Journal of Digital Imaging

, Volume 26, Issue 5, pp 971–976

Comparing Performance of the CADstream and the DynaCAD Breast MRI CAD Systems

CADstream vs. DynaCAD in Breast MRI
  • Joann Pan
  • Basak E. Dogan
  • Selin Carkaci
  • Lumarie Santiago
  • Elsa Arribas
  • Scott B. Cantor
  • Wei Wei
  • R. Jason Stafford
  • Gary J. Whitman
Article
  • 307 Downloads

Abstract

Computer-aided diagnosis (CAD) systems are software programs that use algorithms to find patterns associated with breast cancer on breast magnetic resonance imaging (MRI). The most commonly used CAD systems in the USA are CADstream (CS) (Merge Healthcare Inc., Chicago, IL) and DynaCAD for Breast (DC) (Invivo, Gainesville, FL). Our primary objective in this study was to compare the CS and DC breast MRI CAD systems for diagnostic accuracy and postprocessed image quality. Our secondary objective was to compare the evaluation times of radiologists using each system. Three radiologists evaluated 30 biopsy-proven malignant lesions and 29 benign lesions on CS and DC and rated the lesions’ malignancy status using the Breast Imaging Reporting and Data System. Image quality was ranked on a 0–5 scale, and mean reading times were also recorded. CS detected 70 % of the malignant and 32 % of the benign lesions while DC detected 81 % of the malignant lesions and 34 % of the benign lesions. Analysis of the area under the receiver operating characteristic curve revealed that the difference in diagnostic performance was not statistically significant. On image quality scores, CS had significantly higher volume rendering (VR) (p < 0.0001) and motion correction (MC) scores (p < 0.0001). There were no statistically significant differences in the remaining image quality scores. Differences in evaluation times between DC and CS were also not statistically significant. We conclude that both CS and DC perform similarly in aiding detection of breast cancer on MRI. MRI CAD selection will likely be based on other factors, such as user interface and image quality preferences, including MC and VR.

Keywords

Breast Breast diseases Computer-assisted detection Computer-aided diagnosis (CAD) Diagnostic imaging MR imaging 

Copyright information

© Society for Imaging Informatics in Medicine 2013

Authors and Affiliations

  • Joann Pan
    • 1
  • Basak E. Dogan
    • 2
  • Selin Carkaci
    • 3
  • Lumarie Santiago
    • 2
  • Elsa Arribas
    • 2
  • Scott B. Cantor
    • 4
  • Wei Wei
    • 4
  • R. Jason Stafford
    • 5
  • Gary J. Whitman
    • 2
  1. 1.Department of Biochemistry and Cell BiologyRice UniversityHoustonUSA
  2. 2.Department of Diagnostic RadiologyThe University of Texas MD Anderson Cancer CenterHoustonUSA
  3. 3.Department of Diagnostic RadiologyOhio State University Wexner Medical CenterColumbusUSA
  4. 4.Department of BiostatisticsThe University of Texas MD Anderson Cancer CenterHoustonUSA
  5. 5.Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonUSA

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