Coronary Artery Disease Clinical Trial
— APOLLOOfficial title:
AI Driven National Platform for CT cOronary Angiography for clinicaL and industriaL applicatiOns Registry (APOLLO)
NCT number | NCT05509010 |
Other study ID # | APOLLO |
Secondary ID | |
Status | Recruiting |
Phase | |
First received | |
Last updated | |
Start date | October 1, 2021 |
Est. completion date | December 2027 |
The overall aim is to build an AI driven national Platform for CT cOronary angiography for clinicaL and industriaL applicatiOns (APOLLO) for automated anonymization, reporting, Agatston scoring and plaque quantification in CAD. It is a "one-stop" platform spanning diagnosis to clinical management and prognosis, and aid in predicting pharmacotherapy response.
Status | Recruiting |
Enrollment | 8000 |
Est. completion date | December 2027 |
Est. primary completion date | December 2027 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 21 Years to 80 Years |
Eligibility | Inclusion Criteria: 1. Age =21 years old 2. Signed informed consent 3. Clinically indicated for evaluation by CTCA Exclusion Criteria: 1. Individuals unable to provide informed consent 2. Known complex congenital heart disease 3. Planned invasive angiography for reasons other than CAD 4. Non-cardiac illness with life expectancy < 2 years 5. Pregnancy 6. Concomitant participation in another clinical trial in which subject is subject to investigational drug or device 7. Cardiac event and/or coronary revascularization (percutaneous coronary intervention (PCI) and/or coronary artery bypass grafting (CABG) and/or valvular repair/replacement prior to CTCA 8. Glomerular Filtration Rate = 30mL/min 9. Known allergy to iodinated contrast agent 10. Contraindications to beta blockers or nitroglycerin or adenosine |
Country | Name | City | State |
---|---|---|---|
Singapore | National Heart Centre Singapore | Singapore | |
Singapore | National University Hospital | Singapore | |
Singapore | Tan Tock Seng Hospital | Singapore |
Lead Sponsor | Collaborator |
---|---|
National Heart Centre Singapore | Agency for Science, Technology and Research |
Singapore,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | AI precision toolkits: AI stenosis reporting | Stenosis reporting: Severity of stenosis and accurate anatomical localization of stenosis.
The significance of a stenosis is determined by visual estimation of the maximal grade of luminal narrowing caused by the plaque. As recommended in SCCT guideline (Leipsic et al., 2014) , coronary stenosis can be graded as minimal, mild, moderate, severe and total occluded separately. Following the guideline, a stenosis will be classified as obstructive and non-obstructive. The location of the stenosis uses the SCCT model (Leipsic et al., 2014) |
baseline | |
Primary | AI precision toolkits: Agatston scoring | Agatston scoring: Agatston scoring of calcified plaque. As recommended in SCCT clinical practical guidelines (Leipsic et al., 2014), Agatston scoring programs generally identify pixels that exceed 130 HU as a level corresponding to calcium on a non-contrast study (Agatston et al., 1990) . The reader needs to identify each lesion discrete calcific focus) in each vessel distribution. The summed score for each vessel is generated by the scoring program based on an area-density (Agatston score) (Agatston et al., 1990) measurement of each calcified focus. The total coronary Agatston score is the sum of all calcified lesions in all coronary beds. | baseline | |
Primary | AI precision toolkits: Plaque | Plaque analysis: Plaque volume, burden, type and anatomical locations. Coronary segmentation and plaque analysis is performed for segments with diameter =1.5 mm. Location of plaque uses the SCCT model (Leipsic et al., 2014). For each plaque, the reader marks its start-and end-points, quantifies plaque area,volume and plaque burden, and specifies its type (non-calcified, calcified, or mixed) (Achenbach et al., 2004) . Additionally, non-calcified plaque can be further divided into low attenuation plaque (LAP). A HU <30 will signify LAP and >30 will signify non-LAP. | baseline | |
Primary | AI precision toolkits: EAT analysis | EAT analysis: Total volume and anatomical locations. EAT and pericardial adipose tissue (PAT) are metabolically active fat surrounding the coronary artery and the heart, being associated with increased risk of cardiovascular disease (Villasante et al, 2019) . EAT can be quantified on non-contrast CT scans. The annotations on the CT scans are obtained by manually drawing the pericardium first to define the region. EAT is identi?ed using the adipose tissue attenuation references between -190 and -30 HU (Oikonomou et al., 2018) . Due to the CT scan noise and changing of attenuation, the HU value of fat can vary, so the final EAT region is verified by an experienced radiologist or cardiologist. | baseline | |
Secondary | AI outcome analysis | 1. Mortality (All-cause and/or cardiovascular) | one to five years from baseline | |
Secondary | AI outcome analysis | Major-adverse cardiovascular events (myocardial infarction, stroke, heart failure, revascularisation, arrhythmias, etc) | one to five years from baseline | |
Secondary | AI outcome analysis | Re-hospitalisation | one to five years from baseline |
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