Improvement of semi-quantitative small-animal PET data with recovery coefficients: a phantom and rat study.
OBJECTIVE
To evaluate the accuracy of semi-quantitative small-animal PET data, uncorrected for attenuation, and then of the same semi-quantitative data corrected by means of recovery coefficients (RCs) based on phantom studies.


METHODS
A phantom containing six fillable spheres (diameter range: 4.4-14 mm) was filled with an 18F-FDG solution (spheres/background activity=10.1, 5.1 and 2.5). RCs, defined as measured activity/expected activity, were calculated. Nude rats harbouring tumours (n=50) were imaged after injection of 18F-FDG and sacrificed. The standardized uptake value (SUV) in tumours was determined with small-animal PET and compared to ex-vivo counting (ex-vivo SUV). Small-animal PET SUVs were corrected with RCs based on the greatest tumour diameter. Tumour proliferation was assessed with cyclin A immunostaining and correlated to the SUV.


RESULTS
RCs ranged from 0.33 for the smallest sphere to 0.72 for the largest. A sigmoidal correlation was found between RCs and sphere diameters (r(2)=0.99). Small-animal PET SUVs were well correlated with ex-vivo SUVs (y=0.48x-0.2; r(2)=0.71) and the use of RCs based on the greatest tumour diameter significantly improved regression (y=0.84x-0.81; r(2)=0.77), except for tumours with important necrosis. Similar results were obtained without sacrificing animals, by using PET images to estimate tumour dimensions. RC-based corrections improved correlation between small-animal PET SUVs and tumour proliferation (uncorrected data: Rho=0.79; corrected data: Rho=0.83).


CONCLUSIONS
Recovery correction significantly improves both accuracy of small-animal PET semi-quantitative data in rat studies and their correlation with tumour proliferation, except for largely necrotic tumours.
Aide
Nicolas
N
Groupement Régional d'Etudes sur le cancer Unité Bioticla, EA 1772, Université de Caen and Centre François Baclesse, Caen, France. n.aide@baclesse.fr
Louis
Marie-Hélène
MH
Dutoit
Soizic
S
Labiche
Alexandre
A
Lemoisson
Edwige
E
Briand
Mélanie
M
Nataf
Valérie
V
Poulain
Laurent
L
Gauduchon
Pascal
P
Talbot
Jean-Noël
JN
Montravers
Françoise
F
D000465:Algorithms; D000818:Animals; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009369:Neoplasms / Q000000981:diagnostic imaging*; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000295:instrumentation / Q000379:methods* / Q000662:veterinary*; D051381:Rats; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity