AUTHOR=Chen Rong , Dadario Nicholas B. , Cook Brennan , Sun Lichun , Wang Xiaolong , Li Yujie , Hu Xiaorong , Zhang Xia , Sughrue Michael E. 

TITLE=Connectomic insight into unique stroke patient recovery after rTMS treatment

JOURNAL=Frontiers in Neurology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2023.1063408

DOI=10.3389/fneur.2023.1063408

ISSN=1664-2295

ABSTRACT=An improved understanding of the neuroplastic potential of the brain has allowed advancements in neuromodulatory treatments for acute stroke patients. However, there remains a poor understanding of individual differences in treatment-induced recovery. Individualized information of connectivity disturbances may help predict differences in treatment response and recovery phenotypes.
We studied the medical data of 22 ischemic stroke patients who received MR scans and started repetitive transcranial magnetic stimulation (rTMS) treatment at same day. The functional and motor outcomes were assessed at admission day, 1-day after treatment, 30-days, and 90-days after treatment using four validated standardized stroke outcome scales. Each patient underwent detailed baseline connectivity analyses to identify structural and functional connectivity disturbances. An unsupervised machine learning (ML) agglomerative hierarchical clustering method was utilized to group patients according to outcomes at four time points to identify individual phenotypes in recovery trajectory. 
Patients were a median age of 64, 50% female, and had a median length of stay of 9.5 days. A significant improvement between three four points was demonstrated in three of four validated stroke scales utilized. ML-based analyses identified distinct clusters representing unique patient trajectories for each scale. Quantitative differences were found to exist in structural and functional connectivity analyses of the motor network and subcortical structures between individual clusters which could explain these unique trajectories on the Barthel Index (BI) scale but not on other stroke scales. 
This study demonstrates for the first time the feasibility of using individualized connectivity analyses in differentiating unique phenotypes in rTMS treatment responses and recovery. This personalized connectomic approach may be utilized in the future to better understand patient recovery trajectories with neuromodulatory treatment.