Structural Imaging-Based Biomarkers for Detecting Craving and Predicting Relapse in Subjects With Methamphetamine Dependence
| Autor: | Chang Qi, Xiaobing Fan, Sean Foxley, Qiuxia Wu, Jinsong Tang, Wei Hao, An Xie, Jianbin Liu, Zhijuan Feng, Tieqiao Liu, Yanhui Liao |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Visual analogue scale lcsh:RC435-571 Youden's J statistic Craving Drug seeking computer.software_genre behavioral disciplines and activities 03 medical and health sciences 0302 clinical medicine Methamphetamine dependence Voxel Internal medicine lcsh:Psychiatry mental disorders Medicine 030304 developmental biology Original Research Psychiatry relapse 0303 health sciences Receiver operating characteristic business.industry craving methamphetamine use biomarkers structural imaging Psychiatry and Mental health Cardiology medicine.symptom business computer Structural imaging 030217 neurology & neurosurgery psychological phenomena and processes |
| Zdroj: | Frontiers in Psychiatry, Vol 11 (2021) Frontiers in Psychiatry |
| ISSN: | 1664-0640 |
| Popis: | Background: Craving is the predictor of relapse, and insula cortex (IC) is a critical neural substrate for craving and drug seeking. This study investigated whether IC abnormalities among MA users can detect craving state and predict relapse susceptibility.Methods: A total of 142 subjects with a history of MA dependence completed structural MRI (sMRI) scans, and 30 subjects (10 subjects relapsed) completed 4-month follow-up scans. MA craving was measured by the Visual Analog Scale for Craving. Abnormalities of IC gray matter volume (GMV) between the subjects with and without craving were investigated by voxel-based morphometry (VBM). The receiver operating characteristic (ROC) analysis was performed for the region-of-interest (ROI) of IC GMV to assess the diagnostic accuracy.Results: By comparing whole-brain volume maps, this study found that subjects without craving (n = 64) had a significantly extensive decrease in IC GMV (family-wise error correction, p < 0.05) than subjects with craving group (n = 78). The ROI of IC GMV had a significantly positive correlation with the craving scores reported by MA users. The ROC analysis showed a good discrimination (area under curve is 0.82/0.80 left/right) for IC GMV between the subjects with and without craving. By selecting Youden index cut-off point from whole model group, calculated sensitivity/specificity was equal to 78/70% and 70/75% for left and right IC, respectively. By applying the above optimal cut-off values to 30 follow-up subjects as validations, the results showed a similar sensitivity (73–80%) and specificity (73–80%) for detecting craving state as model group. For predicting relapse susceptibility, the sensitivity (50–55%) was low and the specificity (80–90%) was high.Conclusions: Our study provides the first evidence that sMRI may be used to diagnosis the craving state in MA users based on optimal cut-off values, which could be served as MRI bio-markers and an objective measure of craving state. |
| Databáze: | OpenAIRE |
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