The American College of Radiology (ACR) Committee on Incidental Findings updated its recommendations for managing incidental liver lesions found on CT. The new guidelines were published online September 16 in a white paper in the Journal of the American College of Radiology.
Drawing from published data and expert opinion, the committee updated an algorithm for handling incidental liver lesions found in asymptomatic adult patients on CT scans. The algorithm should not be applied to the management of previously suspected or known lesions, noted lead author Dr. Richard Gore and colleagues. The table below provides an overview of the algorithm.
| Algorithm for managing incidental liver lesions found on CT | |||||
| Course of action | Low-risk patients | High-risk patients | |||
| Lesion size < 1 cm | Lesion size ≥ 1 cm | Lesion size < 1 cm | Lesion size ≥ 1 cm | ||
| Observation | Generally benign | If benign features | If suspicious features | Generally benign | Usually suspicious or flash-filling features |
| Management | No additional workup | No additional workup | Prompt MRI | MRI advised in 3-6 months | Prompt MRI or biopsy |
These are recommendations and should not be viewed as "standard of care," according to the committee. The group hopes that this update will ultimately minimize the amount of unnecessary patient workup.
![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)
