Faculty Bibliography

BACKGROUND:Autism spectrum disorder (ASD) is highly heritable and phenotypically variable. Neuroimaging markers reflecting variation in behavior will provide insights into circuitry subserving core features. We examined functional correlates of ASD symptomology at school-age, while accounting for associated behavioral and cognitive domains, in a longitudinal sample followed from infancy and enriched for those with a genetic liability for ASD. METHODS:Resting state functional connectivity MRIs (fcMRI) and behavioral data were analyzed from 97 school-age children (8.1-12.0 years, 55 males, 15 ASD) with (n = 63) or without (n = 34) a family history of ASD. fcMRI enrichment analysis (EA) was used to screen for associations between network-level functional connectivity and six behaviors of interest in a data-driven manner: social affect, restricted and repetitive behavior (RRB), generalized anxiety, inattention, motor coordination, and matrix reasoning. RESULTS:Functional connectivity between the visual and salience networks was significantly associated with social affect symptoms at school-age after accounting for all other behaviors. Results indicated that stronger connectivity was associated with higher social affect scores. No other behaviors were robustly associated with functional connectivity, though trends were observed between visual-salience connectivity and RRBs. CONCLUSIONS:Connectivity between the visual and salience networks may play an important role in social affect symptom variability among children with ASD and those with genetic liability for ASD. These findings align with and extend earlier reports in this sample of the central role of the visual system during infancy in ASD.

Mass univariate testing on functional connectivity MRI (fcMRI) data is limited by difficulties achieving experiment-wide significance. Recent work addressing this problem has used enrichment analysis, which aggregates univariate screening statistics for a set of variables into a single enrichment statistic. There have been promising results using this method to explore fcMRI-behavior associations. However, there has not yet been a rigorous examination of the statistical properties of enrichment analysis when applied to fcMRI data. Establishing power for fcMRI enrichment analysis will be important for future neuropsychiatric and cognitive neuroscience study designs that plan to include this method. Here, we use realistic simulation methods, which mimic the covariance structure of fcMRI data, to examine the false positive rate and statistical power of one technique for enrichment analysis, over-representation analysis. We find it can attain high power even for moderate effects and sample sizes, and it strongly outperforms univariate analysis. The false positive rate associated with permutation testing is robust.

IMPORTANCE/UNASSIGNED:Down syndrome, resulting from trisomy 21, is the most prevalent chromosomal disorder and a leading cause of intellectual disability. Despite its significant impact on brain development, research on the white matter microstructure in infants with Down syndrome remains limited. OBJECTIVE/UNASSIGNED:To investigate early white matter microstructure in infants with Down syndrome using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). DESIGN/UNASSIGNED:Infants were recruited and scanned between March 2019 and May 2024 as participants in prospective studies conducted by the Infant Brain Imaging Study (IBIS) Network. Data were analyzed in October 2024. SETTING/UNASSIGNED:Data collection occurred at five research centers in Minnesota, Missouri, North Carolina, Pennsylvania, and Washington. PARTICIPANTS/UNASSIGNED:Down syndrome and control infants were scanned at 6 months of age. Control infants had no Down syndrome diagnosis and either had a typically developing older sibling or, if they had an older sibling with autism, were confirmed not to meet clinical best estimate criteria for an autism diagnosis. EXPOSURE/UNASSIGNED:Diagnosis of Down syndrome. MAIN OUTCOMES AND MEASURES/UNASSIGNED:The outcome of interest was white matter microstructure quantified using DTI and NODDI measures. RESULTS/UNASSIGNED:A total of 49 Down syndrome (28 [57.14%] female) and 37 control (18 [48.65%] female) infants were included. Infants with Down syndrome showed significant reductions in fractional anisotropy and neurite density index across multiple association tracts, particularly in the inferior fronto-occipital fasciculus and superior longitudinal fasciculus II, consistent with reduced structural integrity and neurite density. These tracts also demonstrated increased radial diffusivity, suggesting delayed myelination. The inferior fronto-occipital fasciculus and uncinate fasciculus exhibited increased neurite dispersion and fanning in Down syndrome infants, reflected by elevated orientation dispersion index. Notably, the optic tracts in Down syndrome infants exhibited a distinct pattern of elevated fractional anisotropy and axial diffusivity, and lower radial diffusivity and orientation dispersion index, suggesting an early maturation of these pathways. CONCLUSIONS AND RELEVANCE/UNASSIGNED:This first characterization of white matter microstructure in Down syndrome infants reveals widespread white matter developmental delays. These findings provide new insights into the early neurodevelopment of Down syndrome and may inform early therapeutic interventions.

OBJECTIVE:Real-time imaging is useful for the evaluation of wrist instability. However, currently available real-time magnetic resonance imaging (MRI) methods are limited due to their 2D nature or provide insufficient temporal resolution and image quality for quantitative kinematic analysis. This work introduces a novel approach for volumetric dynamic MRI of the wrist joint during active motion and demonstrates the feasibility of tracking carpal bone motion. MATERIALS AND METHODS/METHODS:A flexible 8-element 3 T wrist receive coil and 3D-printed support platform for guiding motion were designed for dynamic wrist imaging. 2D real-time images were acquired using a fat-saturated FLASH sequence with radial sampling and reconstructed with the GRASP algorithm. Corresponding volumetric dynamic wrist images were obtained by assembling 2D real-time images into 3D snapshots using autodetected MRI-visible markers for slice alignment. The proposed method was demonstrated for radial-ulnar deviation on five healthy volunteers. RESULTS:The flexible wrist coil provided high SNR while allowing a wide range of wrist movements. 2D real-time wrist images were acquired with a temporal resolution of 48 ms/frame with negligible streaking artifacts. Carpal bones and metacarpal bones were properly aligned in the assembled dynamic volumes for all five subjects. The excellent bone-to-tissue contrast enabled accurate segmentation of the individual carpal bones on the assembled dynamic volumes. CONCLUSION/CONCLUSIONS:This work introduces a novel wrist coil and demonstrates that real-time volumetric dynamic examination of the moving wrist is feasible. The achieved image quality and high temporal resolution could enable automatic segmentation of carpal bones and quantitative kinematic assessment for evaluating wrist instability.

White matter (WM) fiber tract differences are present in autism spectrum disorder (ASD) and could be important markers of behavior. One of the earliest phenotypic differences in ASD are language atypicalities. Although language has been linked to WM in typical development, no work has evaluated this association in early ASD. Participants came from the Infant Brain Imaging Study and included 321 infant siblings of children with ASD at high likelihood (HL) for developing ASD; 70 HL infants were later diagnosed with ASD (HL-ASD), and 251 HL infants were not diagnosed with ASD (HL-Neg). A control sample of 140 low likelihood infants not diagnosed with ASD (LL-Neg) were also included. Infants contributed expressive language, receptive language, and diffusion tensor imaging data at 6-, 12-, and 24 months. Mixed effects regression models were conducted to evaluate associations between WM and language trajectories. Trajectories of microstructural changes in the right arcuate fasciculus were associated with expressive language development. HL-ASD infants demonstrated a different developmental pattern compared to the HL-Neg and LL-Neg groups, wherein the HL-ASD group exhibited a positive association between WM fractional anisotropy and language whereas HL-Neg and LL-Neg groups showed weak or no association. No other fiber tracts demonstrated significant associations with language. In conclusion, results indicated arcuate fasciculus WM is linked to language in early toddlerhood for autistic toddlers, with the strongest associations emerging around 24 months. To our knowledge, this is the first study to evaluate associations between language and WM development during the pre-symptomatic period in ASD.

Longitudinal analysis is a core aspect of many medical applications for understanding the relationship between an anatomical subject's function and its trajectory of shape change over time. Whereas mixed-effects (or hierarchical) modeling is the statistical method of choice for analysis of longitudinal data, we here propose its extension as hierarchical geodesic polynomial model (HGPM) for multilevel analyses of longitudinal shape data. 3D shapes are transformed to a non-Euclidean shape space for regression analysis using geodesics on a high dimensional Riemannian manifold. At the subject-wise level, each individual trajectory of shape change is represented by a univariate geodesic polynomial model on timestamps. At the population level, multivariate polynomial expansion is applied to uni/multivariate geodesic polynomial models for both anchor points and tangent vectors. As such, the trajectory of an individual subject's shape changes over time can be modeled accurately with a reduced number of parameters, and population-level effects from multiple covariates on trajectories can be well captured. The implemented HGPM is validated on synthetic examples of points on a unit 3D sphere. Further tests on clinical 4D right ventricular data show that HGPM is capable of capturing observable effects on shapes attributed to changes in covariates, which are consistent with qualitative clinical evaluations. HGPM demonstrates its effectiveness in modeling shape changes at both subject-wise and population levels, which is promising for future studies of the relationship between shape changes over time and the level of dysfunction severity on anatomical objects associated with disease.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder diagnosed based on social impairment, restricted interests, and repetitive behaviors. Contemporary theories posit that cerebellar pathology contributes causally to ASD by disrupting error-based learning (EBL) during infancy. The present study represents the first test of this theory in a prospective infant sample, with potential implications for ASD detection.
Method(s): Data from the Infant Brain Imaging Study (n = 94, 68 male) were used to examine 6-month cerebellar functional connectivity magnetic resonance imaging in relation to later (12/24-month) ASD-associated behaviors and outcomes. Hypothesis-driven univariate analyses and machine learning-based predictive tests examined cerebellar-frontoparietal network (FPN; subserves error signaling in support of EBL) and cerebellar-default mode network (DMN; broadly implicated in ASD) connections. Cerebellar-FPN functional connectivity was used as a proxy for EBL, and cerebellar-DMN functional connectivity provided a comparative foil. Data-driven functional connectivity magnetic resonance imaging enrichment examined brain-wide behavioral associations, with post hoc tests of cerebellar connections.
Result(s): Cerebellar-FPN and cerebellar-DMN connections did not demonstrate associations with ASD. Functional connectivity magnetic resonance imaging enrichment identified 6-month correlates of later ASD-associated behaviors in networks of a priori interest (FPN, DMN), as well as in cingulo-opercular (also implicated in error signaling) and medial visual networks. Post hoc tests did not suggest a role for cerebellar connections.
Conclusion(s): We failed to identify cerebellar functional connectivity-based contributions to ASD. However, we observed prospective correlates of ASD-associated behaviors in networks that support EBL. Future studies may replicate and extend network-level positive results, and tests of the cerebellum may investigate brain-behavior associations at different developmental stages and/or using different neuroimaging modalities.
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OBJECTIVE:Previous research has demonstrated that the amygdala is enlarged in children with autism spectrum disorder (ASD). However, the precise onset of this enlargement during infancy, how it relates to later diagnostic behaviors, whether the timing of enlargement in infancy is specific to the amygdala, and whether it is specific to ASD (or present in other neurodevelopmental disorders, such as fragile X syndrome) are all unknown. METHODS:Longitudinal MRIs were acquired at 6-24 months of age in 29 infants with fragile X syndrome, 58 infants at high likelihood for ASD who were later diagnosed with ASD, 212 high-likelihood infants not diagnosed with ASD, and 109 control infants (1,099 total scans). RESULTS:Infants who developed ASD had typically sized amygdala volumes at 6 months, but exhibited significantly faster amygdala growth between 6 and 24 months, such that by 12 months the ASD group had significantly larger amygdala volume (Cohen's d=0.56) compared with all other groups. Amygdala growth rate between 6 and 12 months was significantly associated with greater social deficits at 24 months when the infants were diagnosed with ASD. Infants with fragile X syndrome had a persistent and significantly enlarged caudate volume at all ages between 6 and 24 months (d=2.12), compared with all other groups, which was significantly associated with greater repetitive behaviors. CONCLUSIONS:This is the first MRI study comparing fragile X syndrome and ASD in infancy, demonstrating strikingly different patterns of brain and behavior development. Fragile X syndrome-related changes were present from 6 months of age, whereas ASD-related changes unfolded over the first 2 years of life, starting with no detectable group differences at 6 months. Increased amygdala growth rate between 6 and 12 months occurs prior to social deficits and well before diagnosis. This gradual onset of brain and behavior changes in ASD, but not fragile X syndrome, suggests an age- and disorder-specific pattern of cascading brain changes preceding autism diagnosis.

Purpose : Automated segmentation of in-vivo lamina cribrosa (LC) has been challenging, owing to the complex 3D structure and decreased visibility in the lamina depth. Frangi's vesselness filter, which was originally developed for angiogram segmentation, have been successfully demonstrated in segmenting the ex-vivo LC from micro-CT and second harmonic generation microscopy images. In this project we are proposing a new approach of segmenting the in vivo LC from OCT scans, incorporating the Frangi's vesselness principle to facilitate in vivo LC image analysis in much greater detail compared to our previously described 3D analysis method. Methods : In-vivo spectral-domain OCT scans (Leica, Chicago, IL) were acquired from healthy non-human primates. Scans of varying degree of image quality were selected for the analysis and underwent automated brightness and local contrast enhancement. 3D Frangi's vesselness filter was applied using a fixed setting for scans of all qualities. Our previously described segmentation algorithm was then used to quantify the LC microstructure. The measurements generated from the Frangi analysis and from our own conventional method were compared with a standard reference (manually segmented LC by an expert). Paired t tests were performed to compare if the differences between standard reference and conventional method are greater than the differences between standard reference and Frangi analysis. The visibility of analyzable lamina and dice coefficient were also compared to the conventional method using the same test. Results : In vivo scans acquired from 5 rhesus macaques (3 males, 1 female, aged 4.3-10.7 yrs) were used for the analysis. No significant difference was detected for LC microstructure parameters between Frangi's approach and conventional method with respect to the standard reference, except for significantly higher pore count in Frangi's method (p=0.003; Table). Furthermore, visibility (Figure) was significantly higher for the Frangi method compared to the conventional approach (p<0.001) with no difference detected for the semantic segmentation, as reflected by the dice coefficient. Conclusions : The use of Frangi analysis substantially increase the analyzable lamina while providing similar quantification of the LC microstructure compared to our previous 3D analysis method. This improves the potential for automated and thorough volumetric analysis of in vivo OCT LC image