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A picture archive and communications system (PACS) is a rich source of images and data suitable for creating electronic teaching files (ETF). However, the potential for PACS to support nonclinical applications has not been fully realized: at present there is no mechanism for PACS to identify and store teaching files; neither is there a standardized method for sharing such teaching images. The Medical Image Resource Center (MIRC) is a new central image repository that defines standards for data exchange among different centers. We developed an ETF server that retrieves digital imaging and communication in medicine (DICOM) images from PACS, and enables users to create teaching files that conform to the new MIRC schema. We test-populated our ETF server with illustrative images from the clinical case load of the National Neuroscience Institute, Singapore. Together, PACS and MIRC have the potential to benefit radiology teaching and research. [ABSTRACT FROM AUTHOR]

Volumetric imaging (computed tomography and magnetic resonance imaging) provides increased diagnostic detail but is associated with the problem of navigation through large amounts of data. In an attempt to overcome this problem, a novel 3D navigation tool has been designed and developed that is based on an alternative input device. A 3D mouse allows for simultaneous definition of position and orientation of orthogonal or oblique multiplanar reformatted images or slabs, which are presented within a virtual 3D scene together with the volume-rendered data set and additionally as 2D images. Slabs are visualized with maximum intensity projection, average intensity projection, or standard volume rendering technique. A prototype has been implemented based on PC technology that has been tested by several radiologists. It has shown to be easily understandable and usable after a very short learning phase. Our solution may help to fully exploit the diagnostic potential of volumetric imaging by allowing for a more efficient reading process compared to currently deployed solutions based on conventional mouse and keyboard. [ABSTRACT FROM AUTHOR]

The presentation of cortical arteries is challenging, as most of their course is hidden in the depth of the sulci. Despite that, demonstrating the arteries on the cortical surface is a standard way of their presentation. To keep advantages of surface presentation while lessening its limitation, we propose a novel context-related method of cerebrovasculature presentation by cortical openings consisting in the removal of a selected region from the cortical mantle and exposing underlying structures. We also introduce a reverse than standard vessel-to-context mapping from a gyrus/lobule to vessels supplying it.The method has the following steps: define a cortical opening, develop a tool to perform them, create cortical openings for gyri and lobules with underlying white matter and intracranial arteries, generate labeled and parcellated images for the created openings, and integrate the cortical opening images with the NOW in BRAIN public repository of 8600 3D neuroimages.The cortical openings are created for 64 gyri and six lobules for the left and right cerebral hemispheres resulting in 210 images arranged in triples as spatially corresponding non-parcellated and unlabeled, parcellated by color and unlabeled, and parcellated and labeled images.The cortical opening approach, generally, increases vessel exposure in a higher number of depicted branches, revealing arteries otherwise hidden deep in sulci, a more complete vessel course, and a lower number of required views.The gyrus/lobule-to-arteries mapping facilitates exploration of a studied region, encapsulates all local arteries, and reduces vascular complexity by decomposing the entire vascular system into smaller sets involved in the studied region., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

One of the key challenges in neuroscience is to generate the human nanoscale connectome which requires comprehensive knowledge of synaptome forming the neural microcircuits. The synaptic architecture determines limits of individual mental capacity and provides the framework for understanding neurologic disorders. Here, I address morphology modeling and storage estimation for the human synaptome at the nanoscale. A synapse is defined as a pair of pairs [(presynaptic_neuron),(presynaptic_axonal_terminal);(postsynaptic_neuron),(postsynaptic_dendritic_terminal)]. Center coordinates, radius, and identifier characterize a dendritic or axonal terminal. A synapse comprises topology with the paired neuron and terminal identifiers, location with terminal coordinates, and geometry with terminal radii. The storage required for the synaptome depends on the number of synapses and storage necessary for a single synapse determined by a synaptic model. I introduce three synaptic models: topologic with topology, point with topology and location, and geometric with topology, location, and geometry. To accommodate for a wide range of variations in the numbers of neurons and synapses reported in the literature, four cases of neurons (30;86;100;138 billion) and three cases of synapses per neuron (1,000;10,000;30,000) are considered with three full and simplified (to reduce storage) synaptic models resulting in total 72 cases of storage estimation. The full(simplified) synaptic model of the entire human brain requires from 0.21(0.14) petabytes (PB) to 28.98(18.63) PB for the topologic model, from 0.57(0.32) PB to 78.66(43.47) PB for the point model, and from 0.69(0.38) PB to 95.22(51.75) PB for the geometric model. The full(simplified) synaptic model of the cortex needs from 86.80(55.80) TB to 2.60(1.67) PB for the topologic model, from 235.60(130.02) TB to 7.07(3.91) PB for the point model, and from 285.20(155.00) TB to 8.56(4.65) PB for the geometric model. The topologic model is sufficient to compute the connectome's topology, but it is still too big to be stored on today's top supercomputers related to neuroscience. Frontier, the world's most powerful supercomputer for 86 billion neurons can handle the nanoscale synaptome in the range of 1,000-10,000 synapses per neuron. To my best knowledge, this is the first big data work attempting to provide storage estimation for the human nanoscale synaptome., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wieslaw L. Nowinski. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Stroke management employs a variety of diagnostic imaging modalities, image processing and analysis methods, and treatment procedures. This work categorizes methods for stroke imaging, image processing and analysis, and treatment, and provides their taxonomies illustrated by a state-of-the-art review. Imaging plays a critical role in stroke management, and the most frequently employed modalities are computed tomography (CT) and magnetic resonance (MR). CT includes unenhanced non-contrast CT as the first-line diagnosis, CT angiography, and CT perfusion. MR is the most complete method to examine stroke patients. MR angiography is useful to evaluate the severity of artery stenosis, vascular occlusion, and collateral flow. Diffusion-weighted imaging is the gold standard for evaluating ischemia. MR perfusion-weighted imaging assesses the penumbra. The stroke image processing methods are divided into non-atlas/template-based and atlas/template-based. The non-atlas/template-based methods are subdivided into intensity and contrast transformations, local segmentation-related, anatomy-guided, global density-guided, and artificial intelligence/deep learning-based. The atlas/template-based methods are subdivided into intensity templates and atlases with three atlas types: anatomy atlases, vascular atlases, and lesion-derived atlases. The treatment procedures for arterial and venous strokes include intravenous and intraarterial thrombolysis and mechanical thrombectomy. This work captures the state-of-the-art in stroke management summarized in the form of comprehensive and straightforward taxonomy diagrams. All three introduced taxonomies in diagnostic imaging, image processing and analysis, and treatment are widely illustrated and compared against other state-of-the-art classifications.

The human cerebral cortex is highly convoluted forming patterns of gyri separated by sulci. The cerebral sulci and gyri are fundamental in cortical anatomy as well as neuroimage processing and analysis. Narrow and deep cerebral sulci are not fully discernible either on the cortical or white matter surface. To cope with this limitation, I propose a new sulci presentation method that employs the inner cortical surface for sulci examination from the inside of the cerebrum. The method has four steps, construct the cortical surface, segment and label the sulci, dissect (open) the cortical surface, and explore the fully exposed sulci from the inside. The inside sulcal maps are created for the left and right lateral, left and right medial, and basal hemispheric surfaces with the sulci parcellated by color and labeled. These three-dimensional sulcal maps presented here are probably the first of this kind created. The proposed method demonstrates the full course and depths of sulci, including narrow, deep, and/or convoluted sulci, which has an educational value and facilitates their quantification. In particular, it provides a straightforward identification of sulcal pits which are valuable markers in studying neurologic disorders. It enhances the visibility of sulci variations by exposing branches, segments, and inter-sulcal continuity. The inside view also clearly demonstrates the sulcal wall skewness along with its variability and enables its assessment. Lastly, this method exposes the sulcal 3-hinges introduced here., (© 2023 Anatomical Society.)

Purpose : Integrating neuroradiology with neuroanatomy is essential in medical neuroeducation and neuroimage interpretation. To bridge 2D neuroradiology and 3D neuroanatomy, spatially correlated pairs of labeled images were employed, planar radiologic, and planar-surface combined. Research design : The method employs a 3D fully parcellated and labeled brain atlas extended to the head and neck with about 3000 3D components to create planar radiologic and surface neuroanatomic images. The atlas handles reformatted radiologic images as 3D objects using texture mapping which provides consistency with polygonal 3D neuroanatomic structures. This ensures a precise spatial correspondence of dual 2D-2D/3D images for any composed 3D scene reformatted in arbitrary orientation. The sequences of labeled dual images were created spanning a structure/system of interest in multiple orientations. To facilitate image searching, the image name encodes its content, orientation, and stereotactic location. Results : Labeled dual 2D-2D/3D neuroimage sequences in multiple orientations were created for the cerebrum, brainstem, deep nuclei, cerebral ventricles, intracranial arteries, dural sinuses, extracranial arteries, extracranial veins, trigeminal nerve, head muscles, glands, bones of cranium, and visual system. They all were hierarchically organized as a planar-surface gallery with 42 folders and 502 neuroimages. This gallery was integrated with a public NOW in BRAIN repository at www.nowinbrain.org with more than 7700 neuroimages. Conclusions : Owing to its advantages, simplicity, and free availability, this resource is useful for medical students, residents, educators, and clinicians to study the brain, head, and neck as well as to prepare presentations and teaching materials. The approach might potentially enhance image interpretation by integrating brain atlases with radiologic workstations.

Although the term sulcus is known for almost four centuries, its formal, precise, consistent, constructive, and quantitative definition is practically lacking. As the cerebral sulci (and gyri) are vital in cortical anatomy which, in turn, is central in neuroeducation and neuroimage processing, a new sulcus definition is needed. The contribution of this work is threefold, namely to (1) propose a new, morphology-based definition of the term sulcus (and consequently that of gyrus), (2) formulate a constructive method for sulcus calculation, and (3) provide a novel way for the presentation of sulci. The sulcus is defined here as a volumetric region on the cortical mantle between adjacent gyri separated from them at the levels of their gyral white matter crest lines. Consequently, the sulcal inner surface is demarcated by the crest lines of the gyral white matter of its adjacent gyri. Correspondingly, the gyrus is defined as a volumetric region on the cortical mantle separated from its adjacent sulci at the level of its gyral white matter crest line. This volumetric sulcus definition is conceptually simple, anatomy-based, educationally friendly, quantitative, and constructive. Considering the sulcus as a volumetric object is a major differentiation from other works. Based on the introduced sulcus definition, a method for volumetric sulcus construction is proposed in two, conceptually straightforward, steps, namely, sulcal intersection formation followed by its propagation which steps are to be repeated for every sulcal segment. These sulcal and gyral constructions can be automated by applying existing methods and public tools. As a volumetric sulcus forms an imprint into the white matter, this enables prominent sulcus presentation. Since this type of presentation is novel yet unfamiliar to the reader, also a dual surface presentation was proposed here by employing the spatially co-registered white matter and cortical surfaces. The results were presented as dual surface labeled sulci on eight standard orthogonal views, anterior, left lateral, posterior, right lateral, superior, inferior, medial left, and medial right by using a 3D brain atlas. Moreover, additional 108 labeled images were created with sulcus-oriented views for 27 individual left and right sulci forming 54 dual white matter-cortical surface images strengthening in this way the educational value of the proposed approach. These images were included for public use in the NOWinBRAIN neuroimage repository with over 7700 3D images available at www.nowinbrain.org. The results demonstrated the superiority of white matter surface sulci presentation over the standard cortical surface and cross-sectional presentations in terms of sulcal course, continuity, size, shape, width, depth, side branches, and pattern. To my best knowledge, this is the first work ever presenting the labeling of sulci on all cerebral white matter surfaces as well as on dual white matter-cortical surfaces. Additionally to neuroeducation, three other applications of the proposed approach were discussed, sulcal reference maps, sulcus quantification in terms of new parameters introduced here (sulcal volume, wall skewness, and the number of white matter basins), and an atlas-assisted tool for exploration and studying of cerebral sulci and gyri ., (© 2022 Anatomical Society.)

Despite the tremendous development of various brain-related resources, a large, systematic, comprehensive, extendable, and beautiful repository of 3D reconstructed images of a living human brain expanded to the head and neck is not yet available. I have created such a novel repository and populated it with images derived from a 3D atlas constructed from 3/7 Tesla MRI and high-resolution CT scans. This web-based repository contains 6 galleries hierarchically organized in 444 albums and sub-albums with 5,156 images. Its original features include a systematic design in terms of multiple standard views, modes of presentation, and spatially co-registered image sequences; multi-tissue class galleries constructed from 26 primary tissue classes and 199 sub-classes; and a unique image naming syntax enabling image searching based solely on the image name. Anatomic structures are displayed in 6 standard views (anterior, left, posterior, right, superior, inferior), all views having the same brain size, and optionally with additional arbitrary views. In each view, the images are shown as sequences in three standard modes of presentation, non-parcellated unlabeled, parcellated unlabeled, and parcellated labeled. There are two types of spatially co-registered image sequences (imitating image layers and enabling animation creation), the appearance image sequence (for standard views) and the context image sequence (with a growing number of tissue classes). Color-coded neuroanatomic content makes the brain beautiful and facilitates its learning and understanding. This unique repository is freely available and easily accessible online at www.nowinbrain.org for a wide spectrum of users in medicine and beyond. Its future extensions are in progress., (© 2021. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Human brain atlas development is predominantly research-oriented and the use of atlases in clinical practice is limited. Here I introduce a new definition of a reference human brain atlas that serves education, research and clinical applications, and is extendable by its user. Subsequently, an architecture of a multi-purpose, user-extendable reference human brain atlas is proposed and its implementation discussed. The human brain atlas is defined as a vehicle to gather, present, use, share, and discover knowledge about the human brain with highly organized content, tools enabling a wide range of its applications, massive and heterogeneous knowledge database, and means for content and knowledge growing by its users. The proposed architecture determines major components of the atlas, their mutual relationships, and functional roles. It contains four functional units, core cerebral models, knowledge database, research and clinical data input and conversion, and toolkit (supporting processing, content extension, atlas individualization, navigation, exploration, and display), all united by a user interface. Each unit is described in terms of its function, component modules and sub-modules, data handling, and implementation aspects. This novel architecture supports brain knowledge gathering, presentation, use, sharing, and discovery and is broadly applicable and useful in student- and educator-oriented neuroeducation for knowledge presentation and communication, research for knowledge acquisition, aggregation and discovery, and clinical applications in decision making support for prevention, diagnosis, treatment, monitoring, and prediction. It establishes a backbone for designing and developing new, multi-purpose and user-extendable brain atlas platforms, serving as a potential standard across labs, hospitals, and medical schools., (© 2021. The Author(s).)

Objective  We evaluated the usefulness of a three-dimensional (3D) interactive atlas to illustrate and teach surgical skull base anatomy in a clinical setting. Study Design  A highly detailed atlas of the adult human skull base was created from multiple high-resolution magnetic resonance imaging (MRI) and computed tomography (CT) scans of a healthy Caucasian male. It includes the parcellated and labeled bony skull base, intra- and extracranial vasculature, cranial nerves, cerebrum, cerebellum, and brainstem. We are reporting retrospectively on our experiences with employing the atlas for the simulation and teaching of neurosurgical approaches and concepts in a clinical setting. Setting  The study was conducted at the University Hospital Mainz, Germany, and Hirslanden Hospital, Zürich, Switzerland. Participants  Medical students and neurosurgical residents participated in this study. Results  Handling the layered graphical user interface of the atlas requires some training; however, navigating the detailed 3D content from intraoperative perspectives led to quick comprehension of anatomical relationships that are otherwise difficult to perceive. Students and residents appreciated the collaborative learning effect when working with the atlas on large projected screens and markedly improved their anatomical knowledge after interacting with the software. Conclusion  The skull base atlas provides an effective way to study essential surgical anatomy and to teach operative strategies in this complex region. Interactive 3D computer graphical environments are highly suitable for conveying complex anatomy and to train and review surgical concepts. They remain underutilized in clinical practice., Competing Interests: Conflict of Interest All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements) or nonfinancial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs) in the subject matter or materials discussed in this manuscript., (Thieme. All rights reserved.)

Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.

Noncontrast Computed Tomography (NCCT) of the brain has been the first-line diagnosis for emergency evaluation of acute stroke, so a rapid and automated detection, localization, and/or segmentation of ischemic lesions is of great importance. We provide the state-of-the-art review of methods for automated detection, localization, and/or segmentation of ischemic lesions on NCCT in human brain scans along with their comparison, evaluation, and classification. Twenty-two methods are (1) reviewed and evaluated; (2) grouped into image processing and analysis-based methods (11 methods), brain atlas-based methods (two methods), intensity template-based methods (1 method), Stroke Imaging Marker-based methods (two methods), and Artificial Intelligence-based methods (six methods); and (3) properties of these groups of methods are characterized. A new method classification scheme is proposed as a 2 × 2 matrix with local versus global processing and analysis, and density versus spatial sampling. Future studies are necessary to develop more efficient methods directed toward deep learning methods as well as combining the global methods with a high sampling both in space and density for the merged radiologic and neurologic data., Competing Interests: The authors declare there are no competing interests., (©2020 Nowinski et al.)

Stroke is a leading cause of death and a major cause of permanent disability. Its management is demanding because of variety of protocols, imaging modalities, pulse sequences, hemodynamic maps, criteria for treatment, and time constraints to promptly evaluate and treat. To cope with some of these issues, we propose novel, patented solutions in stroke management by employing multiple brain atlases for diagnosis, treatment, and prediction. Numerous and diverse CT and MRI scans are used: ARIC cohort, ischemic and hemorrhagic stroke CT cases, MRI cases with multiple pulse sequences, and 128 stroke CT patients, each with 170 variables and one year follow-up. The method employs brain atlases of anatomy, blood supply territories, and probabilistic stroke atlas. It rapidly maps an atlas to scan and provides atlas-assisted scan processing. Atlas-to-scan mapping is application-dependent and handles three types of regions of interest (ROIs): atlas-defined ROIs, atlas-quantified ROIs, and ROIs creating an atlas. An ROI is defined by atlas-guided anatomy or scan-derived pathology. The atlas defines ROI or quantifies it. A brain atlas potential has been illustrated in four atlas-assisted applications for stroke occurrence prediction and screening, rapid and automatic stroke diagnosis in emergency room, quantitative decision support in thrombolysis in ischemic stroke, and stroke outcome prediction and treatment assessment. The use of brain atlases in stroke has many potential advantages, including rapid processing, automated and robust handling, wide range of applications, and quantitative assessment. Further work is needed to enhance the developed prototypes, clinically validate proposed solutions, and introduce them to clinical practice.

Background: The skull base region is anatomically complex and poses surgical challenges. Although many textbooks describe this region illustrated well with drawings, scans and photographs, a complete, 3D, electronic, interactive, realistic, fully segmented and labeled, and stereotactic atlas of the skull base has not yet been built. Our goal is to create a 3D electronic atlas of the adult human skull base along with interactive tools for structure manipulation, exploration, and quantification., Methods: Multiple in vivo 3/7 T MRI and high-resolution CT scans of the same normal, male head specimen have been acquired. From the scans, by employing dedicated tools and modeling techniques, 3D digital virtual models of the skull, brain, cranial nerves, intra- and extracranial vasculature have earlier been constructed. Integrating these models and developing a browser with dedicated interaction, the skull base atlas has been built., Results: This is the first, to our best knowledge, truly 3D atlas of the adult human skull base that has been created, which includes a fully parcellated and labeled brain, skull, cranial nerves, and intra- and extracranial vasculature., Conclusion: This atlas is a useful aid in understanding and teaching spatial relationships of the skull base anatomy, a helpful tool to generate teaching materials, and a component of any skull base surgical simulator.

We have recently witnessed an explosion of large-scale initiatives and projects addressing mapping, modeling, simulation and atlasing of the human brain, including the BRAIN Initiative, the Human Brain Project, the Human Connectome Project (HCP), the Big Brain, the Blue Brain Project, the Allen Brain Atlas, the Brainnetome, among others. Besides these large and international initiatives, there are numerous mid-size and small brain atlas-related projects. My contribution to these global efforts has been to create adult human brain atlases in health and disease, and to develop atlas-based applications. For over two decades with my R&D lab I developed 35 brain atlases, licensed to 67 companies and made available in about 100 countries. This paper has two objectives. First, it provides an overview of the state of the art in brain atlasing. Second, as it is already 20 years from the release of our first brain atlas, I summarise my past and present efforts, share my experience in atlas creation, validation and commercialisation, compare with the state of the art, and propose future directions.

Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

Purpose: Because clinical evaluation of noncontrast computed tomography (CT) has a poor sensitivity in the evaluation of acute ischemic stroke, computer-aided diagnosis may be able to facilitate the performance. Recently, we introduced a computational method for the detection and localization of visible infarcts. Herein, we aimed to evaluate and extend a previous method, the Stroke Imaging Marker (SIM), to localize nonvisible hyperacute ischemia., Materials and Methods: On the basis of the SIM and its components-the ratio of percentile differences in subranges of Hounsfield Unit (HU) distribution (P-ratio), ratio of voxels count in ranges of brain CT intensity, median HU attenuation value-the infarct localization was performed in 140 early and follow-up scans of 70 patients. In none of the early scans was the infarct visible to a radiologist or an experienced stroke neuroradiologist. The infarcted hemisphere detection rate (HDR) and sensitivity of infarct localization were measured by overlapping the region of detected tissue in the initial scan, with the gold standard set for the fully visible stroke in the follow-up scan., Results: The best performance of the algorithm was found for the P-ratio including seven percentile subranges within the range of 35th-75th percentile. The modified SIM provided a 76% ischemic HDR and 54% sensitivity in spatial localization of hyperacute ischemia (68% among properly detected infarct sides)., Conclusion: The improved SIM is a dedicated and potentially useful tool for hyperacute nonvisible brain infarct detection from CT scans and may contribute to reduction of image-to-needle time in patients eligible for revascularization therapy., (Copyright © 2016 by the American Society of Neuroimaging.)

Human brain atlases, although prevalent in medical education and stereotactic and functional neurosurgery, are not yet applied practically in neuroradiology. In a step towards introducing brain atlases to neuroradiology, we discuss nine different situations of potential atlas use: (1) to support interpretation of brain scans with clearly visible structures (to increase confidence of non-neuroradiologists); (2) to delineate and label scans of low anatomical content (with indiscernible or poorly visible anatomy); (3) to assist in generating the structured report; (4) to assist in interpreting small deep lesions, since an atlas's anatomical parcellation is higher than that of the interpreted scan; (5) to approximate distorted due to pathology (and unknown to the interpreter) anatomy and label it; (6) to cope with data explosion; (7) to assist in the interpretation of functional scans (to label the activation foci with the underlying anatomy and Brodmann's areas); (8) to support ischemic stroke image handling by means of atlases of anatomy and blood supply territories; and (9) to communicate image interpretation results (diagnosis) to others. The usefulness of the atlas for automatic structure identification, localisation, delineation, labelling and quantification, as well as for reporting and communication, potentially increases the interpreter's efficiency and confidence, as well as expedites image interpretation., (© The Author(s) 2016.)

Despite numerous efforts, a fairly complete (holistic) anatomical model of the whole, normal, adult human brain, which is required as the reference in brain studies and clinical applications, has not yet been constructed. Our ultimate objective is to build this kind of atlas from advanced in vivo imaging. This work presents the taxonomy of our currently developed brain atlases and addresses the design, content, functionality, and current results in the holistic atlas development as well as atlas usefulness and future directions. We have developed to date 35 commercial brain atlases (along with numerous research prototypes), licensed to 63 companies and institutions, and made available to medical societies, organizations, medical schools, and individuals. These atlases have been applied in education, research, and clinical applications. Hundreds of thousands of patients have been treated by using our atlases. Based on this experience, the first version of the holistic and reference atlas of the brain, head, and neck has been developed and made available. The atlas has been created from multispectral 3 and 7 Tesla and high-resolution CT in vivo scans. It is fully 3D, scalable, interactive, and highly detailed with about 3,000 labeled components. This atlas forms a foundation for the development of a multi-level molecular, cellular, anatomical, physiological, and behavioral brain atlas platform.

Background: Although the adult human skull is a complex and multifunctional structure, its 3D, complete, realistic, and stereotactic atlas has not yet been created. This work addresses the construction of a 3D interactive atlas of the adult human skull spatially correlated with the brain, cranial nerves, and intracranial vasculature., New Method: The process of atlas construction included computed tomography (CT) high-resolution scan acquisition, skull extraction, skull parcellation, 3D disarticulated bone surface modeling, 3D model simplification, brain-skull registration, 3D surface editing, 3D surface naming and color-coding, integration of the CT-derived 3D bony models with the existing brain atlas, and validation., Results: The virtual skull model created is complete with all 29 bones, including the auditory ossicles (being among the smallest bones). It contains all typical bony features and landmarks., Comparison With Existing Method(s): The created skull model is superior to the existing skull models in terms of completeness, realism, and integration with the brain along with blood vessels and cranial nerves., Conclusions: This skull atlas is valuable for medical students and residents to easily get familiarized with the skull and surrounding anatomy with a few clicks. The atlas is also useful for educators to prepare teaching materials. It may potentially serve as a reference aid in the reading and operating rooms., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Our objective was to construct a 3D, interactive, and reference atlas of the extracranial vasculature spatially correlated with the intracranial blood vessels, cranial nerves, skull, glands, and head muscles.The atlas has been constructed from multiple 3T and 7T magnetic resonance angiogram (MRA) brain scans, and 3T phase contrast and inflow MRA neck scans of the same specimen in the following steps: vessel extraction from the scans, building 3D tubular models of the vessels, spatial registration of the extra- and intracranial vessels, vessel editing, vessel naming and color-coding, vessel simplification, and atlas validation.This new atlas contains 48 names of the extracranial vessels (25 arterial and 23 venous) and it has been integrated with the existing brain atlas.The atlas is valuable for medical students and residents to easily get familiarized with the extracranial vasculature with a few clicks; is useful for educators to prepare teaching materials; and potentially can serve as a reference in the diagnosis of vascular disease and treatment, including craniomaxillofacial surgeries and radiologic interventions of the face and neck., (© The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.)

Objective: Recent genomewide association studies have implicated the calcium channel, voltage-dependent, L type, alpha 1C subunit (CACNA1C) genetic variant in schizophrenia, which is associated with functional brain changes and cognitive deficits in healthy individuals. However, the impact of CACNA1C on brain white matter integrity in schizophrenia remains unclear. On the basis of prior evidence of CACNA1C-mediated changes involving cortical brain regions, we hypothesize that CACNA1C risk variant rs1006737 is associated with reductions of white matter integrity in the frontal, parietal, and temporal regions and cingulate gyrus., Method: A total of 160 Chinese participants (96 DSM-IV-diagnosed patients with schizophrenia and 64 healthy controls) were genotyped by using blood samples and underwent structural magnetic resonance imaging and diffusion tensor imaging scans from 2008 to 2012. Two-way analysis of covariance was employed to examine CACNA1C-related genotype effects, diagnosis effects, and genotype × diagnosis interaction effects on fractional anisotropy (FA) of relevant brain regions., Results: Significant diagnosis-genotype interactions were observed (left frontal lobe mean FA: F₁,₁₅₆ = 6.22, P = .014; left parietal lobe mean FA: F₁,₁₅₆ = 7.14, P = .008; left temporal lobe mean FA: F₁,₁₅₆ = 8.37, P = .004). Compared with patients who were A carriers, patients who were G homozygotes had lower mean FA in the left frontal lobe (F₁,₉₃ = 2.504, P = .014), left parietal lobe (F₁,₉₃ = 2.37, P = .020), and left temporal lobe (F₁,₉₃ = 3.01, P = .003), with standardized effect sizes of -1.43, -1.3, and -1.0, respectively., Conclusions: CACNA1C risk variant rs1006737 affects cortical white matter integrity in schizophrenia. Further imaging genetic investigations on the mediating effect of CACNA1C in schizophrenia can uncover brain circuitries involved in schizophrenia and suggest potential novel targets for intervention., (© Copyright 2014 Physicians Postgraduate Press, Inc.)

Computer-aided detection/diagnosis (CAD) is a key component of routine clinical practice, increasingly used for detection, interpretation, quantification and decision support. Despite a critical need, there is no clinically accepted CAD system for stroke yet. Here we introduce a CAD system for hemorrhagic stroke. This CAD system segments, quantifies, and displays hematoma in 2D/3D, and supports evacuation of hemorrhage by thrombolytic treatment monitoring progression and quantifying clot removal. It supports seven-step workflow: select patient, add a new study, process patient's scans, show segmentation results, plot hematoma volumes, show 3D synchronized time series hematomas, and generate report. The system architecture contains four components: library, tools, application with user interface, and hematoma segmentation algorithm. The tools include a contour editor, 3D surface modeler, 3D volume measure, histogramming, hematoma volume plot, and 3D synchronized time-series hematoma display. The CAD system has been designed and implemented in C++. It has also been employed in the CLEAR and MISTIE phase-III, multicenter clinical trials. This stroke CAD system is potentially useful in research and clinical applications, particularly for clinical trials.

Background and Purpose: Knowledge of outcome prediction is important in stroke management. We propose a lesion size and location-driven method for stroke outcome prediction using a Population-based Stroke Atlas (PSA) linking neurological parameters with neuroimaging in population. The PSA aggregates data from previously treated patients and applies them to currently treated patients. The PSA parameter distribution in the infarct region of a treated patient enables prediction. We introduce a method for PSA calculation, quantify its performance, and use it to illustrate ischemic stroke outcome prediction of modified Rankin Scale (mRS) and Barthel Index (BI)., Methods: The preliminary PSA was constructed from 128 ischemic stroke cases calculated for 8 variants (various data aggregation schemes) and 3 case selection variables (infarct volume, NIHSS at admission, and NIHSS at day 7), each in 4 ranges. Outcome prediction for 9 parameters (mRS at 7th, and mRS and BI at 30th, 90th, 180th, 360th day) was studied using a leave-one-out approach, requiring 589,824 PSA maps to be analyzed., Results: Outcomes predicted for different PSA variants are statistically equivalent, so the simplest and most efficient variant aiming at parameter averaging is employed. This variant allows the PSA to be pre-calculated before prediction. The PSA constrained by infarct volume and NIHSS reduces the average prediction error (absolute difference between the predicted and actual values) by a fraction of 0.796; the use of 3 patient-specific variables further lowers it by 0.538. The PSA-based prediction error for mild and severe outcomes (mRS  =  [2]-[5]) is (0.5-0.7). Prediction takes about 8 seconds., Conclusions: PSA-based prediction of individual and group mRS and BI scores over time is feasible, fast and simple, but its clinical usefulness requires further studies. The case selection operation improves PSA predictability. A multiplicity of PSAs can be computed independently for different datasets at various centers and easily merged, which enables building powerful PSAs over the community.

Characterization of hematomas is essential in scan reading, manual delineation, and designing automatic segmentation algorithms. Our purpose is to characterize the distribution of intraventricular (IVH) and intracerebral hematomas (ICH) in NCCT scans, study their relationship to gray matter (GM), and to introduce a new tool for quantitative hematoma delineation. We used 289 serial retrospective scans of 51 patients. Hematomas were manually delineated in a two-stage process. Hematoma contours generated in the first stage were quantified and enhanced in the second stage. Delineation was based on new quantitative rules and hematoma profiling, and assisted by a dedicated tool superimposing quantitative information on scans with 3D hematoma display. The tool provides: density maps (40-85HU), contrast maps (8/15HU), mean horizontal/vertical contrasts for hematoma contours, and hematoma contours below a specified mean contrast (8HU). White matter (WM) and GM were segmented automatically. IVH/ICH on serial NCCT is characterized by 59.0HU mean, 60.0HU median, 11.6HU standard deviation, 23.9HU mean contrast, -0.99HU/day slope, and -0.24 skewness (changing over time from negative to positive). Its 0.1(st)-99.9(th) percentile range corresponds to 25-88HU range. WM and GM are highly correlated (R (2)=0.88; p<10(-10)) whereas the GM-GS correlation is weak (R (2)=0.14; p<10(-10)). The intersection point of mean GM-hematoma density distributions is at 55.6±5.8HU with the corresponding GM/hematoma percentiles of 88(th)/40(th). Objective characterization of IVH/ICH and stating the rules quantitatively will aid raters to delineate hematomas more robustly and facilitate designing algorithms for automatic hematoma segmentation. Our two-stage process is general and potentially applicable to delineate other pathologies on various modalities more robustly and quantitatively.

Background: Obesity is increasingly prevalent in bipolar disorder (BD) but data about the impact of elevated body mass index (BMI) on brain white-matter integrity in BD are sparse. Based on extant literature largely from structural magnetic resonance imaging (MRI) studies, we hypothesize that increased BMI is associated with decreased fractional anisotropy (FA) in the frontal, temporal, parietal and occipital brain regions early in the course of BD., Method: A total of 26 euthymic adults (12 normal weight and 14 overweight/obese) with remitted first-episode mania (FEM) and 28 controls (13 normal weight and 15 overweight/obese) matched for age, handedness and years of education underwent structural MRI and diffusion tensor imaging scans., Results: There are significant effects of diagnosis by BMI interactions observed especially in the right parietal lobe (adjusted F(1,48) = 5.02, p = 0.030), occipital lobe (adjusted F(1,48) = 10.30, p = 0.002) and temporal lobe (adjusted F(1,48) = 7.92, p = 0.007). Specifically, decreased FA is found in the right parietal (F(1,48) = 5.864, p = 0.023) and occipital lobes (F(1,48) = 4.397, p = 0.047) within overweight/obese patients compared with normal-weight patients with FEM. Compared with overweight/obese controls, decreased FA is observed in right parietal (F(1,48) = 6.708, p = 0.015), temporal (F(1,48) = 10.751, p = 0.003) and occipital (F(1,48) = 9.531, p = 0.005) regions in overweight/obese patients with FEM., Conclusions: Our findings suggest that increased BMI affects temporo-parietal-occipital brain white-matter integrity in FEM. This highlights the need to further elucidate the relationship between obesity and other neural substrates (including subcortical changes) in BD which may clarify brain circuits subserving the association between obesity and clinical outcomes in BD.

Objective: The purpose of this study was to show the spatial relationship of the colonic marginal blood vessels and the teniae coli on CT colonography (CTC) and the use of the marginal blood vessels for supine-prone registration of polyps and for determination of proper connectivity of collapsed colonic segments., Materials and Methods: We manually labeled the marginal blood vessels on 15 CTC examinations. Colon segmentation, centerline extraction, teniae detection, and teniae identification were automatically performed. For assessment of their spatial relationships, the distances from the marginal blood vessels to the three teniae coli and to the colon were measured. Student t tests (paired, two-tailed) were performed to evaluate the differences among these distances. To evaluate the reliability of the marginal vessels as reference points for polyp correlation, we analyzed 20 polyps from 20 additional patients who underwent supine and prone CTC. The average difference of the circumferential polyp position on the supine and prone scans was computed. Student t tests (paired, two-tailed) were performed to evaluate the supine-prone differences of the distance. We performed a study on 10 CTC studies from 10 patients with collapsed colonic segments by manually tracing the marginal blood vessels near the collapsed regions to resolve the ambiguity of the colon path., Results: The average distances (± SD) from the marginal blood vessels to the tenia mesocolica, tenia omentalis, and tenia libera were 20.1 ± 3.1 mm (95% CI, 18.5-21.6 mm), 39.5 ± 4.8 mm (37.1-42.0 mm), and 36.9 ± 4.2 mm (34.8-39.1 mm), respectively. Pairwise comparison showed that these distances to the tenia libera and tenia omentalis were significantly different from the distance to the tenia mesocolica (p < 0.001). The average distance from the marginal blood vessels to the colon wall was 15.3 ± 2.0 mm (14.2-16.3 mm). For polyp localization, the average difference of the circumferential polyp position on the supine and prone scans was 9.6 ± 9.4 mm (5.5-13.7 mm) (p = 0.15) and expressed as a percentage of the colon circumference was 3.1% ± 2.0% (2.3-4.0%) (p = 0.83). We were able to trace the marginal blood vessels for 10 collapsed colonic segments and determine the paths of the colon in these regions., Conclusion: The marginal blood vessels run parallel to the colon in proximity to the tenia mesocolica and enable accurate supine-prone registration of polyps and localization of the colon path in areas of collapse. Thus, the marginal blood vessels may be used as reference landmarks complementary to the colon centerline and teniae coli.

Background: Abnormalities in the corpus callosum have been reported in patients with schizophrenia for over 30 years but the influence of inter-individual differences and illness characteristics remains to be fully elucidated., Aims: To examine the influence of individual and illness characteristics on the corpus callosum in Chinese Singaporean patients with schizophrenia., Method: Using magnetic resonance and diffusion tensor imaging, mean corpus callosum area, volume and fractional anisotropy were investigated in 120 Chinese Singaporean patients (52 with chronic and 68 with first-episode schizophrenia) and compared with data from 75 matched healthy controls., Results: Both area and volume were significantly reduced in patients relative to controls but no significant differences in corpus callosum existed between genders in either patients or controls. Differences in area and volume of the corpus callosum were greatest in patients whose condition was chronic relative to patients with a first episode and controls. Anterior callosum in patients, regardless of chronicity, was no different to that of controls., Conclusions: Morphological abnormalities in the corpus callosum may increase with illness progression.

Due to its importance and possible applications in visualization, tumor detection and preoperative planning, automatic small bowel segmentation is essential for computer-aided diagnosis of small bowel pathology. However, segmenting the small bowel directly on computed tomography (CT) scans is very difficult because of the low image contrast on CT scans and high tortuosity of the small bowel and its close proximity to other abdominal organs. Motivated by the intensity characteristics of abdominal CT images, the anatomic relationship between the mesenteric vasculature and the small bowel, and potential usefulness of the mesenteric vasculature for establishing the path of the small bowel, we propose a novel mesenteric vasculature map-guided method for small bowel segmentation on high-resolution CT angiography scans. The major mesenteric arteries are first segmented using a vessel tracing method based on multi-linear subspace vessel model and Bayesian inference. Second, multi-view, multi-scale vesselness enhancement filters are used to segment small vessels, and vessels directly or indirectly connecting to the superior mesenteric artery are classified as mesenteric vessels. Third, a mesenteric vasculature map is built by linking vessel bifurcation points, and the small bowel is segmented by employing the mesenteric vessel map and fuzzy connectness. The method was evaluated on 11 abdominal CT scans of patients suspected of having carcinoid tumors with manually labeled reference standard. The result, 82.5% volume overlap accuracy compared with the reference standard, shows it is feasible to segment the small bowel on CT scans using the mesenteric vasculature as a roadmap.

Objectives: Sensitivity of noncontrast computed tomography (NCCT) in detecting hyperacute (< 8 hours) and acute (< 24 hours) cerebral infarction is low. We propose an automatic method to detect and localize ischemic infarct and to assess its volume from a single NCCT scan., Materials and Methods: The method automatically determines attenuation value ranges of cerebrospinal fluid and white and gray matter, separates the brain scan into the left and right hemispheres, and by analyzing hemisphere attenuation value distributions using percentile difference ratios, it detects, localizes, and quantifies the infarct without its segmentation. The method performance was evaluated on 576 patients with clinically confirmed stroke through NCCT scans acquired at 4 centers to measure how it matched with that of experts in detection, localization, and assessment of infarct volume. The time from the onset of symptoms ranged from 1.5 to 72 hours for 450 scans and more than 72 hours for 82 scans, most with pathologic findings in addition to cerebral infarction; the time was unavailable for 44 scans. In addition, the method was compared with the novice's (with 52 scans) and experienced readers' infarct detection (with 21 × 2 scans) in early ischemia detection (with the time from the onset of symptoms ranging from 1.5 to 7 hours)., Results: The method matches 100% the expert's infarct detection when chronic infarcts, leukoaraiosis cases, and infarct volumes less than 2 cm (determined by detection accuracy simulation) are excluded from the analysis. For all cases excluding infarct volumes less than 2 cm, the method detection accuracy is 95.7%. Overall, the method detection accuracy is 83.2%. The early method detection accuracy (≤ 3 hours) is 78.4%. The novice detection accuracy is 27.8% (≤ 3 hours), 37.5% (3 < to ≤ 8 hours), and 77.8% (> 8 hours), whereas the expert detection accuracy for these cases is 100%. Moreover, the method detected all 21 early infarcts, of which 15 were missed by the stroke experts and 14 of 15 were missed by a general radiologist. The method performs automatic analysis in approximately 7 seconds., Conclusions: The results demonstrate potential benefits of our method for enhancing expert's performance because it quickly localizes the infarct and detects cases missed by experts, and it is to be considered as an aid in the emergency department because it substantially outperforms novice readers (100% vs 27%) in infarct detection on NCCT.

Understanding brain pathology along with the underlying neuroanatomy and the resulting neurological deficits is of vital importance in medical education and clinical practice. To facilitate and expedite this understanding, we created a three-dimensional (3D) interactive atlas of neurological disorders providing the correspondence between a brain lesion and the resulting disorder(s). The atlas contains a 3D highly parcellated atlas of normal neuroanatomy along with a brain pathology database. Normal neuroanatomy is divided into about 2,300 components, including the cerebrum, cerebellum, brainstem, spinal cord, arteries, veins, dural sinuses, tracts, cranial nerves (CN), white matter, deep gray nuclei, ventricles, visual system, muscles, glands and cervical vertebrae (C1-C5). The brain pathology database contains 144 focal and distributed synthesized lesions (70 vascular, 36 CN-related, and 38 regional anatomy-related), each lesion labeled with the resulting disorder and associated signs, symptoms, and/or syndromes compiled from materials reported in the literature. The initial view of each lesion was preset in terms of its location and size, surrounding surface and sectional (magnetic resonance) neuroanatomy, and labeling of lesion and neuroanatomy. In addition, a glossary of neurological disorders was compiled and for each disorder materials from textbooks were included to provide neurological description. This atlas of neurological disorders is potentially useful to a wide variety of users ranging from medical students, residents and nurses to general practitioners, neuroanatomists, neuroradiologists and neurologists, as it contains both normal (surface and sectional) brain anatomy and pathology correlated with neurological disorders presented in a visual and interactive way.

Anatomical knowledge of the cranial nerves (CN) is fundamental in education, research and clinical practice. Moreover, understanding CN-related pathology with underlying neuroanatomy and the resulting neurological deficits is of vital importance. To facilitate CN knowledge anatomy and pathology understanding, we created an atlas of CN-related disorders, which is a three-dimensional (3D) interactive tool correlating CN pathology with the underlying surface and sectional neuroanatomy as well as the resulting neurological deficits. A computer platform was developed with: 1) anatomy browser along with the normal brain atlas (built earlier); 2) simulator of CN lesions; 3) tools to label CN-related pathology; and 4) CN pathology database with lesions and disorders, and the resulting signs, symptoms and/or syndromes. The normal neuroanatomy comprises about 2,300 3D components subdivided into modules. Cranial nerves contain more than 600 components: all 12 pairs of cranial nerves (CN I - CN XII) and the brainstem CN nuclei. The CN pathology database was populated with 36 lesions compiled from clinical textbooks. The initial view of each disorder was preset in terms of lesion location and size, surrounding surface and sectional neuroanatomy, and disorder and neuroanatomy labeling. Moreover, path selection from a CN nucleus to a targeted organ further enhances pathology-anatomy relationships. This atlas of CN-related disorders is potentially useful to a wide variety of users ranging from medical students and residents to general practitioners, neuroradiologists and neurologists, as it contains both normal brain anatomy and CN-related pathology correlated with neurological disorders presented in a visual and interactive way.

Three-dimensional (3D) relationships between head muscles and cranial nerves innervating them are complicated. Existing sources present these relationships in illustrations, radiologic scans, or autopsy photographs, which are limited for learning and use. Developed electronic atlases are limited in content, quality, functionality, and/or presentation. We create a truly 3D interactive, stereotactic and high quality atlas, which provides spatial relationships among head muscles, glands and cranial nerves, and correlates them to surface and sectional neuroanatomy. The head muscles and glands were created from a 3T scan by contouring them and generating 3D models. They were named and structured according to Terminologia anatomica. The muscles were divided into: extra-ocular, facial, masticatory and other muscles, and glands into mouth and other glands. The muscles, glands (and also head) were placed in a stereotactic coordinate system. This content was integrated with cranial nerves and neuroanatomy created earlier. To explore this complex content, a scalable user interface was designed with 12 modules including central nervous system (cerebrum, cerebellum, brainstem, spinal cord), cranial nerves, muscles, glands, arterial system, venous system, tracts, deep gray nuclei, ventricles, white matter, visual system, head. Anatomy exploration operations include compositing/decompositing, individual/group selection, 3D view-index mapping, 3D labeling, highlighting, distance measuring, 3D brain cutting, and axial/coronal/sagittal triplanar display. To our best knowledge, this is the first truly 3D, stereotactic, interactive, fairly complete atlas of head muscles, and the first attempt to create a 3D stereotactic atlas of glands. Its use ranges from education of students and patients to research to potential clinical applications., (Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.)

Understanding stroke-related pathology with underlying neuroanatomy and resulting neurological deficits is critical in education and clinical practice. Moreover, communicating a stroke situation to a patient/family is difficult because of complicated neuroanatomy and pathology. For this purpose, we created a stroke atlas. The atlas correlates localized cerebrovascular pathology with both the resulting disorder and surrounding neuroanatomy. It also provides 3D display both of labeled pathology and freely composed neuroanatomy. Disorders are described in terms of resulting signs, symptoms and syndromes, and they have been compiled for ischemic stroke, hemorrhagic stroke, and cerebral aneurysms. Neuroanatomy, subdivided into 2,000 components including 1,300 vessels, contains cerebrum, cerebellum, brainstem, spinal cord, white matter, deep grey nuclei, arteries, veins, dural sinuses, cranial nerves and tracts. A computer application was developed comprising: 1) anatomy browser with the normal brain atlas (created earlier); 2) simulator of infarcts/hematomas/aneurysms/stenoses; 3) tools to label pathology; 4) cerebrovascular pathology database with lesions and disorders, and resulting signs, symptoms and/or syndromes. The pathology database is populated with 70 lesions compiled from textbooks. The initial view of each pathological site is preset in terms of lesion location, size, surrounding surface and sectional neuroanatomy, and lesion and neuroanatomy labeling. The atlas is useful for medical students, residents, nurses, general practitioners, and stroke clinicians, neuroradiologists and neurologists. It may serve as an aid in patient-doctor communication helping a stroke clinician explain the situation to a patient/family. It also enables a layman to become familiarized with normal brain anatomy and understand what happens in stroke.

Background: Although multiple studies demonstrate benefits of high field imaging of cerebrovasculature, a detailed quantitative analysis of complete cerebrovascular system is unavailable. To compare quality of MR angiography (MRA) acquisitions at various field strengths, we used 3-dimensional (3D) geometric cerebrovascular models extracted from 1.5 T/3 T/7 T scans., Methods: The 3D cerebrovascular models were compared in volume, length, and number of branches. A relationship between the vascular length and volume was statistically derived. Acquisition performance was benchmarked against the maximum volume at infinitive length., Results: The numbers of vessels discernible on 1.5 T/3 T/7 T are 138/363/907. 3T shows 3.3(1.9) and 7 T 1.2(9.1) times more arteries (veins) than 1.5 T. The vascular lengths and volumes at 1.5 T/3 T/7 T are 3.7/12.5/22.7 m and 15.8/26.6/28.0 cm(3). For arteries: 3T-1.5 T gain is very high in length, high in volume; 7 T-3T gain is medium in length, small in volume. For veins: 3 T-1.5 T gain is moderate in length, high in volume; 7 T-3T gain is very high in length, moderate in volume. 1.5 T shows merely half of vascular volume. At 3 T 6%, while at 7 T only 1% of vascular volume is missing., Conclusion: Our approach differs from standard approaches based on visual assessment and signal (contrast)-to-noise ratio. It also measures absolute acquisition performance, provides a unique length-volume relationship, and predicts length/volume for intermediate teslages., (Copyright © 2011 by the American Society of Neuroimaging.)

Abnormalities in glutamate signaling and glutamate toxicity are thought to be important in the pathophysiology of bipolar disorder (BD). Whilst previous studies have found brain white matter changes in BD, there is paucity of data about how glutamatergic genes affect brain white matter integrity in BD. Based on extant neuroimaging data, we hypothesized that GRIN2B risk allele is associated with reductions of brain white matter integrity in the frontal, parietal, temporal, and occipital regions and cingulate gyrus in BD. Fourteen patients with BD and 22 healthy controls matched in terms of age, gender and handedness were genotyped using blood samples and underwent diffusion tensor imaging. Compared to G allele, brain FA values were significantly lower in BD patients with risk T allele in left frontal region (P = 0.001), right frontal region (P = 0.002), left parietal region (P = 0.001), left occipital region (P = 0.001), right occipital region (P < 0.001), and left cingulate gyrus (P = 0.001). Further elucidation of the interactions between different glutamate genes and their relationships with such structural, functional brain substrates will enhance our understanding of the link between dysregulated glutamatergic neurotransmission and neuroimaging endophenotypes in BD.

Objective: Human cerebrovasculature has not been quantified in volume, length, and vascular-brain relationships. We investigated this using imaging., Methods: From 0.5-mm 7T and 320-row CT acquisitions, 6 arterial and 4 venous systems were reconstructed, measured, and analyzed., Results: The ratio of the volume of arterial to venous system is approximately 1:3. The ratio of the volume of dural sinuses to vasculature is 1:2. The ratio of the posterior (PCA) to anterior (ACA) to middle cerebral artery (MCA) is 1:2:4 in volume and length. Ratios of left to right vessels are 1:1 for arteries and veins. Ratios of branching frequency for the ACA, MCA, and PCA are 1:1:1. The branching frequency ratio for superficial to deep veins is 1:2. The MCA occupies 1/2 of arterial length and 1/4 of vascular length. The ratio of the length of superficial to deep veins is 1:1 and each is equal to 1/4 of the vascular length. The ratio of cerebrovasculature to brain volume is 2.5%., Conclusions: Despite its enormous complexity, cerebrovasculature is characterized by 4 approximate proportions, 1:1, 1:2, 1:3, 1:4, and their combinations, 1:1:1 and 1:2:4.

Purpose: An automatic, accurate and fast segmentation of hemorrhage in brain Computed Tomography (CT) images is necessary for quantification and treatment planning when assessing a large number of data sets. Though manual segmentation is accurate, it is time consuming and tedious. Semi-automatic methods need user interactions and might introduce variability in results. Our study proposes a modified distance regularized level set evolution (MDRLSE) algorithm for hemorrhage segmentation., Methods: Study data set (from the ongoing CLEAR-IVH phase III clinical trial) is comprised of 200 sequential CT scans of 40 patients collected at 10 different hospitals using different machines/vendors. Data set contained both constant and variable slice thickness scans. Our study included pre-processing (filtering and skull removal), segmentation (MDRLSE which is a two-stage method with shrinking and expansion) with modified parameters for faster convergence and higher accuracy and post-processing (reduction in false positives and false negatives)., Results: Results are validated against the gold standard marked manually by a trained CT reader and neurologist. Data sets are grouped as small, medium and large based on the volume of blood. Statistical analysis is performed for both training and test data sets in each group. The median Dice statistical indices (DSI) for the 3 groups are 0.8971, 0.8580 and 0.9173 respectively. Pre- and post-processing enhanced the DSI by 8 and 4% respectively., Conclusions: The MDRLSE improved the accuracy and speed for segmentation and calculation of the hemorrhage volume compared to the original DRLSE method. The method generates quantitative information, which is useful for specific decision making and reduces the time needed for the clinicians to localize and segment the hemorrhagic regions.

Accurate quantification of haemorrhage volume in a computed tomography (CT) scan is critical in the management and treatment planning of intraventricular (IVH) and intracerebral haemorrhage (ICH). Manual and semi-automatic methods are laborious and time-consuming limiting their applicability to small data sets. In clinical trials measurements are done at different locations and on a large number of data; an accurate, consistent and automatic method is preferred. A fast and efficient method based on texture energy for identification and segmentation of hemorrhagic regions in the CT scans is proposed. The data set for the study was obtained from CLEAR-IVH clinical trial phase III (41 patients' 201 sequential CT scans from ten different hospitals, slice thickness 2.5-10 mm and from different scanners). The DICOM data were windowed, skull stripped, convolved with textural energy masks and segmented using a hybrid method (a combination of thresholding and fuzzy c-means). Artifacts were removed by statistical analysis and morphological processing. Segmentation results were compared with the ground truth. Descriptive statistics, Dice statistical index (DSI), Bland-Altman and mean difference analysis were carried out. The median sensitivity, specificity and DSI for slice identification and haemorrhage segmentation were 86.25%, 100%, 0.9254 and 84.90%, 99.94%, 0.8710, respectively. The algorithm takes about one minute to process a scan in MATLAB(®). A hybrid method-based volumetry of haemorrhage in CT is reliable, observer independent, efficient, reduces the time and labour. It also generates quantitative data that is important for precise therapeutic decision-making.

Accurate segmentation of ventricular cerebrospinal fluid (CSF) regions in stroke CT images is important in assessing stroke patients. Manual segmentation is subjective, time consuming and error prone. There are currently no methods dedicated to extracting ventricular CSF regions in stroke CT images. 102 ischemic stroke CT scans (slice thickness between 3 and 6 mm, voxel size in the axial plane between 0.390 and 0.498 mm) were acquired. An automated template-based algorithm is proposed to extract ventricular CSF regions which accounts for the presence of ischemic infarct regions, image noise, and variations in orientation. First, template VT(2) is registered to the scan using landmark-based piecewise linear scaling and then template VT(1) is used to further refine the registration by partial segmentation of the fourth ventricle. A region of interest (ROI) is found using the registered VT(2). Automated thresholding is then applied to the ROI and the artifacts are removed in the final phase. Sensitivity, dice similarity coefficient, volume error, conformity and sensibility of segmentation results were 0.74 ± 0.12, 0.8 ± 0.09, 0.16 ± 0.11, 0.45 ± 0.39, 0.88 ± 0.09, respectively. The processing time for a 512 × 512 × 30 CT scan takes less than 30 s on a 2.49 GHz dual core processor PC with 4 GB RAM. Experiments with clinical stroke CT scans showed that the proposed algorithm can generate acceptable results in the presence of noise, size variations and orientation differences of ventricular systems and in the presence of ischemic infarcts.

Objective: There are notable similarities between velocardiofacial syndrome and schizophrenia in terms of neurocognitive deficits and brain structural abnormalities. These similarities have supported the role of the armadillo repeat gene deleted in velocardiofacial syndrome (ARVCF) as a susceptibility gene in schizophrenia. This study investigated the relationships between haplotypes of the ARVCF gene and specific intermediate phenotypes in schizophrenia. We hypothesized that ARVCF gene haplotypes influence caudate nucleus volume, fractional anisotropy, and neurocognitive functioning in schizophrenia., Method: Between May 2006 and November 2009, 200 Chinese participants (125 patients with DSM-IV diagnosis of schizophrenia and 75 controls) were genotyped using blood samples, and a subset of 166 participants (99 patients with DSM-IV diagnosis of schizophrenia and 67 controls) underwent structural magnetic resonance imaging, diffusion tensor imaging, and completed neuropsychological testing., Results: The haplotype T-G-A-T-T-G-G-C-T-G-T (ARVCF-Hap1) was significantly associated with fractional anisotropy of the caudate nucleus and executive functioning in patients. Specifically, patients with more copies of ARVCF-Hap1 have lower white matter integrity in caudate nucleus (P = .0008) and greater perseverative errors (P = .00003) on the Wisconsin Card Sorting Test. A trend of lower caudate volume (P = .015) in patients with more copies of ARVCF-Hap1 was also observed., Conclusions: These findings are consistent with known ARVCF gene effects on neurodevelopment in terms of cellular arrangement, migration, and intracellular signaling involving the striatum and may involve interactions with other brain networks such as prefrontal cortex, and they underscore the importance of imaging-genetic studies to elucidate the genetic influences underlying intermediate phenotypes in complex neurobehavioral disorders., (© Copyright 2012 Physicians Postgraduate Press, Inc.)

Existing methods of neuroimage registration typically require high quality scans and are time-consuming. We propose a simple and fast method which allows intra-patient multi-modal and time-series neuroimage registration as well as landmark identification (including commissures and superior/inferior brain landmarks) for sparse data. The method is based on elliptical approximation of the brain cortical surface in the vicinity of the midsagittal plane (MSP). Scan registration is performed by a 3D affine transformation based on parameters of the cortex elliptical fit and by aligning the MSPs. The landmarks are computed using a statistical localization method based on analysis of 53 structural scans without detectable pathology. The method is illustrated for multi-modal registration, analysis of hemorrhagic stroke time series, and ischemic stroke follow ups, as well as for localization of hardly visible or not discernible landmarks in sparse neuroimages. The method also enables a statistical localization of landmarks in sparse morphological/non-morphological images, where landmark points may be invisible.

The existing classifications of cerebral veins have certain problems, including limited adequacy to uniquely describe neurovascular networks in three dimensions (3D), mixture of deep and superficial veins, and ambiguity of territories-based parcellations as veins may course on multiple territories. Classification discrepancies exist in subdivision, region drained, and parcellation criteria. Recent developments in diagnostic imaging and computers enable to acquire, create, and manipulate complete vascular networks, which also call for a new classification of cerebral veins. We propose a new classification suitable for the description of the complete cerebral veins, providing a clear separation of the superficial cortical veins from deep veins, and facilitating presentation and exploration of cerebral veins in 3D with respect to surrounding neuroanatomy. It is based on terminating vascular subsystems (rather than draining regions). It divides the cerebral veins into cortical, deep, and posterior fossa veins. The cortical veins are subdivided into two groups: terminating in dural sinuses and terminating in deep veins. The posterior fossa veins are subdivided also into two groups: terminating in dural sinuses and terminating in deep veins. This classification was illustrated with a cerebrovascular model containing over 1,300 vessels. This new classification has many advantages. It is simple, clear and didactically useful; avoids mixture of superficial and deep veins; shows overall hierarchical structure and topographical relationships including tributaries; is useful in analysis of 3D vascular trees extracted from imaging; and may be used in conjunction with the existing parcellations.

As the human brain is the most complex living organ, constructing its detailed model with exploration capabilities in a form of an atlas is a challenge. Our overall goal is to construct an advanced, detailed, parcellated, labeled, accurate, interactive, three-dimensional (3D), and scalable whole human brain atlas of structure, vasculature, tracts and systems. The objectives of this work are three-fold; to present: (1) method of atlas design and development including design principles, accuracy requirements, atlas content, architecture, functionality, user interface, and customized tools; (2) creation of an atlas of structure and systems including its modeling method and validation; and (3) integration of this atlas with the cerebrovasculature and tracts created earlier. The atlas is created from multiple in vivo 3/7 T scans. Its design based on "pyramidal principle" enables scalability while preserving design principles and exploits interaction paradigm "from blocks to brain". The atlas contains (1) navigator with modules for system/object/object state management, interaction, user interfacing, and rendering; and (2) brain model with cerebrum, cerebellum, brainstem, spinal cord, white matter, deep structures, systems, ventricles, arteries, veins, sinuses, and tracts. The brain model is parcellated, labeled, consistent, realistic, of high resolution, polygonal/volumetric, dissectible, extendable, and deformable. It has over 1700 3D components. The atlas has sub-voxel accuracy of 0.1mm and the smallest vessels of 80 μm. Brain exploration includes dynamic scene composition, manipulation-independent 3D labeling, interaction combined with animation, meta-labeling, and quantification. This atlas is useful in education, research, and clinical applications. It can potentially be foundation for a multi-level molecular-cellular-anatomical-physiological-behavioral platform., (Copyright © 2011 Elsevier B.V. All rights reserved.)