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

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 wit...

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Publicado en:Journal of Digital Imaging Vol. 26; no. 3; pp. 572 - 578
Autores principales: Bargalló, Xavier, Velasco, Martín, Santamaría, Gorane, Amo, Montse, Arguis, Pedro, Sánchez Gómez, Sonia
Formato: research tables/charts Journal Article
Publicado: Springer Nature Jun2013
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2013
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      pub: Springer Nature
      place: New York, New York
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        atl: Role of Computer-Aided Detection in Very Small Screening Detected Invasive Breast Cancers.
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          Bargalló, Xavier
          Velasco, Martín
          Santamaría, Gorane
          Amo, Montse
          Arguis, Pedro
          Sánchez Gómez, Sonia
        affil: Department of Radiology (CDIC), Hospital Clínic de Barcelona, C/Villarroel,170 08036 Barcelona Spain
      sug:
        subj:
          Breast Neoplasms Diagnosis
          Diagnosis, Computer Assisted
          Radiography, Computed
          False Positive Results
          Weights and Measures
          Breast Anatomy and Histology
          Breast Neoplasms Classification
          Retrospective Design
          Sensitivity and Specificity
          Mann-Whitney U Test
          Chi Square Test
          Middle Age
          Aged
          Female
          Human
          Middle Aged: 45-64 years
          Aged: 65+ years
          Female
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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