Monday, November 26 | 11:50 a.m.-12:00 p.m. | SSC01-09 | Room S504CD
Combining coronary CT angiography (CCTA) with stress CT perfusion increases the accuracy of diagnosing in-stent restenosis in patients with heart disease, according to this study to be presented on Monday.Researchers from Centro Cardiologico Monzino in Italy investigated the viability of evaluating possible in-stent restenosis with CCTA, CT perfusion, or the two tests together, compared with the gold standard -- invasive coronary angiography (ICA).
Using these two imaging tests instead of ICA would provide clinicians with a noninvasive alternative to evaluating stents and also involve considerably less radiation, Dr. Saima Mushtaq told AuntMinnie.com.
Among a cohort of 98 patients suspected of having in-stent restenosis, Mushtaq and colleagues found that both CCTA and CT perfusion alone offered high diagnostic accuracy relative to ICA.
The overall performance of CT perfusion was better than that of CCTA: CT perfusion had statistically significant increases in accuracy, sensitivity, and specificity, compared with CCTA, as well as fewer image artifacts and a clearer depiction of small stents. However, combining both tests improved diagnosis even further, with a combined accuracy exceeding 95%.
"CT perfusion is of great value for properly assessing patients who underwent complex and sometimes repeated percutaneous coronary intervention with multiple stent implantations," Mushtaq said.



















![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&fit=crop&h=112&q=70&w=112)