Abstract Library

Welcome to the open-access search for all ENETS abstracts presented at the Annual ENETS Conferences.

Everyone can browse the library to find basic information on abstracts. To get full access to each entry, you will be asked to log in to your myENETS account.

 

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Participants of the 2025 ENETS Conference enjoy full access to the 2025 conference digital resources through myENETS: the abstract booklet, e-posters and videos, slide decks of talks, the poster carousel, and more.

ENETS Abstract Search

#4668 Predictive factors of postoperative recurrence in patients with neuroendocrine tumour of the lung: Prospective analysis of clinicopathologic features and radiomics

Introduction: In localised and locally advanced forms neuroendocrine tumours (NETs) of the lung radical surgical resection represents the standard of care, several clinicopathologic factors are potentially associated with recurrence of disease.

Conference:

Presenting Author: Paravani P

Authors: Paravani P, Russo F, Mazzilli R, Zamponi V, Mancini C,

Keywords: radiomics, predictive role, rfs, lung, lung net,

#4626 Comparison of two prognostic models for the treatment of pancreatic NET with PRRT

Introduction: The efficacy and time to progression (TTP) following peptide receptor radionuclide therapy (PRRT) for pancreatic neuroendocrine tumours varies widely.

Conference:

Presenting Author: Papantoniou D

Authors: Tiensuu Janson E, Fröss-Baron K, Grönberg M, Ziolkowska B,

Keywords: prrt, pancreatic neuroendocrine tumour, predictive model,

#4600 Artificial intelligence in predicting neuroendocrine tumour (NET) outcomes: A model-based prognostic approach

Introduction: Neuroendocrine tumours (NETs) vary widely in clinical behaviour, complicating prognosis. Traditional models often struggle with accuracy due to the complexity of NETs. Artificial intelligence (AI) offers tools for enhanced prognostic precision by analysing complex datasets. This study explores an AI-driven approach to predict outcomes in NET patients at Cantonment General Hospital, Pakistan.

Conference:

Presenting Author: Fatima A

Authors: Fatima A,

Keywords: artificial intelligence, machine learning, Precision medicine, Personalised treatment,

#4566 Predictive value of high-risk histopathological- and molecular criteria for lymph node metastasis in appendiceal neuroendocrine tumours

Introduction: Appendiceal neuroendocrine tumours (aNET) are rare neoplasms for which consensus is needed for follow-up and additional treatment. To unravel the factors behind aNET which showed lymph node metastasis (LNM) in additional right hemicolectomy (RH), we evaluated high-risk histopathological parameters in aNETs and studied molecular parameters.

Conference:

Presenting Author: Bremer B

Authors: Bremer B, Kyriskozoglou V, El Moumni M, Heideman D, Walenkamp-Hageman A,

Keywords: Appendix NET, High-risk histopathological criteria, Serotonin, Driver mutation, Right Hemicolectomy,

#4516 A methylation-based classifier for neuroendocrine tumour detection using smMIP technology

Introduction: DNA methylation plays an important role in NET pathogenesis. Distinct methylation profiles can differentiate between tumour subtypes, predict malignancy potential, and provide insights into tumour progression.

Conference:

Presenting Author:

Authors: Ibrahim J, Mariën L, Vanpoucke T, Neefs I, Vandenhoeck J,

Keywords: neuroendocrine tumour, DNA methylation, biomarker selection, IMPRESS technology, classifier model,