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Computed tomographic features for differentiating benign from malignant liver lesions in dogs

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Title: Computed tomographic features for differentiating benign from malignant liver lesions in dogs
Authors: Leela-Arporn, Rommaneeya Browse this author
Ohta, Hiroshi Browse this author →KAKEN DB
Shimbo, Genya Browse this author
Hanazono, Kiwamu Browse this author
Osuga, Tatsuyuki Browse this author
Morishita, Keitaro Browse this author →KAKEN DB
Sasaki, Noboru Browse this author →KAKEN DB
Takiguchi, Mitsuyoshi Browse this author →KAKEN DB
Keywords: canine
computed tomography
Issue Date: Dec-2019
Publisher: 公益社団法人 日本獣医学会 (The Japanese Society of Veterinary Science)
Journal Title: Journal of veterinary medical science
Volume: 81
Issue: 12
Start Page: 1697
End Page: 1704
Publisher DOI: 10.1292/jvms.19-0278
Abstract: Thus far, there are few computed tomography (CT) characteristics that can distinguish benign and malignant etiologies. The criteria are complex, subjective, and difficult to use in clinical applications due to the high level of experience needed. This study aimed to identify practical CT variables and their clinical relevance for broadly classifying histopathological diagnoses as benign or malignant. In this prospective study, all dogs with liver nodules or masses that underwent CT examination and subsequent histopathological diagnosis were included. Signalments, CT findings and histopathological diagnoses were recorded. Seventy liver nodules or masses in 57 dogs were diagnosed, comprising 18 benign and 52 malignant lesions. Twenty-three qualitative and quantitative CT variables were evaluated using univariate and stepwise multivariate analyses, respectively. Two variables, namely, the postcontrast enhancement pattern of the lesion in the delayed phase (heterogeneous; odds ratio (OR): 14.7, 95% confidence interval (CI): 0.82-262.03, P=0.0429) and the maximal transverse diameter of the lesion (>4.5 cm; OR: 33.3, 95% CI: 2.29-484.18, P=0.0006), were significantly related to the differentiation of benign from malignant liver lesions, with an area under the curve of 0.8910, representing an accuracy of 88.6%. These findings indicate that features from triple-phase CT can provide information for distinguishing pathological varieties of focal liver lesions and for clinical decision making. Evaluations of the maximal transverse diameter and postcontrast enhancement pattern of the lesion included simple CT features for predicting liver malignancy with high accuracy in clinical settings.
Type: article
Appears in Collections:獣医学院・獣医学研究院 (Graduate School of Veterinary Medicine / Faculty of Veterinary Medicine) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 滝口 満喜

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