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Background: Striatal hyperdopaminergia is implicated in the pathoetiology of schizophrenia, but how this relates to dopaminergic midbrain activity is unclear. Neuromelanin (NM)-sensitive magnetic resonance imaging provides a marker of long-term dopamine function. We examined whether midbrain NM-sensitive magnetic resonance imaging contrast-to-noise ratio (NM-CNR) was higher in people with schizophrenia than in healthy control (HC) participants and whether this correlated with dopamine synthesis capacity., Methods: One hundred fifty-four participants (schizophrenia group: n = 74, HC group: n = 80) underwent NM-sensitive magnetic resonance imaging of the substantia nigra and ventral tegmental area (SN-VTA). A subset of the schizophrenia group (n = 38) also received [ 18 F]-DOPA positron emission tomography to measure dopamine synthesis capacity (K i cer ) in the SN-VTA and striatum., Results: SN-VTA NM-CNR was significantly higher in patients with schizophrenia than in HC participants (effect size = 0.38, p = .019). This effect was greatest for voxels in the medial and ventral SN-VTA. In patients, SN-VTA K i cer positively correlated with SN-VTA NM-CNR (r = 0.44, p = .005) and striatal K i cer (r = 0.71, p < .001). Voxelwise analysis demonstrated that SN-VTA NM-CNR was positively associated with striatal K i cer (r = 0.53, p = .005) and that this relationship seemed strongest between the ventral SN-VTA and associative striatum in schizophrenia., Conclusions: Our results suggest that NM levels are higher in patients with schizophrenia than in HC individuals, particularly in midbrain regions that project to parts of the striatum that receive innervation from the limbic and association cortices. The direct relationship between measures of NM and dopamine synthesis suggests that these aspects of schizophrenia pathophysiology are linked. Our findings highlight specific mesostriatal circuits as the loci of dopamine dysfunction in schizophrenia and thus as potential therapeutic targets., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

In this study we evaluate the performance of a fully automated analytical framework for FDOPA PET neuroimaging data, and its sensitivity to demographic and experimental variables and processing parameters. An instance of XNAT imaging platform was used to store the King's College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. By re-engineering the historical Matlab-based scripts for FDOPA PET analysis, a fully automated analysis pipeline for imaging processing and data quantification was implemented in Python and integrated in XNAT. The final data repository includes 892 FDOPA PET scans organized from 23 different studies. We found good reproducibility of the data analysis by the automated pipeline (in the striatum for the Ki cer : for the controls ICC = 0.71, for the psychotic patients ICC = 0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F = 10.7, p < 0.001), with women showing greater dopamine synthesis capacity than men. Our automated analysis pipeline represents a valid resourse for standardised and robust quantification of dopamine synthesis capacity using FDOPA PET data. Combining information from different neuroimaging studies has allowed us to test it comprehensively and to validate its replicability and reproducibility performances on a large sample size.