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

Preoperative prediction of microvascular invasion of hepatocellular carcinoma using (18)F-FDG PET/CT: a multicenter retrospective cohort study.
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Hyun SH, Eo JS, Song BI, Lee JW, Na SJ, Hong IK, Oh JK, Chung YA, Kim TS, Yun M,


Hyun SH, Eo JS, Song BI, Lee JW, Na SJ, Hong IK, Oh JK, Chung YA, Kim TS, Yun M, (click to view)

Hyun SH, Eo JS, Song BI, Lee JW, Na SJ, Hong IK, Oh JK, Chung YA, Kim TS, Yun M,

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European journal of nuclear medicine and molecular imaging 2017 11 22() doi 10.1007/s00259-017-3880-4
Abstract
PURPOSE
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).

METHODS
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.

RESULTS
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). CONCLUSIONS
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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