Malich Ansgar, Schmidt Sabine, Fischer Dorothee R, Facius Mirjam, Kaiser Werner A
Institute of Diagnostic Radiology, Suedharz-Hospital Nordhausen, Dr.-R.-Koch-Street 38, 99734 Nordhausen, Germany.
Eur J Radiol. 2009 Mar;69(3):574-8. doi: 10.1016/j.ejrad.2007.11.038. Epub 2008 Mar 11.
The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively.
All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed.
278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD. Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density.
CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.
回顾性证实计算机辅助检测（CAD）系统在检测乳腺癌方面的临床作用，该系统能检测出放射科医生在含癌乳腺钼靶片中未检测到的癌症。
回顾性分析1992年至2005年在我院有组织学证实的恶性乳腺病变且有乳腺钼靶片的所有患者，重点关注恶性病变的检测时间。所有先前的乳腺钼靶片均由CAD（美国CADx）进行分析。将生成的CAD打印结果与含癌图像进行匹配，以得出乳腺癌的放射学诊断。分析CAD的性能、敏感性以及CAD与放射学特征的关联。
278份乳腺钼靶片符合纳入标准。111例显示出回顾性可见病变（71个肿块、23个单个微钙化簇、16个伴有微钙化的肿块，1例有两个微钙化簇）。CAD检测出54/87个肿块和34/41个微钙化。检测率从9/20（ACR 1）到5/7（ACR 4）不等（45%对71%）。微钙化的检测不受乳腺组织密度的影响。
CAD可能有助于早期检测出细微的乳腺癌病例，否则这些病例可能会漏诊。
