Abstract Library

#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,

#3654 Digital image analysis of Ki-67 heterogeneity of pancreatic neuroendocrine neoplasms with or without liver metastasis

Introduction: Ki-67 is a reliable grading and prognostic biomarker of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). The application of digital image analysis (DIA) enables new digital biomarkers in the assessment of Ki-67 heterogeneity distribution. Our previous study reported that the Morisita-Horn (MH) index, an ecological marker for the measurement of spatial colocalization variants, directly correlated with classification and grading in GEP-NENs and provided prognostic information.

Conference:

Presenting Author: Huang D

Authors: Zhang M, Han X, Ding X, Zhang B, Wang Y,

Keywords: pancreatic, Ki-67 heterogeneity, liver metastasis, Digital image analysis,

#3464 Digital quantification of somatostatin receptor subtype 2 immunostaining in pancreatic neuroendocrine tumors and GH-secreting adenoma: A validation study

Introduction: Somatostatin receptor subtype 2 (SST2) immunostaining (IHC) is routinely performed in neuroendocrine tumors (NET) and recommended in acromegaly guidelines. No univocal score of SST2 IHC has been validated yet.

Conference:

Presenting Author: Campana C

Authors: Campana C, van Koetsveld P, Iyer A, van Velthuysen M, van den Dungen E,

Keywords: SST2, digital image analysis, panNET, staining intensity, percentage of positive cell,

#3317 Digital image analysis of the Ki67 spatial distribution improves classification and grading in gastroenteropancreatic neuroendocrine neoplasms

Introduction: Ki67 is a reliable grading and prognostic biomarker in gastroenteropancreatic neuroendocrine neoplasms (NENs). Intra-tumor heterogeneity of Ki67, correlated with NENs classification, is a valuable factor requiring robust measurement protocols. Digital image analysis enables high accuracy and reproducibility to evaluate the spatial distribution of Ki67.

Conference: 18th Annual ENETS Concerence (2021)

Presenting Author: Huang D

Authors: Huang D, Wang X, Tan C, Sheng W,

Keywords: digital image analysis, Ki67, spatial distribution, NEN, classification, grade,

#737 Impact of Ki-67 Proliferative Index on Survival in Patients with Typical and Atypical Pulmonary Carcinoids

Introduction: Currently pulmonary carcinoids are separated into typical and atypical tumors based on mitotic count and presence of necrosis, according to the WHO classification. Whereas for GEP NETs the ENETS Guidelines have been incorporated into the WHO classification and grading is based on mitotic counts and Ki-67 index, the use of the Ki-67 index for grading pulmonary carcinoids is still under debate.

Conference: 10th Annual ENETSConcerence (2013)

Presenting Author: Rudelius M

Authors: Rudelius M, Swarts D, Cleutjens J, Claessen S, Volante M,

Keywords: pulmonary carcinoids, Ki-67, MIB-1, classification,