Abstract
We aimed to evaluate the novel high-affinity and relatively lipophilic CB(1) receptor (CB(1)R) antagonist radioligand [(125)I]SD7015 for SPECT imaging of CB(1)Rs in vivo using the multiplexed multipinhole dedicated small animal SPECT/CT system, NanoSPECT/CT(PLUS) (Mediso, Budapest, Hungary), in knock-out CB(1) receptor knock-out (CB(1)R-/-) and wildtype mice. In order to exclude possible differences in cerebral blood flow between the two types of animals, HMPAO SPECT scans were performed, whereas in order to confirm the brain uptake differences of the radioligand between knock-out mice and wildtype mice, in vivo scans were complemented with ex vivo autoradiographic measurements using the brains of the same animals. With SPECT/CT imaging, we measured the brain uptake of radioactivity, using %SUV (% standardised uptake values) in CB(1)R-/- mice (n=3) and C57BL6 wildtype mice (n=7) under urethane anaesthesia after injecting [(125)I]SD7015 intravenously or intraperitoneally. The Brookhaven Laboratory mouse MRI atlas was fused to the SPECT/CT images by using a combination of rigid and non-rigid algorithms in the Mediso Fusion™ (Mediso, Budapest, Hungary) and VivoQuant (inviCRO, Boston, MA, USA) softwares. Phosphor imager plate autoradiography (ARG) was performed on 4 μm-thin cryostat sections of the excised brains. %SUV was 8.6±3.6 (average±SD) in CB(1)R-/- mice and 22.1±12.4 in wildtype mice between 2 and 4 h after injection (p<0.05). ARG of identically taken sections from wildtype mouse brain showed moderate radioactivity uptake when compared with the in vivo images, with a clear difference between grey matter and white matter, whereas ARG in CB(1)R(-/-) mice showed practically no radioactivity uptake. [(125)I]SD7015 enters the mouse brain in sufficient amount to enable SPECT imaging. Brain radioactivity distribution largely coincides with that of the known CB(1)R expression pattern in rodent brain. We conclude that [(125)I]SD7015 should be a useful SPECT radioligand for studying brain CB(1)R in mouse and rat disease models.
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