Coronary Artery Disease
Conditions
Brief summary
Develop time-to-event prediction and plaque phenotype classification models for patients with known or suspected coronary artery disease.
Detailed description
Develop time-to-event prediction and plaque phenotype classification models using plaque morphology and composition assessment of CTA which has been validated by histology, applied to representative cohort of patients. Generalizability of models is enhanced by using validated rather than only raw image inputs. Demographic, clinical, and outcome data is collected for enrolled patients as well as last known well dates.
Interventions
DEVICEvascuCAP
time to event and phenotype classification model
Sponsors
Medical University of South Carolina
Elucid Bioimaging Inc.
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Subject must have successfully completed at least one (possibly multiple) CCTA for known or suspected coronary artery disease, which was positive for coronary atherosclerotic changes. * Subject must have been ≥ 18 years of age at the time of the CCTA
Exclusion criteria
* Subject has a history of percutaneous coronary intervention (PCI) with stent implantation and/or coronary artery bypass grafting (CABG) * CCTA taken less than 3 months after deployment of new scanner * Subject with insufficient CCTA image quality
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Time to adverse outcome | >= 2 years | Develop time-to-event model for major adverse cardiac events (MACE) prediction on large retrospective cohort (and enable a prospective collection subsequent to this study). Consistent with this primary endpoint is the evaluation of all imaging-derived data that has a bearing on the diagnosis and prognosis of the subject. |
Countries
United States
Outcome results
None listed