Evidence map›Paper›PMID 30105408›Full record

ArticleEuropean radiology2019

Evaluation of liver parenchyma stiffness in patients with liver tumours: optimal strategy for shear wave elastography.

Wei Zheng, Zhong-Guo Zhou, Chong-Hei Wong, Xiao-Qing Pei, Shu-Lian Zhuang, Qing Li, Min-Shan Chen, An-Hua Li, Fu-Jun Zhang

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In one paragraph

Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

2 citing papers in PubMed, 10 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

9 authors at 4 institutions in 1 country.

Wei ZhengDepartment of Ultrasound, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China; Collaborative Innovation Centre for Cancer Medicine, Guangzhou, Guangdong, 510060, People's Republic of China.
Zhong-Guo ZhouDepartment of Hepatobiliary Oncology, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China; Collaborative Innovation Centre for Cancer Medicine, Guangzhou, Guangdong, 510060, People's Republic of China.
Chong-Hei WongDepartment of Hepatobiliary Oncology, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China; Collaborative Innovation Centre for Cancer Medicine, Guangzhou, Guangdong, 510060, People's Republic of China.
Xiao-Qing PeiDepartment of Ultrasound, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China; Collaborative Innovation Centre for Cancer Medicine, Guangzhou, Guangdong, 510060, People's Republic of China. peixq@sysucc.org.cn.
Shu-Lian ZhuangDepartment of Ultrasonography, the Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong, 510120, People's Republic of China.
Qing LiDepartment of Ultrasound, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China; Collaborative Innovation Centre for Cancer Medicine, Guangzhou, Guangdong, 510060, People's Republic of China.
Min-Shan ChenDepartment of Hepatobiliary Oncology, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China; Collaborative Innovation Centre for Cancer Medicine, Guangzhou, Guangdong, 510060, People's Republic of China.
An-Hua LiDepartment of Ultrasound, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China; Collaborative Innovation Centre for Cancer Medicine, Guangzhou, Guangdong, 510060, People's Republic of China.
Fu-Jun ZhangMinimally Invasive Interventional Centre, Sun Yat-sen University Cancer Centre, State Key Laboratory of Oncology in South China; Collaborative Innovation Centre for Cancer Medicine, Guangzhou, Guangdong, 510060, People's Republic of China. windyangle@163.com.
Sun Yat-sen University · CNState Key Laboratory of Oncology in South ChinaGuangdong Provincial Hospital of Traditional Chinese Medicine · CNSun Yat-sen University Cancer Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine the methodology of non-invasive test for evaluation of liver stiffness (LS) with tumours using two-dimensional (2D) shear wave elastography (SWE).

methodsOne hundred and twenty-seven patients with liver tumours underwent 2D-SWE before surgery to measure liver and spleen stiffness (SS). Two-dimensional SWE values were obtained in the liver at 0-1 cm, 1-2 cm and >2 cm from the tumour edge (PLS-1, PLS-2 and RLS, respectively). The influence of tumour-associated factors was evaluated. The area under the receiver operating characteristic curve (AUC) for each value was analysed to diagnose cirrhosis.

resultsPLS-1 was higher than PLS-2, which was even higher than RLS (p < 0.001). The AUCs of PLS-1, PLS-2, RLS and SS for diagnosing cirrhosis were 0.760, 0.833, 0.940 and 0.676, with the specificity of 75.7%, 67.6%, 90.3% and 77.4%, respectively. Tumour sizes, locations or types showed no apparent influence on 2D-SWE values except for RLS, which was higher in patients with primary hepatic carcinomas (p < 0.05).

conclusionsLS with tumours is best measured at >2 cm away from the tumour edge. SS measurement could be used as an alternative to LS measurement in the event of no available liver for detection. KEY POINTS: • Tumour-associated factors impact background liver stiffness assessment. • Background liver stiffness is best measured at >2 cm from tumour edge. • Spleen stiffness can be an alternative to assess background liver stiffness.

Indexed as

AdultAgedArea Under CurveElasticity Imaging TechniquesFemaleHumansLiverLiver CirrhosisLiver NeoplasmsMaleMiddle AgedProspective StudiesROC CurveSensitivity and SpecificitySpleenTumor BurdenElasticity imaging techniquesLiver cirrhosisLiver neoplasmsSpleenUltrasonography

Identifiers

PMID30105408
OpenAlexW2887747372

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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.