Lung nodule CAD software as a second reader: A multicenter study

被引:57
作者
White, Charles S. [1 ]
Pugatch, Robert [1 ]
Koonce, Thomas [2 ]
Rust, Steven W. [3 ]
Dharaiya, Ekta [4 ]
机构
[1] Univ Maryland, Med Ctr, Baltimore, MD 21201 USA
[2] Little Rock Hematol & Oncol Ctr, Little Rock, AR USA
[3] Battelle Mem Inst, Columbus, OH USA
[4] Philips Med Syst, Highland Hts, KY USA
关键词
CT; lung nodule; computer-aided detection;
D O I
10.1016/j.acra.2007.09.027
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Rationale and Objectives. The purpose of this multicenter, multireader study was to evaluate the performance of computed tomography (CT) lung nodule computer-aided detection (CAD) software as a second reader. Methods and Materials. The study involved 109 patients from four sites. The data were collected from a variety of multidetector CT scanners and had different scan parameters. Each chest CT scan was divided into four quadrants. A group of three expert thoracic radiologists identified nodules between 4 and 30 mm in maximum diameter within each quadrant. The standard of reference was established by a consensus read of these experienced radiologists. The cases were then interpreted by 10 other radiologist readers with varying degrees of experience, without and then with CAD software. These readers identified nodules and assigned an actionability rating to each quadrant before and after using CAD software. Receiver operating characteristic curves were used to measure the performance of the readers without and with CAD software. Results. The average increase in area under the curve for the 10 readers with CAD software was 1.9% for a 95% confidence interval (0.8-8.0%). The area under the curve without CAD software was 86.7% and with CAD software was 88.7%. A nonsignificant correlation was observed between the improvement in sensitivity and experience of the radiologists. The readers also showed a greater improvement in patients with cancer as compared to those without cancer. Conclusions. In this multicenter trial, CAD software was shown to be effective as a second reader by improving the sensitivity of the radiologists in detecting pulmonary nodules.
引用
收藏
页码:326 / 333
页数:8
相关论文
共 15 条
[1]   Lung image database consortium: Developing a resource for the medical imaging research community [J].
Armato, SG ;
McLennan, G ;
McNitt-Gray, MF ;
Meyer, CR ;
Yankelevitz, D ;
Aberle, DR ;
Henschke, CI ;
Hoffman, EA ;
Kazerooni, EA ;
MacMahon, H ;
Reeves, AP ;
Croft, BY ;
Clarke, LP .
RADIOLOGY, 2004, 232 (03) :739-748
[2]   Lung cancer: Performance of automated lung nodule detection applied to cancers missed in a CT screening program [J].
Armato, SG ;
Li, F ;
Giger, ML ;
MacMahon, H ;
Sone, S ;
Doi, K .
RADIOLOGY, 2002, 225 (03) :685-692
[3]   Pulmonary nodules at chest CT: Effect of computer-aided diagnosis on radiologists' detection performance [J].
Awai, K ;
Murao, K ;
Ozawa, A ;
Komi, M ;
Hayakawa, H ;
Hori, S ;
Nishimura, Y .
RADIOLOGY, 2004, 230 (02) :347-352
[4]   Components-of-variance models and multiple-bootstrap experiments: An alternative method for random-effects, receiver operating characteristic analysis [J].
Beiden, SV ;
Wagner, RF ;
Campbell, G .
ACADEMIC RADIOLOGY, 2000, 7 (05) :341-349
[5]   Automated detection of lung nodules in multidetector CT: Influence of different reconstruction protocols on performance of a software prototype [J].
Gurung, J ;
Maataoui, A ;
Khan, M ;
Wetter, A ;
Harth, M ;
Jacobi, V ;
Vogl, TJ .
ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, 2006, 178 (01) :71-77
[6]   Lung tumor growth: Assessment with CT - Comparison of diameter and cross-sectional area with volume measurements [J].
Jennings, SG ;
Winer-Muram, HT ;
Tarver, RD ;
Farber, MO .
RADIOLOGY, 2004, 231 (03) :866-871
[7]   Automated detection of pulmonary nodules on CT images: Effect of section thickness and reconstruction interval - Initial results [J].
Kim, JS ;
Kim, JH ;
Cho, GS ;
Bae, KT .
RADIOLOGY, 2005, 236 (01) :295-299
[8]   Computer-assisted detection of pulmonary nodules:: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings [J].
Marten, K ;
Grillhösl, A ;
Seyfarth, T ;
Obenauer, S ;
Rummeny, EJ ;
Engelke, C .
EUROPEAN RADIOLOGY, 2005, 15 (02) :203-212
[9]   Computer-aided detection and automated CT volumetry of pulmonary nodules [J].
Marten, Katharina ;
Engelke, Christoph .
EUROPEAN RADIOLOGY, 2007, 17 (04) :888-901
[10]   Computer-aided diagnosis as a second reader - Spectrum of findings in CT studies of the chest interpreted as normal [J].
Peldschus, K ;
Herzog, P ;
Wood, SA ;
Cheema, JI ;
Costello, P ;
Schoepf, UJ .
CHEST, 2005, 128 (03) :1517-1523