Functional brain imaging and neurosurgery in subcortical areas often requires visualization of brain nuclei beyond the resolution of current magnetic resonance imaging (MRI) methods. We present techniques used to create: (1) a lower resolution 3D atlas, based on the Schaltenbrand and Wahren print atlas, which was integrated into a stereotactic neurosurgery planning and visualization platform (VIPER); and (2) a higher resolution 3D atlas derived from a single set of manually segmented histological slices containing nuclei of the basal ganglia, thalamus, basal forebrain, and medial temporal lobe. Both atlases were integrated to a canonical MRI (Colin27) from a young male participant by manually identifying homologous landmarks. The lower resolution atlas was then warped to fit the MRI based on the identified landmarks. A pseudo-MRI representation of the high-resolution atlas was created, and a non-linear transformation was calculated in order to match the atlas to the template MRI. The atlas can then be warped to match the anatomy of Parkinson's disease surgical candidates by using 3D automated non-linear deformation methods. By way of functional validation of the atlas, the location of the sensory thalamus was correlated with stereotactic intraoperative physiological data. The position of subthalamic electrode positions in patients with Parkinson's disease was also evaluated in the atlas-integrated MRI space. Finally, probabilistic maps of subthalamic stimulation electrodes were developed, in order to allow group analysis of the location of contacts associated with the best motor outcomes. We have therefore developed, and are continuing to validate, a high-resolution computerized MRI-integrated 3D histological atlas, which is useful in functional neurosurgery, and for functional and anatomical studies of the human basal ganglia, thalamus, and basal forebrain.
brain atlas; Parkinson's disease; stereotactic neurosurgery; image guidance
A gene expression atlas is an essential resource to quantify and understand the multiscale processes of embryogenesis in time and space. The automated reconstruction of a prototypic 4D atlas for vertebrate early embryos, using multicolor fluorescence in situ hybridization with nuclear counterstain, requires dedicated computational strategies. To this goal, we designed an original methodological framework implemented in a software tool called Match-IT. With only minimal human supervision, our system is able to gather gene expression patterns observed in different analyzed embryos with phenotypic variability and map them onto a series of common 3D templates over time, creating a 4D atlas. This framework was used to construct an atlas composed of 6 gene expression templates from a cohort of zebrafish early embryos spanning 6 developmental stages from 4 to 6.3 hpf (hours post fertilization). They included 53 specimens, 181,415 detected cell nuclei and the segmentation of 98 gene expression patterns observed in 3D for 9 different genes. In addition, an interactive visualization software, Atlas-IT, was developed to inspect, supervise and analyze the atlas. Match-IT and Atlas-IT, including user manuals, representative datasets and video tutorials, are publicly and freely available online. We also propose computational methods and tools for the quantitative assessment of the gene expression templates at the cellular scale, with the identification, visualization and analysis of coexpression patterns, synexpression groups and their dynamics through developmental stages.
We propose a workflow to map the expression domains of multiple genes onto a series of 3D templates, or “atlas”, during early embryogenesis. It was applied to the zebrafish at different stages between 4 and 6.3 hpf, generating 6 templates. Our system overcomes the lack of significant morphological landmarks in early development by relying on the expression of a reference gene (goosecoid, gsc) and nuclear staining to guide the registration of the analyzed genes. The proposed method also successfully maps gene domains from partially imaged embryos, thus allowing greater microscope magnification and cellular resolution. By using the workflow to construct a spatiotemporal database of zebrafish, we opened the way to a systematic analysis of vertebrate embryogenesis. The atlas database, together with the mapping software (Match-IT), a custom-made visualization platform (Atlas-IT), and step-by-step user guides are available from the Supplementary Material. We expect that this will encourage other laboratories to generate, map, visualize and analyze new gene expression datasets.
This paper describes the SRI24 atlas, a new standard reference system of normal human brain anatomy, that was created using template-free population registration of high-resolution magnetic resonance images acquired at 3T in a group of 24 normal control subjects. The atlas comprises anatomical channels (T1, T2, and proton density weighted), diffusion-related channels (fractional anisotropy, mean diffusivity, longitudinal diffusivity, mean diffusion-weighted image), tissue channels (CSF probability, gray matter probability, white matter probability, tissue labels), and two cortical parcellation maps. The SRI24 atlas enables multi-channel atlas-to-subject image registration. It is uniquely versatile in that it is equally suited for the two fundamentally different atlas applications: label propagation and spatial normalization. Label propagation, herein demonstrated using DTI fiber tracking, is enabled by the increased sharpness of the SRI24 atlas compared with other available atlases. Spatial normalization, herein demonstrated using data from a young-old group comparison study, is enabled by its unbiased average population shape property. For both propagation and normalization, we also report the results of quantitative comparisons with seven other published atlases: Colin27, MNI152, ICBM452 (warp5 and air12), and LPBA40 (SPM5, FLIRT, AIR). Our results suggest that the SRI24 atlas, although based on 3T MR data, allows equally accurate spatial normalization of data acquired at 1.5T as the comparison atlases, all of which are based on 1.5T data. Furthermore, the SRI24 atlas is as suitable for label propagation as the comparison atlases and detailed enough to allow delineation of anatomical structures for this purpose directly in the atlas.
brain atlas; multi-spectral magnetic resonance imaging; diffusion tensor imaging; unbiased population registration; spatial normalization; label propagation
A longitudinal experiment was conducted to evaluate the effectiveness of new methods for learning neuroanatomy with computer-based instruction. Using a 3D graphical model of the human brain, and sections derived from the model, tools for exploring neuroanatomy were developed to encourage adaptive exploration. This is an instructional method which incorporates graphical exploration in the context of repeated testing and feedback. With this approach, 72 participants learned either sectional anatomy alone or whole anatomy followed by sectional anatomy. Sectional anatomy was explored either with perceptually continuous navigation through the sections or with discrete navigation (as in the use of an anatomical atlas). Learning was measured longitudinally to a high performance criterion. Subsequent tests examined transfer of learning to the interpretation of biomedical images and long-term retention. There were several clear results of this study. On initial exposure to neuroanatomy, whole anatomy was learned more efficiently than sectional anatomy. After whole anatomy was mastered, learners demonstrated high levels of transfer of learning to sectional anatomy and from sectional anatomy to the interpretation of complex biomedical images. Learning whole anatomy prior to learning sectional anatomy led to substantially fewer errors overall than learning sectional anatomy alone. Use of continuous or discrete navigation through sectional anatomy made little difference to measured outcomes. Efficient learning, good long-term retention, and successful transfer to the interpretation of biomedical images indicated that computer-based learning using adaptive exploration can be a valuable tool in instruction of neuroanatomy and similar disciplines.
learning; instruction; neuroanatomy; graphics; interactive
Quantitative measurements from segmentations of human brain magnetic resonance
(MR) images provide important biomarkers for normal aging and disease progression. In this
paper, we propose a patch-based tissue classification method from MR images that uses a
sparse dictionary learning approach and atlas priors. Training data for the method
consists of an atlas MR image, prior information maps depicting where different tissues
are expected to be located, and a hard segmentation. Unlike most atlas-based
classification methods that require deformable registration of the atlas priors to the
subject, only affine registration is required between the subject and training atlas. A
subject specific patch dictionary is created by learning relevant patches from the atlas.
Then the subject patches are modeled as sparse combinations of learned atlas patches
leading to tissue memberships at each voxel. The combination of prior information in an
example-based framework enables us to distinguish tissues having similar intensities but
different spatial locations. We demonstrate the efficacy of the approach on the
application of whole brain tissue segmentation in subjects with healthy anatomy and normal
pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For
each application, quantitative comparisons are made against publicly available,
state-of-the art approaches.
magnetic resonance imaging (MRI); segmentation; sparsity; dictionary; histogram matching; brain; patches
Fiber tracking provides insights into the brain white matter network and has become more and more popular in diffusion MR imaging. Hardware or software phantom provides an essential platform to investigate, validate and compare various tractography algorithms towards a “gold standard”. Software phantoms excel due to their flexibility in varying imaging parameters, such as tissue composition, SNR, as well as potential to model various anatomies and pathologies. This paper describes a novel method in generating diffusion MR images with various imaging parameters from realistically appearing, individually varying brain anatomy based on predefined fiber tracts within a high-resolution human brain atlas. Specifically, joint, high resolution DWI and structural MRI brain atlases were constructed with images acquired from 6 healthy subjects (age 22–26) for the DWI data and 56 healthy subject (age 18–59) for the structural MRI data. Full brain fiber tracking was performed with filtered, two-tensor tractography in atlas space. A deformation field based principal component model from the structural MRI as well as unbiased atlas building was then employed to generate synthetic structural brain MR images that are individually varying. Atlas fiber tracts were accordingly warped into each synthetic brain anatomy. Diffusion MR images were finally computed from these warped tracts via a composite hindered and restricted model of diffusion with various imaging parameters for gradient directions, image resolution and SNR. Furthermore, an open-source program was developed to evaluate the fiber tracking results both qualitatively and quantitatively based on various similarity measures.
Diffusion-weighted MRI; Atlas; Fiber tracking; Tractography; Phantom; Validation
The Allen Brain Atlas (http://www.brain-map.org) provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal.
We describe a neuro imaging protocol that utilizes an anatomical atlas of the human head to guide Diffuse optical tomography of human brain activation. The protocol is demonstrated by imaging the hemodynamic response to median nerve stimulation in three healthy subjects, and comparing the images obtained using a head atlas with the images obtained using the subject-specific head anatomy. The results indicate that using the head atlas anatomy it is possible to reconstruct the location of the brain activation to the expected gyrus of the brain, in agreement with the results obtained with the subject-specific head anatomy. The benefits of this novel method derive from eliminating the need for subject-specific head anatomy and thus obviating the need for a subject-specific MRI to improve the anatomical interpretation of Diffuse optical tomography images of brain activation.
Diffuse Optical Tomography; NIRS; anatomical atlas; MRI; segmentation; registration; inverse problem; human study; somatosensory; PACS: 87.19.lf; PACS: 87.19.lh
An atlas-based IMRT planning technique for prostate cancer was developed and evaluated. A multi-dose atlas was built based on the anatomy patterns of the patients, more specifically, the Percent Distance to the Prostate (PDP) and the concaveness angle formed by the seminal vesicles relative to the anterior-posterior axis. The 70-case dataset was classified using a k-medoids clustering analysis to recognize anatomy pattern variations in the dataset. The best classification, defined by the number of classes or medoids, was determined by the largest value of the average silhouette width. Reference plans from each class formed a multi-dose atlas. The atlas-guided planning (AGP) technique started with matching the new case anatomy pattern to one of the reference cases in the atlas; then a deformable registration between the atlas and new case anatomies transferred the dose from the atlas to the new case to guide inverse planning with full automation. Additional 20 clinical cases were re-planned to evaluate the AGP technique. Dosimetric properties between AGP and clinical plans were evaluated. The classification analysis determined that the 5-case atlas would best represent anatomy patterns for the patient cohort. AGP took approximately 1 min on average (corresponding to 70 iterations of optimization) for all cases. When dosimetric parameters were compared, the differences between AGP and clinical plans were less than 3.5%, albeit some statistical significances observed: Homogeneity index (p > 0.05), conformity index (p < 0.01), bladder gEUD (p < 0.01), and rectum gEUD (p = 0.02). Atlas-guided treatment planning is feasible and efficient. Atlas predicted dose can effectively guide the optimizer to achieve plan quality comparable to that of clinical plans.
pattern recognition; atlas; prostate cancer; IMRT
Conflicts can occur between the principle of freedom of information treasured by librarians and ethical standards of scientific research involving the propriety of using data derived from immoral or dishonorable experimentation. A prime example of this conflict was brought to the attention of the medical and library communities in 1995 when articles claiming that the subjects of the illustrations in the classic anatomy atlas, Eduard Pernkopf's Topographische Anatomie des Menschen, were victims of the Nazi holocaust. While few have disputed the accuracy, artistic, or educational value of the Pernkopf atlas, some have argued that the use of such subjects violates standards of medical ethics involving inhuman and degrading treatment of subjects or disrespect of a human corpse. Efforts were made to remove the book from medical libraries. In this article, the history of the Pernkopf atlas and the controversy surrounding it are reviewed. The results of a survey of academic medical libraries concerning their treatment of the Pernkopf atlas are reported, and the ethical implications of these issues as they affect the responsibilities of librarians is discussed.
Atlases of the human brain, in health and disease, provide a comprehensive framework for understanding brain structure and function. The complexity and variability of brain structure, especially in the gyral patterns of the human cortex, present challenges in creating standardized brain atlases that reflect the anatomy of a population. This paper introduces the concept of a population-based, disease-specific brain atlas that can reflect the unique anatomy and physiology of a particular clinical subpopulation. Based on well-characterized patient groups, disease-specific atlases contain thousands of structure models, composite maps, average templates, and visualizations of structural variability, asymmetry and group-specific differences. They correlate the structural, metabolic, molecular and histologic hallmarks of the disease. Rather than simply fusing information from multiple subjects and sources, new mathematical strategies are introduced to resolve group-specific features not apparent in individual scans. High-dimensional elastic mappings, based on covariant partial differential equations, are developed to encode patterns of cortical variation. In the resulting brain atlas, disease-specific features and regional asymmetries emerge that are not apparent in individual anatomies. The resulting probabilistic atlas can identify patterns of altered structure and function, and can guide algorithms for knowledge-based image analysis, automated image labeling, tissue classification, data mining and functional image analysis.
Imaging of the human fetus using magnetic resonance (MR) is an essential tool for quantitative studies of normal as well as abnormal brain development in utero. However, because of fundamental differences in tissue types, tissue properties and tissue distribution between the fetal and adult brain, automated tissue segmentation techniques developed for adult brain anatomy are unsuitable for this data. In this paper, we describe methodology for automatic atlas-based segmentation of individual tissue types in motion-corrected 3D volumes reconstructed from clinical MR scans of the fetal brain. To generate anatomically correct automatic segmentations, we create a set of accurate manual delineations and build an in utero 3D statistical atlas of tissue distribution incorporating developing grey and white matter as well as transient tissue types such as the germinal matrix. The probabilistic atlas is associated with an unbiased average shape and intensity template for registration of new subject images to the space of the atlas. Quantitative whole brain 3D validation of tissue labeling performed on a set of 14 fetal MR scans (20.57–22.86 weeks gestational age) demonstrates that this atlas-based EM segmentation approach achieves consistently high DSC performance for the main tissue types in the fetal brain. This work indicates that reliable measures of brain development can be automatically derived from clinical MR imaging and opens up possibility of further 3D volumetric and morphometric studies with multiple fetal subjects.
Segmentation of brain images often requires a statistical atlas for providing prior information about the spatial position of different structures. A major limitation of atlas-based segmentation algorithms is their deficiency in analyzing brains that have a large deviation from the population used in the construction of the atlas. We present an expectation-maximization framework based on a Dirichlet distribution to adapt a statistical atlas to the underlying subject. Our model combines anatomical priors with the subject’s own anatomy, resulting in a subject specific atlas which we call an “adaptive atlas”. The generation of this adaptive atlas does not require the subject to have an anatomy similar to that of the atlas population, nor does it rely on the availability of an ensemble of similar images. The proposed method shows a significant improvement over current segmentation approaches when applied to subjects with severe ventriculomegaly, where the anatomy deviates significantly from the atlas population. Furthermore, high levels of accuracy are maintained when the method is applied to subjects with healthy anatomy.
The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.
brain atlas; connectivity-based parcellation; diffusion tensor imaging; functional characterization; resting-state functional connectivity
An interactive atlas of histology was developed for online use by chiropractic students to enable them to practice and self-assess their ability to identify various histological structures. This article discusses the steps in the development, implementation, and usefulness of an interactive atlas of histology for students who take histology examinations.
The atlas was developed by digitizing images imported through a video-microscope using actual microscope slides. Leica EWS 2100 and PowerPoint software were used to construct the atlas. The usefulness of the atlas was assessed through a comparison of histology exam scores between four classes before and four classes after the use of the atlas. Analysis of admissions data, including overall grade point average (GPA), science and nonscience GPA, and a number of course units, was done initially to avoid any identifiable differences in the academic competency between the two being compared. A survey of the students was also done to assess atlas usefulness and students' satisfaction with the atlas.
Analysis of histology exam scores showed that the average scores in the lab exam were significantly higher for the classes that used the atlas. Survey results showed a high level of student satisfaction with the atlas.
The development and use of an online interactive atlas of histology for chiropractic students helped to improve lab exams scores. In addition, students were satisfied with the features and usefulness of this atlas.
atlases [publication type]; chiropractic; education; histology; technology
A World Wide Web Common Gateway Interface package is described for accessing existing online interactive atlases of anatomy. The Web interface accesses the same 2-D and 3-D images of human neuroanatomy, knee anatomy and thoracic viscera that are currently accessed by a custom interactive atlas in distance learning courses. Although the Web interface is too slow to replace the existing atlas, it provides a parallel access path that has much broader potential for development of a distributed distance learning network in anatomy. By maintaining both access methods to the same information sources we continue to satisfy the fast interactivity needs for our local courses, while at the same time providing a migration path to the Web as the capabilities of Web browsers evolve.
For the benefit of the first-year gross anatomy students, we digitized and published on a Web site images that had been collected over a 30-year period. We provided a CD-ROM (compact disk, read-only media) containing the image set in higher quality format to students and faculty. We supplemented basic images with hot topics such as CT angiography, virtual colonography, computer-aided diagnosis, and 3D post-processing. Full motion video and moving JPEG (Joint Photo Expert Group) animations were integrated into the atlas. On the post course questionnaire medical students reported that the images on CD-ROM were helpful during the course and for review prior to examinations. Faculty and medical students used the CD-ROM for problem-based learning sections and facilitator training. The images were clear and easily projected during review sessions and were useful for the small group sessions, where they served as examples of normal anatomy.
Re-engineering; teaching file; Internet-based; CD-ROM
We are developing a three-dimensional (3D) atlas of the human embryonic brain using anatomical landmarks and gene expression data to define major subdivisions through 12 stages of development (Carnegie Stages [CS] 12-23; approx 26-56 days post conception [dpc]). Virtual 3D anatomical models are generated from intact specimens using optical projection tomography (OPT). Using MAPaint software, selected gene expression data, gathered using standard methods of in situ hybridisation and immunohistochemistry, are mapped to a representative 3D model for each chosen Carnegie stage. In these models, anatomical domains, defined on the basis of morphological landmarks and comparative knowledge of expression patterns in vertebrates, are linked to a developmental neuroanatomic ontology. Human gene expression patterns for genes with characteristic expression in different vertebrates (e.g. PAX6, GAD65 and OLIG2) are being used to confirm and/or refine the human anatomical domain boundaries. We have also developed interpolation software that digitally generates a full domain from partial data. Currently, the 3D models and a preliminary set of anatomical domains and ontology are available on the atlas pages along with gene expression data from approximately 100 genes in the HUDSEN Human Spatial Gene Expression Database (www.hudsen.org). The aim is that full 3D data will be generated from expression data used to define a more detailed set of anatomical domains linked to a more advanced anatomy ontology and all of these will be available online, contributing to the long-term goal of the atlas which is to help maximise the effective use and dissemination of data wherever it is generated.
Human embryo; 3D atlas; Gene Expression; OPT; database
To develop a video-based educational tool designed for teaching thoracic anatomy and to examine whether this tool would increase students’ stimulation and motivation for learning anatomy.
Our video-based tool was developed by recording different thoracoscopic procedures focusing on intraoperative live thoracic anatomy. The tool was then integrated into a pre-existing program for first year medical students (n = 150), and included cadaver dissection of the thorax and review of clinical problem scenarios of the respiratory system. Students were guided through a viewing of the videotape that demonstrated live anatomy of the thorax (15 minutes) and then asked to complete a 5-point Likert-type questionnaire assessing the video's usefulness. Apart from this, a small group of entirely different set of students was divided into two groups, one group to view the 15-minute video presentation of thoracoscopy and chest anatomy and the other group to attend a 15-minute lecture of chest anatomy using radiological images. Both groups took a 10-item pretest and post-test multiple choice questions examination to assess short-term knowledge gained.
Of 150 medical students, 119 completed the questionnaires, 88.6% were satisfied with the thoracoscopic video as a teaching tool, 86.4% were satisfied with the quality of the images, 69.2% perceived it to be beneficial in learning anatomy, 96.2% increased their interest in learning anatomy, and 88.5% wanted this new teaching tool to be implemented to the curriculum. Majority (80.7%) of the students increased their interest in surgery as a future career. Post-test scores were significantly higher in the thoracoscopy group (P = 0.0175).
Incorporating live surgery using thoracoscopic video presentation in the gross anatomy teaching curriculum had high acceptance and satisfaction scores from first year medical students. The video increased students’ interest in learning, in clinically applying anatomic fact, and in surgery as a future career.
Medical students; thoracic anatomy; thoracoscopy
Dopaminergic networks modulate neural processing across a spectrum of function from perception to learning to action. Multiple organizational schemes based on anatomy and function have been proposed for dopaminergic nuclei in the midbrain. One schema originating in rodent models delineated ventral tegmental area (VTA), implicated in complex behaviors like addiction, from more lateral substantia nigra (SN), preferentially implicated in movement. However, because anatomy and function in rodent midbrain differs from the primate midbrain in important ways, the utility of this distinction for human neuroscience has been questioned. We asked whether functional definition of networks within the human dopaminergic midbrain would recapitulate this traditional anatomical topology. We first developed a method for reliably defining SN and VTA in humans at conventional MRI resolution. Hand-drawn VTA and SN regions-of-interest (ROIs) were constructed for 50 participants, using individually-localized anatomical landmarks and signal intensity. Individual segmentation was used in seed-based functional connectivity analysis of resting-state functional MRI data; results of this analysis recapitulated traditional anatomical targets of the VTA versus SN. Next, we constructed a probabilistic atlas of the VTA, SN, and the dopaminergic midbrain region comprised (SN plus VTA) from individual hand-drawn ROIs. The combined probabilistic (VTA plus SN) ROI was then used for connectivity-based dual-regression analysis in two independent resting-state datasets (n=69 and n=79). Results of the connectivity-based, dual-regression functional segmentation recapitulated results of the anatomical segmentation, validating the utility of this probabilistic atlas for future research.
VTA; SN; resting-state; ICA; functional connectivity; probabilistic atlas
Currently no high resolution three-dimensional (3-D) digital atlas exists that is optimized for normal human adult anatomy. We have developed the methods for defining, constructing and evaluating a “minimal deformation target” MDT brain for multi-subject studies, which produces a single reproducible target based on the common features of a group of brain images. We are building a digital brain atlas, based on a high-resolution, high contrast MR study — CH brain. In a preliminary study (N=27) MDT optimization of the CH brain resulted in a significant reduction of its individual features, including changes in the central sulcus, Sylvian fissure, ventricular system and temporal lobe regions. The atlas will be created by optimizing the CH brain to a large population (N>100) of normal subjects
Modeling and analysis of MR images of the developing human brain is a challenge due to rapid changes in brain morphology and morphometry. We present an approach to the construction of a spatiotemporal atlas of the fetal brain with temporal models of MR intensity, tissue probability and shape changes. This spatiotemporal model is created from a set of reconstructed MR images of fetal subjects with different gestational ages. Groupwise registration of manual segmentations and voxelwise nonlinear modeling allow us to capture the appearance, disappearance and spatial variation of brain structures over time. Applying this model to atlas-based segmentation, we generate age-specific MR templates and tissue probability maps and use them to initialize automatic tissue delineation in new MR images. The choice of model parameters and the final performance are evaluated using clinical MR scans of young fetuses with gestational ages ranging from 20.57 to 24.71 weeks. Experimental results indicate that quadratic temporal models can correctly capture growth-related changes in the fetal brain anatomy and provide improvement in accuracy of atlas-based tissue segmentation.
Structural MRI; Fetal imaging; Atlas building; Tissue segmentation
A method for automated location of shape differences in diseased anatomical structures via high resolution biomedical atlases annotated with labels from formal ontologies is described. In particular, a high resolution magnetic resonance image of the myocardium of the human left ventricle was segmented and annotated with structural terms from an extracted subset of the Foundational Model of Anatomy ontology. The atlas was registered to the end systole template of a previous study of left ventricular remodeling in cardiomyopathy using a diffeomorphic registration algorithm. The previous study used thresholding and visual inspection to locate a region of statistical significance which distinguished patients with ischemic cardiomyopathy from those with nonischemic cardiomyopathy. Using semantic technologies and the deformed annotated atlas, this location was more precisely found. Although this study used only a cardiac atlas, it provides a proof-of-concept that ontologically labeled biomedical atlases of any anatomical structure can be used to automate location-based inferences.
Ontologies; Medical Atlases; Cardiac Left Ventricle; Computational Anatomy
Due to the rapid anatomical changes that occur within the brain structure in early human development and the significant differences between infant brains and the widely used standard adult templates, it becomes increasingly important to utilize appropriate age- and population-specific average templates when analyzing infant neuroimaging data. In this study we created a new and highly detailed age-specific unbiased average head template in a standard MNI152-like infant coordinate system for healthy, typically developing 6-month-old infants by performing linear normalization, diffeomorphic normalization and iterative averaging processing on 60 subjects’ structural images. The resulting age-specific average templates in a standard MNI152-like infant coordinate system demonstrate sharper anatomical detail and clarity compared to existing infant average templates and successfully retains the average head size of the 6-month-old infant. An example usage of the average infant templates transforms magnetoencephalography (MEG) estimated activity locations from MEG’s subject-specific head coordinate space to the standard MNI152-like infant coordinate space. We also created a new atlas that reflects the true 6-month-old infant brain anatomy. Average templates and atlas are publicly available on our website (http://ilabs.washington.edu/6-m-templates-atlas).
Background: Synostosis or fusion of atlas with occipital bone is known as occipitocervical synostosis, occipitalization of the atlas, or atlanto-occipital fusion. This is a rare congenital malformation at craniovertebral junction. Its incidence ranges from 0.08%–3% in general population. Occipitocervical synostosis result in narrowing of foramen magnum which may compress the brain stem, vertebral artery and cranial nerves. Knowledge of occipitocervical synostosis is important for the surgeons during the surgeries in the craniovertebral region. Hence, the present study was undertaken to determine the incidence and to describe the morphology of the occipitocervical synostosis.
Material and Methods: Two-hundred dry adult human skulls of Indian origin were studied in the Department of anatomy. The base of these skulls was observed for presence of atlanto-occipital fusion. The anteroposterior and transverse diameter of the foramen magnum and diameter of the inferior articular facets were measured in these skulls using digital vernier caliper.
Results: Two skulls showed occipitalization of Atlas (1%). One of the skulls showed partial fusion (0.5%) while the other showed complete occipitalization (0.5%).
Conclusion: The knowledge of bony fusion between the cranial base and the first cervical vertebra is important as such skeletal anomaly may result in sudden unexpected death due to compression of the vital structures such as brain stem and vertebral arteries.
Synostosis; Occipitocervical; Vertebra; Atlas; Proatlas; Sclerotome