Abstract Library
Welcome to the open-access search for all ENETS abstracts presented at the Annual ENETS Conferences.
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ENETS Abstract Search
Introduction: Multidisciplinary Tumor Board (MTB) meetings are a valuable tool to improve the management of solid tumors. Yet, few evidences regarding the real-world impact of Neuroendocrine Neoplasm (NEN)-dedicated MTBs are available.
Conference:
Presenting Author:
Authors: Maratta M, Vitale A, Occhipinti D, Raia S, Menotti S,
Keywords: multidisciplinary tumor board, neuroendocrine cancer, disease management, patient care,
Introduction: Liver metastases are common in neuroendocrine neoplasm (NEN). Cystic NEN liver metastases (cNENLM) are rare, and the efficacy of transarterial embolization (TAE) has not been reported.
Conference:
Presenting Author:
Authors: Yu H, Wang Y, Zhang N, Liu H, Chen L,
Keywords: Transaterial embolization, Neuroendocrine neoplasm, Liver metastasis, Cystic, Efficacy, Safety,
Introduction: STZ-based CT has been used for advanced pNETs with rapid growth, high tumor load or progression to somatostatin analogues (SSA). Evidence supporting use of STZ-based CT in pNET is mainly retrospective, and there is an unmet need of prospective trials in this setting. We present data from the R-GETNE regarding the use of STZ in spanish centers.
Conference:
Presenting Author:
Authors: Esteban-Villarrubia J, Hernando J, Garcia A, Jimenez-Fonseca P, Teulé A,
Keywords: Streptozotocin, Chemotherapy, pNET, GETNE, R-GETNE,
#3370 Finding the outcomes of NEN managed by high dose radiations in Pakistan
Introduction: Considering the oncologic control for aggressive neuroendocrine neoplasm, external beam radiation therapy provides a non-invasive method to safely deliver local therapy to nearly any location in the body.
Conference:
Presenting Author: Fatima A
Authors: Fatima A,
Keywords: external beam radiation, local control, metastasis, solid tumor,
Introduction: Response Evaluation Criteria in Solid Tumors (RECIST) assesses treatment response via tumor progression in patients with neuroendocrine tumors (NET). RAISE combined deep learning models (DLM) with sum of the longest diameter (SLD) of liver lesions and chromogranin A (CgA) to find a surrogate endpoint for RECIST to early predict progression-free survival (PFS).
Conference: 18th Annual ENETS Concerence (2021)
Presenting Author: Pavel M
Authors: Pavel M, Dromain C, Ronot M, Schaefer N, Mandair D,
Keywords: neuroendocrine tumor, deep learning models, progression-free survival, prediction,