Changes in Gray Matter Density, Regional Homogeneity, and Functional Connectivity in Methamphetamine-Associated Psychosis: A Resting-State Functional Magnetic Resonance Imaging (fMRI) Study

Zhang, Shengyu; Hu, Qiang; Tang, Tao; Liu, Chao; Li, Chengchong; Zang, Yong; Cai, Wei-Xiong

doi:10.12659/msm.905354

Cited by 18 publications

(21 citation statements)

References 16 publications

(18 reference statements)

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“…Then, the signals were regressed out, including the global signal, cerebrospinal fluid signal and white matter signal, and the 24 head motion parameters. Afterward, the images were smoothed with the Gaussian kernel using the full width at half maximum of 6 mm and bandpass temporal filtered (0.01–0.1 Hz) to reduce the low-frequency drift and physiological high-frequency noise, including the breath and heartbeats ( 26 ).…”

Section: Methodsmentioning

confidence: 99%

“…MA abuse was found to be associated with structural and functional alterations of the brain. In a study that used functional magnetic resonance imaging (fMRI), Zhang et al researched the resting-state functional connectivity (RSFC) between seeds [region of interest (ROI)] selected with a higher value of ReHo and the whole-brain voxels and found different RSFC performance when compared with healthy controls (HCs) ( 26 ). Furthermore, in the studies conducted by Kohno et al ( 27 , 28 ), the midbrain and dorsolateral prefrontal cortex were chosen as ROIs, referring to previous research results.…”

Section: Introductionmentioning

confidence: 99%

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Treatment Response Prediction and Individualized Identification of Short-Term Abstinence Methamphetamine Dependence Using Brain Graph Metrics

Cui

Yang

et al. 2021

Front. Psychiatry

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Background: The abuse of methamphetamine (MA) worldwide has gained international attention as the most rapidly growing illicit drug problem. The classification and treatment response prediction of MA addicts are thereby paramount, in order for effective treatments to be more targeted to individuals. However, there has been limited progress.Methods: In the present study, 43 MA-dependent participants and 38 age- and gender-matched healthy controls were enrolled, and their resting-state functional magnetic resonance imaging data were collected. MA-dependent participants who showed 50% reduction in craving were defined as responders to treatment. The present study used the machine learning method, which is a support vector machine (SVM), to detect the most relevant features for discriminating and predicting the treatment response for MA-dependent participants based on the features extracted from the functional graph metrics.Results: A classifier was able to differentiate MA-dependent subjects from normal controls, with a cross-validated prediction accuracy, sensitivity, and specificity of 73.2% [95% confidence interval (CI) = 71.23–74.17%), 66.05% (95% CI = 63.06–69.04%), and 80.35% (95% CI = 77.77–82.93%), respectively, at the individual level. The most accurate combination of classifier features included the nodal efficiency in the right middle temporal gyrus and the community index in the left precentral gyrus and cuneus. Between these two, the community index in the left precentral gyrus had the highest importance. In addition, the classification performance of the other classifier used to predict the treatment response of MA-dependent subjects had an accuracy, sensitivity, and specificity of 71.2% (95% CI = 69.28–73.12%), 86.75% (95% CI = 84.48–88.92%), and 55.65% (95% CI = 52.61–58.79%), respectively, at the individual level. Furthermore, the most accurate combination of classifier features included the nodal clustering coefficient in the right orbital part of the superior frontal gyrus, the nodal local efficiency in the right orbital part of the superior frontal gyrus, and the right triangular part of the inferior frontal gyrus and right temporal pole of middle temporal gyrus. Among these, the nodal local efficiency in the right temporal pole of the middle temporal gyrus had the highest feature importance.Conclusion: The present study identified the most relevant features of MA addiction and treatment based on SVMs and the features extracted from the graph metrics and provided possible biomarkers to differentiate and predict the treatment response for MA-dependent patients. The brain regions involved in the best combinations should be given close attention during the treatment of MA.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Treatment Response Prediction and Individualized Identification of Short-Term Abstinence Methamphetamine Dependence Using Brain Graph Metrics

Cui

Yang

et al. 2021

Front. Psychiatry

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“…One study demonstrated that similar gray matter deficits appear to exist within the left perisylvian region of brain in the posterior inferior frontal gyrus and anterior superior temporal gyrus in both MAP and schizophrenia (Aoki et al, 2013). However, a study by Zhang et al, 2018 revealed that functional and structural deficits associated with gray matter MAP significantly differed from those observed in the schizophrenia group. Gray matter deficits unique to MAP, such as those in the orbitofrontal area or the frontopolar BA 10 cortices, have been implicated in contributing to the symptoms of MAP unique to the disorder (Aoki et al, 2013).…”

Section: Imaging Studiesmentioning

confidence: 99%

“…Gray matter deficits unique to MAP, such as those in the orbitofrontal area or the frontopolar BA 10 cortices, have been implicated in contributing to the symptoms of MAP unique to the disorder (Aoki et al, ). Additionally, regional homogeneity was observed to be negatively correlated with positive symptoms in the left orbital interior frontal gyrus in MAP, and regional homogeneity was found to be negatively correlated with negative symptoms in the right superior frontal gyrus in schizophrenia patients (Zhang et al, ).…”

Section: Biological Basis Of Mapmentioning

confidence: 99%

Methamphetamine‐associated psychosis: Clinical presentation, biological basis, and treatment options

Chiang

Lombardi

et al. 2019

Human Psychopharmacology

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Introduction Methamphetamine associated psychosis (MAP) represents a mental disorder induced by chronic methamphetamine use in a subset of users. The prevalence of the disorder has increased in several countries in Europe and Asia where methamphetamine use has increased. MAP remains difficult to distinguish from primary psychiatric disorders, especially schizophrenia, creating complications in prescribing treatment plans to patients. Design This narrative review sought to summarize difficulties related to MAP diagnosis and highlight the need for a better treatment model. Current best practices are described and potential novel therapies and future research suggested. Results Results suggest that clear biological and clinical differences appear between patients presenting with MAP and schizophrenia and that there may exist distinct subgroups within MAP itself. MAP‐specific treatment studies have been few and have focused on the use of antipsychotic medication. Antipsychotic treatment has been shown to alleviate the psychotic symptoms of MAP but produce debilitating adverse effects and fail to adequately address methamphetamine use in patients. Conclusions Continued identification of subgroups within the heterogenous MAP population may lead to better diagnosis, treatment, and outcomes for patients. Psychosocial therapies should be explored in addressing the cooccurring substance use and psychosis in the treatment of MAP.

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“…Resting-state functional magnetic resonance imaging (RS-fMRI) is a noninvasive technique and has provided new opportunities to explore the changes of the structure and function in the brain (14). The blood oxygen level dependent low-frequency oscillation signal in the RS-fMRI denotes spontaneous activity of neurons (15).…”

Section: Introductionmentioning

confidence: 99%

The effect of aerobic dance intervention on brain spontaneous activity in older adults with mild cognitive impairment: A resting‑state functional MRI study

Zhu

Zhang

et al. 2018

Exp Ther Med

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The current study aimed to evaluate the effect of a specially designed moderate-intensity aerobic dance (SDMIAD) on brain spontaneous activity in older adults with mild cognitive impairment (MCI) using resting-state functional magnetic resonance imaging (RS-fMRI). A total of 38 subjects with MCI were recruited to the current study and were randomized into two groups: Exercise (EG, n=19) and control (CG, n=19). The EG was treated with a SDMIAD and usual care for 3 months. The CG only received usual care. None of the patients were administered medicine that affected cognition during the intervention. The cognitive assessments and RS-fMRI examination were performed on the two groups at recruitment and after 3 months. The cognitive functions were assessed by various neuropsychological tests. The brain spontaneous activity change was assessed using an index, the amplitude of low-frequency fluctuation (ALFF) of fMRI signal. Cognitive assessments demonstrated that EG had significantly improved results in the Mini-Mental State Examination, the Montreal Cognitive Assessment, Wechsler Memory Scale-Revised Logical Memory (WMS-R LM) and the Symbol Digit Modalities Test (all P<0.05), and the difference in changes in WMS-R LM from baseline to 3 months between the EG and the CG was also statistically significant (P<0.05) after 3 months of SDMIAD. The performance of all the cognitive assessments did not demonstrate significant differences in CG. Compared with baseline, EG exhibited significantly increased ALFF in several areas, including the bilateral fronto-temporal, entorhinal, anterior cingulate and parohippocampal cortex after 3 months of SDMIAD (P<0.05); whereas the CG exhibited significantly increased ALFF only in a few areas, including right temporal and posterior cingulate cortex (P<0.05). The SDMIAD may effectively improve the cognitive function in older adults with MCI. RS-fMRI provided a quantitative method for evaluating the effect of aerobic exercise on cognitive function.

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Changes in Gray Matter Density, Regional Homogeneity, and Functional Connectivity in Methamphetamine-Associated Psychosis: A Resting-State Functional Magnetic Resonance Imaging (fMRI) Study

Cited by 18 publications

References 16 publications

Treatment Response Prediction and Individualized Identification of Short-Term Abstinence Methamphetamine Dependence Using Brain Graph Metrics

Treatment Response Prediction and Individualized Identification of Short-Term Abstinence Methamphetamine Dependence Using Brain Graph Metrics

Methamphetamine‐associated psychosis: Clinical presentation, biological basis, and treatment options

The effect of aerobic dance intervention on brain spontaneous activity in older adults with mild cognitive impairment: A resting‑state functional MRI study

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