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Updated: Jan 8, 2026
Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Manuscript title: Impact of vessel suppression AI on reading efficiency and nodule detection in CT chest
Kevin T Chorath1, Evan Jacobs2, Ken Tharp1
1Department of Radiology, University of Washington, Seattle, WA, USA.
Background:
Vessel suppression (VS) software enhances pulmonary nodule conspicuity by attenuating vascular and fissural structures, but real-world impact on clinical workflows remains uncertain.
Methods:
We retrospectively analyzed 8,835 chest CT examinations (January 2023-February 2024) interpreted at a single academic institution, comparing pre- and post-VS implementation. Reads by residents and faculty were assessed separately. Outcomes included interpretation time and pulmonary nodule detection, extracted using natural language processing with manual validation.
Results:
Among residents, mean read time decreased from 19.1 to 12.2 minutes (p<0.001), with improved detection of punctate nodules (13.0% vs 24.2%, p<0.001). Faculty showed reduced mean read time (6.6 vs 5.2 minutes, p<0.001) and modest improvement in punctate nodule detection (26.0% vs 29.5%, p=0.042).
Conclusion:
VS improved reading efficiency for both trainees and faculty and substantially increased small-nodule detection among residents and attending radiologists. While the clinical significance of detecting sub-2 mm nodules remains uncertain, efficiency gains support the value of VS in high-volume and training environments. Further study is warranted to define downstream clinical impact and guide management of incidentally detected small nodules.
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