Neuroimaging analysis suggests that the brains of patients with depression are not so different after all

A new meta-analysis suggests that healthy individuals and those with depressive disorders might actually not be so different after all according to their neural signatures on imaging. 

The study of altered functionality and anatomy of the brain in individuals with mental health disorders has been a prevalent practice for many years, with advances in neuroimaging having made significant contributions to the research. While it has been long hypothesized that individuals with major depressive disorders display neurobiological variations compared to their healthy peers, a new study with a large dataset indicates that in many cases the differences observed on imaging are minimal. 

“A key objective in the field of translational psychiatry over the past few decades has been to identify brain biomarkers of major depressive disorder (MDD) to support the development of more effective interventions. Considerable progress has been made toward this aim; however, despite its initial promise, neuroimaging has not been widely translated into clinical practice,” Lianne Schmaal, PhD, from the Center for Youth Mental Health at the University of Melbourne in Australia, wrote in an editorial accompanying the new research. 

Schmaal explained that many studies that have attempted to find the missing link between neuroimaging biomarkers and major depressive disorder lack reproducibility, in part due to small sample sizes, among other things. Schmaal also noted that there is need for more analyses that evaluate the predictive value of these imaging biomarkers. 

This most recent analysis supports that argument. Researchers included data from nearly 2,000 individuals—861 patients and 948 controls. The patients had undergone at least one of multiple neuroimaging exams, including structural MRI, diffusion-tensor imaging, and functional task-based as well as resting-state MRI.  

Using this data, the experts found that the neuroimaging markers explained less than 2% of variances between the patients. On a per-patient level, the accuracy of the biomarkers’ predictive value was consistently less than 56%, regardless of whether the patients’ depression was considered acute or chronic. 

“Results of this case-control study suggest that even for maximum univariate biological differences, deviations between patients with MDD and healthy controls were remarkably small, single-participant prediction was not possible, and similarity between study groups dominated,” the authors explained. 

They went on to suggest that these findings again reveal a greater need for studies that evaluate the predictive value of neuroimaging biomarkers before they can be reliably utilized to personalize treatments. 

The study abstract can be viewed here, and the accompanying editorial can be viewed here.

Hannah murhphy headshot

In addition to her background in journalism, Hannah also has patient-facing experience in clinical settings, having spent more than 12 years working as a registered rad tech. She joined Innovate Healthcare in 2021 and has since put her unique expertise to use in her editorial role with Health Imaging.

Around the web

The two companies aim to improve patient access to high-quality MRI scans by combining their artificial intelligence capabilities.

Positron, a New York-based nuclear imaging company, will now provide Upbeat Cardiology Solutions with advanced PET/CT systems and services. 

The nuclear imaging isotope shortage of molybdenum-99 may be over now that the sidelined reactor is restarting. ASNC's president says PET and new SPECT technologies helped cardiac imaging labs better weather the storm.