Abstract library

10 results for "reproducibility".
#998 Intra and Interobserver Reproducibility of CT and MRI for Measurement of Liver Metastasis as a Basis of RECIST Evaluation in Patients with Neuroendocrine Tumors
Introduction: The reliability of RECIST evaluation in patients with NET has not yet been analyzed.
Conference: 11th Annual ENETS Conference (2014)
Category: Imaging (radiology, nuclear medicine, endoscopy)
Presenting Author: Julia Arfi Rouche
#759 Inter-and Intra-Observers Reproducibility of MRI for the Measurement of NET Liver Metastases
Introduction: Assessment of treatment is based on metastases size measurement.
Conference: 10th Annual ENETS Conference (2013)
Category: Imaging (radiology, nuclear medicine, endoscopy)
Presenting Author: Julia Arfi Rouche
#152 Validation of a new assay that uses 2 monoclonal antibodies to measure intact and fragmented plasma CgA levels
Introduction: Plasma chromogranin A (CgA) levels are elevated in a variety of neuroendocrine tumors (NETs) and are used to aid in diagnosis, prognosis, and monitoring of treatment effects in NETs patients. We evaluated a newer sandwich ELISA assay (Cisbio US, Bedford, MA, USA) that utilizes two monoclonal antibodies that bind to the mid-region of the CgA protein and allow measurement of intact and fragmented circulating CgA. The results from the assay validation indicative of its overall robustness in terms of sensitivity, specificity, reproducibility, and stability are presented here.
Conference: 7th Annual ENETS Conference (2010)
Category: Clinical
Presenting Author: Monica Motwani
#653 Interobserver Variability of Pulmonary Carcinoids
Introduction: Lung carcinoids are neuroendocrine tumors histopathologically classified into typical (TC; no necrosis, <2 mitoses/2 mm2) and atypical (AC; necrosis or 2-10 mitoses/2 mm2). Identification of mitoses may be hampered by the presence of apoptotic cells, and reported prediction of prognosis based on histopathology varies, especially for ACs.
Conference: 10th Annual ENETS Conference (2013)
Category: PRRT-Ablative therapies-Endoscopic treatment
Presenting Author: MSc Dorian Swarts
#813 Comparison of Manual and Automatic Methods of Ki-67 Proliferation Index for Neuroendocrine Tumors: The Development and Validation of a Novel Digital Pathology Tool (Ki-67Counter)
Introduction: Ki-67 proliferation index is an increasingly important biomarker used to grade neuroendocrine tumors. Manual counting methods are laborious and subject to inter- and intra-observer variability. Digital counting methods hold promise for fast and reproducible indices, however, they are fraught with technical difficulties.
Conference: 11th Annual ENETS Conference (2014)
Category: Pathology, grading, staging
Presenting Author: Dr. Lin Yang
Authors: Neltner J, Su H, Xing F, Rosser J, ...
#859 Pancreatic Neuroendocrine Tumors (PNETs): Role of Endoscopic UltraSound-Fine Needle Aspiration (EUS-FNA) and Accuracy of Ki-67 Measurement on Cytological Specimens
Introduction: The role of EUS-FNA in preoperative diagnosis and grading of pNETs is well-established, but it is unclear how Ki-67 expression on cytological specimens obtained by EUS-FNA reflects the value found on surgical specimens.
Conference: 11th Annual ENETS Conference (2014)
Category: Pathology, grading, staging
Presenting Author: Claudio G De Angelis
#935 A Three Tier Grading System Based on Ki-67 Index, Mitotic Count and Necrosis with Cut-Offs Specifically Generated for Lung Neuroendocrine Tumors is Prognostically Effective and Accurate
Introduction: Lung neuroendocrine tumors are catalogued into four categories by the World Health Organization (WHO 2004) classification. Its reproducibility and prognostic efficacy was disputed. The WHO 2010 classification of digestive neuroendocrine neoplasms is based on a Ki-67 index and has proved prognostically effective.
Conference: 11th Annual ENETS Conference (2014)
Category: Pathology, grading, staging
Presenting Author: Professor Guido Rindi
Authors: Rindi G, Klersy C, Inzani F, ...
#1104 Interlaboratory Variability of MIB1 Staining in Well Differentiated Pancreatic Neuroendocrine Tumors
Introduction: In neuroendocrine tumors (NET) grading and staging are the only routinely performed procedures to judge prognosis. Proliferation index using MIB1 staining has been introduced to assess grading. There are discussions on cut-off definitions, automated counting and inter-observer variability.
Conference: 12th Annual ENETS Conference (2015)
Category: Pathology, grading, staging
Presenting Author: Dr. Blank Annika
Authors: Blank A, Wehweck L, Marinoni I, Boos L, ...
Keywords: MIB1, Ki67, grading, NET
#2129 Phosphohistone H3 (PHH3) Immunohistochemical Staining Outperforms Conventional H&E Mitotic Count in Classifying Pulmonary Carcinoids
Introduction: Pulmonary carcinoids (PC) are well-differentiated NETs and are classified as typical carcinoid (TC) and atypical carcinoid (AC). Despite the fact that TC and AC exhibit significant differences in patient survival, their classification depends on relatively subtle differences in mitotic count (MC). Although careful counting of mitotic figures (MF) is essential, it is a very subjective task, time-consuming and lacks of sensitivity and interobserver reproducibility, due to selection bias of the hot spots, heterogeneous distribution of MF, difficulty in distinguishing MF from similar chromatin changes (i.e. in apoptotic cells or due to crush, karyorrhectic debris, pyknosis or apoptosis).
Conference: 15th Annual ENETS conference (2018)
Category: Pathology - grading, staging
Presenting Author: Dr Tu Vinh Luong
#2745 Integrative Genomic Characterization Identifies Molecular Subtypes of Lung Carcinoids
Introduction: Lung carcinoids (LCs) are rare and slow growing primary lung neuroendocrine tumors. The WHO classify LCs into atypical and typical carcinoids. Recent studies have shown that the reproducibility of LCs classification and its prognostic efficacy have high interobserver variability
Conference: 17th Annual ENETS Conference (2020)
Category: Basic Science - Genetics, epigenetics, miRNAs, Omics
Presenting Author: Dr Saurabh V Laddha
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