Volume 59, Issue 3 pp. 292-299
Medical Imaging—Original Article

Evaluation of the effect of zoom function on lesion detection by soft-copy reading of screening mammograms

Phuong Dung Trieu

Corresponding Author

Phuong Dung Trieu

Medical Image Optimization and Perception (MIOPeG), Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia

Correspondence

Ms Phuong Dung Trieu, Medical Image Optimization and Perception (MIOPeG), Faculty of Health Sciences, University of Sydney, Level 5, M building, 75 East Street, Lidcombe, NSW 2141, Australia.

Email: [email protected]

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Patrick Brennan

Patrick Brennan

Medical Image Optimization and Perception (MIOPeG), Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia

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Bruno Giuffre

Bruno Giuffre

Radiology Department, Royal North Shore Hospital, Sydney, New South Wales, Australia

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Claudia Mello-Thoms

Claudia Mello-Thoms

Medical Image Optimization and Perception (MIOPeG), Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia

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Kriscia Tapia

Kriscia Tapia

Medical Image Optimization and Perception (MIOPeG), Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia

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Nicole Santangelo

Nicole Santangelo

BreastScreen NSW, Sydney South West Area Health Service, Sydney, New South Wales, Australia

Radiology Department, Concord Hospital, Sydney, New South Wales, Australia

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Haewon Kim

Haewon Kim

BreastScreen NSW, Sydney South West Area Health Service, Sydney, New South Wales, Australia

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Katherine Cameron

Katherine Cameron

Imaging Partners Online, Sydney, New South Wales, Australia

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Catherine Hayter

Catherine Hayter

Radiology Department, Royal North Shore Hospital, Sydney, New South Wales, Australia

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Glenys Da Costa

Glenys Da Costa

Radiology Department, Royal North Shore Hospital, Sydney, New South Wales, Australia

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Jarmila Sterba

Jarmila Sterba

South Eastern Sydney Illawarra BreastScreen Service, Sydney, New South Wales, Australia

BreastScreen NSW, Northern Sydney and Central Coast Local, Sydney, New South Wales, Australia

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Warwick Lee

Warwick Lee

Medical Image Optimization and Perception (MIOPeG), Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia

BreastScreen NSW, Cancer Institute NSW, Sydney, New South Wales, Australia

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First published: 01 April 2015
Citations: 2
PD Trieu MDR; P Brennan PhD; B Giuffre MBBS, FRANZCR; C Mello-Thoms PhD; K Tapia BA (Eng); N Santangelo BSc (Med), MBBS, FRANZCR; H Kim MBChB; K Cameron BMed (Hons) FRANZCR; C Hayter BSc (Med), MBBS; G Da Costa BSc (Med), MBBS; J Sterba MD, FRANZCR; W Lee MBBS (Hons), BSc (Med), FRANZCR.
Conflict of interest: The authors have no conflicts of interest to disclose.

Abstract

Introduction

This study aims to evaluate the effectiveness of zooming in improving screen-reader performance in reporting digital mammograms.

Method

Two experiments were conducted. In the first experiment, 5 readers were asked to report 59 two-view bilateral mammograms retrospectively with zooming function turned off. The second session was similar to the first one except that zooming was enabled. The task of readers was to assess if the mammograms were normal or abnormal and rate the confidence levels for each of the lesion they detected. The reader performances were evaluated via case sensitivity, lesion sensitivity, specificity, receiver operating characteristics (ROC) area under the curve (AUC) and jackknife free-response receiver operating characteristics (JAFROC) figure of merit (FOM).

Results

There was no significant improvement in overall reader performance in detecting abnormalities in zooming condition compared with no zooming in terms of case sensitivity (96% and 87%, P = 0.285) or lesion sensitivity (88% and 81%, P = 0.224). However, differences in ROC AUC and JAFROC FOM (P ≤ 0.05) were found in two readers when they performed the test set with zooming function.

Conclusion

The results suggested that the use of the zooming function did improve the performance of some readers in detecting abnormal cases.

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