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Preoperative prediction of microvascular invasion of hepatocellular carcinoma using 18F-FDG PET/CT: a multicenter retrospective cohort study

Overview of attention for article published in European Journal of Nuclear Medicine and Molecular Imaging, November 2017
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Title
Preoperative prediction of microvascular invasion of hepatocellular carcinoma using 18F-FDG PET/CT: a multicenter retrospective cohort study
Published in
European Journal of Nuclear Medicine and Molecular Imaging, November 2017
DOI 10.1007/s00259-017-3880-4
Pubmed ID
Authors

Seung Hyup Hyun, Jae Seon Eo, Bong-Il Song, Jeong Won Lee, Sae Jung Na, Il Ki Hong, Jin Kyoung Oh, Yong An Chung, Tae-Sung Kim, Mijin Yun

Abstract

The aim of this study was to assess the potential of tumor (18)F-fluorodeoxyglucose (FDG) avidity as a preoperative imaging biomarker for the prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC). One hundred and fifty-eight patients diagnosed with Barcelona Clinic Liver Cancer stages 0 or A HCC (median age, 57 years; interquartile range, 50-64 years) who underwent (18)F-FDG positron emission tomography with computed tomography (PET/CT) before curative surgery at seven university hospitals were included. Tumor FDG avidity was measured by tumor-to-normal liver standardized uptake value ratio (TLR) of the primary tumor on FDG PET/CT imaging. Logistic regression analysis was performed to identify significant parameters associated with MVI. The predictive performance of TLR and other clinical variables was assessed using receiver operating characteristic (ROC) curve analysis. MVI was present in 76 of 158 patients with HCCs (48.1%). Multivariable logistic regression analysis revealed that TLR, serum alpha-fetoprotein (AFP) level, and tumor size were significantly associated with the presence of MVI (P < 0.001). Multinodularity was not significantly associated with MVI (P = 0.563). The area under the ROC curve (AUC) for predicting the presence of MVI was best with TLR (AUC = 0.704), followed by tumor size (AUC = 0.685) and AFP (AUC = 0.670). We were able to build an improved prediction model combining TLR, tumor size, and AFP by using multivariable logistic regression modeling (AUC = 0.756). Tumor FDG avidity measured by TLR on FDG PET/CT is a preoperative imaging biomarker for the prediction of MVI in patients with HCC.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 24%
Student > Master 4 24%
Researcher 3 18%
Student > Doctoral Student 1 6%
Lecturer 1 6%
Other 2 12%
Unknown 2 12%
Readers by discipline Count As %
Medicine and Dentistry 8 47%
Computer Science 2 12%
Physics and Astronomy 1 6%
Linguistics 1 6%
Unknown 5 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 November 2017.
All research outputs
#19,214,418
of 23,806,312 outputs
Outputs from European Journal of Nuclear Medicine and Molecular Imaging
#2,305
of 3,083 outputs
Outputs of similar age
#330,515
of 441,847 outputs
Outputs of similar age from European Journal of Nuclear Medicine and Molecular Imaging
#28
of 43 outputs
Altmetric has tracked 23,806,312 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,083 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
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