Monday, November 30 | 10:50 a.m.-11:00 a.m. | SSC10-03 | Room S504CD
Size-specific dose estimates (SSDEs) are credited with bringing new levels of accuracy to radiation dose estimates by allowing dose to be tailored to patient size in a straightforward way. But how well SSDE works with automated tube current modulation, another mainstay of CT imaging, is still up for debate.In their study, Kyle McMillan and colleagues from the Mayo Clinic in Rochester, MN, wanted to know if SSDE remained a valid measurement in the face of automated tube current modulation -- a development that could affect CT dose index volume (CTDIvol).
"In a previous paper, it was asserted that the concept of CTDIvol breaks down mathematically when tube current modulation is used," wrote study co-author Cynthia McCollough, PhD, in an email to AuntMinnie.com. "Since SSDE relies on CTDIvol and most modern body imaging is performed with the use of tube current modulation, this could affect the accuracy of SSDE calculations."
The study, performed with a 128-detector-row scanner, aimed to use previously validated Monte Carlo methods to determine the accuracy of SSDE, which represents the mean dose in the center of the scan region.
The results showed strong correlation between CTDIvol-normalized effective dose and water-equivalent diameter, according to the researchers. A general relationship between CTDIvol-to-effective-dose conversion coefficients and patient size is likely sufficient to estimate SSDE for exams acquired with both fixed and modulated tube currents.
![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)
