Abstract
234 pathology-proven FFDM malignant cases and 3872 normal cases were culled retrospectively from 6 screening facilities. For malignant cases, location and size of the biopsied finding and breast density were recorded. All cases were run with a prototype CAD algorithm (Siemens) to evaluate the impact of breast density, lesion size and lesion pathology on CAD performance. The overall CAD sensitivity was 84.2%, with 85.5% sensitivity in "non-dense" breasts and 82.3% in "dense" breasts (p=0.26). No significant difference (p=0.10) was found between CAD sensitivity for ductal lesions (86.4%) and lobular lesions (70.6%). The sensitivity for invasive ductal lesions (86.9%) was slightly higher (p=0.30) than for in-situ lesions (82.6%). The CAD sensitivity for large masses (90.1%) was significantly higher (p<0.001) than for small masses (66.0%). The false mark rate was 1.01. The study indicates that CAD can assist the radiologist in identifying suspicious lesions, independent of breast density, lesion pathology or invasiveness.
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Leichter, I. et al. (2010). Is CAD Able to Assist in the Detection of Subtle Breast Findings – Lobular Cancers, and T1a/T1b Masses in Dense Breasts?. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds) Digital Mammography. IWDM 2010. Lecture Notes in Computer Science, vol 6136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13666-5_64
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DOI: https://doi.org/10.1007/978-3-642-13666-5_64
Publisher Name: Springer, Berlin, Heidelberg
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