Evaluation of atlas based mouse brain segmentation

Magentic Reasonance Imaging for mouse phenotype study is one of the important tools to understand human diseases. In this paper, we present a fully automatic pipeline for the process of morphometric mouse brain analysis. The method is based on atlas-based tissue and regional segmentation, which was originally developed for the human brain. To evaluate our method, we conduct a qualitative and quantitative validation study as well as compare of b-spline and fluid registration methods as components in the pipeline. The validation study includes visual inspection, shape and volumetric measurements and stability of the registration methods against various parameter settings in the processing pipeline. The result shows both fluid and b-spline registration methods work well in murine settings, but the fluid registration is more stable. Additionally, we evaluated our segmentation methods by comparing volume differences between Fmr1 FXS in FVB background vs C57BL/6J mouse strains

Magnetic resonance microimaging of the spinal cord in the SOD1 mouse model of amyotrophic lateral sclerosis detects motor nerve root degeneration

Amyotrophic lateral sclerosis (ALS) is characterized by selective degeneration of motor neurons. Current imaging studies have concentrated on areas of the brain and spinal cord that contain mixed populations of sensory and motor neurons. In this study, ex vivo magnetic resonance microimaging (MRM) was used to separate motor and sensory components by visualizing individual dorsal and ventral roots in fixed spinal cords. MRM at 15 pm in plane resolution enabled the axons of pure populations of sensory and motor neurons to be measured in the lumbar region of the SOD1 mouse model of ALS. MRM signal intensity increased by 38.3% (p < 0.05) exclusively in the ventral motor nerve roots of the lumbar spinal cord of ALS-affected SOD1 mice compared to wildtype littermates. The hyperintensity was therefore limited to white matter tracts arising from the motor neurons, whereas sensory white matter fibers were unchanged. Significant decreases in ventral nerve root volume were also detected in the SOD1 mice, which correlated with the axonal degeneration observed by microscopy. These results demonstrate the usefulness of MRM in visualizing the ultrastructure of the mouse spinal cord. The detailed 3D anatomy allowed the processes of pure populations of sensory and motor neurons to be compared. (C) 2011 Elsevier Inc. All rights reserved

Evaluation of atlas based mouse brain segmentation

Magentic Reasonance Imaging for mouse phenotype study is one of the important tools to understand human diseases. In this paper, we present a fully automatic pipeline for the process of morphometric mouse brain analysis. The method is based on atlas-based tissue and regional segmentation, which was originally developed for the human brain. To evaluate our method, we conduct a qualitative and quantitative validation study as well as compare of b-spline and fluid registration methods as components in the pipeline. The validation study includes visual inspection, shape and volumetric measurements and stability of the registration methods against various parameter settings in the processing pipeline. The result shows both fluid and b-spline registration methods work well in murine settings, but the fluid registration is more stable. Additionally, we evaluated our segmentation methods by comparing volume differences between Fmr1 FXS in FVB background vs C57BL/6J mouse strains

Three-Dimensional Atlas System for Mouse and Rat Brain Imaging Data

Tomographic neuroimaging techniques allow visualization of functionally and structurally specific signals in the mouse and rat brain. The interpretation of the image data relies on accurate determination of anatomical location, which is frequently obstructed by the lack of structural information in the data sets. Positron emission tomography (PET) generally yields images with low spatial resolution and little structural contrast, and many experimental magnetic resonance imaging (MRI) paradigms give specific signal enhancements but often limited anatomical information. Side-by-side comparison of image data with conventional atlas diagram is hampered by the 2-D format of the atlases, and by the lack of an analytical environment for accumulation of data and integrative analyses. We here present a method for reconstructing 3-D atlases from digital 2-D atlas diagrams, and exemplify 3-D atlas-based analysis of PET and MRI data. The reconstruction procedure is based on two seminal mouse and brain atlases, but is applicable to any stereotaxic atlas. Currently, 30 mouse brain structures and 60 rat brain structures have been reconstructed. To exploit the 3-D atlas models, we have developed a multi-platform atlas tool (available via The Rodent Workbench, http://rbwb.org) which allows combined visualization of experimental image data within the 3-D atlas space together with 3-D viewing and user-defined slicing of selected atlas structures. The tool presented facilitates assignment of location and comparative analysis of signal location in tomographic images with low structural contrast

In Vivo 3D Digital Atlas Database of the Adult C57BL/6J Mouse Brain by Magnetic Resonance Microscopy

In this study, a 3D digital atlas of the live mouse brain based on magnetic resonance microscopy (MRM) is presented. C57BL/6J adult mouse brains were imaged in vivo on a 9.4 Tesla MR instrument at an isotropic spatial resolution of 100 μm. With sufficient signal-to-noise (SNR) and contrast-to-noise ratio (CNR), 20 brain regions were identified. Several atlases were constructed including 12 individual brain atlases, an average atlas, a probabilistic atlas and average geometrical deformation maps. We also investigated the feasibility of using lower spatial resolution images to improve time efficiency for future morphological phenotyping. All of the new in vivo data were compared to previous published in vitro C57BL/6J mouse brain atlases and the morphological differences were characterized. Our analyses revealed significant volumetric as well as unexpected geometrical differences between the in vivo and in vitro brain groups which in some instances were predictable (e.g. collapsed and smaller ventricles in vitro) but not in other instances. Based on these findings we conclude that although in vitro datasets, compared to in vivo images, offer higher spatial resolutions, superior SNR and CNR, leading to improved image segmentation, in vivo atlases are likely to be an overall better geometric match for in vivo studies, which are necessary for longitudinal examinations of the same animals and for functional brain activation studies. Thus the new in vivo mouse brain atlas dataset presented here is a valuable complement to the current mouse brain atlas collection and will be accessible to the neuroscience community on our public domain mouse brain atlas website

Prenatal alcohol exposure reduces magnetic susceptibility contrast and anisotropy in the white matter of mouse brains

Prenatal alcohol exposure can result in long-term cognitive and behavioral deficits. Fetal alcohol spectrum disorder (FASD) refers to a range of permanent birth defects caused by prenatal alcohol exposure, and is the most common neurodevelopmental disorder in the US. Studies by autopsy and conventional structural MRI indicate that the midline structures of the brain are particularly vulnerable to prenatal alcohol exposure. Diffusion tensor imaging (DTI) has shown that abnormalities in brain white matter especially the corpus callosum are very common in FASD. Quantitative susceptibility mapping (QSM) is a novel technique that measures tissue’s magnetic property. Such magnetic property is affected by tissue microstructure and molecular composition including that of myelin in the white matter. In this work, we studied three major white matter fiber bundles of a mouse model of FASD and compared it to control mice using both QSM and DTI. QSM revealed clear and significant abnormalities in anterior commissure, corpus callosum, and hippocampal commissure, which were likely due to reduced myelination. Our data also suggested that QSM may be even more sensitive than DTI for examining changes due to prenatal alcohol exposure. Although this is a preclinical study, the technique of QSM is readily translatable to human brain

T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model

Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T1-weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD

Segmentación automática de tejido cerebral en imagen preclínica

En estudios preclínicos neurológicos de imagen de resonancia magnética (MRI) en pequeños animales es común el uso de la segmentación cerebral para su posterior análisis volumétrico y/o registro con otras modalidades de imagen. Este proceso suele realizarse de forma manual, por lo que a menudo se emplea una gran cantidad de tiempo dependiendo del estudio. En este trabajo se propone un nuevo método de segmentación automática basado en registro para facilitar dicho proceso. La propuesta se ha comparado con dos métodos: segmentación manual, que se emplea como referencia, y una segmentación basada en PCNN (Pulse Couple Neural Network) propuesta específicamente para imágenes de rata. El método propuesto consigue buenos resultados en índice de solapamiento y volumen cerebral comparado con el manual, y ofrece además una reducción considerable en el tiempo de ejecución comparado con PCNN.Ingeniería Técnica en Sistemas de Telecomunicació