Sunday, December 1 | 11:35 a.m.-11:45 a.m. | SSA11-06 | Room N230B
Dual-energy CT (DECT) may be more cost-effective than conventional CT or MRI for evaluating incidentally detected renal lesions, based on simulations from an analytical model that serve as the subject of this study to be presented on Sunday.The researchers from Stanford University developed a Markov model to estimate lifetime costs and life expectancy for 64-year-old patients at their institution whose routine imaging exams revealed incidental, indeterminate kidney lesions that were 4 cm or smaller.
Clinicians occasionally encounter incidental renal lesions in otherwise healthy individuals that warrant additional imaging workup. Determining the best imaging modality to examine these cases could help lower costs and reduce the risk of potential complications down the line, Drs. Domenico Mastrodicasa and Bhavik Patel told AuntMinnie.com.
Mastrodicasa, Patel, and colleagues used their Markov model to perform a Monte Carlo simulation comparing three different strategies for evaluating renal lesions involving MRI, multiphase single-energy CT, or single-phase dual-energy CT.
Their comparative analysis indicated that DECT was the most effective modality among the three for most clinical scenarios, with relatively more accurate characterization of the lesions and also a lower overall cost. The lower cost of using DECT was primarily a result of its higher specificity, compared with the other imaging modalities, which could help reduce the need for unnecessary follow-up imaging or treatment, the researchers found.
"Our results may improve decision-making regarding optimal imaging strategy for renal lesion workup," Mastrodicasa said. "Moreover, our findings could be used to refine current imaging recommendation guidelines and could improve the adoption of DECT."


















![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)

