Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder affecting the patient’s performance in academic, social and emotional situations. Traditional methods for diagnosing this condition are based on behavioural evaluations which can lead to controversial diagnoses.
A new study, published in the journal Radiology, led by a research team from the West China Hospital, set out to develop classification models which could allow for the accurate diagnosis of ADHD based on neurological features. Furthermore, the authors set out to be able to further distinguish different subtypes of ADHD using the same classification system.
Separating the ADHD from non-ADHD patients
So how did they do this? The research team used Radiomics, which allows digital Magnetic Resonance Images (MRI) to be converted into datasets from which the necessary information can be gathered.
By doing this the authors were able to identify cerebral features which were specific to ADHD patients as well as the separate sub-groups ADHD-C and ADHD-I. The study compared the MRI scans of 83 ADHD diagnosed children and 87 healthy individuals.
The researchers were able to conclude that ADHD diagnosed patients could be separated from healthy individuals with 74% accuracy. They were also able to distinguish patients diagnosed with the two ADHD sub-types based on their MRIs with 80% accuracy.
This research displays the potential for the development of clinical diagnostic methods using MRIs to diagnose ADHD. This research also adds valuable information about the neurological features associated with this common disorder which may add valuable information for use in future research.
Sun H, Chen Y, Huang Q, Lui S, Huang X, Shi Y, Xu X, Sweeney JA, Gong Q, 2017. Psychoradiologic utility of MR imaging for diagnosis of Attention Deficit Hyperactivity Disorder: a radiomics analysis. Radiology