Identifying poor responders to repetitive transcranial magnetic stimulation using structural brain networks

AI Summary

Lower baseline rich-club connection strength and modularity were associated with non-response and non-remission after 4-week left prefrontal rTMS.
Patients with concurrent low RCS and low modularity had the lowest response and remission rates and showed less treatment-related network reorganisation.
A combined clinical and imaging model improved discrimination over the clinical model alone for predicting response and remission.

TL;DR (AI Generated)

METHODS: In a prospective cohort of 204 depressed patients receiving 4-week left prefrontal rTMS, baseline diffusion MRI was used to quantify structural network rich-club organization and modularity.

RESULTS: Patients with non-response and non-remission showed significantly lower baseline RCS and modularity than their respective comparison groups (all P < 0.05).

Patients with concurrent reductions in both measures (low RCS/low modularity group) had the lowest response and remission rates among the four network groups (both P < 0.05), and this group was independently associated with non-response and non-remission in adjusted logistic models (both P < 0.05).

Basic summary

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Sep 27:111946. doi: 10.1016/j.pnpbp.2026.111946. Online ahead of print.

ABSTRACT

BACKGROUND: The efficacy of repetitive transcranial magnetic stimulation (rTMS) for depression varies widely. We examined whether pretreatment structural brain networks, specifically rich-club connection strength (RCS) and modularity, were associated with this variability and could help predict therapeutic outcomes.

METHODS: In a prospective cohort of 204 depressed patients receiving 4-week left prefrontal rTMS, baseline diffusion MRI was used to quantify structural network rich-club organization and modularity. We assessed their associations with clinical outcomes (improvement, response, remission) and compared the predictive accuracy of clinical, network, and combined models.

RESULTS: Patients with non-response and non-remission showed significantly lower baseline RCS and modularity than their respective comparison groups (all P < 0.05). Patients with concurrent reductions in both measures (low RCS/low modularity group) had the lowest response and remission rates among the four network groups (both P < 0.05), and this group was independently associated with non-response and non-remission in adjusted logistic models (both P < 0.05). The combined clinical-imaging model showed better discrimination than the clinical model alone for both response and remission. In the repeated-scan subsample, the low RCS/low modularity group showed less treatment-related network reorganization.

CONCLUSIONS: Lower baseline RCS and modularity were associated with poorer antidepressant outcome after rTMS in depression. Their combination identified a subgroup with particularly poor clinical improvement and limited network reorganization, suggesting that network-based markers may have prognostic value.

PMID:42801957 | DOI:10.1016/j.pnpbp.2026.111946

Document this CPD