Background: Medical imaging and the resultant ionizing radiation exposure is a public concern due to the possible risk of cancer induction.

Objectives: To assess the accuracy of ultra-low-dose (ULD) chest computed tomography (CT) with denoising versus normal dose (ND) chest CT using the Lung CT Screening Reporting and Data System (Lung-RADS).

Methods: This prospective single-arm study comprised 52 patients who underwent both ND and ULD scans. Subsequently AI-based denoising methods were applied to produce a denoised ULD scan. Two chest radiologists independently and blindly assessed all scans. Each scan was assigned a Lung-RADS score and grouped as 1 + 2 and 3 + 4.

Results: The study included 30 men (58%) and 22 women (42%); mean age 69.9 ± 9 years (range 54–88). ULD scan radiation exposure was comparable on average to 3.6–4.8% of the radiation depending on patient BMI. Denoising increased signal-to-noise ratio by 27.7%. We found substantial inter-observer agreement in all scans for Lung-RADS grouping. Denoised scans performed better than ULD scans when negative likelihood ratio (LR-) was calculated (0.04–-0.08 vs. 0.08–0.12). Other than radiation changes, diameter measurement differences and part-solid nodules misclassification as a ground-glass nodule caused most Lung-RADS miscategorization.

Conclusions: When assessing asymptomatic patients for pulmonary nodules, finding a negative screen using ULD CT with denoising makes it highly unlikely for a patient to have a pulmonary nodule that requires aggressive investigation. Future studies of this technique should include larger cohorts and be considered for lung cancer screening as radiation exposure is radically reduced.