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Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Real-world Evaluation of Computer-aided Pulmonary Nodule Detection Software Sensitivity and False Positive Rate
Raquelle El Alam1,2, Khushboo Jhala1,2, Mark M Hammer1,2
1Department of Radiology, Brigham and Women's Hospital.
Purpose:
Evaluate the false positive rate (FPR) of nodule detection software in real-world use.
Materials And Methods:
A total of 250 nonenhanced chest computed tomography (CT) examinations were randomly selected from an academic institution and submitted to the ClearRead nodule detection system (Riverain Technologies). Detected findings were reviewed by a thoracic imaging fellow. Nodules were classified as true nodules, lymph nodes, or other findings (branching opacity, vessel, mucus plug, etc.), and FPR was recorded. FPR was compared with the initial published FPR in the literature. True diagnosis was based on pathology or follow-up stability. For cases with malignant nodules, we recorded whether malignancy was detected by clinical radiology report (which was performed without software assistance) and/or ClearRead.
Results:
Twenty-one CTs were excluded due to a lack of thin-slice images, and 229 CTs were included. A total of 594 findings were reported by ClearRead, of which 362 (61%) were true nodules and 232 (39%) were other findings. Of the true nodules, 297 were solid nodules, of which 79 (27%) were intrapulmonary lymph nodes. The mean findings identified by ClearRead per scan was 2.59. ClearRead mean FPR was 1.36, greater than the published rate of 0.58 ( P <0.0001). If we consider true lung nodules <6 mm as false positive, FPR is 2.19. A malignant nodule was present in 30 scans; ClearRead identified it in 26 (87%), and the clinical report identified it in 28 (93%) ( P =0.32).
Conclusion:
In real-world use, ClearRead had a much higher FPR than initially reported but a similar sensitivity for malignant nodule detection compared with unassisted radiologists.
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