Photon-counting CT shows promise for better diagnostic performance compared to conventional CT, according to research presented on Sunday at the RSNA 2021 meeting.
"It has the potential for better contrast and noise performance compared to scintillator-based energy integration detector [CT]," presenter Richard Thompson, PhD, of Canon Medical Research Institute USA in Vernon Hills, IL, told session attendees.
Thompson and colleagues conducted a study using a phantom to compare image quality between a prototype photon-counting CT device and a conventional CT system, analyzing for noise, spatial resolution, and accuracy.
The photon-counting prototype was based on a Canon Aquilion One Vision system. Its smallest detector pixel size is 342 µm; each pixel produces measurements of up to six energy bins starting from 20 keV, Thompson said. (Photon-counting detectors generate energy-specific images that are assigned to energy bins in small ranges.)
The investigators scanned a 40-cm water phantom and Sun Nuclear's Gammex multienergy phantom with both the photon-counting prototype and the conventional scanner, comparing both counting and spectral images. The photon-counting CT device produced images with 20% to 25% reduced noise compared to conventional CT and had higher spatial resolution, from 0.60 lp/mm for conventional CT to 0.69 lp/mm for the photon-counting device.
"The initial performance of this prototype photon-counting CT system in both counting and spectral imaging modes demonstrates its potential to achieve better diagnostic performance with reduced dose," Thompson 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)
