Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2025
Incremental diagnostic value of artificial intelligence-derived coronary artery calcium in 18F-flurpiridaz positron emission tomography myocardial perfusion imaging.
СтатьяКлиническое исследование III фазыНазвание и аннотация: Перевод пока не подготовлен
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Barrett Orit, Shanbhag Aakash, Zaid Ryan, Miller Robert J H, Lemley Mark, Builoff Valerie, Liang Joanna X, Kavanagh Paul B, Buckley Christopher, Dey Damini, Berman Daniel S, Slomka Piotr J
Аннотация
BACKGROUND: Positron emission tomography (PET) myocardial perfusion imaging (MPI) is a powerful tool for predicting coronary artery disease (CAD). Coronary artery calcium (CAC) provides incremental risk stratification to PET-MPI and enhances diagnostic accuracy. We assessed the additive value of the CAC score, derived from PET/CT attenuation maps to stress total perfusion deficit (TPD) results using the novel 18F-flurpiridaz tracer in detecting significant CAD.
METHODS: Patients from the 18F-flurpiridaz phase III clinical trial who underwent PET/CT MPI with the 18F-flurpiridaz tracer, had available computed tomography attenuation correction (CTAC) scans for CAC scoring, and underwent invasive coronary angiography (ICA) within a 6-month period between 2011 and 2013 were included. TPD was quantified automatically, and CAC scores from CTAC scans were assessed using artificial intelligence (AI)-derived segmentation and manual scoring. Obstructive CAD was defined as ≥50% stenosis in the left main (LM) artery, or 70% or more stenosis in any of the other major epicardial vessels. Prediction performance for CAD was assessed by comparing the area under receiver operating characteristic curve (AUC) for stress TPD alone and in combination with the CAC score.
RESULTS: Among 498 patients (72% males, median age 63 years) 30.1% had CAD. Incorporating the CAC score resulted in a greater AUC with manual scoring (AUC = .87, 95% confidence interval [CI]: .34-.90; P = .015) and AI-based scoring (AUC = .88, 95% CI: .85-.90; P = .002) compared to stress TPD alone (AUC = .84, 95% CI: .80-.92).
CONCLUSIONS: Combining automatically derived TPD and CAC score enhances 18F-flurpiridaz PET MPI accuracy in detecting significant CAD, offering a method that can be routinely used with PET/CT scanners without additional scanning or technologist time.
METHODS: Patients from the 18F-flurpiridaz phase III clinical trial who underwent PET/CT MPI with the 18F-flurpiridaz tracer, had available computed tomography attenuation correction (CTAC) scans for CAC scoring, and underwent invasive coronary angiography (ICA) within a 6-month period between 2011 and 2013 were included. TPD was quantified automatically, and CAC scores from CTAC scans were assessed using artificial intelligence (AI)-derived segmentation and manual scoring. Obstructive CAD was defined as ≥50% stenosis in the left main (LM) artery, or 70% or more stenosis in any of the other major epicardial vessels. Prediction performance for CAD was assessed by comparing the area under receiver operating characteristic curve (AUC) for stress TPD alone and in combination with the CAC score.
RESULTS: Among 498 patients (72% males, median age 63 years) 30.1% had CAD. Incorporating the CAC score resulted in a greater AUC with manual scoring (AUC = .87, 95% confidence interval [CI]: .34-.90; P = .015) and AI-based scoring (AUC = .88, 95% CI: .85-.90; P = .002) compared to stress TPD alone (AUC = .84, 95% CI: .80-.92).
CONCLUSIONS: Combining automatically derived TPD and CAC score enhances 18F-flurpiridaz PET MPI accuracy in detecting significant CAD, offering a method that can be routinely used with PET/CT scanners without additional scanning or technologist time.