Improving the quantitation accuracy in noninvasive small animal single photon emission computed tomography imaging

IntroductionNoninvasive imaging of small animals to measure biodistributions and pharmacokinetics of radiolabeled agents is increasingly seen as an effective alternative to external counting of tissues obtained by sacrifice and dissection. However, we have observed important disagreements in measuring the accumulation of 111In-labeled antibodies in organs such as liver and kidneys when comparing imaging to ex vivo counting in the same animals. This study was conducted to establish whether this discrepancy could be minimized by selecting the region of interest (ROI) in images at the appropriate color threshold and by correcting for the estimated radioactivity within the blood pool of these organs during imaging.MethodsVials with known concentrations of 111In as phantoms were imaged on a Bioscan NanoSPECT/CT. Thereafter, an 111In-DTPA-IgG antibody as the test agent was administered intravenously to normal rats, and whole body acquisitions were obtained at 2, 24 or 48 h. Immediately following imaging, the animals were sacrificed, the tissues were removed for ex vivo counting and the radioactivity accumulations were then compared.ResultsThe phantom measurements showed that accuracy depended upon setting the correct ROI and that, in turn, depended upon setting the appropriate threshold of the color scale. Under the most unfavorable conditions, this error did not exceed 60%. Compared to the results of ex vivo counting, quantitation by imaging provided high values in liver and kidneys at all three time points by as much as 140%. However, by using the blood radioactivity at the time of sacrifice and the known blood volume in these organs, the disagreement was reduced in all cases to below 25%.ConclusionIn this study, the discrepancy in quantitating organ radioactivity accumulations between noninvasive imaging and necropsy was primarily due to blood pool radioactivity contributing to the in vivo images. The discrepancy may be minimized by subtracting an estimate of this contribution.