Structural Imaging-Based Biomarkers for Detecting Craving and Predicting Relapse in Subjects With Methamphetamine...

Area of Science:

• Neuroimaging
• Addiction Neuroscience
• Psychiatry

Background:

• Craving is a significant predictor of relapse in individuals with substance use disorders.
• The insula cortex (IC) plays a crucial role in mediating craving and drug-seeking behaviors.
• Understanding neural substrates of craving is essential for developing effective relapse prevention strategies.

Purpose of the Study:

• To investigate if insula cortex (IC) abnormalities in methamphetamine (MA) users can accurately detect craving states.
• To determine the potential of IC gray matter volume (GMV) as a predictor of relapse susceptibility.
• To establish structural MRI (sMRI) as a potential diagnostic tool for MA craving.

Main Methods:

• Structural MRI (sMRI) scans were acquired from 142 MA-dependent subjects.
• Voxel-based morphometry (VBM) analyzed gray matter volume (GMV) differences in the IC between craving and non-craving states.
• Receiver operating characteristic (ROC) analysis assessed the diagnostic accuracy of IC GMV for craving detection and relapse prediction.

Main Results:

• Subjects without craving exhibited significantly decreased IC GMV compared to those with craving (p < 0.05).
• IC GMV positively correlated with self-reported MA craving scores, with ROC analysis showing good discrimination (AUC 0.82/0.80).
• Optimal cut-off values demonstrated high sensitivity (70-78%) and specificity (70-75%) for detecting craving states, with high specificity (80-90%) but lower sensitivity (50-55%) for predicting relapse.

Conclusions:

• Structural MRI-based assessment of IC GMV can effectively diagnose craving states in MA users.
• IC GMV serves as a potential MRI biomarker for objectively measuring craving.
• This neuroimaging approach offers a promising tool for addiction treatment and relapse prevention.