Differentiation of malignant and benign incidental breast lesions detected by chest multidetector-row computed tomography: Added value of quantitative enhancement analysis

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Lin, Yu-Pang
Hsu, Hsian-He
Ko, Kai-Hsiung
Chu, Chi-Ming
Chou, Yu-Ching
Chang, Wei-Chou
Chang, Tsun-Hou
Griffith University Author(s)
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2016
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Abstract

To retrospectively determine the association between breast lesion morphology and malignancy and to determine the optimal value of lesion enhancement (HU, Hounsfield units) to improve the diagnostic accuracy of breast cancer in patients with incidental breast lesions (IBLs). A total of 97 patients with 102 IBLs detected from July 2009 to December 2012 were enrolled in this study. Two radiologists analyzed CT images for the presence of malignancy based on the morphology of the lesions alone and in combination with an enhancement value (HU) analysis. There were 36 malignant and 66 benign IBLs. When the morphology and enhancement values were combined, the sensitivity, specificity, and accuracy were 92%, 97%, and 95%, respectively, for reader 1 and 89%, 94%, and 92%, respectively, for reader 2. The addition of HU values led to correct changes in the diagnosis; specifically, the accuracy of the diagnosis of reader 1 and reader 2 improved by 6.9% and 11.8%, respectively. The addition of the enhancement value (HU) to the CT morphology improved the diagnostic accuracy in the differentiation of malignant from benign IBLs by using the region of interest (ROI) to measure the HU within the most suspicious part of the lesion.

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PLoS One

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11

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4

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© 2016 Lin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Clinical sciences

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Lin, YP; Hsu, HH; Ko, KH; Chu, CM; Chou, YC; Chang, WC; Chang, TH, Differentiation of malignant and benign incidental breast lesions detected by chest multidetector-row computed tomography: Added value of quantitative enhancement analysis, PLoS One, 2016, 11 (4), pp. e0154569-

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