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Eur Radiol. 2012 Oct;22(10):2076-84. doi: 10.1007/s00330-012-2437-y. Epub 2012 Jul 20.

Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume.

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  • 1Center for Medical Imaging - North East Netherlands, Department of Radiology, University of Groningen/University Medical Center Groningen, P.O. Box 30.001, 9700RB, Groningen, the Netherlands.

Abstract

OBJECTIVE:

To evaluate performance of computer-aided detection (CAD) beyond double reading for pulmonary nodules on low-dose computed tomography (CT) by nodule volume.

METHODS:

A total of 400 low-dose chest CT examinations were randomly selected from the NELSON lung cancer screening trial. CTs were evaluated by two independent readers and processed by CAD. A total of 1,667 findings marked by readers and/or CAD were evaluated by a consensus panel of expert chest radiologists. Performance was evaluated by calculating sensitivity of pulmonary nodule detection and number of false positives, by nodule characteristics and volume.

RESULTS:

According to the screening protocol, 90.9 % of the findings could be excluded from further evaluation, 49.2 % being small nodules (less than 50 mm(3)). Excluding small nodules reduced false-positive detections by CAD from 3.7 to 1.9 per examination. Of 151 findings that needed further evaluation, 33 (21.9 %) were detected by CAD only, one of them being diagnosed as lung cancer the following year. The sensitivity of nodule detection was 78.1 % for double reading and 96.7 % for CAD. A total of 69.7 % of nodules undetected by readers were attached nodules of which 78.3 % were vessel-attached.

CONCLUSIONS:

CAD is valuable in lung cancer screening to improve sensitivity of pulmonary nodule detection beyond double reading, at a low false-positive rate when excluding small nodules.

KEY POINTS:

• Computer-aided detection (CAD) has known advantages for computed tomography (CT). • Combined CAD/nodule size cut-off parameters assist CT lung cancer screening. • This combination improves the sensitivity of pulmonary nodule detection by CT. • It increases the positive predictive value for cancer detection.

[PubMed - indexed for MEDLINE]
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