Journal of Digital Imaging

, Volume 26, Issue 3, pp 572–577

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

  • Xavier Bargalló
  • Martín Velasco
  • Gorane Santamaría
  • Montse del Amo
  • Pedro Arguis
  • Sonia Sánchez Gómez
Article

DOI: 10.1007/s10278-012-9550-y

Cite this article as:
Bargalló, X., Velasco, M., Santamaría, G. et al. J Digit Imaging (2013) 26: 572. doi:10.1007/s10278-012-9550-y

Abstract

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.

Keywords

Breast neoplasm Cancer detection Computer-assisted detection 

Copyright information

© Society for Imaging Informatics in Medicine 2012

Authors and Affiliations

  • Xavier Bargalló
    • 1
  • Martín Velasco
    • 1
  • Gorane Santamaría
    • 1
  • Montse del Amo
    • 1
  • Pedro Arguis
    • 1
  • Sonia Sánchez Gómez
    • 2
  1. 1.Department of Radiology (CDIC)Hospital Clínic de BarcelonaBarcelonaSpain
  2. 2.Department of RadiologyHospital Marqués ValdecillaSantanderSpain

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