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

• DOI: 10.1292/jvms.19-0278
• Publication Date: 2019-10-09T22:30:00Z
• Authors: Rommaneeya LEELA-...; Hiroshi OHTA; Genya SHIMBO; Kiwamu HANAZONO; Tatsuyuki OSUGA; Keitaro MORISHITA; Noboru SASAKI; Mitsuyoshi TAKIGUCHI
• Keywords: Clinical Significance; Etiology

Thus far, there are few computed tomography (CT) characteristics that can distinguish benign and malignant etiologies.The criteria complex, subjective, difficult to use in clinical applications due the high level of experience needed.This study aimed identify practical CT variables their relevance for broadly classifying histopathological diagnoses as or malignant.In this prospective study, all dogs with liver nodules masses underwent examination subsequent diagnosis were included.Signalments, findings recorded.Seventy 57 diagnosed, comprising 18 52 lesions.Twenty-three qualitative quantitative evaluated using univariate stepwise multivariate analyses, respectively.Two variables, namely, postcontrast enhancement pattern lesion delayed phase (heterogeneous; odds ratio (OR): 14.7, 95% confidence interval (CI): 0.82-262.03,P=0.0429) maximal transverse diameter (>4.5 cm; OR: 33.3, CI: 2.29-484.18,P=0.0006), significantly related differentiation from lesions, an area under curve 0.8910, representing accuracy 88.6%.These indicate features triple-phase provide information distinguishing pathological varieties focal lesions decision making.Evaluations included simple predicting malignancy settings.