The role of gadoxetic acid-enhanced MRI features for predicting microvascular invasion in patients with hepatocellular carcinoma

2021 ◽  
Author(s):  
Hongli Yang ◽  
Ping Han ◽  
Mengting Huang ◽  
Xiaofei Yue ◽  
Linxia Wu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Microvascular Invasion ◽  
Gadoxetic Acid ◽  
Enhanced Mri ◽  
Mri Features

Preoperative gadoxetic acid–enhanced MRI for predicting microvascular invasion in patients with single hepatocellular carcinoma

2017 ◽  
Vol 67 (3) ◽  
pp. 526-534 ◽  
Author(s):  
Sunyoung Lee ◽  
Seong Hyun Kim ◽  
Ji Eun Lee ◽  
Dong Hyun Sinn ◽  
Cheol Keun Park
Keyword(s):  
Hepatocellular Carcinoma ◽  
Microvascular Invasion ◽  
Gadoxetic Acid ◽  
Enhanced Mri

scholarly journals MRI Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Liver Cancer ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 94-106
Author(s):  
Seung Baek Hong ◽  
Sang Hyun Choi ◽  
So Yeon Kim ◽  
Ju Hyun Shim ◽  
Seung Soo Lee ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Size ◽  
Meta Analysis ◽  
Diagnostic Odds Ratio ◽  
Microvascular Invasion ◽  
Hepatobiliary Phase ◽  
Phase Imaging ◽  
Arterial Enhancement ◽  
Mri Features ◽  
Peritumoral Enhancement

<b><i>Purpose:</i></b> Microvascular invasion (MVI) is an important prognostic factor in patients with hepatocellular carcinoma (HCC). However, the reported results of magnetic resonance imaging (MRI) features for predicting MVI of HCC are variable and conflicting. Therefore, this meta-analysis aimed to identify the significant MRI features for MVI of HCC and to determine their diagnostic value. <b><i>Methods:</i></b> Original studies reporting the diagnostic performance of MRI for predicting MVI of HCC were identified in MEDLINE and EMBASE up until January 15, 2020. Study quality was assessed using QUADAS-2. A bivariate random-effects model was used to calculate the meta-analytic pooled diagnostic odds ratio (DOR) and 95% confidence interval (CI) for each MRI feature for diagnosing MVI in HCC. The meta-analytic pooled sensitivity and specificity were calculated for the significant MRI features. <b><i>Results:</i></b> Among 235 screened articles, we found 36 studies including 4,274 HCCs. Of the 15 available MRI features, 7 were significantly associated with MVI: larger tumor size (&#x3e;5 cm) (DOR = 5.2, 95% CI [3.0–9.0]), rim arterial enhancement (4.2, 95% CI [1.7–10.6]), arterial peritumoral enhancement (4.4, 95% CI [2.8–6.9]), peritumoral hypointensity on hepatobiliary phase imaging (HBP) (8.2, 95% CI [4.4–15.2]), nonsmooth tumor margin (3.2, 95% CI [2.2–4.4]), multifocality (7.1, 95% CI [2.6–19.5]), and hypointensity on T1-weighted imaging (T1WI) (4.9, 95% CI [2.5–9.6]). Both peritumoral hypointensity on HBP and multifocality showed very high meta-analytic pooled specificities for diagnosing MVI (91.1% [85.4–94.8%] and 93.3% [74.5–98.5%], respectively). <b><i>Conclusions:</i></b> Seven MRI features including larger tumor size, rim arterial enhancement, arterial peritumoral enhancement, peritumoral hypointensity on HBP, nonsmooth margin, multifocality, and hypointensity on T1WI were significant predictors for MVI of HCC. These MRI features predictive of MVI can be useful in the management of HCC.

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