MURAGAKI Yoshihiro    Department   School of Medicine(Tokyo Women's Medical University Hospital), School of Medicine    Position   Visiting Professor
Article types	Original article
Language	English
Peer review	Peer reviewed
Title	Characteristics of time-activity curves obtained from dynamic (11)C-methionine PET in common primary brain tumors
Journal	Formal name：Journal of neuro-oncology Abbreviation：J Neurooncol ISSN code：15737373/0167594X
Domestic / Foregin	Foregin
Publisher	Springer US
Volume, Issue, Page	136(3),pp.649-658
Author and coauthor	NOMURA Yuichi†, ASANO Yoshitaka, SHINODA Jun, YANO Hirohito, IKEGAME Yuka, KAWASAKI Tomohiro, NAKAYAMA Noriyuki, MARUYAMA Takashi, MURAGAKI Yoshihiro, IWAMA Toru
Publication date	2018/07
Summary	PURPOSE:The aim of this study was to assess whether dynamic PET with11METHODS:One hundred sixty patients with brain tumors (139 gliomas, 9 meningiomas, 4 hemangioblastomas and 8 primary central nervous system lymphomas [PCNSL]) underwent dynamic MET-PET with a 3-dimensional acquisition mode, and the maximum tumor MET-standardized uptake value (MET-SUV) was measured consecutively to construct a time-activity curve (TAC). Furthermore, receiver operating characteristic (ROC) curves were generated from the time-to-peak (TTP) and the slope of the curve in the late phase (SLOPE).RESULTS:The TAC patterns of MET-SUVs (MET-TACs) could be divided into four characteristic types when MET dynamics were analyzed by dividing the MET-TAC into three phases. MET-SUVs were significantly higher in early and late phases in glioblastoma compared to anaplastic astrocytoma, diffuse astrocytoma and the normal frontal cortex (P < 0.05). The SLOPE in the late phase was significantly lower in tumors that included an oligodendroglial component compared to astrocytic tumors (P < 0.001). When we set the cutoff of the SLOPE in the late phase to - 0.04 h-1CONCLUSIONS:The results of this study show that quantification of the MET-TAC for each brain tumor identified by a dynamic MET-PET study could be helpful in the non-invasive discrimination of brain tumor subtypes, in particular gliomas.
DOI	10.1007/s11060-018-2834-4
PMID	29564749