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Updated: Aug 5, 2026
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
Diagnostic performance with sensitivity/specificity optimized computer-aided detection to detect common abnormalities
Miyuki Tomiyama1,2, Masahiro Yanagawa3, Tsubasa Yoshida2
1Artificial Intelligence in Diagnostic Radiology, The University of Osaka Graduate School of Medicine, Suita, Japan.
Japanese Journal of Radiology
|August 3, 2026
Summary
Specificity-optimized computer-aided detection (CAD) improved radiologist specificity for pulmonary opacities without reducing sensitivity. Different CAD settings significantly impact diagnostic performance in chest radiography interpretation.
Area of Science:
- Radiology
- Medical Imaging
- Artificial Intelligence in Medicine
Background:
- Computer-aided detection (CAD) is a decision-support tool for radiologists.
- Previous studies focused on standalone CAD performance at various thresholds.
- This study investigates CAD's impact on radiologist performance in clinical practice.
Purpose of the Study:
- To evaluate how sensitivity-optimized (SE-CAD) and specificity-optimized (SP-CAD) modes affect radiologists' diagnostic performance in chest radiography (CXR).
- To assess the influence of different CAD threshold settings on radiologist diagnostic accuracy.
Main Methods:
- Retrospective diagnostic accuracy study of 375 CXRs (2013-2023) with CT as reference standard.
- Six radiologists interpreted CXRs with and without SE-CAD or SP-CAD assistance.
- Readings were performed in two sessions with a 1-month washout period.
Main Results:
- SP-CAD showed higher specificity than SE-CAD for pulmonary opacities (p < 0.001).
- CAD-assisted reading improved sensitivity for pulmonary opacities and pleural effusions.
- CAD assistance improved specificity for pleural effusions but decreased it for pneumothorax (SE-CAD).
Conclusions:
- Specificity-prioritized CAD demonstrated higher specificity than sensitivity-prioritized CAD for pulmonary opacities, without significant sensitivity reduction.
- Different CAD operating points can influence radiologists' diagnostic performance.
- Preset decision thresholds within AI models impact diagnostic accuracy in AI-assisted radiograph interpretation.
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