计算机辅助检测肺结节在数字化X线胸片肺癌筛查中的应用价值

目的 评价计算机辅助检测(CAD)肺结节系统在数字化X线胸片上肺癌筛查中的应用价值.方法 由1名放射科医师和CAD肺结节检测系统独立阅读100例连续的数字摄影(DR)X线胸片,CAD系统可以检出最长直径在5～15 mm的肺结节.由2名放射科专家(有15年胸部影像诊断经验)进行回顾性阅读,参照相应的CT图像,两人意见达成一致后标记真结节的个数和位置并保存标记结果,将标记结果作为金标准来比较放射科医师和CAD系统的肺结节检测敏感性和假阳性率.结果 放射科医师共检测到95个结节,CAD系统共检测到304个结节.在回顾性检查中2名放射科专家共标记134个真结节,其中放射科医师检测到82个(61.2%),CAD检测到105个(78.4%),CAD系统检测到而被放射科医师漏诊的结节35个,放射科医师检测到而CAD系统漏诊的结节10个.放射科医师应用CAD系统后检测到112个真结节,检测率提高到83.6%.放射科专家意见一致后认为CAD系统检出199个假阳性结节,平均每张胸片约2.0个.结论 在肺癌筛查中放射科医师和CAD系统必须联合应用才可以识别X线胸片中所有的结节.

Computer-aided diagnosis for the detection of the pulmonary nodules on digital chest radiography in lung cancer screening

Objective To evaluate the value of computer-aided detection (CAD) system for pulmonary nodule detection using digital chest radiography in lung cancer screening. Methods One hundred consecutive digital chest radiographs from 6280 outpatients for lung cancer screening were independently reviewed by a thoracic radiologist and a computer-aided pulmonary nodule detection system.The radiographs were also reviewed by two experienced thoracic radiologists and the true nodules confirmed by two radiologists with reference to the CT images were marked and stored as a gold standard in the CAD system. The sensitivity and false positive of the radiologist and the CAD system for the detection of nodules on digital chest radiographs were compared. Results Ninety-five and 304 nodules were identified by radiologist and the CAD system, respectively. Of 134 nodules marked as true nodules by experienced radiologists, 82 (61.2%) and 105 (78. 4% ) nodules were identified by the radiologist and the CAD,respectively. The radiologist missed 35 true nodules which were only detected by CAD. The CAD system missed 10 true nodules which were only detected by radiologist. One hundred and twelve (83.6%) nodules were identified by radiologist with the CAD system. One hundred and ninety-nine nodules identified by CAD were false-positive with a rate of 2. 0 ( 199/100 ) per case. Conclusion Combining review of digital radiographs by radiologist with CAD system can improve the detection of pulmonary nodules in lung cancer screening.