1. Artificial intelligence software in pulmonary nodule assessment
- Author
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Dugal Smith, Phillip Melville, Nicolette Fozzard, Jason Zhang, Patricia Deonarine, Selvanayagam Nirthanan, and Pathmanathan Sivakumaran
- Subjects
Lung Neoplasms ,Artificial Intelligence ,Humans ,Multiple Pulmonary Nodules ,General Medicine ,Sensitivity and Specificity ,Software ,Education ,Retrospective Studies - Abstract
Background: This study tests the impact of the addition of autonomous computed tomography (CT) interpreting software to radiologist assessment of pulmonary nodules. Methods: Computed tomography scans for nodule assessment were identified retrospectively. Lung cancer risk factors, initial radiologist (RAD) report, Philips Lung Nodule software report (computer-aided nodule (CAD)) and radiologist report following the review of CT images and CAD (RAD + CAD) were collected. Follow-up recommendations based on current guidelines were derived from each report. Results: In all, 100 patients were studied. Median maximal diameter of the largest nodule reported by RAD and RAD + CAD were similar at 10.0 and 9.0 mm, respectively ( p = 0.06) but were reported as larger by CAD at 11.8 mm ( p Discussion: This study suggests that autonomous software use can alter radiologist assessment of pulmonary nodules such that suggested follow-up is altered.
- Published
- 2022