Role of Computer-Aided Detection in Very Small Screening Detected Invasive Breast Cancers

• Published in: Journal of digital imaging Vol. 26; no. 3; pp. 572 - 577
• Main Authors: Bargalló, Xavier, Velasco, Martín, Santamaría, Gorane, del Amo, Montse, Arguis, Pedro, Sánchez Gómez, Sonia
• Format: Journal Article
• Language: English
• Published: New York Springer-Verlag 01.06.2013; Springer Nature B.V
• Subjects: Aged; Asymmetry; Breast; Breast Neoplasms - diagnostic imaging; Calcification; Cancer; Computer aided design; Density; Diagnosis, Computer-Assisted - methods; Distortion; Female; Humans; Imaging; Mammography; Medicine; Medicine & Public Health; Middle Aged; Neoplasm Invasiveness - diagnostic imaging; Radiology; Retrospective Studies; Screening; Sensitivity and Specificity; Cancer detection; Breast neoplasm; Computer-assisted detection
• ISSN: 0897-1889; 1618-727X
• DOI: 10.1007/s10278-012-9550-y

This study aims to assess computer-aided detection (CAD) performance with full-field digital mammography (FFDM) in very small (equal to or less than 1 cm) invasive breast cancers. Sixty-eight invasive breast cancers less than or equal to 1 cm were retrospectively studied. All cases were detected with FFDM in women aged 49–69 years from our breast cancer screening program. Radiological characteristics of lesions following BI-RADS descriptors were recorded and compared with CAD sensitivity. Age, size, BI-RADS classification, breast density type, histological type of the neoplasm, and role of the CAD were also assessed. Per-study specificity and mass false-positive rate were determined by using 100 normal consecutive studies. Thirty-seven (54.4 %) masses, 17 (25 %) calcifications, 6 (8.8 %) masses with calcifications, 7 (10.3 %) architectural distortions, and 1 asymmetry (1.5 %) were found. CAD showed an overall sensitivity of 86.7 % (masses, 86.5 %; calcifications, 100 %; masses with calcifications, 100 %; and architectural distortion, 57.14 %), CAD failed to detect 9 out of 68 cases: 5 of 37 masses, 3 of 7 architectural distortions, and 1 of 1 asymmetry. Fifteen out of 37 masses were hyperdense, and all of them were detected by CAD. No association was seen among mass morphology or margins and detectability. Per-study specificity and CAD false-positive rate was 26 % and 1.76 false marks per study. In conclusion, CAD shows a high sensitivity and a low specificity. Lesion size, histology, and breast density do not influence sensitivity. Mammographic features, mass density, and thickness of the spicules in architectural distortions do influence.