Department of Radiology, University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, OH 44106-5000, USA.
J Thorac Imaging. 2010 Feb;25(1):41-7. doi: 10.1097/RTI.0b013e3181aa34ed.
Computer-aided detection (CAD) has shown potential to assist physicians in the detection of lung nodules on chest radiographs, but widespread acceptance has been stymied by high false-positive rates. Few studies have examined the potential for dual energy subtraction (DES) to improve CAD performance.
Institutional review board approval was obtained, the requirement for informed consent was waived because the study was retrospective, and practices conformed to Health Insurance Portability and Accountability Act regulations. The CAD program was applied retrospectively to dual energy posteroanterior (PA) chest radiographs of 36 patients (17 women, 19 men, mean age 69 y) with 48 pathology proven lung nodules. Results were analyzed to determine the stand-alone CAD program false-positive rates, and sensitivity by nodule subtlety and location. Statistical analysis was performed using the chi(2) or Fisher exact tests for independence of sensitivities between standard PA and DES radiography. Differences in the mean false-positives per image (FPPI) between radiographic modalities were determined using the paired Students t test, and bootstrap confidence intervals were obtained to confirm results.
The sensitivity of the CAD program with the standard PA was 46% (22 of 48 nodules) compared with 67% (32 of 48 nodules) using the DES soft tissue or bone-subtracted view (P=0.064). The average number of FPPI identified by CAD was significantly lower using DES (FPPI(soft tissue) = 1.64) when compared with the standard PA chest radiograph (FPPI(PA) = 2.39) (P<0.01).
DES has the potential to improve stand-alone CAD performance by both increasing sensitivity for certain subtle lung cancer lesions and decreasing overall CAD false-positive rates.
计算机辅助检测（CAD）已显示出在胸部 X 光片上协助医生检测肺结节的潜力，但由于高假阳性率，其广泛应用受到了阻碍。很少有研究探讨双能减影（DES）在提高 CAD 性能方面的潜力。
本研究获得了机构审查委员会的批准，由于研究是回顾性的，且符合《健康保险流通与责任法案》的规定，因此免除了患者知情同意的要求。回顾性地将 CAD 程序应用于 36 例（17 名女性，19 名男性；平均年龄 69 岁）患者的双能前后位（PA）胸部 X 光片，这些患者均有 48 个经病理证实的肺结节。分析结果以确定独立 CAD 程序的假阳性率，以及根据结节细微程度和位置的敏感性。使用卡方检验或 Fisher 确切概率法对标准 PA 和 DES 射线照相之间的敏感性进行独立性分析。使用配对 t 检验确定两种影像学模式之间的平均每幅图像假阳性率（FPPI）差异，使用 bootstrap 置信区间来确认结果。
标准 PA 时 CAD 程序的敏感性为 46%（48 个结节中的 22 个），而软组织结构或骨组织减影视图时的敏感性为 67%（48 个结节中的 32 个）（P=0.064）。与标准 PA 胸部 X 光片相比，DES 时 CAD 识别的平均 FPPI 数量显著降低（FPPI（软组织）=1.64，FPPI（PA）=2.39）（P<0.01）。
DES 有可能通过提高某些细微肺癌病变的敏感性和降低总体 CAD 假阳性率，来改善独立 CAD 性能。
