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Comparing senior residents performance to radiologists in lung cancer detection
Author(s): Badera Al Mohammad; Stephen L. Hillis; Warren Reed; Charbel Saade; Patrick C. Brennan
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Paper Abstract

Background: Lung cancer, the leading cause of cancer death worldwide, can be survived if early detection through screening programs occurs. However if a large scale lung cancer screening program needs to be implemented, it may require a substantial increase in qualified readers’ numbers. To investigate whether senior radiology residents may potentially increase the pool of available readers in screening for lung cancer, by comparing their performance with that of board-certified radiologists. Methodology: Twenty board-certified radiologists and ten senior residents read sixty chest CT scans. Thirty cases had surgically or biopsy-proven lung cancer and the remaining thirty were cancer-free cases. The cancer cases were validated by four expert radiologists who located the malignant lung nodules. Reader performance was evaluated by calculating sensitivity, location sensitivity, specificity, area under the receiver-operating-characteristic curve (AUC) and sensitivity at fixed specificity = 0.8. Results: Readers had the following (radiologists, residents) pairs of values: sensitivity = (0.782, 0.687); location sensitivity = (0.702, 0.597); specificity = (0.8, 0.83); AUC = (0.844, 0.85) and sensitivity for fixed 0.8 specificity = (0.74, 0.73). Conclusion: Initial findings suggest that senior residents compare favorably with board-certified radiologists based on the similarity of the AUCs and the summary ROC curves in terms of the ability to discriminate between diseased and non-diseased patients. However, they have demonstrated significantly lower detection sensitivity than board-certified radiologists and may require additional training, considering the importance of having high sensitivity when screening for cancer.

Paper Details

Date Published: 4 March 2019
PDF: 13 pages
Proc. SPIE 10952, Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, 109520Y (4 March 2019); doi: 10.1117/12.2512755
Show Author Affiliations
Badera Al Mohammad, The Univ. of Sydney (Australia)
Stephen L. Hillis, The Univ. of Iowa (United States)
Warren Reed, The Univ. of Sydney (Australia)
Charbel Saade, American Univ. of Beirut (Lebanon)
Patrick C. Brennan, The Univ. of Sydney (Australia)

Published in SPIE Proceedings Vol. 10952:
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

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