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

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...

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Autores principales:	Phuong Dung (Yun) Trieu, Sarah J. Lewis, Tong Li, Karen Ho, Dennis J. Wong, Oanh T. M. Tran, Louise Puslednik, Deborah Black, Patrick C. Brennan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/46ebad74dc0546fab67bc3fd0f86dbc0
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spelling	oai:doaj.org-article:46ebad74dc0546fab67bc3fd0f86dbc02021-12-02T17:02:05ZImproving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback10.1038/s41598-021-89214-32045-2322https://doaj.org/article/46ebad74dc0546fab67bc3fd0f86dbc02021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89214-3https://doaj.org/toc/2045-2322Abstract 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.Phuong Dung (Yun) TrieuSarah J. LewisTong LiKaren HoDennis J. WongOanh T. M. TranLouise PuslednikDeborah BlackPatrick C. BrennanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Phuong Dung (Yun) Trieu Sarah J. Lewis Tong Li Karen Ho Dennis J. Wong Oanh T. M. Tran Louise Puslednik Deborah Black Patrick C. Brennan Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback
description	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.
format	article
author	Phuong Dung (Yun) Trieu Sarah J. Lewis Tong Li Karen Ho Dennis J. Wong Oanh T. M. Tran Louise Puslednik Deborah Black Patrick C. Brennan
author_facet	Phuong Dung (Yun) Trieu Sarah J. Lewis Tong Li Karen Ho Dennis J. Wong Oanh T. M. Tran Louise Puslednik Deborah Black Patrick C. Brennan
author_sort	Phuong Dung (Yun) Trieu
title	Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback
title_short	Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback
title_full	Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback
title_fullStr	Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback
title_full_unstemmed	Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback
title_sort	improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/46ebad74dc0546fab67bc3fd0f86dbc0
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Improving radiologist's ability in identifying particular abnormal lesions on mammograms through training test set with immediate feedback

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