Feasibility of a Deep Learning-based Algorithm for Non-invasive Assessment of Vulnerable Coronary Plaque
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
AgeNot listed
SponsorGE Healthcare
About this trial
The primary objective of this study is to assess the accuracy in terms of sensitivity, specificity, negative and positive predicted values of the DL-based algorithm with respect to correct identification of the plaque and associated vulnerability grade.
Eligibility criteria
Qualifiers
Patients referred for a clinically indicated CCTA and ICA with OCT imaging examinations;
Diagnosis of chronic coronary syndrome, known CAD, or stable angina; AND,
Patients with ACS that may undergo a CCTA and not refer directly to the Cath lab for revascularization procedures.
Disqualifiers
Contradictions to contrast;
Contraindications for beta blocker;
BMI >30;
High heart rate ≥75 BPM;
Trial design
Treatments tested in this trial
- Deep Learning-based Vulnerable Plaque Detection and Assessment Tool
Treatment groups
200 Participants
are divided into 1 treatment groupSponsors and collaborators
GE Healthcare
Lead sponsor
Azienda Socio-Sanitaria Territoriale di Pavia
Collaborator
Source ClinicalTrials.gov