Noninvasive quantification of 18F-FLT human brain PET for the assessment of tumour proliferation in patients with high-grade glioma.
OBJECTIVE
Compartmental modelling of 3′-deoxy-3′-[18F]-fluorothymidine (18F-FLT) PET-derived kinetics provides a method for noninvasive assessment of the proliferation rate of gliomas. Such analyses, however, require an input function generally derived by serial blood sampling and counting. In the current study, 18F-FLT kinetic parameters obtained from image-derived input functions were compared with those from input functions derived from arterialized blood samples.


METHODS
Based on the analysis of 11 patients with glioma (WHO grade II-IV) a procedure for the automated extraction of an input function from 18F-FLT brain PET data was derived. The time-activity curve of the volume of interest with the maximum difference in 18F-FLT uptake during the first 5 min after injection and the period from 60 to 90 min was corrected for partial-volume effects and in vivo metabolism of 18F-FLT. For each patient a two-compartment kinetic model was applied to the tumour tissue using the image-derived input function. The resulting kinetic rate constants K1 (transport across the blood-brain barrier) and Ki (metabolic rate constant or net influx constant) were compared with those obtained from the same data using the input function derived from blood samples. Additionally, the metabolic rate constant was correlated with the frequency of tumour cells stained with Ki-67, a widely used immunohistochemical marker of cell proliferation.


RESULTS
The rate constants from kinetic modelling were comparable when the blood sample-derived input functions were replaced by the image-derived functions (K1,img and K1,sample, r = 0.95, p < 10(-5); Ki,img and Ki,sample, r = 0.86, p < 0.001). A paired t-test showed no significant differences in the parameters derived with the two methods (K1,img and K1,sample, p = 0.20; Ki,img and Ki,sample, p = 0.92). Furthermore, a significant correlation between Ki,img and the percentage of Ki-67-positive cells was observed (r = 0.73, p = 0.01).


CONCLUSIONS
Kinetic modelling of 18F-FLT brain PET data using image-derived input functions extracted from human brain PET data with the practical procedure described here provides information about the proliferative activity of brain tumours which might have clinical relevance especially for monitoring of therapy response in future clinical trials.
Backes
Heiko
H
Max Planck Institute for Neurological Research with Klaus-Joachim-Zülch-Laboratories, Gleueler Str 50, 50931 Cologne, Germany. backes@nf.mpg.de
Ullrich
Roland
R
Neumaier
Bernd
B
Kracht
Lutz
L
Wienhard
Klaus
K
Jacobs
Andreas H
AH
D001158:Arteries / Q000503:physiopathology; D001921:Brain / Q000098:blood supply / Q000000981:diagnostic imaging* / Q000378:metabolism / Q000473:pathology; D001932:Brain Neoplasms / Q000098:blood supply / Q000000981:diagnostic imaging* / Q000378:metabolism / Q000473:pathology*; D049109:Cell Proliferation; D015224:Dideoxynucleosides / Q000378:metabolism; D005910:Glioma / Q000098:blood supply / Q000000981:diagnostic imaging* / Q000378:metabolism / Q000473:pathology*; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D049268:Positron-Emission Tomography; D015203:Reproducibility of Results; D012189:Retrospective Studies
D015224:Dideoxynucleosides; C002854:alovudine