International Consortium for Multimodality Phenotyping in Adults With Non-compaction (NONCOMPACT)

Stanford University logo

Stanford University




Non-Compaction Cardiomyopathy


Diagnostic Test: Computed tomography (CT)
Diagnostic Test: Magnetic resonance imaging (MRI)
Diagnostic Test: Echocardiography

Study type


Funder types



SSU00099737 (Other Identifier)

Details and patient eligibility


Non-compaction cardiomyopathy (NCCM) is a heterogeneous, poorly understood disorder characterized by a prominent inner layer of loose myocardial tissue, and associated with heart failure, stroke, severe rhythm irregularities and death. For a growing population diagnosed with NCCM there is a need for better risk stratification to appropriately allocate (or safely withhold) these impactful preventive measures. The goal of this international consortium is 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. 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. Discovery of pathological structural signatures through innovative imaging techniques, in relation to myocardial contractility, will advance our understanding of NCCM.


600 estimated patients




18+ years old


No Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria:

  • ≥18 years old
  • Hypertrabeculation of the left ventricle fulfilling the echo-based Jenni criteria of NCCM
  • Clinical cardiac MRI examination performed or planned

Exclusion Criteria (general cohort):

  • Complex congenital disease (including transposition great arteries, tetralogy of Fallot, tricuspid atresia, truncus arteriosis, single ventricle, hypoplastic left heart, pulmonary atresia, double-outlet RV), neuromuscular disorders or isolated RV non-compaction
  • Inability to provide informed consent
  • Contra-indications to MRI, which apply if the clinical cardiac MRI has not yet been performed at the time of study enrollment: permanent pacemakers/ICDs, MRI contrast medium allergy, significant arrhythmia with highly irregular RR intervals, severe dyspnea with inability to lay flat/breath hold, inability to communicate with the MRI technician or follow commands for any reason (psychosis, agitation, etc.), other site-specific contra-indications to clinical MRI of the heart.

Exclusion Criteria (cardiac CT examination):

  • Age <21 years
  • Decompensated heart failure, or otherwise clinically unstable
  • BMI>40 kg/m2
  • Pregnancy (or cannot be ruled out)
  • Known iodine contrast medium allergy
  • Kidney dysfunction: eGFR<45 ml/min
  • Thyroid disease: toxic multinodular goiter, Graves' disease, Hashimoto's thyroiditis

Trial design

600 participants in 1 patient group

Multimodality imaging
Patients who have undergone echocardiography and cardiac MRI as part of their clinical management A research cardiac CT scan will be performed in eligible participants
Diagnostic Test: Echocardiography
Diagnostic Test: Magnetic resonance imaging (MRI)
Diagnostic Test: Computed tomography (CT)

Trial contacts and locations



Central trial contact

Katie DeSutter, BS; Koen Nieman, MD, PhD

Data sourced from

Clinical trials

Find clinical trialsTrials by location
© Copyright 2024 Veeva Systems