Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback

Article


Trieu, Phuong Dung (Yun), Lewis, Sarah J., Li, Tong, Ho, Karen, Wong, Dennis J., Tran, Oanh T. M., Puslednik, Louise, Black, Deborah and Brennan, Patrick C.. 2021. "Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback." Scientific Reports. https://doi.org/10.1038/s41598-021-89214-3
Article Title

Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback

ERA Journal ID201487
Article CategoryArticle
AuthorsTrieu, Phuong Dung (Yun), Lewis, Sarah J., Li, Tong, Ho, Karen, Wong, Dennis J., Tran, Oanh T. M., Puslednik, Louise, Black, Deborah and Brennan, Patrick C.
Journal TitleScientific Reports
Number of Pages8
Year2021
PublisherNature Publishing Group
Place of PublicationUnited Kingdom
ISSN2045-2322
Digital Object Identifier (DOI)https://doi.org/10.1038/s41598-021-89214-3
Web Address (URL)https://www.nature.com/articles/s41598-021-89214-3
Abstract

It has been shown that there are differences in diagnostic accuracy of cancer detection on mammograms, from below 50% in developing countries to over 80% in developed world. One previous study reported that radiologists from a population in Asia displayed a low mammographic cancer detection of 48% compared with over 80% in developed countries, and more importantly, that most lesions missed by these radiologists were spiculated masses or stellate lesions. The aim of this study was to explore the performance of radiologists after undertaking a training test set which had been designed to improve the capability in detecting a specific type of cancers on mammograms. Twenty-five radiologists read two sets of 60 mammograms in a standardized mammogram reading room. The first test set focused on stellate or spiculated masses. When radiologists completed the first set, the system displayed immediate feedback to the readers comparing their performances in each case with the truth of cancer cases and cancer types so that the readers could identify individual-based errors. Later radiologists were asked to read the second set of mammograms which contained different types of cancers including stellate/spiculated masses, asymmetric density, calcification, discrete mass and architectural distortion. Case sensitivity, lesion sensitivity, specificity, receiver operating characteristics (ROC) and Jackknife alternative free-response receiver operating characteristics (JAFROC) were calculated for each participant and their diagnostic accuracy was compared between two sessions. Results showed significant improvement among radiologists in case sensitivity (+ 11.4%; P < 0.05), lesion sensitivity (+ 18.7%; P < 0.01) and JAFROC (+ 11%; P < 0.01) in the second set compared with the first set. The increase in diagnostic accuracy was also recorded in the detection of stellate/spiculated mass (+ 20.6%; P < 0.05). This indicated that the performance of radiologists in detecting malignant lesions on mammograms can be improved if an appropriate training intervention is applied after the readers’ weakness and strength are identified.

Keywordsmammograms ; cancer detection
ANZSRC Field of Research 2020429999. Other health sciences not elsewhere classified
Byline AffiliationsUniversity of Sydney
University of Medicine and Pharmacy, Vietnam
University of Western Sydney
St Matthews Catholic School, Australia
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