Evidence map›Paper›PMID 35048134›Full record

ArticleEuropean radiology2022

Prediction of microvascular invasion in HCC by a scoring model combining Gd-EOB-DTPA MRI and biochemical indicators.

Kun Zhang, Shuang-Shuang Xie, Wen-Cui Li, Zhao-Xiang Ye, Zhi-Wei Shen, Wen Shen

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In one paragraph

Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

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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

6 authors at 4 institutions in 1 country.

Kun ZhangDepartment of Radiology, First Central Clinical College, Tianjin Medical University, 22 Qixiangtai Road, Heping District, Tianjin, 300070, China.
Shuang-Shuang XieDepartment of Radiology, Tianjin Medical Imaging Institute, School of Medicine, Tianjin First Central Hospital, Nankai University, Nankai District, No. 24 Fukang Road, Tianjin, 300192, China.
Wen-Cui LiDepartment of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Zhao-Xiang YeDepartment of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Zhi-Wei ShenPhilips Healthcare, The World Profit Centre, No. 16 Tianze Road, Chaoyang District, Beijing, 100125, China.
Wen ShenDepartment of Radiology, Tianjin Medical Imaging Institute, School of Medicine, Tianjin First Central Hospital, Nankai University, Nankai District, No. 24 Fukang Road, Tianjin, 300192, China. shen_hos@163.com.
Nankai University · CNTianjin Medical University Cancer Institute and Hospital · CNPhilips (China) · CNTianjin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to establish a reliable diagnostic scoring model for the preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients based on gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) and biochemical indicators.

methodsThis retrospective study included 129 patients with HCC at our hospital from 2014 to 2020. Based on the intratumoral and peritumoral features on Gd-EOB-DTPA MRI and biochemical indicators, a scoring model was developed for preoperative prediction of MVI, and examined for diagnostic efficacy according to postoperative pathological results. The scoring model was further externally validated in an independent cohort of 63 HCC patients.

resultsLogistic regression analysis was performed to identify five parameters related to MVI, including maximum tumor diameter, peritumoral low intensity in the hepatobiliary phase, incomplete capsule, apparent diffusion coefficient (ADC), and [alkaline phosphatase (ALP) (U/L) + gamma-glutamyl transpeptidase (GGT) (U/L)] / lymphocyte count (× 10

conclusionThe scoring model based on Gd-EOB-DTPA MRI and biochemical indicators provides a reliable tool for preoperative prediction of MVI in HCC patients. KEY POINTS: • The scoring model based on Gd-EOB-DTPA MRI and biochemical indicators is practical for preoperative prediction of MVI in HCC patients. • AGLR is an independent risk factor for MVI. • The scoring model could help implement more appropriate interventions, potentially leading to precise and individualized treatments based on the biological characteristics of the tumor.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsContrast MediaGadolinium DTPAHumansMagnetic Resonance ImagingRetrospective StudiesContrast MediaGadolinium DTPAgadolinium ethoxybenzyl DTPABiomarkersHepatocellular carcinomaMagnetic resonance imagingNeoplasm invasionStatistical model

Identifiers

PMID35048134
OpenAlexW4205587407

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Registered trials

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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.