Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses

Rianne Hupse*, Maurice Samulski, Marc Lobbes, Ard den Heeten, Mechli W. Imhof-Tas, David Beijerinck, Ruud Pijnappel, Carla Boetes, Nico Karssemeijer

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


We developed a computer-aided detection (CAD) system aimed at decision support for detection of malignant masses and architectural distortions in mammograms. The effect of this system on radiologists' performance depends strongly on its standalone performance. The purpose of this study was to compare the standalone performance of this CAD system to that of radiologists. In a retrospective study, nine certified screening radiologists and three residents read 200 digital screening mammograms without the use of CAD. Performances of the individual readers and of CAD were computed as the true-positive fraction (TPF) at a false-positive fraction of 0.05 and 0.2. Differences were analysed using an independent one-sample t-test. At a false-positive fraction of 0.05, the performance of CAD (TPF = 0.487) was similar to that of the certified screening radiologists (TPF = 0.518, P = 0.17). At a false-positive fraction of 0.2, CAD performance (TPF = 0.620) was significantly lower than the radiologist performance (TPF = 0.736, P <0.001). Compared to the residents, CAD performance was similar for all false-positive fractions. The sensitivity of CAD at a high specificity was comparable to that of human readers. These results show potential for CAD to be used as an independent reader in breast cancer screening. aEuro cent Computer-aided detection (CAD) systems are used to detect malignant masses in mammograms aEuro cent Current CAD systems operate at low specificity to avoid perceptual oversight aEuro cent A CAD system has been developed that operates at high specificity aEuro cent The performance of the CAD system is approaching that of trained radiologists aEuro cent CAD has the potential to be an independent reader in screening.
Original languageEnglish
Pages (from-to)93-100
JournalEuropean Radiology
Issue number1
Publication statusPublished - Jan 2013


  • Mammography
  • Computer-assisted diagnosis
  • Breast
  • Mass screening
  • Neoplasms

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