Yuan Ren, Vos Patrick M, Cooperberg Peter L
Department of Radiology, Vancouver General Hospital, Vancouver, British Columbia, V5Z 1M9 Canada.
AJR Am J Roentgenol. 2006 May;186(5):1280-7. doi: 10.2214/AJR.04.1969.
Our objective was to evaluate the performance of a computer-aided detection (CAD) system for pulmonary nodule detection using low-dose screening CT images.
One hundred fifty consecutive low-dose screening CT examinations were independently evaluated by a radiologist and a CAD pulmonary nodule detection system (R2 Technology) designed to identify nodules larger than 4 mm in maximum long-axis diameter. All discrepancies between the two techniques were reviewed by one of another two radiologists working in consensus with the initial interpreting radiologist, and a "true" nodule count was determined. Detected nodules were classified by size, density, and location. The performance of the initial radiologist and the CAD system were compared.
The radiologist detected 518 nodules and the CAD system, 934 nodules. Of the 1,106 separate nodules detected using the two techniques, 628 were classified as true nodules on consensus review. Of the true nodules present, the radiologist detected 518 (82%) of 628 nodules and the CAD, 456 (73%) of 628 nodules. All 518 radiologist-detected nodules were true nodules, and 456 (49%) of 934 of CAD-detected nodules were true nodules. The radiologist missed 110 true nodules that were only detected by CAD. In six patients, these were the only nodules detected in the examination, changing the imaging follow-up protocol. CAD identified 478 lesions that on consensus review were false-positive nodules, a rate of 3.19 (478/150) per patient.
CAD detected 72.6% of true nodules and detected nodules in six (4%) patients not identified by radiologists, changing the imaging follow-up protocol of these subjects. In this study, the combined review of low-dose CT scans by both the radiologist and CAD was necessary to identify all nodules.
我们的目的是使用低剂量筛查CT图像评估一种计算机辅助检测（CAD）系统在肺结节检测方面的性能。
由一名放射科医生和一个旨在识别最大长轴直径大于4mm结节的CAD肺结节检测系统（R2 Technology）对连续150例低剂量筛查CT检查进行独立评估。两种技术之间的所有差异由另外两名与最初解读的放射科医生达成共识的放射科医生之一进行复查，并确定“真正的”结节数量。检测到的结节按大小、密度和位置进行分类。比较最初放射科医生和CAD系统的性能。
放射科医生检测到518个结节，CAD系统检测到934个结节。在使用这两种技术检测到的1106个独立结节中，经共识复查，628个被分类为真正的结节。在存在的真正结节中，放射科医生检测到628个结节中的518个（82%），CAD检测到628个结节中的456个（73%）。放射科医生检测到的所有518个结节都是真正的结节，而CAD检测到的934个结节中有456个（49%）是真正的结节。放射科医生漏诊了仅由CAD检测到的110个真正结节。在6名患者中，这些是检查中仅检测到的结节，改变了影像随访方案。CAD识别出478个经共识复查为假阳性结节的病变，每位患者的假阳性率为3.19（478/150）。
CAD检测到72.6%的真正结节，并在6名（4%）未被放射科医生识别的患者中检测到结节，改变了这些患者的影像随访方案。在本研究中，放射科医生和CAD对低剂量CT扫描进行联合复查对于识别所有结节是必要的。
