Jason P. Lerch

Previous studies have demonstrated that white matter (WM) lesions bias automated brain tissue classifications and cerebral volume measurements. However, filling WM lesions using the intensity of neighbouring normal-appearing WM has been shown to increase the accuracy of automated volume measurements in the brain. In the present study, we investigate the influence of WM lesions on cortical thickness (CTh) measures and assessed the impact of lesion filling on both cross-sectional/longitudinal and global/regional measurements of CTh in multiple sclerosis (MS) patients. Fifty MS patients were studied at baseline as well as after three and six years of follow-up. CTh was estimated using a fully automated pipeline (CIVET) on T1-weighted magnetic resonance images data acquired at 1.5 Tesla without (original) and with WM lesion filling (filled). WM lesions were semi-automatically segmented and then filled with the mean intensity of the neighbouring voxels. For both original and filled T1 images we investigated and compared the main CIVET’s steps: tissue classification, surfaces generation and CTh measurement. On the original T1 images, the majority of WM lesion volume (72%) was wrongly classified as gray matter (GM). After lesion filling the accuracy of WM lesions classification improved significantly (p < 0.001, 94% of WM lesion volume correctly classified) as well as the WM surface generation (p < 0.0001). The mean CTh computed on the original T1 images, overall time points, was significantly thinner (p < 0.001) compared the CTh estimated on the filled T1 images. The vertex-wise longitudinal analysis performed on the filled T1 images showed an increased number of vertices in the fronto-temporal region with a significantly decrease of CTh over time compared the analysis performed on the original images. These results indicate that WM lesions bias the CTh estimation both cross-sectionally as well as longitudinally. The lesion filling approach significantly improved the accuracy of the regional CTh estimation and has an impact also on the global estimation of CTh.

Background: Huntington Disease (HD) is a neurodegenerative disorder in which caspase activation and cleavage of substrates, including the huntingtin protein, has been invoked as a pathological mechanism. Specific changes in caspase-2 (casp2) activity have been suggested to contribute to the pathogenesis of HD, however unique casp2 cleavage substrates have remained elusive. We thus utilized mice completely lacking casp2 (casp2-/-) to examine the role played by casp2 in the progression of HD. This 'substrate agnostic' approach allows us to query the effect of casp2 on HD progression without pre-defining proteolytic substrates of interest. Results: YAC128 HD model mice lacking casp2 show protection from well-validated motor and cognitive features of HD, including performance on rotarod, swimming T-maze, pre-pulse inhibition, spontaneous alternation and locomotor tasks. However, the specific pathological features of the YAC128 mice including striatal volume loss and testicular degeneration are unaltered in mice lacking casp2. The application of high-resolution magnetic resonance imaging (MRI) techniques validates specific neuropathology in the YAC128 mice that is not altered by ablation of casp2. Conclusions: The rescue of behavioral phenotypes in the absence of pathological improvement suggests that different pathways may be operative in the dysfunction of neural circuitry in HD leading to behavioral changes compared to the processes leading to cell death and volume loss. Inhibition of caspase-2 activity may be associated with symptomatic improvement in HD.

Background: Children whose mothers consumed alcohol during pregnancy exhibit widespread brain abnormalities and a complex array of behavioral disturbances. Here, we used a mouse model of fetal alcohol exposure to investigate relationships between brain abnormalities and specific behavioral alterations during adulthood.Results: Mice drank a 10% ethanol solution throughout pregnancy. When fetal alcohol-exposed offspring reached adulthood, we used high resolution MRI to conduct a brain-wide screen for structural changes and found that the largest reduction in volume occurred in the olfactory bulbs. Next, we tested adult mice in an associative olfactory task and found that fetal alcohol exposure impaired discrimination between similar odors but left odor memory intact. Finally, we investigated olfactory bulb neurogenesis as a potential mechanism by performing anin vitroneurosphere assay,in vivolabeling of new cells using BrdU, andin vivolabeling of new cells using a transgenic reporter system. We found that fetal alcohol exposure decreased the number of neural precursor cells in the subependymal zone and the number of new cells in the olfactory bulbs during the first few postnatal weeks.Conclusions: Using a combination of techniques, including structural brain imaging,in vitroandin vivocell detection methods, and behavioral testing, we found that fetal alcohol exposure results in smaller olfactory bulbs and impairments in odor discrimination that persist into adulthood. Furthermore, we found that these abnormalities in olfactory bulb structure and function may arise from deficits in the generation of new olfactory bulb neurons during early postnatal development.

The motivation behind this paper is to aid the automatic phenotyping of mouse embryos, wherein multiple embryos embedded within a single tube were scanned using Magnetic Resonance Imaging (MRI).

The laboratory mouse, with its genetic similarity to humans and rich set of tools for manipulating its genome, has emerged as one of the key models for experimental investigation of the genotype/phenotype relationships in mammals. Recent innovations have made MRI an increasingly popular tool for examining the phenotype of genetically altered mice. Advances in field strengths, mouse handling, image analysis and statistics have contributed greatly in this regard. In this chapter, we illustrate the methods necessary to achieve high-throughput phenotyping of genetically altered mice using multiple-mouse MRI combined with advanced image analysis techniques and statistics.