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Pretreatment TMS-EEG connectivity assessment as a potential predictor of rTMS effectiveness in chronic pain: A
Enrico De Martino1, Bruno Andry Nascimento Couto1, Anne Jakobsen1
1Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg, Denmark.
Objective:
Around half of chronic pain patients report pain intensity reduction to high-frequency (10 Hz) repetitive transcranial magnetic stimulation (rTMS) delivered to the primary motor cortex (M1). However, the other half do not respond, making it essential to identify which patients are likely to benefit before starting treatment. Combining TMS with electroencephalogram (TMS-EEG) allows for exploring cortical connectivity, and evaluating this connectivity before administering rTMS may provide insights into which patients are likely to respond favorably to the treatment.
Methods:
Seven chronic pain patients underwent TMS-EEG assessment of M1 before ten daily sessions of 10 Hz rTMS. Pain intensity was measured at baseline and post-treatment, with responders defined as those showing a 30 % reduction on an 11-point numerical rating scale. TMS-evoked potentials were analyzed using the debiased weighted phase lag index to assess connectivity, quantified by phase (connections exceeding the 95 % confidence interval) and space (Euclidean distance between significantly connected EEG channels). Normative connectivity values were also collected from 82 healthy volunteers.
Results:
Four patients responded to M1 rTMS, while three did not, with an average pain intensity reduction of 1.4±1.5. TMS-EEG showed low connectivity indices in all responders to rTMS, whereas two non-responders had higher indices, above the 75th percentile of healthy volunteers.
Conclusions:
This pilot feasibility study showed that the use of TMS-EEG informed rTMS is feasible, and proceeding to larger randomized clinical trials will allow to test this approach.
Significance:
Pre-treatment TMS-EEG connectivity measures may identify rTMS responders, optimizing chronic pain management.
