Tuesday, November 28 | 11:00 a.m.-11:10 a.m. | SSG02-04 | Room S504AB
Customizing CT contrast dose while also improving efficacy and patient safety is an ongoing challenge. In this presentation, U.S. researchers will offer a way to do just that for coronary CT angiography (CCTA) exams.Traditionally, physicians have used contrast media in CCTA following a one-size-fits-all approach, Dr. Philipp von Knebel Doeberitz told AuntMinnie.com. Automated attenuation-based tube voltage selection (ATVS) algorithms, however, can automatically select appropriate tube voltages for CCTA exams, which, in turn, can optimize contrast dose protocol.
Researchers from the Medical University of South Carolina used an ATVS algorithm to fine-tune the contrast medium protocol of the CCTA exams of various patients. The ATVS algorithm divided the patients into seven groups based on their vessel attenuation profiles. Physicians then scanned each group using a different contrast dose corresponding to the distinct tube voltage determined by ATVS.
"We were able to safely achieve contrast dose reductions of up to 50% while maintaining diagnostic attenuation within the coronary arteries by reducing the iodine delivery rate according to tube voltage," von Knebel Doeberitz said.
Now that they have successfully investigated the possibility of tailoring CCTA parameters, they can start moving toward personalized contrast media injection, he 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&dpr=2&fit=crop&h=167&q=70&w=250)
