Evidence map›Paper›PMID 34429624›Full record

ArticleInfection and drug resistance2021

Differentiating Between an Atypical Hepatic Abscess and Tumor Metastasis Using Magnetic Resonance Imaging and Hepatobiliary Phase Imaging.

Li-Yong Zhuo, Li-Hong Xing, Xi Ma, Yu Zhang, Ze-Peng Ma, Xiao-Ping Yin, Jia-Ning Wang

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Article in Infection and drug resistance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

What it found

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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

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Li-Yong Zhuo *Department of CT-MRI Diagnostic, Affiliated Hospital of Hebei University, Baoding, People's Republic of China.
Li-Hong Xing *Department of CT-MRI Diagnostic, Affiliated Hospital of Hebei University, Baoding, People's Republic of China.
Xi MaDepartment of CT-MRI Diagnostic, Affiliated Hospital of Hebei University, Baoding, People's Republic of China.
Yu ZhangDepartment of CT-MRI Diagnostic, Affiliated Hospital of Hebei University, Baoding, People's Republic of China.
Ze-Peng MaDepartment of CT-MRI Diagnostic, Affiliated Hospital of Hebei University, Baoding, People's Republic of China.
Xiao-Ping YinDepartment of CT-MRI Diagnostic, Affiliated Hospital of Hebei University, Baoding, People's Republic of China.
Jia-Ning WangDepartment of CT-MRI Diagnostic, Affiliated Hospital of Hebei University, Baoding, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify diffusion-weighted imaging (DWI) patterns and conspicuity discrepancies on hepatobiliary phase imaging (HBPI) to distinguish atypical hepatic abscesses from hepatic metastases. MATERIALS AND

methodsThis retrospective study recruited 31 patients with 43 atypical hepatic abscesses and 32 patients with 35 hepatic metastases who underwent gadobenate dimeglumine-enhanced magnetic resonance imaging. All lesions were confirmed by pathological or clinical diagnosis. For the qualitative and quantitative analyses, the signal intensity, DWI pattern, apparent diffusion coefficient, degree of perilesional edema, perilesional hyperemia, perilesional signal on HBPI, conspicuity, size discrepancy between sequences, contrast-to-noise ratio, signal-to-noise ratio, and relative enhancement ratio on dynamic phases were independently assessed by two radiologists. Significant findings for differentiating the two groups were identified via univariate and multivariate analyses with a nomogram for predicting atypical hepatic abscesses. The interobserver agreement was also analyzed for each variable.

resultsThe multivariate analysis revealed that the conspicuity discrepancy (odds ratio [OR] 34.78, 95% confidence interval [CI] 2.09-579.47, p = 0.013) and non-peripheral high signal intensity (SI) rim on DWI (OR 67.46, 95% CI 2.64, 1723.20, p = 0.011) were significant independent factors for predicting atypical hepatic abscesses. They were also shown to be high predictor points on the nomogram. When any of the set criteria were satisfied, 97.7% of atypical hepatic abscesses were correctly identified, with a specificity of 65.7%. When both criteria were combined, the specificity was up to 100%, with a sensitivity of 44.9%.

conclusionConspicuity discrepancy and a non-peripheral high SI rim on DWI are reliable and meaningful features that can distinguish atypical hepatic abscesses from hepatic metastases.

Indexed as

abscesshepatocyte-specific contrastlivermetastasisMRI

Identifiers

PMID34429624
PMCPMC8380289

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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.