Exploring the potential of context-sensitive CADe in screening mammography (Tourassi et al, 2010)

Georgia D. Tourassi, Maciej A. Mazurowski, and Brian P. Harrawood at Duke University Ravin Advanced Imaging Laboratories in collaboration with Elizabeth A. Krupinski presents a novel method of combining eye gaze data with Computer-Assisted Detection algorithms to improve detection rates for malignant masses in mammography. This contextualized method holds a potential for personalized diagnostic support.

Purpose: Conventional computer-assisted detection CADe systems in screening mammography provide the same decision support to all users. The aim of this study was to investigate the potential of a context-sensitive CADe system which provides decision support guided by each user’s focus of attention during visual search and reporting patterns for a specific case.

Methods: An observer study for the detection of malignant masses in screening mammograms was conducted in which six radiologists evaluated 20 mammograms while wearing an eye-tracking device. Eye-position data and diagnostic decisions were collected for each radiologist and case they reviewed. These cases were subsequently analyzed with an in-house knowledge-based CADe system using two different modes:  conventional mode with a globally fixed decision threshold and context-sensitive mode with a location-variable decision threshold based on the radiologists’ eye dwelling data and reporting information.

Results: The CADe system operating in conventional mode had 85.7% per-image malignant mass sensitivity at 3.15 false positives per image FPsI . The same system operating in context-sensitive mode provided personalized decision support at 85.7%–100% sensitivity and 0.35–0.40 FPsI to all six radiologists. Furthermore, context-sensitive CADe system could improve the radiologists’ sensitivity and reduce their performance gap more effectively than conventional CADe.

Conclusions: Context-sensitive CADe support shows promise in delineating and reducing the radiologists’ perceptual and cognitive errors in the diagnostic interpretation of screening mammograms more effectively than conventional CADe.

• G. D. Tourassi, M. A. Mazurowski, B. P. Harrawood and E. A. Krupinski, "Exploring the potential of context-sensitive CADe in screening mammography," Medical Physics 37, 5728-5736. Online, PDF.