Abstract Library

#4455 Multicentric ENETS morphological and molecular appraisal of high-grade gastroenteropancreatic neuroendocrine neoplasms (HG-GEP-NEN): Distinguishing NET G3 from NEC

Introduction: HG-GEP-NEN are classified into neuroendocrine tumours grade 3 (NET G3) and neuroendocrine carcinomas (NEC). This distinction is crucial as it affects patient prognosis and treatments but can be challenging.

Conference:

Presenting Author: Tihy M

Authors: Tihy M, Solstad O, Oudijk L, Bräutigam K, Bani M,

Keywords: HG-GEP-NEN, neuroendocrine neoplasm, NEC, NET G3, Classification, Review, criteria, diagnosis, pathology,

#4454 Impact of pathological review of neuroendocrine neoplasms (NENs) within the French national ENDOCAN/TENpath network

Introduction: NENs are rare tumours which can benefit from specialised pathological assessment. In France, the ENDOCAN/TENpath network, composed of 33 expert pathologists in 20 centres, provides consultations (2nd readings) at the request of non-specialist pathologists. Challenging cases are reviewed in monthly virtual meetings grouping all expert pathologists (third readings).

Conference:

Presenting Author: Tihy M

Authors: Tihy M, Scoazec J, Bani M, Boulagnon-Rombi C, Poté N,

Keywords: NEN, Pathology, Review, Neuroendocrine Neoplasm,

#4388 Pancreatic neuroendocrine tumours (pNET) and MUTYH germline (GPV) and somatic (SPV) pathogenic variants: A multinational study

Introduction: GPV and SPV in MUTYH are rare in pNET patients (pts).

Conference:

Presenting Author: Riechelmann R

Authors: Riechelmann R, Torrezan G, Cingarlini S, Raj N, Bergsland E,

Keywords: pancreatic neuroendocrine tumour, MUTYH, germline, pathogenic variants, mutations,

#4281 Automated (artificial intelligence) vs. manual evaluation of the somatostatin-receptor 2A and proliferation marker Ki-67 in neuroendocrine neoplasms: A pilot study

Introduction: Digital image analysis methods are currently being equipped with artificial intelligence (AI). Various AI applications are already in use to determine Ki-67. To date, there is no specialised AI application available to determine the somatostatin-receptor 2A (SSTR2A).

Conference:

Presenting Author:

Authors: Kaemmerer D, Lupp A, Klöppel G, Ayako I, Kasajima A,

Keywords: artificial intelligence, Ki-67, SSTR2A, usability, neuroendocrine neoplasm,

#4134 Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumors in the lungNENomics project

Introduction: The lungNENomics project analysed 300 lung neuroendocrine tumors (NETs), of which 259 cases were pathologically reviewed by six expert pathologists.

Conference:

Presenting Author: Mathian E

Authors: Mathian E, Drouet Y, Sexton-Oates A, Papotti M, Pelosi G,

Keywords: Lung neuroendocrine neoplasm, Pathology, Deep-learning, Ki-67, PHH3,