Optimizing TMS Coil Placement Approaches for Targeting the Dorsolateral Prefrontal Cortex in Depressed Adolescents: An Electric Field Modeling Study

High-frequency repetitive transcranial magnetic stimulation (rTMS) to the left dorsolateral prefrontal cortex (L-DLPFC) shows promise as a treatment for treatment-resistant depression in adolescents. Conventional rTMS coil placement strategies include the 5 (Formula presented.), the Beam F3, and the magnetic resonance imaging (MRI) neuronavigation methods. The purpose of this study was to use electric field (E-field) models to compare the three targeting approaches to a computational E-field optimization coil placement method in depressed adolescents. Ten depressed adolescents (4 females, age: (Formula presented.)) participated in an open-label rTMS treatment study and were offered MRI-guided rTMS five times per week over 6–8 weeks. Head models were generated based on individual MRI images, and E-fields were simulated for the four targeting approaches. Results showed a significant difference in the induced E-fields at the L-DLPFC between the four targeting methods ((Formula presented.), (Formula presented.)). Post hoc pairwise comparisons showed that there was a significant difference between any two of the targeting methods (Holm adjusted (Formula presented.)), with the 5 (Formula presented.) rule producing the weakest E-field ((Formula presented.)), followed by the F3 method ((Formula presented.)), followed by MRI-guided ((Formula presented.)), and followed by the computational approach ((Formula presented.)). Variance analysis showed that there was a significant difference in sample variance between the groups ((Formula presented.), (Formula presented.)), with F3 having the largest variance. Participants who completed the full course of treatment had median E-fields correlated with depression symptom improvement ((Formula presented.), (Formula presented.)). E-field models revealed limitations of scalp-based methods compared to MRI guidance, suggesting computational optimization could enhance dose delivery to the target.