A small randomized, double-blind trial suggests that MRI-based measures of brain structure may help predict which patients with major depressive disorder will show early symptom improvement after treatment with the traditional Chinese medicine Yueju Pill. In the four-day study, Yueju Pill and escitalopram were both associated with lower depression rating scores, but only Yueju Pill was linked to a rise in blood levels of brain-derived neurotrophic factor (BDNF).
Major depressive disorder (MDD) is a common mental health condition and a leading cause of disability. Scientists have been looking for biological tools that could reduce the “trial-and-error” process of choosing treatments.
In a randomized, double-blind, placebo-controlled pilot trial conducted at the Fourth People’s Hospital of Taizhou, researchers enrolled 28 outpatients diagnosed with MDD and assigned them to one of two four-day treatment regimens. One group received Yueju Pill plus a placebo version of escitalopram, while the other received escitalopram plus a placebo version of Yueju Pill.
Depression severity was measured with the 24-item Hamilton Depression Scale (HAMD-24). Participants also provided blood samples for serum BDNF testing, and underwent multimodal MRI before treatment to support analyses of brain-network features.
After treatment, both groups showed significant reductions in HAMD-24 scores. A key biological difference was that only the Yueju Pill group showed a significant increase in serum BDNF, a protein involved in neuronal growth and brain plasticity that has been linked in prior research to depression and antidepressant response.
Using MRI-derived networks, the researchers reported that morphological (structure-based) brain networks—rather than functional networks—were associated with predicting changes in symptoms. In analyses comparing the two treatments, the study found that gyrification index-based morphological networks could predict symptom change rates in both groups. However, sulcus depth-based networks and cortical thickness-based networks were reported as predictive only in the Yueju Pill group, linking to changes in depressive symptoms and BDNF, respectively.
Subnetwork analyses highlighted the brain’s visual network as independently predictive of changes in both depressive symptoms (in sulcus depth-based analyses) and BDNF levels (in cortical thickness-based analyses) following Yueju Pill treatment.
The study’s lead author, Dr. Yuxuan Zhang, said the findings could support treatment selection earlier in care: “The brain networks can then be fed to the predictive models constructed in this study to predict patients' responses to Yueju Pill treatment. Based on the predicted responses, we can then determine whether the patient is suitable for Yueju Pill treatment.”
The results were published in General Psychiatry (2025; 38(5): e102041). The authors described the work as preliminary and noted limitations typical of pilot research, including the small sample size and the short four-day observation window, which may be too brief to assess steady-state effects for some antidepressants. Larger, multicenter studies would be needed to confirm whether MRI-based predictors can reliably guide individualized treatment choices.
