Functional analysis of the neuronal network in patients with functional disorder of basal ganglia using non-invasive neurotransmitter imaging

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The basal ganglia are undoubtedly among the most complex and least understood structures in the mammalian forebrain. In this study, we evaluated phosphoinositide turnover in the cerebrum and dopamine metabolism in the basal ganglia using ^<11>C-diacylglycerol-positron emission computed tomography (PET) and ^<18>F-fluorodopa-PET in patients with functional disorder of basal ganglia before and after treatment.^<11>C-diacylglycerol-PET of Parkinson's disease showed acceleration of the phosphoinositide turnover of the bilateral striatum and functional supression of the ipsilateral thalamus. These results indicate the superiority of the indirect pathway through subthalamic nucleus in patients with Parkinson's disease.^<11>C-diacylglycerol-PET studies in patients with cerebral infarction revealed hyperaccumlation in the prefrontal area in the subacute stage of cerebral infarction. The hyperaccumlation of ^<11>C-diacylglycerol in the prefrontal area in the subacute stage may indicate network plasticity in the cerebrum.Serial ^<18>F-fluorodopa-PET studies revealed hyperfunction of the presynaptic dopaminergic cells of the bilateral striatum in bobble-head doll syndrome. The suppression of output systems caused by hyperfunction of the presynaptic dopaminergic cells may play an important role of the occurrence of bobble-head doll movement.In the diffuse infiltrating tumor of the basal ganglia, ^<18>F-fluorodopa-PET study revealed that the presynaptic dopaminergic cells of the bilateral striatum were consistent within the tumor. In the expansive tumor such as metastatic tumors, ^<18>F-fluorodopa-PET showed accumulation of ^<18>F-fluorodopa in the striatum around the tumor. These results indicate that ^<18>F-fluorodopa-PET studies contribute to a qualitative diagnosis of the tumor in the basal ganglia.These PET data will be practical use for in vivo analysis of human basal ganglia and direct prediction of the network plasticity in the cerebrum.