Brain Imaging Advances Improve Depression Treatment Targeting and Neurodegenerative Disease Diagnosis

New research demonstrates that MRI-based brain imaging is improving clinical outcomes across neurological and psychiatric conditions, from enhancing depression treatment response to enabling more accurate diagnosis of rare neurodegenerative diseases.

In a study published June 24 in JAMA Psychiatry, researchers found that using MRI scans to guide accelerated transcranial magnetic stimulation (aTMS) produced significantly better outcomes for patients with treatment-resistant depression compared to traditional scalp-based targeting. Forty patients ages 22 to 80 with major depressive disorder that hadn't responded to medication were randomly assigned to receive aTMS using either traditional scalp measurements or MRI targeting. After one month, patients who received MRI-targeted treatment had significantly lower depression symptoms, with response rates of 80% compared to 60% for the usual TMS group. Researchers noted that a larger trial is needed to confirm these results.

TMS uses magnetic pulses applied outside the skull to modulate brain activity and has been FDA-approved for treating major depressive disorder in adults since 2008. However, targeting has relied on scalp-based measurements, which cannot account for differences in brain structure between individuals. In accelerated TMS, patients receive multiple treatment sessions per day, condensing several weeks of treatment into a single week.

Separately, researchers at the Sant Pau Research Institute in Barcelona have developed an MRI-based tool that can more accurately identify progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD), two rare and underdiagnosed atypical Parkinsonian disorders. The study, published in The Journal of Prevention of Alzheimer's Disease, shows that structural MRI can be used both to enrich clinical trials with patients who have a high probability of underlying four-repeat tau pathology and to track disease progression with greater sensitivity than current approaches.

PSP and CBD are classified as primary four-repeat tauopathies, defined by pathological aggregates of tau protein. Because they share many symptoms with Parkinson's disease and Alzheimer's disease, they have been difficult to diagnose. The Sant Pau team applied an MRI-based logistic regression model previously trained on autopsy-confirmed cases. They found that in PSP, the disease-specific signature affected deep brain structures, particularly the midbrain and pons, along with selective cortical thinning. In CBD, cortical regions related to motor control and sensory integration were more prominently affected. The MRI-derived models can identify PSP or CBD with high accuracy.

The researchers noted that MRI-based signatures can track disease progression more accurately than current approaches, and the most powerful application may be in improving recruitment for PSP and CBD clinical trials. Participants in the current study were enrolled in the 4 Repeat Tauopathy Neuroimaging Initiative and from a Phase II/III clinical trial of Davunetide for PSP treatment. Scanner heterogeneity and the need for validation in independent patient cohorts remain hurdles before widespread adoption.

Meanwhile, at the annual meeting of the French Society of Radiology in Paris, experts discussed how artificial intelligence and brain imaging are transforming psychiatry. Researchers presented algorithms capable of identifying differences of just two to three percent in brain tissue or white matter pathways. Models built on thousands of MRI scans can already anticipate the onset of psychosis or predict how a bipolar patient will respond to lithium years in advance. Experts emphasized that while AI provides new tools for understanding neural trajectories, the patient must remain at the center of care and that technology should complement, not replace, clinical judgment.