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The message matters: changes to binary Computer Aided Detection recommendations affect cancer detection in low

Francesca Patterson¹, Melina A Kunar²

¹Department of Psychology, The University of Warwick, Coventry, CV4 7AL, UK. frankiepatterson16@gmail.com.

Cognitive Research: Principles and Implications

|September 1, 2024

Summary

Binary Computer Aided Detection (CAD) systems reduce miss errors in mammography. A definitive message indicating potential cancer presence lowered errors more effectively than messages shown for every mammogram.

Keywords:

Artificial intelligence Automation Binary CAD Computer Aided Detection (CAD)Low prevalence Mammogram Over-reliance

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Area of Science:

Medical Imaging
Radiology
Artificial Intelligence in Healthcare

Background:

Computer Aided Detection (CAD) systems assist in cancer detection in mammograms.
Existing CAD systems can cause over-reliance, increasing miss errors and false alarms when inaccurate.
Overlaying CAD cues on mammograms can occlude tissue and exacerbate over-reliance.

Purpose of the Study:

To investigate over-reliance effects with a binary CAD system providing messages alongside mammograms.
To assess the impact of message certainty and presentation frequency on cancer detection performance.

Main Methods:

A binary CAD system was developed, reporting messages instead of overlaying cues.
Message certainty (possible cancer vs. present/absent) and presentation (only for possible cancer vs. all mammograms) were manipulated.
Reader performance was evaluated based on miss errors and false alarms.

Main Results:

Over-reliance effects were observed with binary CAD systems.
Miss errors were reduced when the CAD message was definitive and presented only for possible cancer.
Binary CAD systems showed potential for improving cancer detection accuracy compared to overlay cue systems.

Conclusions:

Binary CAD systems can mitigate some over-reliance issues associated with traditional CAD.
Definitive, targeted messaging in binary CAD systems appears more effective in reducing diagnostic errors.
Further research into binary CAD design can optimize its role in mammographic screening.