Coronary CT Angiogram - Prognostic Value of Adverse Plaque Features in Guiding Treatment (CT-PLAQUE)
NCT07212751
All-cause Death, Arterial Occlusive Diseases
Hong Kong
View Trial DetailsNCT Number: NCT07544277
Coronary artery disease (CAD) is the leading cause of mortality and morbidity worldwide. Coronary Computed Tomography angiography (CCTA) gained a pivotal clinical role for excellent sensitivity in rule-out CAD, but has limited specificity for a tendency to overestimate stenoses and for the lack of information about their hemodynamic impact. Fractional Flow Reserve derived from CT (FFR-CT) and stress CT perfusion (CTP) have been recently proposed to complement CCTA in the non-invasive assessment of myocardial ischemia, increasing the specificity and avoiding unnecessary catheterization. However, on energy-integrating (EID)-CT, FFR-CT has suboptimal performance, while CTP is affected by high radiation exposure. Both these approaches may benefit by the introduction of the new Photon Counting Detector (PCD)-CT technology, but data completely lacks. Aim of the study is to assess the performance of PCD-CT in the identification of significant CAD combining CCTA with FFR-CT and spectral CTP.
Trial opening soon.
Get Notified18 year and older
All sexes
Observational
Azienda Ospedaliero-Universitaria Sant'Andrea, Roma, RM, Italy
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: 36 months
CCTA-derived stenosis and plaque characterization; CT-FFR values from commercial and in-house solutions; CTP-derived iodine uptake measurement; invasive FFR as reference standard. Comparison of off-site versus on-site CT-FFR solutions determined against invasive FFR.
Time frame: 36 months
Coronary stenosis severity at CCTA; myocardial iodine uptake at baseline, rest, and stress CTP; diagnostic performance of iodine uptake values against invasive FFR.
Time frame: 36 months
Blinded analysis of baseline CCTA for qualitative and quantitative plaque characteristics, with correlation to invasive FFR. Inter-rater agreement assessment between two expert readers. Deep learning-based radiomic feature extraction from plaques and vessel walls. Development of a data-driven feature selection pipeline to predict hemodynamically significant stenosis from CCTA data, using invasive FFR as reference.
Contact information is provided by the study sponsor or research team.
Anna Palmisano, Medicine and Surgery
CONTACT
Davide Vignale, Medicine and Surgery
CONTACT
IRCCS San Raffaele
Other
Acronym: SURE-CT
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