Evaluating Brain Regions That Characterize Attention Deficit/Hyperactivity Disorder Based on SPECT Images and Machine Learning Models

Abstract

Like other neurodevelopmental disorders, ADHD (attention deficit/hyperactivity disorder) typically manifests in preschool-aged children and results in impairments in an individual's personal, social, academic, or occupational functioning. According to the Diagnostic and Statistical Manual of Mental Disorders-V, there is no biological characteristic that is fundamental to the definition of ADHD diagnosis. However, several studies have already proposed neurobiological basis that demonstrate abnormalities in brain perfusion in different areas of the brain of an ADHD patient, but without consensus. For this reason, the aim of this study is to evaluate images of the brain SPECT (Single Photon Emission Computed Tomography) to assess whether there are brain regions that are more promising than others for ADHD diagnosis. Among the different brain regions analyzed, the one that has achieved the best accuracy in classifying ADHD is the frontal cortex with an accuracy of 80% in predicting ADHD.