MRI, brain differences, and autism

MRI: Sagittal view of the brain. Photo courtesy of Wikipedia commons.

You may have read the news reports blaring the finding of an “autism test” that could lead to early and definitive diagnosis of autism. The new evaluation, which has proved worthy of its own name, the Lange-Lainhart test, uses magnetic resonance imaging (MRI) techniques to image brain areas to detect changes associated with autism.

I’ve been unable to find the complete paper, reported to have been published in Autism Research on Nov. 29; the journal has only papers through October available on its Website as of this writing. According to reports, however, the authors state that the new test was 94% accurate in identifying who was autistic and who wasn’t among 60 males tested. The participants in the study were ages  8 to 26; 30 were diagnosed with what the researchers call “high-functioning autism,” and 30 were typically developing.

The imaging technique the authors used involves tracing water diffusion along axons, the long connectors that link neurons to other neurons or tissues. This diffusion tensor imaging process yields an image that can highlight variations in the patterns of these connective pathways in different areas of the brain. This study focused on six brain areas associated with language, social, and emotional functioning, all of which are traditionally considered to be problematic among people with autism.

In the brains of non-autistic participants, the flow patterns were organized in a typical way that indicated connectivity among the brain regions. In the participants diagnosed with high-functioning autism, the flow was disorganized in a pattern common to the autistic group, indicating less connectivity and interaction and thus less exchange of information in the network. The researchers repeated the test on another, smaller set of participants, 12 with autism and 7 without, and produced similar results.

These findings imply that autistic brains may operate like a set of computer hardware components that cannot communicate very well with each other while still functioning perfectly well separately. There may be camera that captures a visual image without trouble or a microphone that captures a voice clearly, but the system lacks the network necessary to integrate the two inputs into a unified perception.

The news reports I’ve read on the study make a big deal out the prospect that this imaging breakthrough could lead to earlier diagnosis of autism, something that most experts believe is key to ameliorating some of its negative manifestations. But experts also urge the standard cautious optimism, and rightfully so.

For one thing, the participants in this study were ages 8 to 26, not within the time frame for early diagnosis of autism, and all of them were male. The study findings can’t tell us whether their brains present with these differences as a result of developing with autism, or whether they have autism because their brains are built this way. Before there can be talk of “early diagnosis” and linking these changes to manifestations of autism, we’d need studies showing these differences in much younger children. Further, given the frequent findings of differences between males and females on the spectrum, investigations involving autistic girls and women are necessary.

This study is not the first to use imaging to identify distinctions between autistic and non-autistic people. Other studies have also done so, finding pattern variations in the neuronal tracts of children with autism compared to children without it, in critical areas relevant to the clinical symptoms of autism.

While I find these results intriguing, I note one thing that no one seems to have commented on. In the reports I’ve read about this study, the researchers observe that currently, the only way to diagnose autism is based on a symptom checklist, questionnaires, screenings, and so on—any autism parents reading this will know that drill—and the ultimate call relies on the expertise of the medical professional conducting the evaluations. The implication of these comments is that we need some better, more unequivocal, less-subjective methods of identifying autistic people.

Yet, presumably the autistic boys and men they used for this study were diagnosed using just such subjective evaluation, and their autism diagnoses appear to have been confirmed in 94% of cases by similarities of MRI findings. In my mind, this outcome suggests that the process of subjective evaluation seems to be working pretty well. Of course, we’re a visual species and like our decisions to be given literally in black and white. Such MRI results may fulfill a need that has less to do with correct outcomes than it does with a dose of visual confirmation–and satisfaction.

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