Prognostic value of a three-scale grading system based on combining molecular imaging with 68Ga-DOTATATE and 18F-FDG PET/CT in patients with metastatic gastroenteropancreatic neuroendocrine neoplasias.
Oncotarget
; 11(6): 589-599, 2020 Feb 11.
Article
em En
| MEDLINE
| ID: mdl-32110279
ABSTRACT
We investigated on the added prognostic value of a three-scale combined molecular imaging with 68Ga-DOTATATE and 18F-FDG PET/CT, (compared to Ki-67 based histological grading), in gastroenteropancreatic neuroendocrine neoplasia patients. 85 patients with histologically proven metastatic gastroenteropancreatic neuroendocrine neoplasias, who underwent combined PET/CT imaging were retrospectively evaluated. Highest Ki-67 value available at time of 18F-FDG PET/CT was recorded. Patients were classified according to World Health Organization/European Neuroendocrine Tumor Society histological grades (G1, G2, G3) and into three distinct imaging categories (C1 all lesions are 18F-FDG negative/68Ga-DOTATATE positive, C2 patients with one or more 18F-FDG positive lesions, all of them 68Ga-DOTATATE positive, C3 patients with one or more 18F-FDG positive lesions, at least one of them 68Ga-DOTATATE negative). The primary endpoint of the study was Progression-Free Survival, assessed from the date of 18F-FDG PET/CT to the date of radiological progression according to Response Evaluation Criteria In Solid Tumors version 1.1. Classification according to histological grade did not show significant statistical difference in median Progression-Free Survival between G1 and G2 but was significant between G2 and G3 patients. In contrast, median Progression-Free Survival was significantly higher in C1 compared to C2 and in C2 compared to C3 patients, revealing three distinctive imaging categories, each with highly distinctive prognosis. Our three-scale combined 68Ga-DOTATATE/18F-FDG PET imaging classification holds high prognostic value in patients with metastatic gastroenteropancreatic neuroendocrine neoplasias.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article