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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

False positive marks on unsuspicious screening mammography with computer-aided detection.

Mary C Mahoney¹, Karthikeyan Meganathan

¹Barrett Cancer Center, University of Cincinnati Medical Center, 234 Goodman Street, Mail Location 772, Cincinnati, OH 45267, USA. mahonemc@healthall.com

Journal of Digital Imaging

|May 7, 2011

Summary

Computer-aided detection (CAD) systems in mammography screening generate many false positives, but most are easily dismissed by radiologists. This study found minimal differences between two CAD systems in specificity and false positive rates.

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Area of Science:

Radiology
Medical Imaging
Artificial Intelligence in Healthcare

Background:

Computer-aided detection (CAD) systems are used as an aid in screening mammography.
A high rate of false positive detections can hinder the effectiveness of CAD systems.
Evaluating the performance of different CAD systems is crucial for optimizing their clinical utility.

Purpose of the Study:

To retrospectively evaluate the specificity, false positive rate, and ease of dismissing false positive marks from two CAD systems.
To compare the performance of two CAD systems in screening mammography.
To investigate the impact of breast density on CAD system performance.

Main Methods:

Retrospective review of 100 screening mammographic studies with normal follow-up.
Evaluation of two CAD systems, recording breast density, CAD marks, and radiologist's ease of dismissing false positives.
Calculation of specificity for all marks, mass marks, and calcification marks for each CAD system.

Main Results:

Specificities varied between CAD versions for all marks (23% vs. 15%), mass marks (35% vs. 17%), and calcification marks (62% vs. 75%).
No significant difference in the number of marks per case for all marks or mass marks.
A statistically significant difference was observed in calcification marks per case (p < 0.01).
Most false positive marks (84% and 88%) were classified as very easy/easy to dismiss.

Conclusions:

The two CAD systems showed minor differences in specificity and false positive marks.
False positive marks generated by CAD systems are generally easy for radiologists to dismiss.
Further research is warranted to explore statistically non-significant differences in performance between dense and non-dense breasts.