Fraioli Francesco, Bertoletti Linda, Napoli Alessandro, Pediconi Federica, Calabrese Francesca Antonella, Masciangelo Raffaele, Catalano Carlo, Passariello Roberto
Department of Radiological Sciences, University of Rome La Sapienza, Viale Regina Elena 324, Rome, Italy.
J Thorac Imaging. 2007 Aug;22(3):241-6. doi: 10.1097/RTI.0b013e318033aae8.
To evaluate the performance of a computer-aided detection (CAD) algorithm in the detection of pulmonary nodules on high-resolution multidetector row computed tomography images in a large, homogeneous screening population, and to evaluate the effect of the system output on the performance of radiologists, using receiver operating characteristic analysis. Three radiologists with variable experience (1 to 7 y), independently read the 200 computed tomography scans and assigned each nodule candidate a confidence score (1-2-3: unlikely, probably, and definitely a nodule). CAD was applied to all scans; successively readers reevaluated all findings of the CAD, assigning, in consensus, a confidence score (1 to 3). The reference standard was established by the consensus of 2 experienced radiologists with 30 and 15 years of experience. Results were used to generate an free-response receiver operating characteristic analysis. The reference standard showed 125 nodules. Sensitivity for readers I-II-III was 57%, 68%, and 46%. A double reading resulted in an increase in sensitivity up to 75%. With CAD, sensitivity was increased to 94%, 96%, and 94% for readers I, II, and III. The area under the free-response receiver operating characteristic curve (Az) was 0.72, 0.82, 0.55, and 0.84 for readers I, II, III, and the CAD, when considering all nodules. Differences between readers I-II and CAD were not significant (P=0.9). There was a significant difference between reader III and the CAD. For nodules <6-mm Az was 0.40, 0.47, 0.14, and 0.72 for readers I, II, III, and the CAD. Differences between all readers and the CAD were significant (P<0.05). CAD can aid in daily radiologic routine detecting a substantial number of nodules unseen by radiologists. This is true for both board-certified radiologists and for less experienced readers especially in the detection of small nodules.
为了在一个大型、同质化的筛查人群中，评估计算机辅助检测（CAD）算法在高分辨率多排螺旋计算机断层扫描图像上检测肺结节的性能，并使用接受者操作特征分析来评估系统输出对放射科医生性能的影响。三位经验各异（1至7年）的放射科医生独立阅读了200份计算机断层扫描，并为每个结节候选对象分配一个置信度评分（1 - 2 - 3：不太可能、可能、肯定是结节）。CAD应用于所有扫描；随后，阅读者重新评估CAD的所有结果，共同给出一个置信度评分（1至3）。参考标准由两位分别有30年和15年经验的资深放射科医生共同确定。结果用于生成自由反应接受者操作特征分析。参考标准显示有125个结节。阅读者I - II - III的敏感度分别为57%、68%和46%。二次阅读使敏感度提高到75%。使用CAD时，阅读者I、II和III的敏感度分别提高到94%、96%和94%。在考虑所有结节时，阅读者I、II、III和CAD的自由反应接受者操作特征曲线下面积（Az）分别为0.72、0.82、0.55和0.84。阅读者I - II与CAD之间的差异不显著（P = 0.9）。阅读者III与CAD之间存在显著差异。对于直径<6毫米的结节，阅读者I、II、III和CAD的Az分别为0.40、0.47、0.14和0.72。所有阅读者与CAD之间的差异均显著（P<0.05）。CAD有助于日常放射学检查，能检测出放射科医生大量未发现的结节。对于获得委员会认证的放射科医生和经验较少的阅读者都是如此，尤其是在检测小结节方面。
