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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Main Authors: Sonja Schwarz, Dirk-André Clevert, Michael Ingrisch, Thomas Geyer, Vincent Schwarze, Johannes Rübenthaler, Marco Armbruster
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Diagnostics
Subjects:
Online Access:https://www.mdpi.com/2075-4418/11/7/1244
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spelling 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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