A diffusion tensor brain template for rhesus macaques.

Diffusion tensor imaging (DTI) is a powerful and noninvasive imaging method for characterizing tissue microstructure and white matter organization in the brain. While it has been applied extensively in research studies of the human brain, DTI studies of non-human primates have been performed only recently. The growing application of DTI in rhesus monkey studies would significantly benefit from a standardized framework to compare findings across different studies. A very common strategy for image analysis is to spatially normalize (co-register) the individual scans to a representative template space. This paper presents the development of a DTI brain template, UWRMAC-DTI271, for adolescent Rhesus Macaque (Macaca mulatta) monkeys. The template was generated from 271 rhesus monkeys, collected as part of a unique brain imaging genetics study. It is the largest number of animals ever used to generate a computational brain template, which enables the generation of a template that has high image quality and accounts for variability in the species. The quality of the template is further ensured with the use of DTI-TK, a well-tested and high-performance DTI spatial normalization method in human studies. We demonstrated its efficacy in monkey studies for the first time by comparing it to other commonly used scalar-methods for DTI normalization. It is anticipated that this template will play an important role in facilitating cross-site voxelwise DTI analyses in Rhesus Macaques. Such analyses are crucial in investigating the role of white matter structure in brain function, development, and other psychopathological disorders for which there are well-validated non-human primate models.

A Rare Complication of Fine-Needle Aspiration of Neck Structures.

Fine-needle aspiration (FNA) is a generally accepted tool for safe diagnostic evaluation in the workup of lesions and masses. Aside from the commonly discussed risks of infection and minor bleeding related to skin puncture, other more serious complications have been reported sparingly. We present two cases of pneumothorax from FNA of neck structures, which have been theorized but not previously reported to our knowledge. Discussion of cases of this complication rather than solely a theoretical understanding of it will aid in diagnosis and management of this complication.

A Comparison of E6H4 and G175-405 p16-specific Monoclonal Antibodies in Oropharyngeal Squamous Cell Carcinoma.

The purpose of this investigation is to directly compare G175-405 and E6H4 p16-specific antibodies as immunomarkers of HPV-driven oropharyngeal carcinoma. The investigators designed a retrospective analysis using specimens from an archived tissue bank with known in situ hybridization and polymerase chain reaction status for HPV DNA. Fifty randomly selected oropharyngeal specimens were evaluated with both the G175-405 and E6H4 p16-specific monoclonal antibodies. Two pathologists, blinded to the HPV-specific testing status, evaluated p16 positivity for both antibody clones. Interrater agreement was determined using a Cohen κ coefficient. Sensitivity and specificity values were calculated using a standard 2×2 contingency table, then compared using McNemar test. Interrater agreement for interpretation of p16 expression was 92% (κ=0.84) for the G175-405 clone and 100% for the E6H4 clone (κ=1.0). The G175-405 stain had a sensitivity of 0.917 and specificity of 0.846. The E6H4 stain had a sensitivity of 1.000 and specificity of 0.769. Using McNemar test, there were no significant differences found for sensitivity (P=0.480) or specificity (P=0.480) values. The results of this study suggest that though both G175-405 and E6H4 antibody stains are statistically comparable immunomarkers for HPV-driven oropharyngeal carcinoma, the E6H4 clone offers improved interobserver reliability.

Atypical development of white matter microstructure of the corpus callosum in males with autism: a longitudinal investigation.

BACKGROUND: The corpus callosum is the largest white matter structure in the brain, and it is the most consistently reported to be atypical in diffusion tensor imaging studies of autism spectrum disorder. In individuals with typical development, the corpus callosum is known to undergo a protracted development from childhood through young adulthood. However, no study has longitudinally examined the developmental trajectory of corpus callosum in autism past early childhood. METHODS: The present study used a cohort sequential design over 9 years to examine age-related changes of the corpus callosum in 100 males with autism and 56 age-matched males with typical development from early childhood (when autism can first be reliably diagnosed) to mid-adulthood (after development of the corpus callosum has been completed) (3 to 41 years of age). RESULTS: The group with autism demonstrated a different developmental trajectory of white matter microstructure in the anterior corpus callosum's (genu and body) fractional anisotropy, which suggests atypical brain maturation in these regions in autism. When analyses were broken down by age group, atypical developmental trajectories were present only in the youngest participants (10 years of age and younger). Significant main effects for group were found in terms of decreased fractional anisotropy across all three subregions of the corpus callosum (genu, body, and splenium) and increased mean diffusivity, radial diffusivity, and axial diffusivity in the posterior corpus callosum. CONCLUSIONS: These longitudinal results suggest atypical early childhood development of the corpus callosum microstructure in autism that transitions into sustained group differences in adolescence and adulthood. This pattern of results provides longitudinal evidence consistent with a growing number of published studies and hypotheses regarding abnormal brain connectivity across the life span in autism.

Longitudinal processing speed impairments in males with autism and the effects of white matter microstructure.

The present study used an accelerated longitudinal design to examine group differences and age-related changes in processing speed in 81 individuals with autism spectrum disorder (ASD) compared to 56 age-matched individuals with typical development (ages 6-39 years). Processing speed was assessed using the Wechsler Intelligence Scale for Children-3rd edition (WISC-III) and the Wechsler Adult Intelligence Scale-3rd edition (WAIS-III). Follow-up analyses examined processing speed subtest performance and relations between processing speed and white matter microstructure (as measured with diffusion tensor imaging [DTI] in a subset of these participants). After controlling for full scale IQ, the present results show that processing speed index standard scores were on average 12 points lower in the group with ASD compared to the group with typical development. There were, however, no significant group differences in standard score age-related changes within this age range. For subtest raw scores, the group with ASD demonstrated robustly slower processing speeds in the adult versions of the IQ test (i.e., WAIS-III) but not in the child versions (WISC-III), even though age-related changes were similar in both the ASD and typically developing groups. This pattern of results may reflect difficulties that become increasingly evident in ASD on more complex measures of processing speed. Finally, DTI measures of whole-brain white matter microstructure suggested that fractional anisotropy (but not mean diffusivity, radial diffusivity, or axial diffusivity) made significant but small-sized contributions to processing speed standard scores across our entire sample. Taken together, the present findings suggest that robust decreases in processing speed may be present in ASD, more pronounced in adulthood, and partially attributable to white matter microstructural integrity.

Max Margin General Linear Modeling for Neuroimage Analyses.

General linear modeling (GLM) is one of the most commonly used approaches to perform voxel based analyses (VBA) for hypotheses testing in neuroimaging. In this paper we tie support vector machine based regression (SVR) and classical significance testing to provide the benefits of max margin estimation in the GLM setting. Using Welch-Satterthwaite approximations, we compute degrees of freedom (df) of error (also known as residual df) for ε-SVR. We demonstrate that ε-SVR can result not only in robustness of estimation but also improved residual df compared to the very commonly used ordinary least squares (OLS) estimation. This can result in higher sensitivity to signal in neuroimaging studies and also allow for better control of confounding effects of nuisance covariates. We demonstrate the application of our approach in white matter analyses using diffusion tensor imaging (DTI) data from autism and emotion-regulation studies.

Diffusion tensor imaging in autism spectrum disorder: a review.

White matter tracts of the brain allow neurons and neuronal networks to communicate and function with high efficiency. The aim of this review is to briefly introduce diffusion tensor imaging methods that examine white matter tracts and then to give an overview of the studies that have investigated white matter integrity in the brains of individuals with autism spectrum disorder (ASD). From the 48 studies we reviewed, persons with ASD tended to have decreased fractional anisotropy and increased mean diffusivity in white matter tracts spanning many regions of the brain but most consistently in regions such as the corpus callosum, cingulum, and aspects of the temporal lobe. This decrease in fractional anisotropy was often accompanied by increased radial diffusivity. Additionally, the review suggests possible atypical lateralization in some white matter tracts of the brain and a possible atypical developmental trajectory of white matter microstructure in persons with ASD. Clinical implications and future research directions are discussed.