Real-world data of non-invasive stimulation of the human insula-prefrontal cortices using deep TMS to treat anxiety for occupational stress and generalized anxiety disorder

Assessments of variability in cortical and subcortical measurements and within-network connectivity of the brain using test-retest data

The evaluation and diagnosis of structural changes in brain caused by disease or treatment over time has become one of the important applications of medical imaging methods, in particular MRI, and it is growing. It is critical to evaluate the reliability of the changes in measurements observed in an individual patient for any clinical decision-making. In this paper, we calculated the repeatability coefficient (RC) as a measure of uncertainty for MRI measurements of subcortical volumes and cortical thickness, and within-network connectivity using test-retest data of 20 healthy subjects. We also evaluated changes in 13 patients who received 20 sessions of transcranial magnetic stimulation as a treatment. The most reliable measure seems to be in the thickness of the left occipital with RC% of 3.5 and the least reliable measure is the brain connectivity within visual network using Yeo's atlas with RC% of 29.4. The most sensitive measure to the percentage of true changes in treated patients is the connectivity within subcortical network of AAL with 76.9%.Clinical Relevance- The results of this study can be useful for evaluating changes in the gray matter structures or functional connectivity of the brain due to a neurological disease such as Alzheimer's or Parkinson's. Also, the obtained results can be used to evaluate the changes caused by any intervention or treatment that may have any positive or negative effect on the brain.