3D Computational Approach to Morphological Brain Abnormalities in Autism
Date
4-10-2021
Location
Online
Description
Autism Spectrum Disorder (ASD) is defined as an idiopathic lifelong neurodevelopmental disorder that develops in early childhood. Its prevalence is broad, yet its nature remains elusive. This research describes a project related to the construction of computational phantoms, including brain structures for use in radiological, therapeutic, and diagnostic capacities. Three computational brain phantoms corresponding to two pediatric ASD patients and one control patient were constructed using magnetic resonance imaging (MRI). Twelve structures, four from each patient, were outlined from MRI sets via 3DSlicer segmentation software and were imported to 3D modeling software Rhinoceros for geometric manipulation and analysis. Rhinoceros enabled conversion of the segmentation into a non-uniform rational basis spline (NURBS) surface phantom. These phantoms can be used to study optimization of image quality and radiation dose for patients with ASD who have unique neuro-morphology. Given the wide neurological, behavioral, and morphological variations in patients with autism, individualized treatment plans involving an accurate, representative computational model are valuable. The aim is to develop a repository of data collected from these phantoms into a comprehensive dosimetry database. This novel set of computational brain models present details that are crucial during radiation dose evaluation for ASD patients enduring diagnostic imaging or radiotherapy.
Presentation Type
Presentation
3D Computational Approach to Morphological Brain Abnormalities in Autism
Online
Autism Spectrum Disorder (ASD) is defined as an idiopathic lifelong neurodevelopmental disorder that develops in early childhood. Its prevalence is broad, yet its nature remains elusive. This research describes a project related to the construction of computational phantoms, including brain structures for use in radiological, therapeutic, and diagnostic capacities. Three computational brain phantoms corresponding to two pediatric ASD patients and one control patient were constructed using magnetic resonance imaging (MRI). Twelve structures, four from each patient, were outlined from MRI sets via 3DSlicer segmentation software and were imported to 3D modeling software Rhinoceros for geometric manipulation and analysis. Rhinoceros enabled conversion of the segmentation into a non-uniform rational basis spline (NURBS) surface phantom. These phantoms can be used to study optimization of image quality and radiation dose for patients with ASD who have unique neuro-morphology. Given the wide neurological, behavioral, and morphological variations in patients with autism, individualized treatment plans involving an accurate, representative computational model are valuable. The aim is to develop a repository of data collected from these phantoms into a comprehensive dosimetry database. This novel set of computational brain models present details that are crucial during radiation dose evaluation for ASD patients enduring diagnostic imaging or radiotherapy.