Research at Beth Israel Deaconess Medical Center (BIDMC) has made some promising observations regarding the potential to actually personalize transcranial magnetic stimulation (TMS) therapy for depression. The researchers used an approach inverse to the conventional method, and by doing so were able to use distinct clusters of depressive symptoms to predict clinical improvement in depressed patients.
Traditionally, patients are sub-grouped based on having similar functional network patterns after analyzing brain activity. Following this, therapeutic application is determined and treatment is applied to the patient based on what the corresponding brain targets are for stimulation. So, rather than identifying particular clusters of symptoms, or biotypes, and then looking for ways to treat those distinct biotypes, the researchers tried an opposite approach by actually starting with the desired therapeutic response and correlating that to specific anatomical targets for stimulation. By doing so, this research has begun to pave the way for personalizing TMS therapy and hopefully allowing it to have an even higher success rate among patients with treatment-resistant depression.
What Exactly Did This Study Do and What Made It So Groundbreaking?
This research provided the first instance of distinct symptom clusters responding to distinct treatment targets for patients undergoing TMS therapy.
This recent study provided the first evidence of actually distinguishing between two different clusters of depressive symptoms and subsequently using different anatomical targets for TMS treatment. But what does that actually mean? Essentially, the researchers wanted to take some common symptoms of depression and group them separately based on some of their characteristics. In this study, they identified two clusters: “dysphoric,” which included symptoms like sadness, decreased interest, and suicidality, and “anxiosomatic,” which included symptoms like insomnia, irritability, and sexual disinterest. In a way, these created distinct depression symptom profiles that the researchers could use to apply different treatments.
Because most repetitive transcranial magnetic stimulation (rTMS) studies have focused on targeting a particular brain region called the dorsolateral prefrontal cortex (DLPFC), the researchers in this study were able to identify two separate targets within the left DLPFC that would be relevant for their study. These two cortical targets had been previously associated with clinical improvement of the symptoms involved in each of their described symptom clusters.
Therefore, the researchers formulated this “inverse approach” that we have mentioned. This approach involved actually localizing specific circuits and the corresponding scalp targets (where the electrodes would be placed for the TMS therapy) that relate to the desired post-treatment improvement in those specific symptoms. By doing it this way, the researchers are potentially opening the door to make TMS therapy more personalized to the patient’s symptoms and what exactly needs to be improved.
By using a mapping technique and some previously developed strategies from their own studies, the researchers ultimately created “symptom-response maps.” After applying a clustering algorithm, two symptom-response patterns and the corresponding TMS target sites were identified: dysphoric and anxiosomatic.
This successful identification using this technique was obviously great news for the researchers, and the next step was to take this information and further apply it to TMS therapy.
What Did the Researchers Learn and How Did They Relate It to TMS Therapy?
The researchers were able to construct an atlas for the DLPFC region and use it to make important predictions about symptom response.
After the researchers created their symptom-response maps, they were able to make a TMS target atlas of the DLPFC based on these maps. As a result, they were actually able to use it to accurately predict clinical improvement in a completely separate set of patients by predicting an expected symptom-response ratio that related to where a patient’s brain was stimulated during treatment. On top of that, the researchers demonstrated at a group level that their target maps were able to predict improvement in dysphoric and anxiosomatic symptoms reported in some previous rTMS studies.
It has been known that depression presents very differently among different individuals, which has created complications in determining which treatments are best for depressed patients. Though official diagnostic criteria has been established over time, classifying subtypes of depression based on distinct symptoms has yet to reach a consensus in the field of psychiatry. Furthermore, any previous classifications that have been attempted have failed to actually improve outcomes of treatment. By translating these differences into symptom-specific targets within the brain however, the researchers hope that this will ultimately improve TMS therapy for individuals with treatment-resistant depression.
With TMS therapy being a non-invasive, alternative treatment involving electrical stimulation of specific areas of the brain, it offers a more neurobiological approach to treating depression. In discovering how symptoms can potentially be mapped to specific functional networks in the brain and working backwards based on the desired symptom improvement, this research provides groundbreaking information to apply to the future of guided TMS therapy.
What Are the Potential Limitations of This Research and What Does It Mean For the Future of TMS Therapy For Depression?
These findings are certainly a step in the right direction, and though preliminary, have the potential to greatly improve TMS therapy in the future.
The first limitation that the authors noted regarding their study was the differences in actual brain areas stimulated across different patients. In other words, approximation methods for targeting the DLPFC region tend to vary, especially given that some methods are a bit dated. Due to this, localizing and targeting the DLPFC in different patients tended to result in variable locations for stimulation. These differences in stimulation site could have partly played into the discovery of the two unique symptom-response patterns.
Additionally, this research was done on a relatively small sample size, which always makes it difficult to generalize research findings to an entire population of patients. The other important thing to remember is that this research does not necessarily prove that you can map one particular symptom of depression to one particular area of the brain or one specific brain circuit. Rather, this study found that clusters, or groups, of symptoms correlated to particular target sites.
The good news is, the researchers believe that the success of their mapping technique can potentially be applied to mapping regions of the brain outside of just the DLPFC. Generating atlases that incorporate other regions of interest is important for applying TMS therapy to treatment of symptoms for other psychiatric disorders.
All in all, it appears that in terms of personalizing depression treatment, TMS therapy might be the best candidate. Because research is exploring the ability to target brain regions in a more precise and relevant way, TMS therapy might just be capable of having an even higher success rate.
To summarize, this research provides some preliminary evidence that clinicians may be able to further improve TMS therapy by actually making it more personalized to the patient based on their symptoms. By using various technologies to map symptoms and responses, the researchers began to create atlases that have the potential to accurately predict a patient’s response to TMS treatment. Selecting targets within the brain that correlate to treating a specific set of symptoms definitely provides one possible way that clinicians can start to individualize TMS therapy. This research does not necessarily prove one way or another that there are exact answers for what brain region to target to improve a particular symptom, but it certainly sheds light on how we can continue to explore important relationships and patterns within TMS therapy for depression and other disorders.
