PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
August 1, 2013The Neuroradiology Journal28 citationsOpen Access

Correlation between Cerebral Blood Volume Measurements by Perfusion-Weighted Magnetic Resonance Imaging and Two-Year Progression-Free Survival in Gliomas

View Full Paper
MSMaria Vittoria SpampinatoCSChiara SchiarelliACAlessandro Cianfoni

Key Points

Key points are not available for this paper at this time.

Abstract

Our goal was to determine whether relative cerebral blood volume (rCBV) can serve as an adjunct to histopathologic grading in the assessment of gliomas, with the hypothesis that rCBV can predict two-year survival. We evaluated 29 newly diagnosed gliomas (13 WHO grade II, seven grade III, nine grade IV; 17 astrocytomas, 12 oligodendroglial tumors). Dynamic susceptibility-weighted contrast-enhanced perfusion MR images and CBV maps were obtained. rCBVmax measurements (maximum tumor CBV/contralateral normal tissue CBV) and progression-free survival (PFS) were recorded. Receiver operating characteristic curves and Kaplan-Meier survival curves were calculated for rCBVmax and histologic grade. rCBVmax measurements differed between gliomas without (2.38 +/- 1.22) and with progression (5.57 +/- 2.84) over two years. The optimal rCBVmax cut-off value to predict progression was 2.95. rCBVmax < 2.95 was a significant predictor of two-year PFS, almost as accurate as WHO grade II. In the pure astrocytoma subgroup, the optimal rCBVmax cut-off value to predict progression was 2.85. In this group rCBVmax < 2.85 was a significant predictor of two-year PFS, an even better predictor of two-year PFS than WHO grade II. rCBVmax can be used to predict two-year PFS in patients with gliomas, independent of pathologic findings, especially in tumors without oligodendroglial components.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Spampinato et al. (2013) studied this question.

synapsesocial.com/papers/6a17f9731b114e5976b4b88chttps://doi.org/10.1177/197140091302600404
Ask AI
Helpful
Bookmark
Share
View Full Paper