Monday, December 2 | 11:20 a.m.-11:30 a.m. | SSC04-06 | Room S102CD
The combination of fractional flow reserve CT (FFR-CT) and conventional coronary CT angiography (CCTA) proved to be effective at ruling out major adverse cardiac events for emergency patients with acute chest pain in this study to be discussed on Monday.FFR-CT is increasingly being integrated into the diagnostic workup for chronic stable chest pain, though its utility for acute chest pain is less understood, noted Dr. Richard Bayer and colleagues from the Medical University of South Carolina.
The researchers, thus, set out to determine the potential benefits of using FFR-CT in addition to CCTA to evaluate emergency chest pain. They used commercially available software for their FFR-CT analysis, which had a turnaround time of approximately three and a half hours.
In all, they examined 31 patients with acute chest pain; roughly half were positive for stenosis on CCTA and had an FFR-CT score of less than 0.8. Among those with a positive FFR-CT, 20% had a major adverse cardiac event within the first 30 days following initial examination. In contrast, only one patient with a negative FFR-CT (6%) had a major adverse event.
The findings of this preliminary study suggested that FFR-CT plus CCTA could help estimate the risk of major adverse events in emergency patients more effectively than other evaluation strategies, including CCTA alone. Ultimately, FFR-CT could help differentiate between patients who would benefit from further invasive testing and those who could safely be discharged, the researchers concluded.


















![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)

