Abstract Library
Welcome to the open-access search for all ENETS abstracts presented at the Annual ENETS Conferences.
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ENETS Abstract Search
Introduction: Accurate contouring for [68Ga]DOTATATE PET in NEN is challenging due to differing physiological uptake for the liver, spleen and other organs. This poses a significant problem for absolute thresholding algorithms using a single threshold, even if the threshold is based on liver uptake (as suggested for FDG PET by PERCIST). Improved contouring of PET to measure [68Ga]DOTATATE-avid tumour volume could help clinical translation of this potential biomarker.
Conference:
Presenting Author: Chan D
Authors: Chan D, Mokhtar S, Bernard E, Diakos C, Sabahi Z,
Keywords: prognostic biomarker, PET imaging, [68Ga]DOTATATE, Total Lesion Volume,
Introduction: Neuroendocrine Neoplasms (NENs) are heterogeneous neoplasms, whose metastatic potential is challenging to predict. Extracellular vesicles (EVs) have been described as mediators of communication between the tumor cells and their microenvironment, driving the formation of metastatic niches.
Conference:
Presenting Author: Angelioudaki I
Authors: Angelioudaki I, Pantazatou V, Tzingounis A, Kataki A, Memos N,
Keywords: Extracellular vesicles, plasma, Gastroenteropancreatic NEN,
Introduction: Since 2016 both digestive neuroendocrine neoplasms (D-NENs) and non-digestive NENs (ND-NENs) cases are treated within NETwerk, an ENETS Center of Excellence
Conference: 17th Annual ENETSConcerence (2020)
Presenting Author:
Authors: Vandamme T, De Backer L, Dero I, Galdermans D, Abrams P,
Keywords: non-digestive NENs, gastroenteropancreatic NENs,
Introduction: A few previous studies have shown that nomograms can predict the survival rates of patients with neuroendocrine neoplasms (NENs).
Conference: 14th Annual ENETSConcerence (2017)
Presenting Author: Wei W
Authors: Wei W, Cheng F, Jie C, Zhiwei Z, Ye C,
Keywords: Gastroenteropancreatic Neuroendocrine Neoplasms, Nomogram, Prognosis,
Introduction: The classification of lung neuroendocrine neoplasms (Lung-NENs) according to the WHO classification 2010 for GEP-NENs, including a provisional category for Lung-NET G3 with Ki67 >20%, may have prognostic implications.
Conference: 14th Annual ENETSConcerence (2017)
Presenting Author: Kasajima A
Authors: Kasajima A, Oka N, Ishida H, Sakurada A, Kameya T,
Keywords: Lung NEN,