Funovics M, Schamp S, Lackner B, Wunderbaldinger P, Lechner G, Wolf G
Universitätsklinik für Radiodiagnostik, Wien.
Wien Med Wochenschr. 1998;148(14):321-4.
Because of the rapid development of computer systems for digitalization and image analysis, they play an increasing important role in computer-assisted diagnosis (CAD). Especially in the field of mammography, the early signs of malignancy are relatively uniform and therefore more easily detected by a computer algorithm. In this study, we tested one of the few commercially available systems for the detection of both microcalcifications and suspicious, spiculated solid lesions on 40 cases of proven breast carcinomas. These mammograms were analyzed by three independent observers with and without knowledge of the computer results, respectively. Depending on the time of their radiologic experience, the sensitivity of the observers alone was 92.4%, 86.1% and 82%. With knowledge of the computer interpretation, sensitivity of all three observers rose significantly to 100%, 92.7%, and 95%, respectively. However, due to a high number of false positive results of the computer algorithm (0.4 markers per image), the positive predictive value of the interpretations worsened from 100%, 92.7%, and 95.5% to 86.4%, 97.3%, and 91.1%, respectively. It can be expected that future developments will soon overcome this problem and CAD will become an effective tool in screening mammography.
由于用于数字化和图像分析的计算机系统的快速发展,它们在计算机辅助诊断(CAD)中发挥着越来越重要的作用。特别是在乳腺钼靶摄影领域,恶性肿瘤的早期迹象相对一致,因此更容易被计算机算法检测到。在本研究中,我们测试了少数几种可商购的系统之一,该系统用于检测40例经证实的乳腺癌中的微钙化和可疑的、有毛刺的实性病变。这些乳腺钼靶照片分别由三名独立观察者进行分析,他们有的知道计算机结果,有的不知道。根据他们的放射学经验时长,仅观察者的敏感度分别为92.4%、86.1%和82%。在知道计算机解读结果后,所有三名观察者的敏感度分别显著提高到100%、92.7%和95%。然而,由于计算机算法的假阳性结果数量较多(每张图像0.4个标记),解读结果的阳性预测值分别从100%、92.7%和95.5%降至86.4%、97.3%和91.1%。可以预期,未来的发展将很快克服这个问题,CAD将成为乳腺钼靶筛查中的有效工具。