Solitary sternal metastasis from hepatocellular carcinoma detected by F-18 FDG PET/CT

Predicting Overall Survival with Deep Learning from 18F-FDG PET-CT Images in Patients with Hepatocellular Carcinoma before Liver Transplantation

Positron emission tomography and computed tomography with 18F-fluorodeoxyglucose (18F-FDG PET-CT) were used to predict outcomes after liver transplantation in patients with hepatocellular carcinoma (HCC). However, few approaches for prediction based on 18F-FDG PET-CT images that leverage automatic liver segmentation and deep learning were proposed. This study evaluated the performance of deep learning from 18F-FDG PET-CT images to predict overall survival in HCC patients before liver transplantation (LT). We retrospectively included 304 patients with HCC who underwent 18F-FDG PET/CT before LT between January 2010 and December 2016. The hepatic areas of 273 of the patients were segmented by software, while the other 31 were delineated manually. We analyzed the predictive value of the deep learning model from both FDG PET/CT images and CT images alone. The results of the developed prognostic model were obtained by combining FDG PET-CT images and combining FDG CT images (0.807 AUC vs. 0.743 AUC). The model based on FDG PET-CT images achieved somewhat better sensitivity than the model based on CT images alone (0.571 SEN vs. 0.432 SEN). Automatic liver segmentation from 18F-FDG PET-CT images is feasible and can be utilized to train deep-learning models. The proposed predictive tool can effectively determine prognosis (i.e., overall survival) and, thereby, select an optimal candidate of LT for patients with HCC.

Extrahepatic metastasis of hepatocellular carcinoma arising from a hepatic adenoma without concurrent intrahepatic recurrence

Hepatocellular carcinoma (hcc) arising from a hepatic adenoma is a rare phenomenon accounting for fewer than 5% of hcc cases; it seldom recurs after resection of the primary tumour. We report a case of extrahepatic metastasis of hcc arising from a hepatic adenoma that presented as a solitary sternal metastasis without any evidence of intrahepatic recurrence. Our patient was initially treated with radiation therapy and bland embolization, without response. Subsequently, the patient developed progressive disease while taking sorafenib. He later received chemotherapy with docetaxel and gemcitabine, with the development of multiple pulmonary and splenic nodules. However, he remained free of intrahepatic recurrence. To the best of our knowledge, this is the first case of extrahepatic metastasis of hcc arising from a hepatic adenoma without evidence of intrahepatic recurrence.

Predictive Value of 18F-FDG PET/CT for Vascular Invasion in Patients With Hepatocellular Carcinoma Before Liver Transplantation

BACKGROUND

Positron emission tomography-computed tomography using F-fluorodeoxyglucose (F-FDG PET/CT) has been widely used in oncology. Vascular invasion of hepatocellular carcinoma (HCC) is associated with a high risk of tumor recurrence and low survival rates after liver transplantation (LT). This retrospective study determined the predictive value of F-FDG PET/CT for vascular invasion in patients with HCC before LT.

METHODS

Sixty-five patients with HCC who underwent F-FDG PET/CT before LT were retrospectively included between January 2010 and July 2012. Volumes of interest (VOIs) were drawn for the tumors and normal liver tissues, and the standardized uptake value (SUV) in each VOI was measured. The maximal SUV (SUVmax) of the tumor, the ratio of tumor SUVmax to normal liver SUVmax (TSUVmax/LSUVmax), and the ratio of tumor SUVmax to normal liver SUVmean (TSUVmax/LSUVmean) were measured. The predictive value of metabolic parameters and conventional prognostic factors were analyzed.

RESULTS

Vascular invasion was pathologically confirmed in 15 (23.08%) of 65 patients. Compared with patients without vascular invasion, patients with vascular invasion exhibited significantly higher serum alpha-fetoprotein (AFP) (P < 0.001), larger tumor size (P = 0.001), higher tumor number (P = 0.017), and higher SUVmax, TSUVmax/LSUVmax ratio, and higher TSUVmax/LSUVmean ratio (P = 0.008, P = 0.002, and P = 0.006, respectively). Univariate analysis revealed that SUVmax, TSUVmax/LSUVmax ratio, and TSUVmax/LSUVmean ratio of FDG PET/CT were significantly associated with vascular invasion in patients with HCC before LT (P = 0.019, P = 0.018, and P = 0.015, respectively). Multivariate analysis revealed that the TSUVmax/LSUVmean ratio of F-FDG PET/CT was a significant predictor of vascular invasion (P = 0.04) and that the TSUVmax/LSUVmax ratio of F-FDG PET/CT was an independent predictor of vascular invasion, although this finding demonstrated borderline statistical significance (P = 0.06) in patients with HCC before LT.

CONCLUSIONS

According to the study results, the TSUVmax/LSUVmean ratio is an independent and significant predictor of vascular invasion, and the TSUVmax/LSUVmax ratio of F-FDG PET/CT is an independent predictor of vascular invasion, which is the main negative outcome after LT. Therefore, FDG PET/CT can provide vital information for determining prognosis and selecting an optimal candidate of LT for HCC.

Reprogramming of glucose metabolism in hepatocellular carcinoma: Progress and prospects

Hepatocellular carcinoma (HCC) is one of the most lethal cancers, and its rate of incidence is rising annually. Despite the progress in diagnosis and treatment, the overall prognoses of HCC patients remain dismal due to the difficulties in early diagnosis and the high level of tumor invasion, metastasis and recurrence. It is urgent to explore the underlying mechanism of HCC carcinogenesis and progression to find out the specific biomarkers for HCC early diagnosis and the promising target for HCC chemotherapy. Recently, the reprogramming of cancer metabolism has been identified as a hallmark of cancer. The shift from the oxidative phosphorylation metabolic pathway to the glycolysis pathway in HCC meets the demands of rapid cell proliferation and offers a favorable microenvironment for tumor progression. Such metabolic reprogramming could be considered as a critical link between the different HCC genotypes and phenotypes. The regulation of metabolic reprogramming in cancer is complex and may occur via genetic mutations and epigenetic modulations including oncogenes, tumor suppressor genes, signaling pathways, noncoding RNAs, and glycolytic enzymes etc. Understanding the regulatory mechanisms of glycolysis in HCC may enrich our knowledge of hepatocellular carcinogenesis and provide important foundations in the search for novel diagnostic biomarkers and promising therapeutic targets for HCC.