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.
The proposed research is relevant to the public health because recognition of pathological myocardial non- compaction and identification of patients at risk for embolic stroke, ventricular arrhythmia and sudden cardiac death will allow for more effective use of life-saving measures, but also avoid unnecessary ICD implantations and anticoagulation in healthy individuals with benign hypertrabeculation. Thus, the proposed research is relevant to the NIH's mission that pertains to the discovery of fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability.
