Connor Benjamin Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Peter Timms European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.
The investigation of neuroimaging methods as prediction tools has been prompted by the search to improve the treatment results of obsessive-compulsive disorder (OCD), a complicated mental health illness. The development and promise of neuroimaging indicators in predicting treatment response are summarized in this abstract. OCD, which is characterized by upsetting obsessions and repeated behaviors, shows a range of reactions to therapies, calling for customized strategies. The structure, connections, and neurochemistry of the brain may be studied using neuroimaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI, diffusion tensor imaging (DTI), positron emission tomography (PET), and magnetic resonance spectroscopy (MRS). Potential prognostic indicators include aberrant patterns discovered by fMRI, changed brain areas shown by structural MRI, and disturbed white matter connections discovered by DTI. Serotonin abnormalities, particularly those shown by PET and MRS, provide a biological component to prediction. Predictive models are developing as a result of fusing these insights with machine learning and combining various data to improve the accuracy of treatment estimates. Complexity of the disorder, the requirement for standardized protocols, and the integration of diverse data sources are obstacles, nevertheless. In spite of obstacles, the convergence of neuroimaging and OCD therapy prediction offers personalized therapies, less suffering, and enhanced quality of life. The possibility of a paradigm change in psychiatric treatment is becoming more apparent as this field develops.
Keywords:neuroimaging markers (NM), Predicting treatment response (PTR), obsessive-compulsive disorder (OCD), E-views Software