Multicomponent Relaxometry in Autism Spectrum Disorder: Preliminary Insights

Saturday, May 14, 2016: 11:30 AM-1:30 PM
Hall A (Baltimore Convention Center)
D. C. Dean1, A. Freeman1, D. P. Samsin1, S. Kecskemeti1, N. Matsunami2, M. Leppert2, N. Lange3, J. E. Lainhart1 and A. L. Alexander1, (1)Waisman Center, University of Wisconsin-Madison, Madison, WI, (2)University of Utah, Salt Lake City, UT, (3)McLean Hospital, Cambridge, MA
Background: Important to white matter and the establishment of brain connectivity is myelin. It is accepted that normal brain function relies on rapid and coordinated brain messaging afforded by myelinated axons, while recent studies have suggested that autism spectrum disorder (ASD) is associated with alterations to white matter (for review, see Travers et al., 2012). While several neuroimaging techniques that are sensitive to changes in myelin have been used to study white matter in ASD, these neuroimaging techniques are inherently non-specific to changes in myelin content. Multi-component analysis of relaxation time data, also termed multi-component relaxometry, may provide a more sensitive measure of myelin content through measurement of myelin water fraction (MWF; Alexander et al. 2011). The study of brain’s myleoarchitecture using MCR may thus provide important new insights into the neurological substrates of ASD and illuminate key brain regions involved in the development and onset of ASD.

Objectives: We examined the extent to which the underlying white matter microstructure, as measured by relaxometry and multicomponent relaxometry measures, compared in a small sample of ASD and typically developing (TD) individuals. Specifically, we compared quantitative R1 relaxation rates, R2 relaxation rates, and MWF in these individuals.

Methods: MRI Acquisition: Participants for this study consisted of 22 individuals between 10 and 42 years of age, 14 of which were diagnosed with ASD.  Magnetic resonance imaging (MRI) data were acquired from each participant using a 32 channel head RF coil on a 3.0 Tesla GE MR750 scanner. Multiple flip-angle spoiled gradient echo (SPGR) and balanced steady-state free precession (bSSFP) images were acquired and mcDESPOT post-processing (Deoni et al. 2013) was used to calculate R1 (1/T1), R2 (1/T2), and MWF parameter maps. Images were subsequently non-linearly registered to the MNI template using the Advanced Normalization Tools (ANTS) software. Voxelwise linear regressions, corrected for multiple comparisons using the FDR, examined differences between ASD and TD groups, while co-varying for age.   

Results: No significant age differences were observed between the two groups (p=0.67). MWF was found to be significantly (p<0.05, FDR corrected) reduced in the genu of the corpus callosum in the ASD group compared to the TD group (Fig. 1A). R2 was also observed to be reduced in smaller clusters near the thalamus and pontine crossing tract of the brain stem (Fig. 1B). R1 was not observed to significantly differ between the groups.

Conclusions:  Our preliminary findings suggest that, within this small sample, the ASD group has reduced MWF in genu of the corpus callosum, compared to the TD group, while also having reduced R2 near the thalamus and brain stem. These findings agree well with the current literature that describes alterations of white matter microstructure associated with ASD while also suggesting the possibility of that these white matter alterations may result from atypical myelin content. While these findings are promising, it is important to note that the small sample size of the current study limits our ability to interpret these findings. Future analyses will extend these characteristics in a larger sample of individuals.