Abstract Library

#4623 [68Ga]Ga-DOTA-Exendin-4 PET/CT for the localisation of insulinoma: Results of an international, dual-centre, retrospective, open-label real-world imaging study

Introduction: Benign insulinomas are the main cause of endogenous hyperinsulinemic hypoglycaemia (EHH) in adults, with surgery as the only cure. Pancreas-preserving procedures are preferred, making precise localisation crucial. Recent studies indicate that GLP-1R imaging, such as [68Ga]Ga-DOTA-exendin-4 (68Ga-Ex4) PET/CT, outperforms conventional imaging in identifying insulinomas.

Conference:

Presenting Author: Fricke J

Authors: Fricke J, Laubner K, Schildmeijer M, Menz L, Christ E,

Keywords: GLP1-Receptor PET/CT, Insulinoma, nesidioblatosis, endogenous hyperinsulinemic hypoglycaemia, real-life data,

#4613 Correlation of serum cytokeratin 18, ferritin, cancer antigen 125, and beta-2 microglobulin with tumour grade and stage in pancreatic neuroendocrine tumours

Introduction: Pancreatic neuroendocrine neoplasms (PNENs) remain challenging to diagnose, with limited reliable serum biomarkers available for early detection and prognostication.

Conference:

Presenting Author: Janas K

Authors: Janas K, Rosiek V, Kos-Kudła B,

Keywords: NEN, biomarker, analysis, diagnostic, pancreatic tumour,

#4612 Intraoperative beta-probe for pathological tissue detection in GEP-NET patients: A prospective phase II trial

Introduction: Accurate localisation of gastroenteropancreatic neuroendocrine tumours (GEP-NET) is essential for successful radical surgery. Radio guided surgery (RGS) is an innovative technique that may enhance lesion detection.

Conference:

Presenting Author: Bertani E

Authors: Bertani E, Fumagalli Romario U, Collamati F, Ferrari M, Mattana F,

Keywords: radio guided surgery, surgery, neuroendocrine tumour, GEP-NET, gastrointestinal tumour,

#4586 Base on neuroendocrine tumour classification in CT imaging using pretrained vision transformers and data augmentation

Introduction: Neuroendocrine tumours (NETs) are a group of cancers that can be difficult to distinguish from other malignancies in CT imaging. Their diverse appearance often leads to diagnostic challenges, requiring advanced techniques to improve classification accuracy. Pretrained Vision Transformers (ViTs) have shown promise in medical image analysis, but additional methods are needed to enhance model robustness, particularly when dealing with complex and heterogeneous tumour characteristics.

Conference:

Presenting Author:

Authors: Li H, Tang Z, Ding Z, Chen Y, Li H,

Keywords: Vision transformers, Cancer Detection, Transfer Learning, Medical Image Analysis,

#4583 Improved assessment of gene rearrangements by targeting non-coding DNA regions in patients diagnosed with pancreatic neuroendocrine neoplasms

Introduction: Whole-genome sequencing projects documented the heterogeneity of pancreatic neuroendocrine neoplasms (PanNEN), while showing that few core pathways are consistently affected in their tumorigenesis. Comprehensive genomic profiling (CGP) of real-world cases is expected to recapitulate such heterogeneity for patient stratification and to inform precision therapy. While coding DNA is the focus of current CGP panels, the potential of targeting non-coding DNA (ncDNA) to improve structural variants detection has not been widely explored in this context.

Conference:

Presenting Author: Agnoletto C

Authors: Agnoletto C, Trevisani E, Borghesani M, Landoni L, Luchini C,

Keywords: neuroendocrine, non-coding DNAs, structural variants, clinical relevance, CGP panel,