A preoperative computed tomography radiomics model to predict disease-free survival in patients with pancreatic neuroendocrine tumors.

Autor:	Homps M; Department of Diagnostic and Interventional Imaging, APHP, Hôpital Cochin, Paris F-75014, France.; Faculté de Médecine, Université Paris Cité, Paris F-75006, France., Soyer P; Department of Diagnostic and Interventional Imaging, APHP, Hôpital Cochin, Paris F-75014, France.; Faculté de Médecine, Université Paris Cité, Paris F-75006, France., Coriat R; Faculté de Médecine, Université Paris Cité, Paris F-75006, France.; Department of Gastroenterology and Digestive Oncology, AP-HP, Hôpital Cochin, Paris F-75014, France., Dermine S; Faculté de Médecine, Université Paris Cité, Paris F-75006, France.; Department of Gastroenterology and Digestive Oncology, AP-HP, Hôpital Cochin, Paris F-75014, France., Pellat A; Faculté de Médecine, Université Paris Cité, Paris F-75006, France.; Department of Gastroenterology and Digestive Oncology, AP-HP, Hôpital Cochin, Paris F-75014, France., Fuks D; Faculté de Médecine, Université Paris Cité, Paris F-75006, France.; Department of Surgery, Hôpital Cochin, APHP, Paris F-75014, France., Marchese U; Faculté de Médecine, Université Paris Cité, Paris F-75006, France.; Department of Surgery, Hôpital Cochin, APHP, Paris F-75014, France., Terris B; Faculté de Médecine, Université Paris Cité, Paris F-75006, France.; Department of Pathology, Center for Rare Adrenal Diseases, AP-HP, Hôpital Cochin, Paris F-75014, France., Groussin L; Faculté de Médecine, Université Paris Cité, Paris F-75006, France.; Department of Endocrinology, Center for Rare Adrenal Diseases, AP-HP, Hôpital Cochin, Paris F-75014, France., Dohan A; Department of Diagnostic and Interventional Imaging, APHP, Hôpital Cochin, Paris F-75014, France.; Faculté de Médecine, Université Paris Cité, Paris F-75006, France., Barat M; Department of Diagnostic and Interventional Imaging, APHP, Hôpital Cochin, Paris F-75014, France.; Faculté de Médecine, Université Paris Cité, Paris F-75006, France.
Jazyk:	angličtina
Zdroj:	European journal of endocrinology [Eur J Endocrinol] 2023 Oct 17; Vol. 189 (4), pp. 476-484.
DOI:	10.1093/ejendo/lvad130
Abstrakt:	Importance: Imaging has demonstrated capabilities in the diagnosis of pancreatic neuroendocrine tumors (pNETs), but its utility for prognostic prediction has not been elucidated yet. Objective: The aim of this study was to build a radiomics model using preoperative computed tomography (CT) data that may help predict recurrence-free survival (RFS) or OS in patients with pNET. Design: We performed a retrospective observational study in a cohort of French patients with pNETs. Participants: Patients with surgically resected pNET and available CT examinations were included. Interventions: Radiomics features of preoperative CT data were extracted using 3D-Slicer® software with manual segmentation. Discriminant features were selected with penalized regression using least absolute shrinkage and selection operator method with training on the tumor Ki67 rate (≤2 or >2). Selected features were used to build a radiomics index ranging from 0 to 1. Outcome and Measure: A receiving operator curve was built to select an optimal cutoff value of the radiomics index to predict patient RFS and OS. Recurrence-free survival and OS were assessed using Kaplan-Meier analysis. Results: Thirty-seven patients (median age, 61 years; 20 men) with 37 pNETs (grade 1, 21/37 [57%]; grade 2, 12/37 [32%]; grade 3, 4/37 [11%]) were included. Patients with a radiomics index >0.4 had a shorter median RFS (36 months; range: 1-133) than those with a radiomics index ≤0.4 (84 months; range: 9-148; P = .013). No associations were found between the radiomics index and OS (P = .86). Competing Interests: Conflict of interest: The authors declare no conflict of interest in relation to the present study. (© The Author(s) 2023. Published by Oxford University Press on behalf of European Society of Endocrinology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
Databáze:	MEDLINE
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