Structural Neuroimaging Predictors of Benefits from Pivotal Response Treatment

Thursday, May 11, 2017: 12:00 PM-1:40 PM
Golden Gate Ballroom (Marriott Marquis Hotel)
J. P. Hegarty1, G. W. Gengoux2, J. M. Phillips2, S. Tanaka2, T. W. Frazier3, A. L. Reiss2 and A. Y. Hardan2, (1)Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, (2)Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, (3)Cleveland Clinic Center for Autism, Cleveland, OH
Background: Autism spectrum disorder (ASD) is a heterogeneous disorder and several neurobiologic measures have been examined to identify potential subgroups, with limited success thus far. Applying neuroimaging methodologies to identify prognostic markers or indicators of treatment response may be an alternative approach to address this heterogeneity. To date, no biomarker of treatment response has been identified for any biological or behavioral intervention in autism. Additionally, there is a growing need for innovative, efficient, cost-­effective treatment models guided by biological markers of treatment response to optimize results and long­term outcome. This is particularly true for very young children with ASD when the brain is most plastic and time should not be wasted in implementing treatments that might not be beneficial.

Objectives: The goal of this investigation is to use a hypothesis­-generating approach and apply multimodal imaging techniques to help identify biomarkers of treatment response. In this investigation, we aim at applying structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) to identify biomarkers of pivotal response training (PRT) treatment response. The development of biosignatures of treatment response is critical and the present study is the first step in providing evidence supporting the possibility of identifying biomarkers to predict response to behaviorally­ and biologically-­based treatments.

Methods: The PRT intervention consisted of teaching parents behavioral techniques to facilitate language development. PRT training lasted at least 12 consecutive weeks with one session per week. Sessions included in­ vivo coaching of parent implementation of PRT techniques with their child, as well as review and feedback on videos of parents practicing PRT at home. Objective and subjective outcome measures were obtained at baseline and at the end of treatment. High­ resolution anatomical MRI and DTI scans are being obtained on children with ASD before and after their participation in PRT. Correlations between neuroimaging measures (volume and surface) and fractional anisotropy (FA)) in language areas (e.g. superior longitudinal fasciculus(SLF)) and changes in outcome measures were examined.

Results:  Eighteen children with ASD have participated in this study to date. Anatomical MRI and DTI scans have been obtained on all individuals at baseline (prior to treatment). Five follow­up scans (post ­treatment) have successfully been collected. Neuroimaging and treatment data are available on 8 participants as the additional scans and behavioral information are being processed. A relationship between the volume (n=8; rs= -0.81, p= 0.015) and surface area (n=8; rs= -0.82, p= 0.013) of the inferior frontal gyrus, which contains Broca’s area, were significantly associated with changes in the number of utterances as assessed during structured laboratory observation (Figure 1). Cortical thickness was also associated with expressive communication (n=7; rs= -0.88, p= 0.008) as assessed with PLS-5. Associations between FA in the SLF and changes in several language measures were observed including the number of utterances during structured laboratory observation and number of words produced out of 396 on the MacArthur­Bates Communicative Development Inventories.

Conclusions:  Preliminary findings from this pilot study suggest that neuroimaging measures are potentially useful as predictors of treatment response. Additional analyses will be completed as more data become available. We will discuss these findings and highlight the advantages and challenges of using neuroimaging information in clinic trials to assess treatment response and biologic changes due to the intervention.