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As CDC describes it “ Mental health is a very broad term that encompasses our emotional, psychological and social well-being”
Psychiatric disorders are the major cause of the disturbance of mental health. Mental and addictive disorders were estimated to affect more than a billion people globally. While the scientific community is fighting vigorously against this silent pandemic, there are some fundamental challenges that remain to date.
First & foremost, the way these diseases are categorized is not deemed ’valid’ mainly because the recognized mental disorders are not separated by discrete natural boundaries. These classifications are clinically very useful because they help in understanding the presenting symptoms, determining treatment options, and also to evaluate the outcomes.
Such classifications are in a way a great hindrance to the progress of meaningful valid research in this domain.
This is where “ Radiology” as a field has started playing a major role in influencing the existing diagnostic constructs.
Imaging techniques including the good old MRI and its rather recent derivatives like fMRI(functional MRI), diffusion-tensor imaging, tractography, and perfusion mapping have led to several research works that have led to a rethinking of how these conditions have been viewed and treated.
I will list a few examples:
Schizophrenia, one of the complex and debilitating categories of mental illness with a median population period prevalence of 3.3 per 1000, has consistently demonstrated changes in the left superior temporal gyrus and medial temporal lobe in several voxel-based morphometric studies.
In cases of border personality disorders, which are often not clinically identified, a decrease in white matter integrity in brain regions like the cingulum and fornix has been demonstrated. The feeling of anger in such disorders has shown an association with fractional anisotropy in the cingulum.
As of today, most of these pattern associations rely on the analysis of quantitative imaging data rather than a subjective visual reading of the images. This is where the recent advancements in deep learning-based artificial intelligence techniques have been touted as potential game changers.
And as they say, these are very early days. The future looks very promising!!