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Proceedings Paper

Identification of missed pulmonary nodules on low-dose CT lung cancer screening studies using an automatic detection system
Author(s): Carol L. Novak; Li Fan; Jianzhong Qian; Guo-Qing Wei; David P. Naidich M.D.
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Paper Abstract

Multi-slice CT (MSCT) scanners allow nodules as small as 3mm to be identified during screening. However the associated large data sets make it challenging for radiologists to identify all small nodules in a reasonable amount of time. Computer-aided detection may play a critical role in identifying missed nodules. 13 MSCT screening studies, initially interpreted as "non-actionable" by a radiologist, were selected from participants in a lung cancer screening study. The study protocol defines "actionable" studies as those containing at least 1 solid non-calcified nodule larger than 3mm, for which follow-up studies are recommended to exclude interval growth. An automatic detection algorithm was applied to the 13 studies to determine whether it might detect missed nodules, and whether any of these were of sufficient size to be considered "actionable". There were a total of 138 automatically detected candidate nodules, an average of 10.6 per patient. 83 candidates were characterized as true positives, yielding a positive predictive value of 60.1%. 10 automatically detected candidates were judged to be actionable nodules greater than 3mm in diameter. 6 of 13 (46%) patients had at least one "actionable" finding detected by the computer that had been overlooked in the initial exam.

Paper Details

Date Published: 22 May 2003
PDF: 9 pages
Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); doi: 10.1117/12.480101
Show Author Affiliations
Carol L. Novak, Siemens Corporate Research, Inc. (United States)
Li Fan, Siemens Corporate Research, Inc. (United States)
Jianzhong Qian, Siemens Corporate Research, Inc. (United States)
Guo-Qing Wei, Siemens Corporate Research, Inc. (United States)
David P. Naidich M.D., New York Univ. Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 5034:
Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment
Dev P. Chakraborty; Elizabeth A. Krupinski, Editor(s)

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