Seung Hyup Hyun1, Jae Seon Eo2, Bong-Il Song3, Jeong Won Lee4, Sae Jung Na5, Il Ki Hong6, Jin Kyoung Oh7, Yong An Chung7, Tae-Sung Kim8, Mijin Yun9. 1. Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea. 2. Department of Nuclear Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea. 3. Department of Nuclear Medicine, Dongsan Medical Center, Keimyung University School of Medicine, Daegu, South Korea. song@dsmc.or.kr. 4. Department of Nuclear Medicine, International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon, South Korea. 5. Department of Nuclear Medicine, Uijeongbu St. Mary's Hospital, The Catholic University of Korea, Seoul, South Korea. 6. Department of Nuclear Medicine, Kyung Hee University Hospital, School of Medicine, Kyung Hee University, Seoul, South Korea. 7. Department of Nuclear Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Incheon, South Korea. 8. Department of Nuclear Medicine, Research Institute and Hospital, National Cancer Center, Goyang, South Korea. 9. Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea. yunmijin@yuhs.ac.
Abstract
PURPOSE: The aim of this study was to assess the potential of tumor 18F-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 18F-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.
PURPOSE: The aim of this study was to assess the potential of tumor 18F-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 18F-FDG positron emission tomography with computed tomography (PET/CT) before curative surgery at seven university hospitals were included. TumorFDG 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:TumorFDG 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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