Computer-aided diagnosis: impact on nodule detection among community level radiologists. A multi-reader study

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• 作者：Naidich ; David P. ; Ko ; Jane P. ; Stoeckel ; Jonathan ; Abinanti ; Nicole ; Lu ; Stanley ; Moses ; Daniel ; et. al.
• 关键词：Computer-aided diagnosis ; Lung nodules ; Multidetector CT
• 刊名：International Congress Series
• 出版年：2004
• 出版时间：June, 2004
• 年：2004
• 卷：1268
• 期：Complete
• 页码：902-907
• 全文大小：261 K

文摘

Early detection of lung nodules is an important clinical indication for obtaining routine CT studies of the thorax. To date, research has focused on the sensitivity of computer-aided diagnosis (CAD) compared with expert chest radiologists typically using data obtained from single detector CT scanners. The present study focuses on the use of CAD as a second reader supplementing four nonexpert “community level” radiologists using state-of-the-art multidetector high resolution data sets. Evaluations of 18 cases with a total of 87 nodules (average 4.8 per case) were subsequently validated by a panel of two expert dedicated chest radiologists. Only 21 % of nodules were identified by all four readers; 17 % were identified only by CAD. The mean sensitivity of readers before CAD was 49 % while following CAD this improved to 72 % (p<0.001). When analyzed by individual lobes, the percentage of these in which nodules could be identified increased from 36 % prior to CAD to 44 % following CAD (p<0.001). These data support the use of CAD as a second reader specifically for nonexpert radiologists in general clinical practice.