<0.01),fECV值评估肝细胞癌分化程度的曲线下面积(area under curve,AUC)为0.869(95% CI:0.759~0.979);高分化组与低分化组诊断界值为28.56%,灵敏度为71%,特异度为90%。
结论:
fECV可以作为肝脏多期动态增强CT检查中无创性评估肝细胞癌分化程度的指标。
Abstract
Objective:
To explore the value of extracellular volume fraction (fECV) in assessing the degree of differentiation of hepatocellular carcinoma (HCC).
Methods:
A total of 41 patients with HCC diagnosed by surgical pathology and routine liver multi-phase dynamic contrast-enhanced CT scan were enrolled in Liaoning Cancer Hospital Institute. The absolute enhancement values of the liver tumor (Etumor) and the aorta (Eaorta) were c
alculated by the plain and equilibration period (after injection of the contrast agent for 140 s)
and then we calculated the fECV values by the following formula: fECV(%)=Etumor/Eaorta[100-Hct (%)]. According to the Edmondson-Steiner classification of HCC
the lower grade group (grade Ⅰ and Ⅱ) and the higher grade group (grade Ⅲ and Ⅳ) were compared. We explored whether the difference of fECV value between the two groups was statistically significant.
Results:
The fECV value of the tumor in lower grade group was (30.617.84)%
and that in the higher grade group was (21.136.17)%. The fECV values of the HCC in the lower grade group and the higher grade group were statistically significant (
P
<0.01)
and the area under curve (AUC) of the fECV value for evaluating the differentiation of HCC was 0.869 (95% CI: 0.759~0.979); the diagnostic boundary value of the lower grade group and the higher grade group was 28.56%. The sensitivity was 71% and the specificity was 90%.
Conclusion:
Extracellular volume fraction can be used as an indicator for non-invasive assessment of HCC differentiation by liver multi-phase dynamic contrast-enhanced CT examination.
Application of magnetic resonance elastography in the identification of benign and malignant liver lesions and prognostic prediction of malignant tumors
Study on optimizing the prediction model for microvascular invasion in hepatocellular carcinoma by integrating peripheral blood immune cells and FS-T2WI radiomics
Nomogram prediction model of contrast-enhanced ultrasound combined with clinical and pathological features to evaluate the risk of early recurrence after surgical resection of hepatocellular carcinoma
Contrast-enhanced ultrasound for the diagnosis of intrahepatic cholangiocarcinoma: debates, focus areas and emerging perspectives
LI-RADS analysis and differential diagnosis of intrahepatic cholangiocarcinoma by contrast-enhanced ultrasound
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