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Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach
Raviteja Kotikalapudi1, Balint Kincses1,2, Matthias Zunhammer2
1Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Medicine Essen, Essen, Germany.
Pain
|June 15, 2023
Summary
Brain structure can predict individual pain sensitivity. Cortical thickness in specific brain regions, like the anterior cingulate gyrus, helps forecast pain thresholds, offering potential for new pain biomarkers.
Area of Science:
- Neuroscience
- Pain Research
- Medical Imaging
Background:
- Individual differences in pain sensitivity are significant and can predict or accompany pain conditions.
- Previous studies suggest links between pain thresholds and brain morphology, but replication and predictive power remain uncertain.
Purpose of the Study:
- To develop and validate a predictive model for individual pain sensitivity using structural brain imaging data.
- To assess the reliability and specificity of brain morphology in predicting pain thresholds.
Main Methods:
- Utilized structural magnetic resonance imaging (sMRI)-based cortical thickness data from a multicentre dataset of 131 healthy participants.
- Constructed a predictive model for pain sensitivity (pain thresholds) and evaluated its cross-validated performance.
- Analyzed model coefficients to identify key brain regions influencing pain sensitivity predictions.
Main Results:
- The predictive model demonstrated statistically significant and clinically relevant performance (Pearson r = 0.36, P < 0.0002, R2 = 0.13).
- Predictions were specific to physical pain thresholds and unaffected by confounding factors like anxiety or depression.
- Key predictors included cortical thickness in the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole, negatively correlated with pain sensitivity.
Conclusions:
- Structural brain morphology, specifically cortical thickness, can reliably predict individual pain sensitivity.
- This study provides proof-of-concept for using brain morphology to forecast pain sensitivity.
- Findings support the development of future multimodal, brain-based biomarkers for pain assessment.
