A rhesus monkey reference label atlas for template driven segmentation

Vervet MRI atlas and label map for fully automated morphometric analyses

Currently available non-human primate templates typically require input of a skull-stripped brain for structural processing. This can be a manually intensive procedure, and considerably limits their utility. The purpose of this study was to create a vervet MRI population template, associated tissue probability maps (TPM), and a label atlas to facilitate true fully automated Magnetic Resonance Imaging (MRI) structural analyses for morphometric analyses. Structural MRI scans of ten vervet monkeys (Chlorocebus aethiops) scanned at three time points were used in this study. An unbiased population average template was created using a symmetric diffeomorphic registration (SyN) procedure. Skull stripping, segmentation, and label map generation were performed using the publically available rhesus INIA19 MRI template and NeuroMap label atlas. A six-class TPM and a six-layer two-class normalization template was created from the vervet segmentation for use within the Statistical Parametric Mapping (SPM) framework. Fully automated morphologic processing of all of the vervet MRI scans was then performed using the vervet TPM and vervet normalization template including skull-stripping, segmentation and normalization. The vervet template creation procedure resulted in excellent skull stripping, segmentation, and NeuroMap atlas labeling with 720 structures successfully registered. Fully automated processing was accomplished for all vervet scans, demonstrating excellent skull-stripping, segmentation, and normalization performance. We describe creation of an unbiased vervet structural MRI population template and atlas. The template includes an associated six-class TPM and DARTEL six-layer two-class normalization template for true fully automated skull-stripping, segmentation, and normalization of vervet structural T1-weighted MRI scans. We provide the most detailed vervet label atlas currently available based on the NeuroMaps atlas with 720 labels successfully registered. We additionally describe a novel method for atlas label generation that capitalizes on previous work in this area using high-dimensional highly accurate image matching procedures for inter-species morphologic normalization.

A diffusion tensor MRI atlas of the postmortem rhesus macaque brain

The rhesus macaque (Macaca mulatta) is the most widely used nonhuman primate for modeling the structure and function of the brain. Brain atlases, and particularly those based on magnetic resonance imaging (MRI), have become important tools for understanding normal brain structure, and for identifying structural abnormalities resulting from disease states, exposures, and/or aging. Diffusion tensor imaging (DTI)-based MRI brain atlases are widely used in both human and macaque brain imaging studies because of the unique contrasts, quantitative diffusion metrics, and diffusion tractography that they can provide. Previous MRI and DTI atlases of the rhesus brain have been limited by low contrast and/or low spatial resolution imaging. Here we present a microscopic resolution MRI/DTI atlas of the rhesus brain based on 10 postmortem brain specimens. The atlas includes both structural MRI and DTI image data, a detailed three-dimensional segmentation of 241 anatomic structures, diffusion tractography, cortical thickness estimates, and maps of anatomic variability among atlas specimens. This atlas incorporates many useful features from previous work, including anatomic label nomenclature and ontology, data orientation, and stereotaxic reference frame, and further extends prior analyses with the inclusion of high-resolution multi-contrast image data.

Atlas-guided segmentation of vervet monkey brain MRI

The vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model.

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.