Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions
Background: To evaluate the diagnostic accuracy of quantitative perfusion parameters in contrast-enhanced ultrasound to differentiate malignant from benign liver lesions. Methods: In this retrospective study 134 patients with a total of 139 focal liver lesions were included who underwent contrast en...
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doaj-020365112b4e4eb5938d2e20375855b52021-07-23T13:37:17ZengMDPI AGDiagnostics2075-44182021-07-01111244124410.3390/diagnostics11071244Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver LesionsSonja Schwarz0Dirk-André Clevert1Michael Ingrisch2Thomas Geyer3Vincent Schwarze4Johannes Rübenthaler5Marco Armbruster6Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 München, GermanyDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 München, GermanyDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 München, GermanyDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 München, GermanyDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 München, GermanyDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 München, GermanyDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377 München, GermanyBackground: To evaluate the diagnostic accuracy of quantitative perfusion parameters in contrast-enhanced ultrasound to differentiate malignant from benign liver lesions. Methods: In this retrospective study 134 patients with a total of 139 focal liver lesions were included who underwent contrast enhanced ultrasound (CEUS) between 2008 and 2018. All examinations were performed by a single radiologist with more than 15 years of experience using a second-generation blood pool contrast agent. The standard of reference was histopathology (<i>n</i> = 60), MRI or CT (<i>n</i> = 75) or long-term CEUS follow up (<i>n</i> = 4). For post processing regions of interests were drawn both inside of target lesions and the liver background. Time–intensity curves were fitted to the CEUS DICOM dataset and the rise time (RT) of contrast enhancement until peak enhancement, and a late-phase ratio (LPR) of signal intensities within the lesion and the background tissue, were calculated and compared between malignant and benign liver lesion using Student’s <i>t</i>-test. Quantitative parameters were evaluated with respect to their diagnostic accuracy using receiver operator characteristic curves. Both features were then combined in a logistic regression model and the cumulated accuracy was assessed. Results: RT of benign lesions (14.8 ± 13.8 s, <i>p</i> = 0.005), and in a subgroup analysis, particular hemangiomas (23.4 ± 16.2 s, <i>p</i> < 0.001) differed significantly to malignant lesions (9.3 ± 3.8 s). The LPR was significantly different between benign (1.59 ± 1.59, <i>p</i> < 0.001) and malignant lesions (0.38 ± 0.23). Logistic regression analysis with RT and LPR combined showed a high diagnostic accuracy of quantitative CEUS parameters with areas under the curve of 0.923 (benign vs. malignant) and 0.929 (hemangioma vs. malignant. Conclusions: Quantified CEUS parameters are helpful to differentiate malignant from benign liver lesions, in particular in case of atypical hemangiomas.https://www.mdpi.com/2075-4418/11/7/1244liver diagnostic imagingneoplasmultrasonographyimage enhancementimage processingcomputer-assisted |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sonja Schwarz Dirk-André Clevert Michael Ingrisch Thomas Geyer Vincent Schwarze Johannes Rübenthaler Marco Armbruster |
spellingShingle |
Sonja Schwarz Dirk-André Clevert Michael Ingrisch Thomas Geyer Vincent Schwarze Johannes Rübenthaler Marco Armbruster Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions Diagnostics liver diagnostic imaging neoplasm ultrasonography image enhancement image processing computer-assisted |
author_facet |
Sonja Schwarz Dirk-André Clevert Michael Ingrisch Thomas Geyer Vincent Schwarze Johannes Rübenthaler Marco Armbruster |
author_sort |
Sonja Schwarz |
title |
Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions |
title_short |
Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions |
title_full |
Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions |
title_fullStr |
Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions |
title_full_unstemmed |
Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions |
title_sort |
quantitative analysis of the time–intensity curve of contrast-enhanced ultrasound of the liver: differentiation of benign and malignant liver lesions |
publisher |
MDPI AG |
series |
Diagnostics |
issn |
2075-4418 |
publishDate |
2021-07-01 |
description |
Background: To evaluate the diagnostic accuracy of quantitative perfusion parameters in contrast-enhanced ultrasound to differentiate malignant from benign liver lesions. Methods: In this retrospective study 134 patients with a total of 139 focal liver lesions were included who underwent contrast enhanced ultrasound (CEUS) between 2008 and 2018. All examinations were performed by a single radiologist with more than 15 years of experience using a second-generation blood pool contrast agent. The standard of reference was histopathology (<i>n</i> = 60), MRI or CT (<i>n</i> = 75) or long-term CEUS follow up (<i>n</i> = 4). For post processing regions of interests were drawn both inside of target lesions and the liver background. Time–intensity curves were fitted to the CEUS DICOM dataset and the rise time (RT) of contrast enhancement until peak enhancement, and a late-phase ratio (LPR) of signal intensities within the lesion and the background tissue, were calculated and compared between malignant and benign liver lesion using Student’s <i>t</i>-test. Quantitative parameters were evaluated with respect to their diagnostic accuracy using receiver operator characteristic curves. Both features were then combined in a logistic regression model and the cumulated accuracy was assessed. Results: RT of benign lesions (14.8 ± 13.8 s, <i>p</i> = 0.005), and in a subgroup analysis, particular hemangiomas (23.4 ± 16.2 s, <i>p</i> < 0.001) differed significantly to malignant lesions (9.3 ± 3.8 s). The LPR was significantly different between benign (1.59 ± 1.59, <i>p</i> < 0.001) and malignant lesions (0.38 ± 0.23). Logistic regression analysis with RT and LPR combined showed a high diagnostic accuracy of quantitative CEUS parameters with areas under the curve of 0.923 (benign vs. malignant) and 0.929 (hemangioma vs. malignant. Conclusions: Quantified CEUS parameters are helpful to differentiate malignant from benign liver lesions, in particular in case of atypical hemangiomas. |
topic |
liver diagnostic imaging neoplasm ultrasonography image enhancement image processing computer-assisted |
url |
https://www.mdpi.com/2075-4418/11/7/1244 |
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