Depressive disorders are potentially debilitating conditions that can have a profound negative impact on a person’s physical, psychological, and socioeconomic well-being.
The good news about depression is that it is treatable. When a person who has depression receives appropriate clinical care – which typically involves a combination of therapy and medication – they can achieve improved health and better overall quality of life.
The bad news about depression treatment is that it doesn’t always work. Experts estimate that as many as one-third of people who get professional help for depression don’t have successful outcomes. Many of these individuals have what mental health professionals refer to as treatment-resistant depression.
Nontraditional services such as transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), and ketamine treatment have proved to be extremely beneficial for some people who have treatment-resistant depression. But millions of others continue to suffer.
To complement the clinical efforts that have been devoted to diagnosing and treating this disorder, some experts have turned to neuroimaging for additional insights. In recent years, several studies have used EEGs, MRIs, and a host of additional technologies in an attempt to identify common structural and/or functional characteristics in the brains of people who have treatment-resistant depression.
What Is Treatment-Resistant Depression?
At first glance, the term “treatment-resistant depression” appears to be a straightforward, easily understood descriptor. If someone has depression, and they don’t respond to treatment, they must have treatment-resistant depression, right?
Mental health experts have not yet established a universally agreed-upon definition of treatment-resistant depression. However, among the various parameters that clinicians are using to describe this disorder, two primary characteristics have emerged:
- The “depression” part of treatment-resistant depression typically refers to people who have major depressive disorder (MDD). This type of depression is characterized by severe symptoms that last for at least two weeks and impair a person’s ability to function in one or more important areas of life.
- The “treatment-resistant” part of the term usually means that a person has taken at least two different types of antidepressant medications for an appropriate amount of time as directed by a qualified professional, but has not experienced an easing of symptoms.
As described in a January 2020 review in the journal Neuropsychiatric Disease and Treatment, several mental health experts have proposed other criteria for treatment-resistant depression, such as:
- No response after taking one antidepressant for a period of six to eight weeks
- Lack of improvement after receiving electroconvulsive therapy
- Inadequate response after taking optimized doses of prescription medications and receiving ECT
Other attempts to define this disorder are more complex. In 2017, Abebaw Fekadu, Jacek G. Donocik, and Anthony J. Cleare outlined a multidimensional model for identifying treatment-resistant depression. This approach, which is called the Maudsley Staging Method (MSM), scores patients on the severity of their symptoms, the duration of their depressive episodes, and their response to various types of treatment.
The professional back-and-forth over treatment-resistant depression has also involved terminology.
For example, the definition of an “adequate” response to medication can vary considerably from one clinician to the next. Additionally, as the authors of the Neuropsychiatric Disease and Treatment review reported, some professionals have suggested referring to this condition as “difficult-to-treat depression” instead of treatment-resistant depression.
With the standards for diagnosing treatment-resistant depression not yet settled, could neuroimaging provide the conclusive data that ends the debate?
What Is Neuroimaging?
Neuroimaging uses several technologies and techniques to create pictures of how the brain is structured and how it works. To create these images, professionals may use electroencephalograms (EEGs), diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), magnetic resonance imaging (MRI), positron emission topography (PET), and computerized tomography (CT).
Boadie W. Dunlop, MD, and Helen S. Mayberg, MD, discussed these approaches and other aspects of using neuroimaging to classify depression in an article that was published in the November-December 2017 edition of the journal Cerebellum.
Here is how they described some of the many ways that various neuroimaging technologies have been used to research depression and other mood disorders:
- MRI and CT scans create static images that can help researchers identify the size and/or volume of certain areas of the brain.
- Functional MRIs (fMRIs) and PET scans can detect brain activity through changes in regional blood flow or energy metabolism
- A DTI can examine white matter tracts that are responsible for connecting brain regions.
- MRS can identify variances in chemical composition among different regions of the brain.
Neuroimaging has not yet proved to be an effective means of differentiating the brains of healthy individuals from those who have depression, Dunlop and Mayberg wrote. But they believe that this approach shows great promise for identifying subtypes of depression and different types of mood disorders.
The researchers described three approaches that researchers have taken in an attempt to accomplish this:
- Examining people who have subtypes of depression such as psychotic, melancholic, or atypical, and trying to identify correlating features through neuroimaging
- Attempting to identify reactivity patterns in the brain while subjects are focused on cognitive or emotional stimuli
- Employing machine learning to find connectivity or reactivity patterns in neuroimages, then using these patterns to group patients for further study, which could lead to the identification of previously undefined subtypes of depression
Dunlop and Mayberg also discussed a potential fourth approach: Linking patients’ treatment outcomes with neuroimaging data that was collected before they began treatment. The goal, they explained, would be to identify characteristics that correlate with various outcomes, then use this information to try to predict treatment outcomes of new patients.
While identifying disorders or subtypes is one of the more promising potential uses of neuroimaging, the researchers noted that this is not the only contribution that neurobiology can make. Advances in this field may also lead to improvements in how depression, bipolar disorder, and similar conditions are treated, they asserted.
“Approaches that characterize brain states responsive to specific interventions offer the possibility of advancing further, past the current trial-and-error, algorithm-based application of psychotherapy, medication, and brain stimulation to a personalized psychiatry that can choose the treatment most likely to benefit the individual patient,” they wrote.
Can Neuroimaging Help to Define Treatment-Resistant Depression?
In January 2022, the journal Neuroscience and Biobehavioral Reviews published a systematic review of studies related to the neurobiology of treatment-resistant depression.
In their introduction, the authors of this review noted the following:
- Research indicates that one-third of patients who develop major depressive disorder continue to struggle with the symptoms of this condition after receiving four different antidepressants.
- Studies suggest that several areas of the brain – including the prefrontal cortex (PFC), anterior cingulate cortex (ACC), amygdala, insula, hippocampus, salience network, and default mode network (DMN) – may play a role in treatment-resistant depression.
After reviewing 29 studies on the neurobiology of depression that had been published in international peer-reviewed journals, the team determined that alterations in the default mode network appear to be significant differentiators between treatment-resistant and treatment-responsive depression.
The default mode network is a group of interconnected areas of the brain that exhibit lower activity when people are concentrating on tasks or engaged with external stimuli, and higher levels of activity when people are in a state of rest and not focused on the world around them
The team found that brain scans of people with treatment-resistant depression were more likely to reveal the following neurobiological characteristics:
- Reduced functional connectivity within the default mode network
- Reduced functional connectivity between parts of the default mode network and other areas of the brain
- Hyperactivity within default mode network regions
- Aberrant activity and functional connectivity in the occipital lobe
The findings of this review suggest that [treatment-resistant depression] may be an MDD-subtype with its own characteristic neurobiological features, of which dysfunction of the [default mode network] may be the most notable,” wrote the review team’s lead author, Nora Runa of the University of Amsterdam’s Department of Psychiatry.
“However, the question remains whether these impairments are specific to [treatment-resistant depression] or whether they are a more severe version of the impairments present in the general MDD population,” Runa added.