European Radiology

, Volume 25, Issue 2, pp 402–409 | Cite as

Effect of radiologists’ experience on breast cancer detection and localization using digital breast tomosynthesis

  • Maram M. AlakhrasEmail author
  • Patrick C. Brennan
  • Mary Rickard
  • Roger Bourne
  • Claudia Mello-Thoms



The objectives are To to compare the diagnostic performance of combined digital breast tomosynthesis (DBT) and digital mammography (DM) with that of DM alone, as a function of radiologists’ experience with DBT.


Ethical committee approval was obtained. Fifty cases (27 cancer, 23 normal), each containing both digital mammography (DM) and digital breast tomosynthesis (DBT) images, were reviewed by 26 radiologists, divided into three groups according to level of experience with DBT (none, workshop experience, and clinical experience). The radiologists’ diagnostic performance using DM was compared with that using DM + DBT, and evaluated by area under receiver-operating characteristic curve (AUC), jackknife free-response receiver-operator characteristics figure of metric (JAFROC FOM), sensitivity, location sensitivity, and specificity.


For all readers combined, performance using DM + DBT was significantly higher than for DM alone by both AUC (0.788 vs 0.681, p < 0.001) and JAFROC FOM (0.745 vs 0.621, p < 0.001). Similar results were obtained for readers with no DBT experience (AUC 0.775 vs 0.682, p = 0.004; JAFROC FOM 0.695 vs 0.603, p = 0.016) and with clinical DBT experience (AUC 0.789 vs 0.681, p = 0.042; and JAFROC FOM 0.764 vs 0.632, p = 0.031).


Addition of DBT to DM significantly improves radiologists’ diagnostic performance whether or not they have prior DBT experience.

Key points

Adding DBT to DM increased the number of detected cancers

DBT + DM led to more accurate localization of breast cancers than DM

Addition of DBT improved radiologistsperformance regardless of prior DBT experience

High-volume radiologists with different DBT experience levels performed similarly on DM + DBT


Digital breast tomosynthesis Digital mammography Breast cancer Diagnostic performance Radiologists’ experience 



The authors gratefully acknowledge the generous funding support provided by Australia’s National Breast Cancer Foundation under the Novel Concept Award Scheme. The authors thank Sydney Breast Clinic for providing the images, Hologic for their efforts in setting up the workstations and Jordan University of Science and Technology for their sponsorship.

The scientific guarantor of this publication is Maram Mustafa Alakhras. No complex statistical methods were necessary for this paper. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Methodology: Retrospective, Diagnostic study, Performed at one institution.


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Copyright information

© European Society of Radiology 2014

Authors and Affiliations

  • Maram M. Alakhras
    • 1
    Email author
  • Patrick C. Brennan
    • 1
  • Mary Rickard
    • 1
    • 2
  • Roger Bourne
    • 1
  • Claudia Mello-Thoms
    • 1
    • 3
  1. 1.Medical Image Perception and Optimization Group (MIOPeG)Faculty of Health Sciences The University of SydneySydneyAustralia
  2. 2.Sydney Breast ClinicSydneyAustralia
  3. 3.Department of Biomedical Informatics and Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghUSA

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