Quantitative organ time activity curve extraction from rodent PET images without anatomical prior

Purpose: Numerous new drug candidates fail because of inadequate pharmacokinetics. Positron emission tomography (PET) enables the noninvasive characterization of the drug in humans and animals. The aim of the present work was the comparison of methods for the extraction of organ time activity curves from rodent PET images without requiring resort to anatomical information. Methods: The rodent organs were segmented using the local means analysis method and the accuracy of the time activity curve (TAC) estimated using four methods was compared: The mean TAC (Mean), the TAC computed in a selection of organ voxels (ROIopt), and the TAC corrected for partial volume effect using the geometric transfer matrix (GTM) method. The accuracy of the TAC estimated using the three methods was compared on phantom simulations and on experimental data sets on mice injected with fluorothymidine. Results: The segmentation quality measured on phantom simulation was 80% of overlap between segmented and gold standard organs. On the phantom simulations, the error on the TAC estimation on phantom simulations was lower for ROIopt (8%) than using the GTM (18%) and the Mean (27%) methods. Similar results were achieved on the experimental data sets: ROIopt (5.8%), GTM (9.7%), and Mean (12%). Conclusions: The new ROI optimization method was fast and precise for all homogeneous organs, while mean organ TAC computation led as expected to important errors. GTM improved the quantification accuracy but showed instabilities due to segmentation errors and to small organ sizes. Partial volume effect correction or limitation is thus possible for the extraction of precise organ TACs without requiring either manual delineation or an anatomical modality.