Abstract Library

#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,

#4540 Retrospective analysis of somatostatin receptors expression in cohort of thoracic neuroendocrine neoplasms with immunohistochemistry method or PET/CT Ga68 DOTA-TATE

Introduction: Somatostatin receptors (SSTRs) expression in cohort of thoracic neuroendocrine neoplasms (NENs) is still not fully described. We attempted to evaluate the SSTR expression by IHC and PET/CT with Ga68 DOTA-TATE, as well as the sensitivity of both methods.

Conference:

Presenting Author: Evdokimova E

Authors: Evdokimova E, Vorobeva M, Zhulikov Y, Markovich A, Gorbunova V,

Keywords: NEN, thoracic, SSTR, IHC, DOTATATE, lung, thymus, mediastinum, LCNC, NET,

#4492 Utility of NETest 2.0 as a biomarker for neuroendocrine tumours: The Swiss experience – Real-world data

Introduction: The NETest 2.0 is a PCR assay of circulating mRNA, scored 0-100. It has been developed as a biomarker to diagnose neuroendocrine neoplasia (NEN) and to provide tumour prognostic information.

Conference:

Presenting Author: Chirindel A

Authors: Chirindel A, Wild D, Voegeli M, de Dosso S, Siebenhüner A,

Keywords: NETest, tumour biomarker, NEN, disease presence, disease progression,

#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,

#4484 Experiences of combining narrative care and case care in the nursing of patients with neuroendocrine tumours

Introduction: Patients with neuroendocrine tumours have a long course of disease, facing not only physical pain but also complex psychological changes.

Conference:

Presenting Author: Tang Y

Authors: Xie W, Gu T, Tang Y, Liu G, Zhu Y,

Keywords: neuroendocrine tumour, narrative care, case care,