Tuesday, December 3 | 11:00 a.m.-11:10 a.m. | SSG02-04 | Room S104A
Automated calculation of extracellular volume on 3D CT is as accurate as manual measurements on conventional CT and MRI, and it may facilitate the diagnosis and prognosis of cardiac amyloidosis, according to researchers from France.Cardiac extracellular volume is a quantitative parameter that helps in the diagnosis of several heart diseases. Traditionally, clinicians have measured extracellular volume on conventional MRI and CT using a manual technique that is time-consuming and often imprecise, Dr. Mohamed Nouri from Henri Mondor University Hospital told AuntMinnie.com.
Seeking to improve the efficiency of measuring extracellular volume, Nouri and colleagues developed software capable of automatically performing this task on 3D CT scans of the heart. They validated the software on the cases of dozens of patients with cardiac amyloidosis who underwent noncontrast and contrast-enhanced cardiac CT.
The software performed 3D segmentation of the cardiac CT scans and automatically measured the extracellular volumes of every patient. The segmentation process took approximately 20 seconds.
The researchers found that the automated and manual extracellular volume measurements correlated very well, with a coefficient of determination of 0.8, suggesting that the technique is feasible for testing in a broader patient cohort.
"The software allows a global and segmented extracellular volume measurement and provides a bull's-eye representation of the measurements performed and will allow this parameter to be integrated into daily practice," Nouri 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&dpr=2&fit=crop&h=167&q=70&w=250)
