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Publication year
2011Source
Academic Radiology, 18, 12, (2011), pp. 1507-14ISSN
Annotation
01 december 2011
Publication type
Article / Letter to editor

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Organization
Radiology
Journal title
Academic Radiology
Volume
vol. 18
Issue
iss. 12
Page start
p. 1507
Page end
p. 14
Subject
ONCOL 5: Aetiology, screening and detectionAbstract
RATIONALE AND OBJECTIVES: To evaluate the impact of computer-aided detection (CAD, IQQA-Chest; EDDA Technology, Princeton Junction, NJ) used as second reader on the detection of small pulmonary nodules in chest radiography (CXR). MATERIALS AND METHODS: A total of 113 patients (mean age 62 years) with CT and CXR within 6 weeks were selected. Fifty-nine patients showed 101 pulmonary nodules (diameter 5-15mm); the remaining 54 patients served as negative controls. Six readers of varying experience individually evaluated the CXR without and with CAD as second reader in two separate reading sessions. The sensitivity per lesion, figure of merit (FOM), and mean false positive per image (mFP) were calculated. Institutional review board approval was waived. RESULTS: With CAD, the sensitivity increased for inexperienced readers (39% vs. 45%, P < .05) and remained unchanged for experienced readers (50% vs. 51%). The mFP nonsignificantly increased for both inexperienced and experienced readers (0.27 vs. 0.34 and 0.16 vs. 0.21). The mean FOM did not significantly differ for readings without and with CAD irrespective of reader experience (0.71 vs. 0.71 and 0.84 vs. 0.87). All readers together dismissed 33% of true-positive CAD candidates. False-positive candidates by CAD provoked 40% of all false-positive marks made by the readers. CONCLUSION: CAD improves the sensitivity of inexperienced readers for the detection of small nodules at the expense of loss of specificity. Overall performance by means of FOM was therefore not affected. To use CAD more beneficial, readers need to improve their ability to differentiate true from false-positive CAD candidates.
This item appears in the following Collection(s)
- Academic publications [227693]
- Electronic publications [107311]
- Faculty of Medical Sciences [86198]
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