Differentiation of pilocytic astrocytoma from glioblastoma using a machine-learning framework based upon quantitative T1 perfusion MRI

Autor:	Neha Vats, Anirban Sengupta, Rakesh K. Gupta, Rana Patir, Sandeep Vaishya, Sunita Ahlawat, Jitender Saini, Sumeet Agarwal, Anup Singh
Rok vydání:	2022
Předmět:	Biomedical Engineering Biophysics Radiology Nuclear Medicine and imaging
Zdroj:	Magnetic resonance imaging.
ISSN:	1873-5894
Popis:	Differentiation of Pilocytic Astrocytoma (PA) from glioblastoma is difficult using conventional MRI parameters. The purpose of this study was to differentiate these two similar in appearance tumors using quantitative TThis retrospective study included age/sex and location matched 26 PA and 33 glioblastoma patients with tumor histopathological characterization performed using WHO 2016 classification. Multi-parametric MRI data were acquired at 3 T scanner and included TTThe approach of using quantitative T
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c61c4ae72577355451416799d4388b2 https://pubmed.ncbi.nlm.nih.gov/36572323 Zobrazit plný text záznamu Full Text from ScienceDirect