Acupuncture is an effective treatment in migraine without aura (MWoA), but the neurological mechanism has not been investigated using multimodal magnetic resonance imaging (MRI). This trial will combine functional MRI, structural MRI, and diffusion tensor imaging to explore the potential neural mechanism of acupuncture on MWoA, and will use machine learning approach to predict acupuncture treatment effects.
In this multimodal neuroimaging randomized controlled trial, a total of 60 MWoA participants will be randomly allocated to two groups: the real acupuncture treatment group and the sham acupuncture control group. This trial will include a 4-week baseline phase, a 4-week treatment phase, and a 12-week follow-up phase. Participants will undergo 12 acupuncture or sham acupuncture sessions during the treatment phase. The Headache Diary, Migraine-Specific Quality of Life Questionnaire, Headache Impact Test, Beck Depression Inventory-II, and Beck Anxiety Inventory will be utilized to evaluate the clinical efficacy. Multimodal MRI scans will be employed to investigate the mechanism of acupuncture at baseline, at the end of treatment, and after follow-up. Multimodal MRI data will be used to predict acupuncture treatment effects using machine learning technology.
This study hypothesized that acupuncture therapy may treat MWoA by restoring the neuropathological alterations in brain activity. Our finding should provide valuable scientific proof for the effects of acupuncture and demonstrate the usefulness of acupuncture in the treatment of MWoA. Moreover, acupuncture response prediction might decrease healthcare expenses and time lags for patients.
[ChiCTR2100044251].