Benign liver lesions: implications of detection in cancer patients

1995 ◽  
Vol 5 (4) ◽  
Author(s):  
J.N. Bruneton ◽  
C. Raffaelli ◽  
C. Maestro ◽  
B. Padovani
Keyword(s):  
Cancer Patients ◽  
Liver Lesions ◽  
Benign Liver ◽  
Benign Liver Lesions

scholarly journals Quantitative Analysis of the Time–Intensity Curve of Contrast-Enhanced Ultrasound of the Liver: Differentiation of Benign and Malignant Liver Lesions

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1244
Author(s):  
Sonja Schwarz ◽  
Dirk-André Clevert ◽  
Michael Ingrisch ◽  
Thomas Geyer ◽  
Vincent Schwarze ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Diagnostic Accuracy ◽  
Late Phase ◽  
Focal Liver Lesions ◽  
Liver Lesions ◽  
Contrast Enhanced Ultrasound ◽  
Contrast Enhanced ◽  
Malignant Lesions ◽  
Benign Liver ◽  
Benign 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 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 (n = 60), MRI or CT (n = 75) or long-term CEUS follow up (n = 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 t-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, p = 0.005), and in a subgroup analysis, particular hemangiomas (23.4 ± 16.2 s, p < 0.001) differed significantly to malignant lesions (9.3 ± 3.8 s). The LPR was significantly different between benign (1.59 ± 1.59, p < 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.

Primary benign liver lesions

2017 ◽  
Vol 95 ◽  
pp. 378-398 ◽  
Author(s):  
Luigi Grazioli ◽  
Roberta Ambrosini ◽  
Barbara Frittoli ◽  
Marco Grazioli ◽  
Mario Morone
Keyword(s):  
Liver Lesions ◽  
Benign Liver ◽  
Benign Liver Lesions

Hyperintense benign liver lesions on spin-echo T1-weighted MR images: pathologic correlations

1997 ◽  
Vol 22 (4) ◽  
pp. 410-417 ◽  
Author(s):  
D. Mathieu ◽  
M. Paret ◽  
A.-E. Mahfouz ◽  
F. Caseiro-Alves ◽  
J. Tran Van Nhieu ◽  
...  
Keyword(s):  
Spin Echo ◽  
Liver Lesions ◽  
Mr Images ◽  
Benign Liver ◽  
Benign Liver Lesions

Diagnosis and management of solid benign liver lesions

2014 ◽  
Vol 11 (12) ◽  
pp. 737-749 ◽  
Author(s):  
Jacques Belghiti ◽  
François Cauchy ◽  
Valérie Paradis ◽  
Valérie Vilgrain
Keyword(s):  
Liver Lesions ◽  
Diagnosis And Management ◽  
Benign Liver ◽  
Benign Liver Lesions

scholarly journals Laparoscopic left lateral resection is the gold standard for benign liver lesions: a case–control study

HPB ◽  
2014 ◽  
Vol 16 (2) ◽  
pp. 183-187 ◽  
Author(s):  
Safi Dokmak ◽  
Vikram Raut ◽  
Béatrice Aussilhou ◽  
Fadhel Samir Ftériche ◽  
Olivier Farges ◽  
...  
Keyword(s):  
Gold Standard ◽  
Case Control Study ◽  
Case Control ◽  
Liver Lesions ◽  
Benign Liver ◽  
Control Study ◽  
Benign Liver Lesions

Benign liver lesions

2017 ◽  
Vol 35 (12) ◽  
pp. 700-706
Author(s):  
Alastair J. Hayes ◽  
Damian J. Mole
Keyword(s):  
Liver Lesions ◽  
Benign Liver ◽  
Benign Liver Lesions

An algorithm for the accurate identification of benign liver lesions

2004 ◽  
Vol 187 (2) ◽  
pp. 274-279 ◽  
Author(s):  
Joseph Kim ◽  
Syed A Ahmad ◽  
Andrew M Lowy ◽  
Joseph F Buell ◽  
Linda J Pennington ◽  
...  
Keyword(s):  
Liver Lesions ◽  
Accurate Identification ◽  
Benign Liver ◽  
Benign Liver Lesions
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