# Long Term efficacy of rTMS in Managing MTBI-related Headache

> **NIH VA I01** · VA SAN DIEGO HEALTHCARE SYSTEM · 2021 · —

## Abstract

Abstract
 Persistent headache is one of the most common debilitating symptoms in military personnel
suffering from mild traumatic brain injury (MTBI). Along with headaches, these patients also suffer
from associated mood and attentional deficit. Conventional analgesics have not been shown to be
effective in managing these debilitating symptoms and consist of untoward side effects and abusive
complication. Our preliminary study indicates a week long course of non-invasive central
neuromodulation method called repetitive transcranial magnetic stimulation (rTMS) at the left motor
cortex (LMC) can significantly alleviate MTB related headache symptoms up to one month without
significant side effects in comparison to sham control. Ongoing prospective clinical survey in patients
receiving treatments also suggests rTMS provides a feasible non-invasive long-term therapeutic option
for MTBI related headache (MTBI-HA) management. This proposal aims to further validate the long-
term effect of rTMS in managing MTBI-HA up to 2-3 months by comparing the treatment effect of
active-rTMS (Group A) to sham-rTMS (Group B) at LMC in: 1) reducing the intensity, frequency and
duration of MTBI-HA and the overall analgesic usage; and 2) improving quality of life, mood and
functions in patients with MTBI.

## Key facts

- **NIH application ID:** 10093997
- **Project number:** 5I01RX002506-04
- **Recipient organization:** VA SAN DIEGO HEALTHCARE SYSTEM
- **Principal Investigator:** ALBERT Y. LEUNG
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2021
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2018-01-01 → 2023-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10093997

## Citation

> US National Institutes of Health, RePORTER application 10093997, Long Term efficacy of rTMS in Managing MTBI-related Headache (5I01RX002506-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10093997. Licensed CC0.

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