Li Jiang, Van Uitert Robert, Yao Jianhua, Petrick Nicholas, Franaszek Marek, Huang Adam, Summers Ronald M
Diagnostic Radiology Department, Clinical Center National Institutes of Health, Bethesda, Maryland 20892-1182, USA.
Med Phys. 2008 Aug;35(8):3527-38. doi: 10.1118/1.2938517.
Computed tomographic colonography (CTC) computer aided detection (CAD) is a new method to detect colon polyps. Colonic polyps are abnormal growths that may become cancerous. Detection and removal of colonic polyps, particularly larger ones, has been shown to reduce the incidence of colorectal cancer. While high sensitivities and low false positive rates are consistently achieved for the detection of polyps sized 1 cm or larger, lower sensitivities and higher false positive rates occur when the goal of CAD is to identify "medium"-sized polyps, 6-9 mm in diameter. Such medium-sized polyps may be important for clinical patient management. We have developed a wavelet-based postprocessor to reduce false positives for this polyp size range. We applied the wavelet-based postprocessor to CTC CAD findings from 44 patients in whom 45 polyps with sizes of 6-9 mm were found at segmentally unblinded optical colonoscopy and visible on retrospective review of the CT colonography images. Prior to the application of the wavelet-based postprocessor, the CTC CAD system detected 33 of the polyps (sensitivity 73.33%) with 12.4 false positives per patient, a sensitivity comparable to that of expert radiologists. Fourfold cross validation with 5000 bootstraps showed that the wavelet-based postprocessor could reduce the false positives by 56.61% (p <0.001), to 5.38 per patient (95% confidence interval [4.41, 6.34]), without significant sensitivity degradation (32/45, 71.11%, 95% confidence interval [66.39%, 75.74%], p=0.1713). We conclude that this wavelet-based postprocessor can substantially reduce the false positive rate of our CTC CAD for this important polyp size range.
计算机断层结肠成像（CTC）计算机辅助检测（CAD）是一种检测结肠息肉的新方法。结肠息肉是可能会癌变的异常生长物。已证实，检测并切除结肠息肉，尤其是较大的息肉，可降低结直肠癌的发病率。虽然对于检测直径1厘米或更大的息肉始终能实现高灵敏度和低假阳性率，但当CAD的目标是识别直径6 - 9毫米的“中等”大小息肉时，灵敏度较低且假阳性率较高。这类中等大小的息肉对于临床患者管理可能很重要。我们开发了一种基于小波的后处理器，以降低此息肉大小范围内的假阳性。我们将基于小波的后处理器应用于44例患者的CTC CAD检查结果，这些患者在分段非盲法光学结肠镜检查中发现了45个直径为6 - 9毫米的息肉，并且在回顾性分析CT结肠成像图像时可见。在应用基于小波的后处理器之前，CTC CAD系统检测到了33个息肉（灵敏度为73.33%），每位患者有12.4例假阳性，其灵敏度与专家放射科医生相当。通过5000次自抽样进行的四重交叉验证表明，基于小波的后处理器可将假阳性降低56.61%（p <0.001），降至每位患者5.38例假阳性（95%置信区间[4.41, 6.34]），且灵敏度无显著下降（32/45，71.11%，95%置信区间[66.39%，75.74%]，p = 0.1713）。我们得出结论，这种基于小波的后处理器可大幅降低我们的CTC CAD在这一重要息肉大小范围内的假阳性率。
