Evidence map›Paper›PMID 35111631›Full record

ArticleQuantitative imaging in medicine and surgery2022

Histogram peritumoral enhanced features on MRI arterial phase with extracellular contrast agent can improve prediction of microvascular invasion of hepatocellular carcinoma.

Xinxin Wang, Yunfeng Sun, Xueyan Zhou, Zhiwei Shen, Hongxia Zhang, Jiqing Xing, Yang Zhou

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Article in Quantitative imaging in medicine and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Evaluation and prediction of Ki-67 expression in hepatocellular carcinoma.World journal of gastrointestinal oncology · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Review
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xinxin Wang *Department of Radiology, Harbin Medical University Cancer Hospital, Harbin, China.
Yunfeng Sun *Department of Radiology, Harbin Medical University Cancer Hospital, Harbin, China.
Xueyan ZhouSchool of Technology, Harbin University, Harbin, China.
Zhiwei ShenPhilips Healthcare China, Beijing, China.
Hongxia ZhangDepartment of Radiology, Harbin Medical University Cancer Hospital, Harbin, China.
Jiqing XingDepartment Physical Education, Harbin Engineering University, Harbin, China.
Yang ZhouDepartment of Radiology, Harbin Medical University Cancer Hospital, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreoperative microvascular invasion (MVI) prediction plays an important role in therapeutic decision-making of hepatocellular carcinoma (HCC). This study aimed to investigate the value of histogram based on the arterial phase (AP) of magnetic resonance imaging (MRI) with extracellular contrast agent compared with radiological features for predicting MVI of solitary HCC.

methodsIn total, 113 patients with pathologically proven solitary HCC were retrospectively enrolled who received surgical resection and underwent preoperative abdominal MRI. The patients were divided into the ≤3 cm [small HCC (sHCC)] cohort and the >3 cm cohort. Based on pathological analysis of surgical specimens, the patients were classified into MVI negative (MVI-) and MVI positive (MVI+) groups. Peritumoral and intratumoral histogram features [mean, median, standard deviation (Std), coefficient of variation (CV), skewness, kurtosis] were acquired on AP subtraction images and radiological features [size, capsule, corona enhancement, corona enhancement thickness (CET), CET group]. Receiver operating characteristic (ROC) curve was constructed to assess predictive capability. Subgroup analysis of patients with a visible corona enhancement based on the CET cut-off value was performed.

resultsNone of the features extracted from the intratumor area were significantly different between the MVI+ and MVI- groups in both cohorts. Histogram defined peritumoral (peri-) mean, median, kurtosis, and radiological features including CET and CET group were associated with MVI in sHCCs. Peri-mean, median, Std and radiological features including incomplete capsule, CET, and CET group were associated with MVI in HCC >3 cm. In multivariate logistic regression analysis, the CET group and peri-mean were independent predictors for HCC >3 cm with an area under the curve (AUC) of 0.741. Peri-mean was an independent predictor for sHCC (AUC =0.798). Subgroup analysis of the corona enhancement using 8 mm as a cut-off value showed 100% sensitivity and negative predictive value (NPV).

conclusionsPeritumoral AP enhanced degree on MRI showed an encouraging predictive performance for preoperative prediction of MVI, especially in sHCCs. CET ≤8 mm could be used as a negative predictive marker for MVI.

Indexed as

contrast enhancementhepatocellular carcinoma (HCC)magnetic resonance imaging (MRI)Microvascular invasion (MVI)quantitative analysis

Identifiers

PMID35111631
PMCPMC8739130

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