Department of Radiology, Aga Khan University Hospital, Karachi, Pakistan.
Int J Gen Med. 2011;4:815-9. doi: 10.2147/IJGM.S26127. Epub 2011 Dec 6.
To evaluate (1) whether or not the addition of computer-assisted diagnosis (CAD) to 64-slice multidetector computed tomography (CT) can be used as a screening tool for detection of pulmonary nodules in routine CT chest examinations and (2) whether or not to advocate the incorporation of CAD as a screening tool into our daily practice.
A retrospective cross-sectional analysis of 109 consecutive patients who had all undergone routine contrast-enhanced CT chest examinations for indications other than lung cancer at the Radiology Department of Aga Khan University Hospital, Karachi, between November 2010 and January 2011. All examinations were evaluated in terms of the detection of pulmonary nodules by a consultant radiologist and CAD (ImageChecker CT Algorithm R2 Technology) software. The ability of CAD software to detect pulmonary nodules was evaluated against the reference standard. In addition, a chest radiologist also calculated the number of pulmonary nodules. The sensitivity and specificity of the CAD software were calculated against the reference standard by using a 2 × 2 table. The Mann-Whitney U test was applied to compare the performances of CAD and the radiologist.
CAD detected 610 pulmonary nodules while the radiologist detected only 113. The reference standard declared 198 pulmonary nodules to be true nodules. CAD detected 95% of all true nodules (189/198), whereas the radiologist detected only 57% (113/198). In the detection of true pulmonary nodules, CAD had 98% sensitivity compared with the radiologist who had 57% sensitivity; the statistical difference between their performances had a P value <0.001.
Considering the high sensitivity of CAD to detect nearly all true pulmonary nodules, we advocate its application as a screening tool in all CT chest examinations for the early detection of pulmonary nodules and lung carcinoma.
评估（1）计算机辅助诊断（CAD）是否可与 64 层多排螺旋 CT（CT）联合用于常规 CT 胸部检查中肺结节的筛查，以及（2）是否应将 CAD 纳入筛查工具应用于日常实践。
回顾性分析 2010 年 11 月至 2011 年 1 月在卡拉奇 Aga Khan 大学医院放射科接受常规增强 CT 胸部检查的 109 例连续患者的资料，这些患者的检查均非因肺癌而进行。由一名顾问放射科医师和 CAD（ImageChecker CT Algorithm R2 Technology）软件对所有检查进行评估，以评估 CAD 软件检测肺结节的能力。使用 2×2 表根据参考标准计算 CAD 软件检测肺结节的敏感性和特异性。用 Mann-Whitney U 检验比较 CAD 和放射科医师的性能。
CAD 检测到 610 个肺结节，而放射科医师仅检测到 113 个。参考标准确定 198 个肺结节为真结节。CAD 检测到所有真结节的 95%（189/198），而放射科医师仅检测到 57%（113/198）。在检测真肺结节时，CAD 的敏感性为 98%，而放射科医师的敏感性为 57%；两者之间的性能差异具有统计学意义（P 值<0.001）。
鉴于 CAD 对检测几乎所有真肺结节的高敏感性，我们主张将其应用于所有 CT 胸部检查中，以早期发现肺结节和肺癌。
