depth phenotyping, including clinical information, pedigree data, genetics, echocardiography and MRI, and follow patients for up to 3 years. We will apply machine-learning based analytics to develop predictive models and compare their performance to currently used models and treatment criteria. Secondly, in a subset of patients we will perform high-resolution cardiac CT for detailed structural characterization of the myocardial wall. Novel analytical methods will be developed to characterize the 3D architectural complexity based on pathophysiological hypothesis, but also using hypothesis-free analyses of raw images using deep learning techniques. In addition, we will investigate associations between myocardial structure and regional contractile function, as assessed by echo and MRI. The aim of this proposal is to identify a structural signature associated with pathological non-compaction and improve developed risk prediction models. This international consortium dedicated to NCCM will be the first to collect genetic and multi-modality imaging data. Discovery of pathological structural signatures through innovative imaging techniques, in relation to myocardial contractility, will advance our understanding of NCCM. There is an urgent clinical need for diagnostic techniques that detect pathological non-compaction and identify patients at risk of devastating complications. This study is clinically relevant because the developed predictive models may permit more effective, personalized preventive care in a growing number of individuals diagnosed with non-compaction cardiomyopathy.

总结