Unlike in other fields where biopsy, while invasive, can often be conducted in a relatively low-risk outpatient procedure, clinicians would typically only consider a brain biopsy in extraordinary circumstances. As such, psychiatry, perhaps more than any other field of medicine, stands to benefit from improvements in non-invasive diagnostic and monitoring methods.
Compared to other areas of specialty, we still understand relatively little about the fundamental pathophysiology of mental illnesses. In fact, a major criticism of the DSM-5-TR, the current gold-standard reference used to inform mental health diagnoses, is that it focuses almost exclusively on symptoms as diagnostic criteria with little to no mention of underlying biological causes, except perhaps when evaluating a differential diagnosis .
We acknowledge that mental illness is incredibly complex, and many institutions worldwide are dedicating significant resources to understanding more about the brain and behavior.
At Gradient Health, we believe that computer vision and machine learning in medical imaging holds potential to provide mental health researchers and clinicians with much-needed insights into the biological mechanisms underlying mental illness and recovery.
Precision Medicine to Improve Patient Outcomes.
The Precision Medicine Initiative, launched in the US in 2015, aims to “pioneer a new model of patient-powered research that promises to accelerate biomedical discoveries and provide clinicians with new tools, knowledge, and therapies to select which treatments will work best for which patients” .
In the years since, much progress has been made, in particular in the application of precision medicine in oncology, where genetic testing of biopsied tissue and medical imaging is increasingly used in the diagnosis and monitoring of cancer and the development and study of targeted therapies. However, other areas of medicine, such as psychiatry, are perhaps not as advanced in terms of tapping the potential of precision medicine to improve outcomes for patients.
Below, we explore an example that highlights the importance of identifying the underlying biological cause of behavioral changes and disturbances in order to select the most effective treatment.
Similar Symptoms, Different Causes, Different Treatments.
Understanding the etiology of disordered eating is crucial in distinguishing PANDAS (Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections) from typical ARFID (Avoidant/Restrictive Food Intake Disorder), as the treatments for these conditions differ significantly .
In rare cases in PANDAS, disordered eating may arise due to an autoimmune response triggered by a streptococcal infection, which affects the basal ganglia in the brain, leading to sudden onset food restrictions and other neuropsychiatric symptoms. On the other hand, ARFID is typically a standalone eating disorder unrelated to an autoimmune response. Accurate identification of the underlying cause is essential to provide the most effective treatment.
For PANDAS, immunomodulatory therapies, such as intravenous immunoglobulin or corticosteroids, may be required to target the autoimmune component, while ARFID may necessitate behavioral interventions and nutritional rehabilitation.
Without an accurate assessment of the biological cause of presentation with disordered eating, children with PANDAS may be exclusively treated with Cognitive-Behavioral Therapy and Exposure and Response Therapy without addressing the underlying autoimmune response and thus would likely not achieve full resolution of their distressing condition.
The role of medical imaging in developing and delivering Precision Psychiatry.
Imaging biomarkers refer to quantifiable indicators obtained through non-invasive medical imaging techniques, such as magnetic resonance imaging (MRI) or positron emission tomography (PET) . These biomarkers have the potential to revolutionize precision psychiatry by providing objective, biological measures of mental health conditions.
By identifying specific changes in brain structure, function, or neurochemistry associated with a particular psychiatric disorder, imaging biomarkers can help improve diagnostic accuracy and aid in monitoring treatment efficacy and predicting patient outcomes. The development and validation of imaging biomarkers in psychiatry holds significant promise for overcoming the current limitations of symptom-based diagnostic criteria, ultimately advancing our understanding of mental illnesses and enhancing patient care.
At Gradient Health, we are proud to provide innovators with the curated data they need in their pursuit of making precision medicine a reality in both research and routine care, and look forward to seeing the application of this technology to improving patient outcomes.
- T. R. Insel et al., “Research Domain Criteria (RDoC): Toward a New Classification Framework for Research on Mental Disorders,” American Journal of Psychiatry, vol. 167, no. 7, pp. 748–751, Jul. 2010, doi: 10.1176/appi.ajp.2010.09091379.
- “FACT SHEET: President Obama’s Precision Medicine Initiative,” whitehouse.gov, Jun. 29, 2015. https://obamawhitehouse.archives.gov/the-press-office/2015/01/30/fact-sheet-president-obama-s-precision-medicine-initiative
- G. True, “PANS & Eating Disorder/Food Restrictions & Toolkits/Handouts,” Aspire, Feb. 2022, [Online]. Available: https://aspire.care/families-parents-caregivers/pans-eating-disorder-food-restrictions/
- J. W. Prescott, “Quantitative Imaging Biomarkers: The Application of Advanced Image Processing and Analysis to Clinical and Preclinical Decision Making,” Journal of Digital Imaging, vol. 26, no. 1, pp. 97–108, Mar. 2012, doi: 10.1007/s10278-012-9465-7.