Automatically targeting the dorsolateral subthalamic nucleus for functional connectivity-guided rTMS therapy

Abstract

Aim: Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have provided evidence that repetitive transcranial magnetic stimulation (rTMS) exerts treatment effects via functional connectivity (FC) from a superficial stimulation target to a deep effective region. The dorsolateral subthalamic nucleus (DL-STN) is an effective target in deep brain stimulation surgery for Parkinson’s disease (PD), but its targeting highly depends on well-trained neurosurgeons and is not easily used for FC-guided rTMS. We aimed to devise a method for automatically localizing the DL-STN, and further develop a one-stop plug-in of rs-fMRI FC analysis to assist future individualized FC-guided rTMS. Methods: Based on structural and iron-sensitive MRI of 78 participants, two raters defined the DL-STN coordinates with very high reliability. The averaged coordinates in the standard Montreal Neurological Institute (MNI) space were: left DL-STN, x: -11.89 ± 0.82, y: -14.51 ± 1.00, and z: -6.40 ± 1.01 and the right DL-STN, x: 12.53 ± 0.77, y: -13.97 ± 0.86, and z: -6.57 ± 0.99. As the individual distances from the averaged coordinates were less than 3 mm (within one voxel for most rs-fMRI studies) for all 78 participants, we defined the average coordinates as AutoSTN. We then developed a one-stop plug-in named Connectivity and Coordinates Converting Assistant Toolbox (CC-CAT) and performed AutoSTN FC analysis. Results: The AutoSTN seed showed significant FC with the motor cortices in all participants. Conclusion: The AutoSTN-based rs-fMRI FC could guide future rTMS on PD. The one-stop plug-in CC-CAT can be used for any FC-guided rTMS treatment.