Biomedical Engineering Reference
In-Depth Information
[46, 47], it was reported that the neurons in the inferior olive were large in young
autistic individuals (9-12 years of age), whereas these neurons were small and
pale in older cases (
>
22 years). More recently, Bailey et al. [35] have reported
olivary abnormalities in five autistic patients.
According to these reviewed studies, different anatomical structures of the
brain have been identified as being involved in the abnormal neurodevelopment
associated with autism. Classic MRI structural findings are consistent with respect
to some brain structures, while observations with respect to other structures have
differed among studies. This lack of consistency may be due, at least in part,
to the unavailability of larger sample sizes and closely matched control groups.
The failure to account for significant confounding factors (e.g., age, sex, IQ, so-
cioeconomic status, mental retardation, handedness) may also play a major role
in causing these uncertainties and inconsistencies. The reported structural MRI
findings, on the other hand, cannot be directly correlated to the neuropathological
findings in autism. However, several important and consistently replicated results
suggest an elevated brain volume in autism, particularly in young children. Other
regions of the brain were identified, perhaps with less certainty, as being directly
involved in the abnormal neurodevelopment associated with autism, particularly
the white matter and the CC.
Consequently, more studies are needed to narrow the gap between the neu-
roimaging and neuropathological researches in autism. Challenges for future stud-
ies also include an understanding of how the brain grows and changes over time
in autism, and how these changes are related to clinical manifestations and im-
pairments. Longitudinal studies are hence necessary to track the course of brain
development in autism. In addition, autism may benefit a great deal from the new
imaging modalities such as diffusion tensor imaging (DT-MRI). This imaging
modality offers a good opportunity to learn about white matter in autism. Some
studies that use DT-MRI to probe white matter differences in several developmen-
tal disorders including autism have already been published, as mentioned above
(e.g., see [29] for DT-MRI use in autism).
It is worth noting at this point that it remains unclear as to whether the inter-
connectivity findings are the cause of autism or its result.
Our Contributions
In this work, we aim at using the reported abnormalities in some brain regions
in order to devise a way that permits the classification of autistic vs. normal subjects
by analyzing their respective magnetic resonance images (MRIs). To overcome
the limitations and shortcomings of the volumetric studies, we base our analyzes
on shape descriptions and geometric models. We focus on analysis of the WM
and the CC since these two brain structures were extensively studied and have
been shown to provide coherent discriminatory measurements between autistic
and normal subjects.
