中分化[标准化均数差(standardized mean difference,SMD)=0.98;95% CI:0.57~1.39],高分化
vs
低分化(SMD=2.19;95% CI:1.60~2.79),中分化
vs
低分化(SMD=1.03;95% CI:0.83~1.23)结果显示,ADC
mean
鉴别高、中、低分化HCC各组间差异均有统计学意义(
P
<0.000 01)。ADC
mean
和ADC
min
术前定量预测低分化HCC的合并灵敏度为0.84和0.81(
Z
=-0.186,
P
=0.852)、特异度为0.81和0.67(
Z
=-0.445,
P
=0.656)、受试者工作特征曲线的曲线下面积为0.881 5和0.859 8(
Z
=-0.170,
P
=0.865),差异均无统计学意义。
结论:
ADC
mea
n 及ADC
min
术前定量预测低分化HCC均具有较高的诊断效能,但两者差异无统计学意义;ADC
mean
与HCC组织学病理分化程度正相关,可作为一种可靠、无创的术前定量
预测HCC组织学病理分级的重要手段。
Abstract
Objective:
To investigate the feasibility of magnetic resonance apparent diffusion coefficient (ADC) value in predicting the histopathological grade of hepatocellular carcinoma (HCC) by meta-analysis
and to compare the diagnostic efficacy of ADC mean value (ADC
mean
) and ADC minimum value (ADC
min
) in preoperative quantitative prediction of poorly differentiated HCC.
Methods:
Related researches were researched from January 2000 to October 2020 for studying the diagnostic value of ADC value in the degree of differentiation (well
medium and poor differentiation) of HCC in databases. Two researchers independently screened the literature and extracted data according to the inclusion and exclusion criteria
and evaluated the quality of the included studies. And then the included studies were analyzed with using statistical software.
Results:
Totally 18 up-to-standard literatures (7 in Chinese and 11 in English) were included
including 1 807 HCC columns (329 well differentiated
1 048 moderately differentiated
and 430 poorly differentiated). There was no publication bias in each study (
P
>0.1). The results showed high differentiation
vs
medium differentiation [standardized mean difference (SMD)=0.98; 95% CI: 0.57-1.39]
high differentiation
vs
low differentiation (SMD=2.19; 95% CI: 1.60-2.79)
moderate differentiationvs low differentiation (SMD=1.03; 95% CI: 0.83-1.23). The differences of ADC
mean
in the identification of high
middle and low differentiation HCC groups were statistically significant (
P
<0.000 01) . The combined sensitivity
specificity and area under summary receiver operating characteristic curve of ADC
mean
and ADC
min
in preoperative quantitative prediction of poorly differentiated HCC were 0.84 and 0.81 (
Z
=-0.186
P
=0.852)
0.81 and 0.67 (
Z
=-0.445
P
=0.656)
0.881 5 and 0.859 8 (
Z
=-0.170
P
=0.865)
respectively. The difference was not statistically significant.
Conclusion:
The ADC
mean
and ADC
min
had high diagnostic efficiency in preoperative quantitative prediction of poorly differentiated HCC
but there was no significant difference between them. ADC
mean
was positively correlated with the degree of histological and pathological differentiation of HCC
which could be used as a reliable and noninvasive method to quantitatively predict the histological and pathological grading of HCC.
Study on optimizing the prediction model for microvascular invasion in hepatocellular carcinoma by integrating peripheral blood immune cells and FS-T2WI radiomics
Application of magnetic resonance elastography in the identification of benign and malignant liver lesions and prognostic prediction of malignant tumors
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
LI-RADS analysis and differential diagnosis of intrahepatic cholangiocarcinoma by contrast-enhanced ultrasound
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Related Author
Pengfei YANG
Yiping GAO
Mingxia JIANG
Kai SU
Shuangqing CHEN
Dong LIU
Xutong HUANG
Wenxin MA
Related Institution
Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University
Department of Radiology, Suzhou BOE Hospital
Department of Radiology, Third Affiliated Hospital of Naval Medical University
MR Collaboration, United Imaging Research
Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine