Quantitative mouse brain phenotyping based on single and multispectral MR protocols.

Sophisticated image analysis methods have been developed for the human brain, but such tools still need to be adapted and optimized for quantitative small animal imaging. We propose a framework for quantitative anatomical phenotyping in mouse models of neurological and psychiatric conditions. The framework encompasses an atlas space, image acquisition protocols, and software tools to register images into this space. We show that a suite of segmentation tools (Avants, Epstein et al., 2008) designed for human neuroimaging can be incorporated into a pipeline for segmenting mouse brain images acquired with multispectral magnetic resonance imaging (MR) protocols. We present a flexible approach for segmenting such hyperimages, optimizing registration, and identifying optimal combinations of image channels for particular structures. Brain imaging with T1, T2* and T2 contrasts yielded accuracy in the range of 83% for hippocampus and caudate putamen (Hc and CPu), but only 54% in white matter tracts, and 44% for the ventricles. The addition of diffusion tensor parameter images improved accuracy for large gray matter structures (by >5%), white matter (10%), and ventricles (15%). The use of Markov random field segmentation further improved overall accuracy in the C57BL/6 strain by 6%; so Dice coefficients for Hc and CPu reached 93%, for white matter 79%, for ventricles 68%, and for substantia nigra 80%. We demonstrate the segmentation pipeline for the widely used C57BL/6 strain, and two test strains (BXD29, APP/TTA). This approach appears promising for characterizing temporal changes in mouse models of human neurological and psychiatric conditions, and may provide anatomical constraints for other preclinical imaging, e.g. fMRI and molecular imaging. This is the first demonstration that multiple MR imaging modalities combined with multivariate segmentation methods lead to significant improvements in anatomical segmentation in the mouse brain.

Least-square NUFFT methods applied to 2-D and 3-D radially encoded MR image reconstruction.

Radially encoded MRI has gained increasing attention due to its motion insensitivity and reduced artifacts. However, because its samples are collected nonuniformly in the k-space, multidimensional (especially 3-D) radially sampled MRI image reconstruction is challenging. The objective of this paper is to develop a reconstruction technique in high dimensions with on-the-fly kernel calculation. It implements general multidimensional nonuniform fast Fourier transform (NUFFT) algorithms and incorporates them into a k-space image reconstruction framework. The method is then applied to reconstruct from the radially encoded k-space data, although the method is applicable to any non-Cartesian patterns. Performance comparisons are made against the conventional Kaiser-Bessel (KB) gridding method for 2-D and 3-D radially encoded computer-simulated phantoms and physically scanned phantoms. The results show that the NUFFT reconstruction method has better accuracy-efficiency tradeoff than the KB gridding method when the kernel weights are calculated on the fly. It is found that for a particular conventional kernel function, using its corresponding deapodization function as a scaling factor in the NUFFT framework has the potential to improve accuracy. In particular, when a cosine scaling factor is used, the NUFFT method is faster than KB gridding method since a closed-form solution is available and is less computationally expensive than the KB kernel (KB griding requires computation of Bessel functions). The NUFFT method has been successfully applied to 2-D and 3-D in vivo studies on small animals.

High-throughput morphologic phenotyping of the mouse brain with magnetic resonance histology.

The Mouse Biomedical Informatics Research Network (MBIRN) has been established to integrate imaging studies of the mouse brain ranging from three-dimensional (3D) studies of the whole brain to focused regions at a sub-cellular scale. Magnetic resonance (MR) histology provides the entry point for many morphologic comparisons of the whole brain. We describe a standardized protocol that allows acquisition of 3D MR histology (43-microm resolution) images of the fixed, stained mouse brain with acquisition times <30 min. A higher resolution protocol with isotropic spatial resolution of 21.5 microm can be executed in 2 h. A third acquisition protocol provides an alternative image contrast (at 43-microm isotropic resolution), which is exploited in a statistically driven algorithm that segments 33 of the most critical structures in the brain. The entire process, from specimen perfusion, fixation and staining, image acquisition and reconstruction, post-processing, segmentation, archiving, and analysis, is integrated through a structured workflow. This yields a searchable database for archive and query of the very large (1.2 GB) images acquired with this standardized protocol. These methods have been applied to a collection of both male and female adult murine brains ranging over 4 strains and 6 neurologic knockout models. These collection and acquisition methods are now available to the neuroscience community as a standard web-deliverable service.

Quantitative anatomy of the guinea pig endolymphatic sac.

The endolymphatic sac is believed to represent one of the primary loci for endolymph volume regulation in the inner ear. Quantitative analysis of physiologic measurements from the endolymphatic sac requires knowledge of the anatomy of the structure, specifically the luminal volume and the variation of cross-sectional area with distance along the sac. Recently techniques have become available to make these measurements. In the present study, fixed, isolated specimens of the guinea pig endolymphatic sac were imaged by high-resolution magnetic resonance microscopy (MRM) or by histological serial sections. Structures were reconstructed and quantified using image analysis software. In specimens imaged by MRM the endolymphatic sac volume, including tissue and lumen, was 359 nl for the intraosseous region and 106 nl for the extraosseous region, totaling 465 nl for the entire structure. The luminal volumes were 131 nl for the intraosseous region and 13 nl for the extraosseous region, totaling 144 nl. In histological specimens the volume, including tissue and lumen, was 414 nl for the intraosseous region and 121 nl for the extraosseous region, totaling 535 nl for the entire structure. The luminal volumes were 152 nl for the intraosseous region and 26 nl for the extraosseous region, totaling 179 nl. Differences in volume estimates obtained by the two methods were not statistically significant and variation was dominated by inter-specimen variation. Pooling the data, the total volume of the endolymphatic sac in the guinea pig including tissue and lumen was 506 nl (S.D. 100, n=17) and the volume of the lumen was 169 nl (S.D. 48, n=14).

Magnetic resonance histology for morphologic phenotyping.

Magnetic resonance histology (MRH) images of the whole mouse have been acquired at 100-micron isotropic resolution at 2.0 T with image arrays of 256 x 256 x 1024. Higher resolution (50 x 50 x 50 microns) of limited volumes has been acquired at 7.1T with image arrays of 512 x 512 x 512. Even higher resolution images (20 x 20 x 20 microns) of isolated organs have been acquired at 9.4 T. The volume resolution represents an increase of 625000 x over conventional clinical MRI. The technological basis is summarized that will allow basic scientists to begin using MRH as a routine method for morphologcic phenotyping of the mouse. MRH promises four unique attributes over conventional histology: 1). MRH is non-destructive; 2). MRH exploits the unique contrast mechanisms that have made MRI so successful clinically; 3). MRH is 3-dimensional; and 4). the data are inherently digital. We demonstrate the utility in morphologic phenotyping a whole C57BL/6J mouse.

Developing an anatomical model of the human laryngeal cartilages from magnetic resonance imaging.

The purpose of this work was to construct a three-dimensional anatomical framework of the cartilages of the human larynx. The framework included representative surface models of the four laryngeal cartilages and estimated attachment points for the intrinsic laryngeal muscles. High-resolution magnetic resonance imaging (MRI) was used to scan one female and four male human cadaveric larynges. The cartilages were segmented manually from the MRI volume for analysis. Two of these larynges were subsequently dissected and the landmark distances on the cartilages measured for comparison with the MRI measures and previous studies. The MRI measures were 8% smaller than the anatomical measures and 12% smaller than data reported in the literature. A laryngeal coordinate system was defined using the plane of symmetry of the cricoid cartilage. Measures of cricoid cartilage symmetry had less than 3% difference between the two sides for a series of measures. An algorithm for registering larynges that minimized the root-mean-square distance between the surface of a reference cricoid cartilage and the surfaces of nonisotropically scaled candidate cricoid cartilages was evaluated. This study provided an anatomical framework for registering different larynges to the same coordinate space.

Morphologic phenotyping with MR microscopy: the visible mouse.

A method for rapid morphologic phenotyping is demonstrated by using magnetic resonance microscopy. Whole fixed C57BL/6J mice were imaged at 110-microm isotropic resolution; limited volumes of the intact specimen, at 50-microm isotropic resolution; and isolated organs, at 25-microm isotropic resolution. The three-dimensional imaging technique was applied to uricase knockout mice to demonstrate the method for the evaluation of morphologic phenotype.