Liver Imaging Reporting and Data System Category 5: MRI Predictors of Microvascular Invasion and Recurrence After Hepatectomy for Hepatocellular Carcinoma

Chen, Jingbiao; Zhou, Jing; Kuang, Sichi; Zhang, Yao; Xie, Sidong; He, Baorong; Deng, Ying; Yang, Hao; Shan, Qungang; Wu, Jun; Sirlin, Claude B.; Wang, Jin

doi:10.2214/ajr.19.21168

Cited by 64 publications

(65 citation statements)

References 32 publications

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“…At present, the semantic features (e.g., peritumoral enhancement, non-smooth tumor margin, and peritumoral hypo-intensity at the hepatobiliary phase) derived from preoperative imaging may be potential independent predictors for MVI status in HCC (11,12,36,40,44,45,47). However, there is no consensus.…”

Section: Discussionmentioning

confidence: 99%

“…Many studies focusing on MVI status prediction in HCC demonstrate that image features (e.g., tumor size, peritumoral enhancement, non-smooth tumor margin, peritumoral hypo-intensity at the hepatobiliary phase, intra-tumoral artery, and non-nodule type) are correlated with MVI status in HCC, which can be utilized to predict MVI status in HCC ( 10 – 12 , 30 , 36 , 38 , 40 , 44 – 47 ). Among them, peritumor enhancement and non-smooth tumor margin are considered as important independent predictors in different studies ( 11 , 44 – 46 ). However, mosaic architecture is the only independent predictor of MVI in Liver Imaging Reporting and Data System category 5 (LR-5) HCCs based on LI-RADS ( 44 ).…”

Section: Discussionmentioning

confidence: 99%

“…Among them, peritumor enhancement and non-smooth tumor margin are considered as important independent predictors in different studies ( 11 , 44 – 46 ). However, mosaic architecture is the only independent predictor of MVI in Liver Imaging Reporting and Data System category 5 (LR-5) HCCs based on LI-RADS ( 44 ). The conflicting results can be partially attributed to the limited case numbers in different retrospective observational studies.…”

Section: Discussionmentioning

confidence: 99%

“…The selection procedure is shown in Figure 1 (23). In total, 33 studies involving nine studies based on radiomics (17)(18)(19)(24)(25)(26)(27)(28)(29)) and 24 studies based on non-radiomics (10)(11)(12)(13)(14)(15)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47) were eligible for this diagnostic meta-analysis. A total of 5,462 HCC patients were included.…”

Section: Literature Selection and Quality Assessmentmentioning

confidence: 99%

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Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis

et al. 2020

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Background: To compare the predictive power between radiomics and non-radiomics (conventional imaging and functional imaging methods) for preoperative evaluation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: Comprehensive publications were screened in PubMed, Embase, and Cochrane Library. Studies focusing on the discrimination values of imaging methods, including radiomics and non-radiomics methods, for MVI evaluation were included in our meta-analysis. Results: Thirty-three imaging studies with 5,462 cases, focusing on preoperative evaluation of MVI status in HCC, were included. The sensitivity and specificity of MVI prediction in HCC were 0.78 [95% confidence interval (CI): 0.75-0.80; I 2 = 70.7%] and 0.78 (95% CI: 0.76-0.81; I 2 = 0.0%) for radiomics, respectively, and were 0.73 (95% CI: 0.71-0.75; I 2 = 83.7%) and 0.82 (95% CI: 0.80-0.83; I 2 = 86.5%) for non-radiomics, respectively. The areas under the receiver operation curves for radiomics and non-radiomics to predict MVI status in HCC were 0.8550 and 0.8601, respectively, showing no significant difference. Conclusion: The imaging method is feasible to predict the MVI state of HCC. Radiomics method based on medical image data is a promising application in clinical practice and can provide quantifiable image features. With the help of these features, highly consistent prediction performance will be achieved in anticipation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Literature Selection and Quality Assessmentmentioning

confidence: 99%

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Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis

et al. 2020

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“…The system addresses the full spectrum of liver lesions and pseudolesions with a 5-point scale reflecting the relative likelihood of HCC, from LR-1 (definitely benign) to LR-5 (definitely HCC) and LR-M. Although LI-RADS was conceived as a diagnostic system, LI-RADS imaging features (12–14) as well as some non-LI-RADS imaging features, such as tumor number (6) and irregular tumor margins (10, 15, 16), may provide prognostic information. However, to the best of our knowledge, few studies have attempted to identify major and ancillary imaging features predicting ER in patients with eHCC after curative resection as determined by LI-RADS.…”

Section: Introductionmentioning

confidence: 99%

The Role of Preoperative Dynamic Contrast-enhanced 3.0-T MR Imaging in Predicting Early Recurrence in Patients With Early-Stage Hepatocellular Carcinomas After Curative Resection

et al. 2019

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Objectives: Liver resection is potentially curative for early-stage hepatocellular carcinoma (eHCC) in patients with well-preserved liver function. The prognosis of these patients after resection is still unsatisfactory because of frequent early recurrence (ER). Therefore, we investigated the role of preoperative dynamic contrast-enhanced 3.0-T MR imaging in predicting ER of eHCC after curative resection.Methods From May 2014 to October 2017, we retrospectively analyzed 82 patients with eHCC who underwent dynamic MR imaging and subsequently underwent curative resection. Liver Imaging Reporting and Data System (LI-RADS) v2018 major and ancillary imaging features, as well as two non-LI-RADS MR imaging features (irregular tumor margin and tumor number), were evaluated. A multivariate Cox regression analysis was used to identify independent predictors, and two models (preoperative and postoperative prediction models) were developed.Results ER was observed in 25 patients (25/82, 30.5%). In the univariate analyses, preoperative alpha-fetoprotein (AFP) level >200 ng/ml, three MR imaging features (multifocal tumors, corona enhancement, and irregular tumor margin), and microvascular invasion (MVI) were associated with ER. In the multivariate analysis, corona enhancement (hazard ratio [HR]: 2.970; p = 0.013) and irregular tumor margin (HR: 2.377; p = 0.048) were independent predictors in the preoperative prediction model, and preoperative AFP level >200 ng/ml (HR: 2.493; p = 0.044) plus corona enhancement (HR: 3.046; p = 0.014) were independent predictors in the postoperative prediction model (microvascular invasion [MVI] was not; p = 0.061). When combined with both predictors, the specificity for ER in the preoperative prediction model was 98.2% (56/57), which was comparable to that of the postoperative prediction model [96.7% (55/57)].Conclusions Our results demonstrated that preoperative MR imaging features (corona enhancement and irregular tumor margin) have the potential to preoperatively identify high-risk ER patients with eHCC, with a specificity >90%.

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Does Training in LI‐RADS Version 2018 Improve Readers' Agreement with the Expert Consensus and Inter‐reader Agreement in MRI Interpretation?

Zhang

Ren

et al. 2021

Magnetic Resonance Imaging

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Background: The Liver Imaging Reporting and Data System (LI-RADS) was established for noninvasive diagnosis for hepatocellular carcinoma (HCC). However, whether training can improve readers' agreement with the expert consensus and inter-reader agreement for final categories is still unclear. Purpose: To explore training effectiveness on readers' agreement with the expert consensus and inter-reader agreement. Study Type: Prospective. Subjects: Seventy lesions in 61 patients at risk of HCC undergoing liver MRI; 20 visiting scholars. Field Strength/Sequence: 1.5 T or 3 T, Dual-echo T 1 WI, Fast spin-echo T 2 WI, SE-EPI DWI, and Dynamic multiphase fast gradient-echo T 1 WI. Assessment: Seventy lesions assigned LI-RADS categories of LR1-LR5, LR-M, and LR-TIV by three radiologists in consensus were randomly selected, with 10 cases for each category. The consensus opinion was the standard reference. The third radiologist delivered the training. Twenty readers reviewed images independently and assigned each an LI-RADS category both before and after the training.

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Liver Imaging Reporting and Data System Category 5: MRI Predictors of Microvascular Invasion and Recurrence After Hepatectomy for Hepatocellular Carcinoma

Cited by 64 publications

References 32 publications

Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis

Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis

The Role of Preoperative Dynamic Contrast-enhanced 3.0-T MR Imaging in Predicting Early Recurrence in Patients With Early-Stage Hepatocellular Carcinomas After Curative Resection

Does Training in LI‐RADS Version 2018 Improve Readers' Agreement with the Expert Consensus and Inter‐reader Agreement in MRI Interpretation?

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