Clinicopathological features and outcome of esophageal neuroendocrine tumor: A retrospective multicenter survey by the digestive endoscopy society of Taiwan.

BACKGROUND & AIMS: Esophageal neuroendocrine tumors (NET) are very rare and mostly carcinomic, carrying poor prognosis. There is still no guideline or consensus on the treatment for esophageal NET. METHODS: Patients with histologically-proven esophageal neuroendocrine tumor were recruited from 9 hospitals in Taiwan between 2002 and 2017. Clinical, laboratory, radiological, endoscopic, pathological data, treatment strategies, follow-up periods, and survivals were collected retrospectively. RESULTS: In total, 39 esophageal NET were analyzed and 38 were neuroendocrine carcinoma (NEC). Sixteen (41%) patients had mixed components with either adenocarcinoma (N = 9, 23%) or squamous-cell carcinoma (SCC) (N = 7, 18%). 64.1% of the patients experienced dysphagia and ulcerative mass was the most comment endoscopic finding. There was a higher proportion of drinkers (54.1%), betel chewers (21.6%) and smokers (64.9%) among the patients than in the general population in Taiwan. Five patients (12.8%) had been diagnosed with other cancers. Definite chemoradiotherapy (N = 14, 35.9%) and surgery (N = 7, 17.9%) were the major treatment. Patients with Ki-67% above the median level (50%) in the tumors tended to have worse survival (P = 0.06). However, presence of mixed component was not a significant survival predictor in our study (P = 0.56). CONCLUSION: Mixed component of an esophageal NET is commonly observed. Staged workup and the principle of treatment can follow that for the common cancer type of esophagus. The risk factors and behaviors of esophageal NEC in Taiwan seem to be similar to that of esophageal SCC.

Substance use and esophageal neuroendocrine neoplasm: A case-control study.

Esophageal neuroendocrine neoplasms (NEN) are extremely rare and little is known about their risk factors. To identify the potential risk factors, we evaluated whether the history of substance use, including alcohol, tobacco and areca nut consumption was associated with esophageal NEN. Forty-one esophageal NEN patients diagnosed between 2002 and 2019 from 17 hospital in Taiwan were enrolled as the cases. Controls were participants who received complete esophagogastroduodenoscopy in an endoscopic cohort and 123 eligible controls were matched to 41 cases (3:1) on age and gender. Alcohol drinking and cigarette smoking significantly increased the risk of esophageal NEN, with about a fourfold risk increase in alcohol drinkers as well as cigarette smokers. Moreover, use of cigarette smoking and alcohol consumption in combination demonstrated the highest risk of esophageal NEN with the risk increasing up to 20 times compared with non-users. Alcohol consumption and cigarette smoking significantly increase risk of esophageal NEN and both alcohol and cigarette users had the highest risk.

Hyperspectral Imaging Combined with Artificial Intelligence in the Early Detection of Esophageal Cancer.

This study uses hyperspectral imaging (HSI) and a deep learning diagnosis model that can identify the stage of esophageal cancer and mark the locations. This model simulates the spectrum data from the image using an algorithm developed in this study which is combined with deep learning for the classification and diagnosis of esophageal cancer using a single-shot multibox detector (SSD)-based identification system. Some 155 white-light endoscopic images and 153 narrow-band endoscopic images of esophageal cancer were used to evaluate the prediction model. The algorithm took 19 s to predict the results of 308 test images and the accuracy of the test results of the WLI and NBI esophageal cancer was 88 and 91%, respectively, when using the spectral data. Compared with RGB images, the accuracy of the WLI was 83% and the NBI was 86%. In this study, the accuracy of the WLI and NBI was increased by 5%, confirming that the prediction accuracy of the HSI detection method is significantly improved.

Clinical features and outcomes of gastric neuroendocrine tumors after endoscopic diagnosis and treatment: A Digestive Endoscopy Society of Tawian (DEST).

Gastric neuroendocrine tumors (GNETs) are a heterogeneous group of neoplasm with varying biological characteristics. This study aimed to investigate the clinical features and outcomes of GNET patients after endoscopic diagnosis and treatment in a multicenter registry. Patients with GNETs confirmed histologically were recruited from 17 hospitals between January 2010 and April 2016 in Taiwan. Clinical, laboratory, radiological, endoscopic, pathological data, treatment strategies, follow-up periods, and survivals were collected retrospectively. Totally 187 (107 female, 80 male) patients were recruited. Mean ( ±â€Šstandard deviation [SD]) age and size of tumors were 63.2-year-old ( ±â€Š14.6) and 2.3-cm ( ±â€Š3.0). World Health Organization (WHO) grading were 93 (49.7%) G1, 26 (13.9%) G2, 40 (21.4%) G3, and 28 (15.0%) unknown. G3 patients were older (mean ±â€ŠSD, 71.6 ±â€Š12.4 vs. 60.9 ±â€Š14.3/56.7 ±â€Š15.4 years), larger (6.1 ±â€Š4.0 vs.1.2 ±â€Š1.3/2.4 ±â€Š2.5 cm), more distally located (35.0% vs. 7.6%/15.4%), lower proportion of superficial lesions (17.5% vs. 61.9%/53.8%) and higher rates of lymphovascular invasion (32.5% vs. 3.2%/7.7%) than G1/G2. There was no nodal or distant organ metastases despite different grading of lesions≦10 mm and those <20 mm limited to mucosa and submucosa layers. GNETs larger than 20 mm with G1, G2, and G3 had lymph node (LN) metastatic rates of 21.4%, 30.0%, and 59.3%, respectively. Survivals were different between grading for those >20 mm (log-rank test P = .02). Male gender (P = .01), deeper invasion (P = .0001), nodal (P < .0001), and distant organ metastases (P = .0001) were associated with worse outcome. In conclusion, treatment strategies for GNET should be decided by grading, size, invasiveness, and LN metastasis risk. Curative endoscopic resection is feasible for G1/2 lesions less than 20 mm and limited to mucosa/submucosa layers without lymphovascular invasion.