Evidence map›Paper›PMID 36435877›Full record

ArticleEuropean radiology2023

The value of quantitative MR elastography-based stiffness for assessing the microvascular invasion grade in hepatocellular carcinoma.

Lina Zhang, Mengsi Li, Jie Zhu, Yao Zhang, Yuanqiang Xiao, Mengshi Dong, Linqi Zhang, Jin Wang

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Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 20 citations in OpenAlex.

  1. [Research advances of magnetic resonance elastography for assessing the bioinvasiveness in hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Lina ZhangDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong, 510630, People's Republic of China.
Mengsi LiDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong, 510630, People's Republic of China.
Jie ZhuDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong, 510630, People's Republic of China.
Yao ZhangDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong, 510630, People's Republic of China.
Yuanqiang XiaoDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong, 510630, People's Republic of China.
Mengshi DongDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong, 510630, People's Republic of China.
Linqi ZhangDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong, 510630, People's Republic of China.
Jin WangDepartment of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), No. 600, Tianhe Road, Guangzhou, Guangdong, 510630, People's Republic of China. wangjin3@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-6424-8254
Sun Yat-sen University · CN

Funding

Clinical Research Foundation of the 3rd Affiliated Hospital of Sun Yat-sen University YHJH201901Guangdong Basic and Applied Basic Research Foundation 2021A1515010582Key Research and Development Program of Guangdong Province 2019B020235002National Natural Science Foundation of China 82101994National Natural Science Foundation of China 91959118SKY Radiology Department International Medical Research Foundation of China Z-2014-07-2101
6 · The paper itself

Abstract

objectivesTo evaluate the potential diagnostic value of MR elastography (MRE)-based stiffness to noninvasively predict the microvascular invasion (MVI) grade in hepatocellular carcinoma (HCC).

methodsOne hundred eighty-five patients with histopathology-proven HCC who underwent MRI and MRE examinations before hepatectomy were retrospectively enrolled. According to the three-tiered MVI grading system, the MVI was divided into negative-MVI (n = 89) and positive-MVI (n = 96) groups, and the latter group was categorized into mild-MVI (n = 49) and severe-MVI (n = 47) subgroups. Logistic regression and area under the receiver operating characteristic curve (AUC) analyses were used to determine the predictors associated with MVI grade and analyze their performances, respectively.

resultsAmong the 185 patients, tumor size ≥ 50 mm (p = 0.031), tumor stiffness (TS)/liver stiffness (LS) > 1.47 (p = 0.001), TS > 4.33 kPa (p < 0.001), and nonsmooth tumor margin (p = 0.006) were significant independent predictors for positive-MVI. Further analyzing the subgroups, tumor size ≥ 50 mm (p < 0.001), TS > 5.35 kPa (p = 0.001), and AFP level > 400 ng/mL (p = 0.044) were independently associated with severe-MVI. The models incorporating MRE and clinical-radiological features together performed better for evaluating positive-MVI (AUC: 0.846) and severe-MVI (AUC: 0.802) than the models using clinical-radiological predictors alone (AUC: positive-/severe-MVI, 0.737/0.743). Analysis of recurrence-free survival and overall survival showed the predicted positive-MVI/severe-MVI groups based on combined models had significantly poorer prognoses than predicted negative-MVI/mild-MVI groups, respectively (all p < 0.05).

conclusionsMRE-based stiffness was an independent predictor for both the positive-MVI and severe-MVI. The combination of MRE and clinical-radiological models might be a useful tool for evaluating HCC patients' prognoses underwent hepatectomy by preoperatively predicting the MVI grade. KEY POINTS: • The severe-microvascular invasion (MVI) grade had the highest tumor stiffness (TS), followed by mild-MVI and non-MVI, and there were significances among the three different MVI grades. • MR elastography (MRE)-based stiffness value was an independent predictor of positive-MVI and severe-MVI in hepatocellular carcinoma (HCC) preoperatively. • When combined with clinical-radiological models, MRE could significantly improve the predictive performance for MVI grade. Patients with predicted positive-MVI/severe-MVI based on the combined models had worse recurrence-free survival and overall survival than those with negative-MVI/mild-MVI, respectively.

Indexed as

Carcinoma, HepatocellularElasticity Imaging TechniquesLiver NeoplasmsHumansMagnetic Resonance ImagingNeoplasm InvasivenessRetrospective StudiesElasticity imaging techniquesHepatocellular carcinomaMagnetic resonanceMicrovessel

Identifiers

PMID36435877
OpenAlexW4310276557

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.