fMRI: Imaging’s Next Frontier

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fmri-autism-new.jpg - fMRI Autism
(a) MR image (left) illustrates anatomic ROIs for A1 and STG. Activation maps (middle and right) demonstrate greater activity within STG, but not A1, in the control group compared with the nonsedated autism group (control > autism alert, middle image) and greater activation within both STG and A1 in the nonsedated compared with the sedated autism group (autism alert > sed, right image). (b, c) Bar charts show (b) spread and (c) amplitude of activation of individual subjects within ROIs (two-sample t tests; ** = P < .01, * = P < .05, with Bonferroni adjustment). sed = sedated.
Source: Radiology 2011;260(2):521-530

Behavioral diagnoses, such as autism and attention-deficit hyperactivity disorder (ADHD), are notoriously complex. Observational protocols are subjective, thus diagnostic accuracy remains questionable. Symptoms and behaviors typically persist for years prior to diagnosis, exacerbating the challenges of the disorders. A number of researchers are exploring the diagnostic potential of fMRI in several disorders. 

Autism: New light, but are rads in the dark?

“We need a medical evaluation for autism,” says Joy Hirsch, PhD, director of the Functional MRI (fMRI) Laboratory at Columbia University in New York City. Currently, parents or caregivers complete a subjective rating scale to inform the diagnosis. The ideal protocol, says Hirsch, entails a medical evaluation that examines the child’s anatomy and physiology and provides a level of certainty that data are consistent with an autism diagnosis.

Structural imaging is not up to snuff, as the structure of the autistic brain is indiscriminable from a healthy brain. However, fMRI may fill the gap. Hirsch and colleagues reported that children with autism were not as responsive to passive auditory stimuli as typical children, in a study published August 2011 in Radiology. Specifically, the researchers quantified reduced BOLD (blood-oxygen-level-dependent) activation within the superior temporal gyrus among autistic children compared with healthy children.

The approach offers numerous advantages. “It takes about five minutes to collect the data and requires very little post-processing,” says Hirsch. Statistical parametric mapping, the post-processing technique, is standard and readily available at U.S. medical centers. However, this early research must be repeated and replicated in a larger sample size to determine its sensitivity.

Another challenge with the use of fMRI to diagnose autism, says Nicholas T. Lange, PhD, director of the neurostatistics laboratory at Harvard Medical School in Boston, is the lack of a biological reference point for the disorder. Imaging data cannot be connected to an established physical scale.

Dyslexia: Early identification

Dyslexia presents similar diagnostic challenges. Currently, children with developmental dyslexia are not diagnosed until after a delay in learning to read, says Nadine Gaab, PhD, assistant professor of pediatrics at Boston Children’s Hospital. “It has long-lasting mental health implications. Children with dyslexia are more likely to have depression and low self-esteem.”

She and her colleagues are attempting to determine if fMRI can be employed to identify children at risk for dyslexia several years earlier. Research has indicated that children with a strong family history of dyslexia showed differences in the junction between the parietal and temporal lobe and the cuneiform gyrus compared with children without a family history of the learning disability.  

Gaab and colleagues are at the mid-point of a five-year project. They have imaged 1,000 pre-reading children with a strong family history of dyslexia. During the screening process, they identified children at behavioral risk for dyslexia. They plan to follow children longitudinally and review fMRI exams of children eventually diagnosed with dyslexia to determine if fMRI data could be used to develop a diagnostic tool.

ADHD: A work in progress

ADHD poses many challenges. One of the most significant is an accurate clinical diagnosis, says Xiabo Li, PhD, assistant professor of radiology at the Albert Einstein College of Medicine in New York City. Diagnostic criteria are behavior-based, which can be subjective. The disorder is both under- and over-diagnosed, according to a study published October 2012 in the Journal of Attention Disorders. Results of the 10-year study of more than 10,000 five to 13-year old children found only 39.5 percent of children taking ADHD medication in South Carolina and 28.3 percent in Oklahoma actually met the case definition of ADHD.

In many cases, the hyperactivity or impulsivity component of ADHD is fairly obvious from a behavioral perspective. In contrast, inattention symptoms are quite diverse and can be confused with symptoms of other co-morbid disorders.

Li believes fMRI could help reduce the uncertainty and offer a reliable imaging marker for the disorder to provide an earlier, more definitive diagnosis. She has leveraged fMRI to compare the patterns the brain uses to handle attention tasks in healthy children and compare these with children with