Abstract Library

#4487 Fast pancreatic cancer diagnosis using lightweight Mamba framework

Introduction: Pancreatic cancer is a deadly malignancy often diagnosed too late for effective treatment. Fast and precise identification of pathological regions in histopathology images is essential but limited by current slow methods. We present a framework to accelerate this process and enhance diagnostic support.

Conference:

Presenting Author:

Authors: Shengzhe Y, Yan K,

Keywords: Pancreatic Cancer, Lightweight Mamba Architecture, Pathology Region Classification and Recognition,

#4462 Clustering of gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) using machine learning (ML) and comparison with tumour, node, metastasis (TNM) staging: A population-based study using surveillance, epidemiology, and end results (SEER)

Introduction: TNM 8 is the staging system for GEP-NEN, guiding prognosis and treatment. However, it does not include important prognostic factors such as age, sex, race, and morphology.

Conference:

Presenting Author: Mortagy M

Authors: Mortagy M, El Asmar M, White B, Chandrakumaran K, Ramage J,

Keywords: Clustering, Machine learning, GEP-NEN, TNM Staging, Survival Analysis, SEER,

#4413 Efficacy and safety of adjuvant peptide receptor radionuclide therapy after curative surgery of locoregional limited small intestine neuroendocrine neoplasia (APSIN) – A multi-centre, prospective, randomised, controlled, phase III study

Introduction: Our multi-centre, prospective, open-label, two-arm parallel group, randomised, controlled, phase III study will address the efficacy and safety of adjuvant peptide receptor radionuclide therapy after curative surgery of locoregional limited small intestine neuroendocrine neoplasia.

Conference:

Presenting Author: Eilsberger F

Authors: Eilsberger F, Luster M, Rau J, Avci H, Schade-Brittinger C,

Keywords: adjuvant therapy, neuroendocrine neoplasia, small intestine, peptide receptor radionuclide therapy, PRRT,

#4408 Metabolic syndrome (MetS) and metastatic disease in patients with sporadic small intestine neuroendocrine tumour (SiNET)

Introduction: Small intestine neuroendocrine tumours (SiNETs) are rare neoplasms in which the identification of new risk factors is essential. Metabolic syndrome (MetS) is a cluster of risk factors that lead to increased mortality, especially by cardiovascular (CV) causes. MetS diagnosis is obtained with International Diabetes Federation (IDF) 2005 criteria.

Conference:

Presenting Author: Minotta R

Authors: Minotta R, Liccardi A, Cannavale G, Benevento E, Di Iasi G,

Keywords: small intestine neuroendocrine tumour, metabolic syndrome, metastatic disease, survival, progression, metastasis,

#4086 Prognostic significance of metabolomics clusters in extra-pancreatic NETs: Lung NET sub-analysis

Introduction: Metabolic flexibility is one of the key hallmarks of cancer and metabolites are the final products of this adaptation, reflecting the aberrant changes that support cancer cells proliferation and survival. In a previous metabolomics study carried out by our group, multiplatform untargeted metabolomic profiling (GC-MS, CE-MS and LC-MS) performed on plasma samples from 77 advanced G1-2 extra-pancreatic NET patients demonstrated that these patients have a distinct metabolomic profile, and identified methionine, porphyrin and tryptophan metabolism as the most relevant dysregulated pathways associated with the prognosis of NETs. Furthermore, a 3-metabolite signature was able to stratify patients in 3 distinct prognostic clusters, with cluster 3 associated with the best prognosis.

Conference:

Presenting Author:

Authors: La Salvia A, Lens-Pardo A, Carretero-Puche C, Capdevila J, Benavent M,

Keywords: metabolimics, prognostic biomarker, lung neuroendocrine tumor, metabolomic signature,