Reducing target E-field variability in repetitive TMS through online motion compensation

Area of Science:

• Neuroscience
• Medical Physics

Background:

• Repetitive transcranial magnetic stimulation (rTMS) effectiveness hinges on precise targeting and dosing for neurophysiological outcomes, especially in treating major depressive disorder (MDD).
• Neuronavigation aids accurate coil placement, but minor coil deviations during extended rTMS protocols can substantially alter the induced electric field (E-field).
• Motion-induced E-field variability poses a challenge to consistent rTMS treatment delivery.

Purpose of the Study:

• To quantitatively analyze coil-target movement during rTMS sessions.
• To introduce and evaluate a novel methodology for compensating motion-induced E-field variability.
• To enhance the reliability of rTMS for clinical applications like MDD treatment.

Main Methods:

• Analyzed coil-target movement (position, rotation) in 200 rTMS sessions across 20 adults with MDD.
• Simulated induced E-fields and quantified variability within and across sessions.
• Developed a real-time algorithm adjusting stimulator output based on coil position and precomputed E-fields.

Main Results:

• E-field variability was mainly driven by scalp-normal displacement and rotation, with lateral movement having a lesser impact.
• The novel amplitude adjustment method significantly reduced target E-field variability.
• Within-session E-field variability decreased by 41% (from 2.85% to 1.67%), and across-session variability decreased by 74% (from 6.77% to 1.73%).

Conclusions:

• This study provides the first quantitative analysis of motion during rTMS treatment.
• A practical, low-computational-cost method for compensating motion-induced E-field variability was developed.
• The proposed approach is suitable for clinical implementation, improving rTMS treatment reliability, especially for patients prone to movement.