Neuroscience
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Brain Morphology of Cannabis Users With or Without Psychosis: A Pilot MRI Study
Chapters
Summary August 18th, 2020
This is a 3T magnetic resonance imaging study aiming to investigate grey matter volume differences between cannabis-induced psychosis patients and non-psychotic chronic cannabis users.
Transcript
The aim of this study was to investigate the morphological brain differences between chronic cannabis users with cannabis-induced psychosis and non-psychotic cannabis users without any psychiatric condition and correlate the brain deficits with selective sociodemographic, clinical, and psychosocial variables. Studying brain alteration induced by cannabis consumption may represent a crucial step in the early detection and treatment of patient at high risk of developing of psychotic picture. Magnetic resonance imaging is a non-invasive and relatively safe method to investigate brain alterations.
It does not use radiations and does not cause pain, therefore it is applicable to a younger population, which is particularly exposed to cannabis consumption. The use of magnetic resonance to investigate cannabis-induced alterations carries considerable social and cultural implications. Therefore, the results achieved via this technique may lead to significant educational and economic considerations.
Demonstrating the procedure will be Claudia Cinnante, a neuroradiologist of our institute. Instruct the participant to lie down in a supine position on the bed of the 3 Tesla MRI scanner. Provide earplugs and headphones to block noise, and place a radio-frequency coil over the participant's head.
Instruct the subject to remain still, then run an MRI session from the workstation in the control room. Run a three-plane gradient echo scan for alignment and localization and perform a shim procedure to generate a homogenous constant magnetic field. Start an echo planar imaging protocol for MRI.
The parameters for the acquisition of a high resolution T1 weighted three-dimensional brain scan are already set in the imaging program and should not be changed. When finished, remove the participant from the MRI scanner room. Transfer the MRI data to a disk and close the session.
Use the Script_pre-processing script file to perform the pre-processing steps in MATLAB. For segmentation, process the structural image to distinguish and separate the white matter tissues, the gray matter tissues, and the cerebrospinal fluid into different images by running the segment. mat batch file.
Next, run the createtemplate. mat batch file to determine the nonlinear deformations for registering the gray matter and white matter images of all participants. Perform special normalization to adapt the MRI images to an anatomical standard template by running the Normalize to MNI.
mat batch file. After spatial normalization, perform an isotropic Gaussian kernel of six millimeter full width at half maximum Gaussian kernel to increase the signal to noise ratio and to account for subtle variations in anatomic structures, by running the Normalize to MNI. mat batch file.
Perform a one-way analysis of variance, or ANOVA, in the context of a general linear model design to compare GM volumes between CIP patients and non-psychotic cannabis users with gender and age as controlling variables by running the one-way ANOVA batch file. For the CIP group, carry out whole brain regression analyses to explore whether the scores in all the clinical and psychosocial scales employed in this study were significantly correlated with GM volume changes. Run the regression analysis batch file with a clinical scale of interest.
There were no differences in terms of gender, age, age of onset of dependency, and educational level between cannabis-induced psychotic patients and non-psychotic chronic users. However, cannabis-induced psychotic patients showed higher scores in one temperament dimension and one character dimension of the temperament and character inventory. Non-psychotic cannabis users also showed higher scores compared to cannabis-induced psychotic patients in one subdimension of the Neighborhood scale, in the SES total scores, in the quality of life index, in the GAF scale, and in one character dimension of the TCI scale.
VBM analysis showed that cannabis-induced psychotic patients had extensive gray matter decreases compared to non-psychotic chronic users in several brain regions within the prefrontal temporal limbic network, including, for example, the right prefrontal gyrus, the superior temporal gyrus, and insula. Notably, no gray matter reductions were observed in non-psychotic chronic users compared to cannabis-induced psychotic patients. Overall, the results suggest that cannabis-induced psychosis is characterized by selective brain reductions that are not present in non-psychotic economists users.
Therefore, neuroimaging studies may provide a potential ground for identifying the putative biomarkers associated with the risk of developing psychosis in cannabis users. A step forward to this paper would be to integrate the other neuroimaging or electrophysiological approaches such as functional MRI, PET, or EEG, with a final aim to investigate whether there are functional disturbances or electrical abnormalities in these patients. We believe that a structural MRI should be implemented in today clinical practice when dealing with patients with psychosis and a history of cannabis abuse.
Gray matter volume decreasing in specific brain structures suggests that the endocannabinoid system may be a target for future neuroimaging, genetic, and epigenetic studies.
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