An intra-individual comparison of MRI, [18F]-FET and [18F]-FLT PET in patients with high-grade gliomas.
OBJECTIVE
Intra-individual spatial overlap analysis of tumor volumes assessed by MRI, the amino acid PET tracer [18F]-FET and the nucleoside PET tracer [18F]-FLT in high-grade gliomas (HGG).


METHODS
MRI, [18F]-FET and [18F]-FLT PET data sets were retrospectively analyzed in 23 HGG patients. Morphologic tumor volumes on MRI (post-contrast T1 (cT1) and T2 images) were calculated using a semi-automatic image segmentation method. Metabolic tumor volumes for [18F]-FET and [18F]-FLT PETs were determined by image segmentation using a threshold-based volume of interest analysis. After co-registration with MRI the morphologic and metabolic tumor volumes were compared on an intra-individual basis in order to estimate spatial overlaps using the Spearman's rank correlation coefficient and the Mann-Whitney U test.


RESULTS
[18F]-FLT uptake was negative in tumors with no or only moderate contrast enhancement on MRI, detecting only 21 of 23 (91%) HGG. In addition, [18F]-FLT uptake was mainly restricted to cT1 tumor areas on MRI and [18F]-FLT volumes strongly correlated with cT1 volumes (r = 0.841, p<0.001). In contrast, [18F]-FET PET detected 22 of 23 (96%) HGG. [18F]-FET uptake beyond areas of cT1 was found in 61% of cases and [18F]-FET volumes showed only a moderate correlation with cT1 volumes (r = 0.573, p<0.001). Metabolic tumor volumes beyond cT1 tumor areas were significantly larger for [18F]-FET compared to [18F]-FLT tracer uptake (8.3 vs. 2.7 cm3, p<0.001).


CONCLUSIONS
In HGG [18F]-FET but not [18F]-FLT PET was able to detect metabolic active tumor tissue beyond contrast enhancing tumor on MRI. In contrast to [18F]-FET, blood-brain barrier breakdown seems to be a prerequisite for [18F]-FLT tracer uptake.
Department of Neurology, Innsbruck Medical University, Innsbruck, Austria.
Martha
M
Nowosielski
Department of Oto-, Rhino- and Laryngology with 4D Visualization Lab, Innsbruck Medical University, Innsbruck, Austria; Department of Radiology, Computational Image Analysis and Radiology Lab (CIR), Medical University of Vienna, Vienna, Austria.
Matthew D
MD
DiFranco
Department of Nuclear Medicine, Innsbruck Medical University, Innsbruck, Austria.
Daniel
D
Putzer
Department of Neurosurgery, Innsbruck Medical University, Innsbruck, Austria; Department of Neurosurgery, Mannheim Medical University, Mannheim, Germany.
Marcel
M
Seiz
Department of Radiology, Innsbruck Medical University, Innsbruck, Austria.
Wolfgang
W
Recheis
European Institute for Molecular Imaging (EIMI) at the Westphalian Wilhelms University, Münster, Germany; Department of Geriatrics at Evangelische Kliniken, Johanniter Krankenhaus, Bonn, Germany.
Andreas H
AH
Jacobs
Department of Neurology, Innsbruck Medical University, Innsbruck, Austria.
Günther
G
Stockhammer
Department of Neurology, Innsbruck Medical University, Innsbruck, Austria; Department of Neurology and Wilhelm-Sander Neurooncology Unity, University Hospital and Medical School Regensburg, Regensburg, Germany.
Markus
M
Hutterer
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D019788:Fluorodeoxyglucose F18; D005910:Glioma / Q000175:diagnosis*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D049268:Positron-Emission Tomography / Q000379:methods*
D019788:Fluorodeoxyglucose F18