Evidence map›Paper›PMID 38112787›Full record

ArticleAbdominal radiology (New York)2024

Preoperative evaluation of MRI features and inflammatory biomarkers in predicting microvascular invasion of combined hepatocellular cholangiocarcinoma.

Juan Zhang, Wei Dong, Wanmin Liu, Jiazhao Fu, Tian Liao, Yinqiao Li, Lei Huo, Ningyang Jia

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Article in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Juan Zhang *Department of Radiology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Wei Dong *Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Wanmin Liu *Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Jiazhao FuDepartment of Organ Transplantation, Changhai Hospital, First Affiliated Hospital of Naval Medical University, Shanghai, China.
Tian LiaoDepartment of Ultrasound, Changsha Hospital of Traditional Chinese Medicine, Changsha, China.
Yinqiao LiSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
Lei HuoDepartment of Radiology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai, China. leidfgd@163.com.
Ningyang JiaDepartment of Radiology, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital of Naval Medical University, Shanghai, China. ningyangjia@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMicrovascular invasion (MVI) is a significant prognostic factor in combined hepatocellular cholangiocarcinoma (cHCC-CCA). However, its diagnosis relies on postoperative histopathologic analysis. This study aims to identify preoperative inflammatory biomarkers and MR-imaging features that can predict MVI in cHCC-CCA.

methodsThis retrospective study enrolled 119 patients with histopathologically confirmed cHCC-CCA between January 2016 and December 2021. Two radiologists, unaware of the clinical data, independently reviewed all MR image features. Univariable and multivariable analyses were performed to determine the independent predictors for MVI among inflammatory biomarkers and MRI characteristics. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the diagnostic performance.

resultsMultivariable logistic regression analysis identified four variables significantly associated with MVI (p < 0.05), including two inflammatory biomarkers [albumin-to-alkaline phosphatase ratio (AAPR) and aspartate aminotransferase-to-neutrophil ratio index (ANRI)] and two MRI features (non-smooth tumor margin and arterial phase peritumoral enhancement). A combined model for predicting MVI was constructed based on these four variables, with an AUC of 0.802 (95% CI 0.719-0.870). The diagnostic efficiency of the combined model was higher than that of the imaging model.

conclusionInflammatory biomarkers and MRI features could be potential predictors for MVI in cHCC-CCA. The combined model, derived from inflammatory biomarkers and MRI features, showed good performance in preoperatively predicting MVI in cHCC-CCA patients.

Indexed as

Bile Duct NeoplasmsCarcinoma, HepatocellularCholangiocarcinomaLiver NeoplasmsBile Ducts, IntrahepaticBiomarkersHumansMagnetic Resonance ImagingNeoplasm InvasivenessRetrospective StudiesBiomarkersCombined hepatocellular cholangiocarcinomaInflammatory biomarkersMagnetic resonance imagingMicrovascular invasionRisk factors

Identifiers

PMID38112787
PMCPMC10909765

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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.