Analysis of ischemic stroke MR images by means of brain atlases of anatomy and blood supply territories

RATIONALE AND OBJECTIVES: A method for atlas-assisted analysis of stroke magnetic resonance images that is a part of a stroke computer-assisted diagnosis system supporting rapid and quantitative checking of thrombolysis conditions is presented. MATERIALS AND METHODS: Two brain atlases are used for analysis: atlas of anatomy (AA) and atlas of blood supply territories (BSTs). To map these atlases onto scans, two methods are used at present: (1) fast Talairach transformation and (2) midsagittal plane and brain's bounding box matching. After atlas-to-scan mapping, both atlases are superimposed onto the studied images and can be used to get their underlying anatomy and BSTs. To speed up the process of analysis, the system automatically analyzes entire regions occupied by the infarct and penumbra. RESULTS: By using both atlases, the system calculates the following values for each infarct and penumbra region: (1) names of all anatomic structures and BSTs within the region, (2) volumes of occupancy for each structure and territory, and (3) percentages of occupancy for each structure and territory. In addition, the system calculates the infarct-middle cerebral artery (MCA) territory ratio for diffusion-weighted images and the penumbra-MCA territory ratio for perfusion images. Atlas-assisted analysis is fast, and calculations take less than 10 seconds. CONCLUSION: This method potentially facilitates and speeds up stroke data analysis, as well as supports decision making.     

Fast Talairach Transformation for magnetic resonance neuroimages

We introduce and validate the Fast Talairach Transformation (FTT). FTT is a rapid version of the Talairach transformation (TT) with the modified Talairach landmarks. Landmark identification is fully automatic and done in 3 steps: calculation of midsagittal plane, computing of anterior commissure (AC) and posterior commissure (PC) landmarks, and calculation of cortical landmarks. To perform these steps, we use fast and anatomy-based algorithms employing simple operations. FTT was validated for 215 diversified T1-weighted and spoiled gradient recalled (SPGR) MRI data sets. It calculates the landmarks and warps the Talairach-Tournoux atlas fully automatically in about 5 sec on a standard computer. The average distance errors in landmark localization are (in mm): 1.16 (AC), 1.49 (PC), 0.08 (left), 0.13 (right), 0.48 (anterior), 0.16 (posterior), 0.35 (superior), and 0.52 (inferior). Extensions to FTT by introducing additional landmarks and applying nonlinear warping against the ventricular system are addressed. Application of FTT to other brain atlases of anatomy, function, tracts, cerebrovasculature, and blood supply territories is discussed. FTT may be useful in a clinical setting and research environment: (1) when the TT is used traditionally, (2) when a global brain structure positioning with quick searching and labeling is required, (3) in urgent cases for quick image interpretation (eg, acute stroke), (4) when the difference between nonlinear and piecewise linear warping is negligible, (5) when automatic processing of a large number of cases is required, (6) as an initial atlas-scan alignment before performing nonlinear warping, and (7) as an initial atlas-guided segmentation of brain structures before further local processing.     

Automatic registration of brain magnetic resonance images based on Talairach reference system

PURPOSE: To demonstrate a robust registration method of brain magnetic resonance (MR) images based on the Talairach reference system with automatic determinations of the fiducial points. MATERIALS AND METHODS: Eight specified landmark points of the Talairach reference system are determined after successfully extracting the midsagittal plane from three-dimensional MR imaging (MRI) data. Projection information of the image intensity is used to determine the midline of the cerebrum in axial and coronal view images, which is a necessary step for extraction of the midsagittal plane. To find the landmarks of anterior commissure (AC) and posterior commissure (PC) in the midsagittal plane, we adopt two-step shape matching that properly finds locations of the corpus callosum (CC), and then AC and PC, respectively. The shape matching is performed on the edge-enhanced midsagittal plane image to minimize dependency on image intensity variation. Other landmark points of the Talairach reference system are determined by fitting the intensity curve of the cutview with the Gaussian model. RESULTS: The proposed method automatically determines seven landmark points, except the inferior point (IP), and the brain MR images can be successfully registered with the Talairach reference system. CONCLUSION: The suggested registration method can be applied to any MR images for functional studies. It can also be applied to patients unless their brains are highly deformed or have a highly deformed CC.     

Diffeomorphic brain mapping based on T1‐weighted images: Improvement of registration accuracy by multichannel mapping

Purpose:

To improve image registration accuracy in neurodegenerative populations.

Materials and Methods:

This study used primary progressive aphasia, aged control, and young control T1‐weighted images. Mapping to a template image was performed using single‐channel Large Deformation Diffeomorphic Metric Mapping (LDDMM), a dual‐channel method with ventricular anatomy in the second channel, and a dual‐channel with appendage method, which utilized a priori knowledge of template ventricular anatomy in the deformable atlas.

Results:

Our results indicated substantial improvement in the registration accuracy over single‐contrast‐based brain mapping, mainly in the lateral ventricles and regions surrounding them. Dual‐channel mapping significantly (P < 0.001) reduced the number of misclassified lateral ventricle voxels (based on a manually defined reference) over single‐channel mapping. The dual‐channel (w/appendage) method further reduced (P < 0.001) misclassification over the dual‐channel method, indicating that the appendage provides more accurate anatomical correspondence for deformation.

Conclusion:

Brain anatomical mapping by shape normalization is widely used for quantitative anatomical analysis. However, in many geriatric and neurodegenerative disorders, severe tissue atrophy poses a unique challenge for accurate mapping of voxels, especially around the lateral ventricles. In this study we demonstrate our ability to improve mapping accuracy by incorporating ventricular anatomy in LDDMM and by utilizing a priori knowledge of ventricular anatomy in the deformable atlas. J. Magn. Reson. Imaging 2013;37:76–84. © 2012 Wiley Periodicals, Inc.     

An elastic computerized brain atlas for the analysis of clinical PET/SPET data

An elastic computerized brain atlas was developed for the analysis of positron emission tomography/single-photon emission tomography (PET/SPET) data. It consists of a set of digital anatomical contours and a template of regions of interest, schematically describing the brain, derived from a currently used anatomical/functional brain atlas. A warping algorithm, matching equivalent contours, was implemented to elastically fit the atlas to individual brain images. The elastic computerized brain atlas was applied to representative magnetic resonance imaging (MRI)-PET/SPET studies, MRI providing the anatomical information used by the matching procedure. The atlas is suited for clinical use in a nuclear medicine environment.     

A computerized adjustable brain atlas

A computerized brain atlas, adjustable to the patients anatomy, has been developed. It is primarily intended for use in positron emission tomography, but may also be employed in other fields utilizing neuro imaging, such as stereotactic surgery, transmission computerized tomography (CT) and magnetic resonance imaging (MRI). The atlas is based on anatomical information obtained from a digitized cryosectioned brain. It can be adjusted to fit a wide range of images from individual brains with normal anatomy. The corresponding transformation is chosen so that the modified atlas agrees with a set of CT or NMR images of the patient. The computerized atlas can be used to improve the quantification and evaluation of PET data by:

Automatic measurement of the labyrinth using image registration and a deformable inner ear atlas

RATIONALE AND OBJECTIVES: This article presents a new method for measuring the shape of the cochlea, vestibule, semi-circular canals, and internal auditory canal using image registration and a deformable inner ear atlas. MATERIALS AND METHODS: Computed tomography images of the inner ear are analyzed by placing them into a common orientation and then registering a digital atlas of the inner ear to the data set. The atlas is deformed from its original shape to match the shape of the inner ear in the computed tomography data set using inverse consistent elastic image registration. This process produces an individualized inner ear atlas containing subject-specific measurements and segmentations of the inner ear anatomy in the target computed tomography data set. The shape measurements include the volume and length of the cochlea, vestibule, semi-circular canals, and internal auditory canal; and the angles between the semi-circular canals. RESULTS: A simulated population of inner ear shapes were generated based on the shape of a real population of inner ear shapes and were used to characterize the measurement error of this method. The deformable atlas was used to measure the shape of the left and right inner ear of six individuals. CONCLUSION: Measurement error for 15 of the 24 measurements of our simulated population had an average error of less than 1% and only one measurement had an average error greater than 2.54%. The deformable human inner ear atlas shows promise as a new method for automatically measuring the shape of the labyrinth.     

Segmentation of brain MRI in young children

RATIONALE AND OBJECTIVES: This article deals with an automatic tissue segmentation of brain magnetic resonance imaging (MRI) in young children. MATERIALS AND METHODS: We examine the suitability of state-of-the-art methods developed for the adult brain when applied to the segmentation of the brain MRI in young children. We develop a method of creation of a population-specific atlas in young children using a single manual segmentation. The method is based on nonlinear propagation of the segmentation into population and subsequent affine alignment into a reference space and averaging. RESULTS: Using this approach, we significantly improve the performance of the popular expectation-maximization algorithm on brain MRI in young children. The method can be used for building probabilistic atlases with any number of structures. We compare resulting algorithm with nonrigid registration-based label propagation. CONCLUSIONS: Finally, both methods are used to measure the volume of seven brain structures and measure the growth between 1 and 2 years of age.     

Dorsoventral extension of the talairach transformation and its automatic calculation for magnetic resonance neuroimages

The Talairach transformation (TT), the most prevalent method for brain normalization and atlas-to-data warping, is conceptually simple, fast and can be automated. Two problems with the TT in the clinical setting that are addressed in this article are reduced accuracy at the orbitofrontal cortex and upper corpus callosum (CC) and unsuitability for functional neurosurgery because of incomplete scanning. To increase dorsoventral accuracy, we introduce 2 additional landmarks: the top of the CC (SM) and the most ventral point of the orbitofrontal cortex on the midsagittal slab (IM). A method for their automatic calculation is proposed and validated against 55 diversified magnetic resonance (MR) imaging cases. The SM and IM landmarks are identified accurately and robustly in an automatic way. The average error of SM localization is 0.69 mm, and 91% of all cases have an error not greater than 1 mm. The average error of IM localization is 0.98 mm, approximately three quarters of cases have an error not greater than 1 mm, and 95% of all cases have an error not larger than 2 mm. The SM is correlated (R(2) = 0.72) with the most superior cortical landmark, whereas the IM is only loosely correlated (R(2) = 0.22) with the most inferior cortical landmark. On average, the original TT overlays the atlas axial plate at -24 on the orbitofrontal cortex as opposed to the correct plate at -28. Therefore, 1-dimensional ventral scaling in the original TT is insufficient to cope with variability in the orbitofrontal cortex. The key advantages of our approach are the preserved conceptual simplicity of the TT, fully automatic identification of the new landmarks, improved accuracy of the atlas-to-data match without compromising performance, and enabled TT use in functional neurosurgery when a dorsal part of the brain is not available in the scan.     

Computerized localization of brain structures in single photon emission computed tomography using a proportional anatomical stereotactic atlas

An accurate identification of cerebral structures is necessary to perform quantification of single photon emission computed tomography (SPELT). We have developed an anatomical localization system that accounts for individual brain shapes and sizes by using the Talairach proportional grid system. The locations of the commissural lines, which define the stereotactic coordinate system, are calculated from the external landmarks provided by the canthomeatal line. This is validated on MRI images. When applied to SPELT data, the use of a neuroanatomical atlas data along with the automaticity of the processing guarantees a high degree of objectivity and inter-observer reproducibility.     

脑室内脑膜瘤的影像学表现及其病理基础

目的探讨脑室内脑膜瘤影像学特征及其病理基础。方法通过回顾性分析经手术病理证实的11例脑室内脑膜瘤的CT、MRI表现,总结其影像学特征及其病理基础。结果本组11例患者,其中8例位于侧脑室,3例位于三脑室。除1例与瘤周脑组织分界不清、浸润性生长、水肿较明显外,余肿瘤呈不规则形分叶状(7例)或类圆形(3例)、边界较清,相应脑室不同程度扩大,邻近脑实质轻度水肿。MRI表现为T1WI等(2例)或稍低信号(9例),T2WI表现为等、稍高或混杂高信号,增强扫描呈显著不均匀强化。CT平扫表现为均匀或不均匀略高密度影。结论脑室内脑膜瘤的影像学表现具有特征性,MRI结合CT能较好地显示肿瘤的病理解剖特征。     

Rapid and automatic localization of the anterior and posterior commissure point landmarks in MR volumetric neuroimages

RATIONALE AND OBJECTIVE: Accurate identification of the anterior commissure (AC) and posterior commissure (PC) is critical in neuroradiology, functional neurosurgery, human brain mapping, and neuroscience research. Moreover, major stereotactic brain atlases are based on the AC and PC. Our goal is to provide an algorithm for a rapid, robust, accurate and automatic identification of AC and PC. MATERIALS AND METHOD: The method exploits anatomical and radiological properties of AC, PC and surrounding structures, including morphological variability. The localization is done in two stages: coarse and fine. The coarse stage locates the AC and PC on the midsagittal plane by analyzing their relationships with the corpus callosum, fornix, and brainstem. The fine stage refines the AC and PC in a well-defined volume of interest, analyzing locations of lateral and third ventricles, interhemispheric fissure, and massa intermedia. RESULTS: The algorithm was developed using simple operations, like histogramming, thresholding, region growing, 1D projections. It was tested on 94 diversified T1W and SPGR datasets. After the fine stage, 71 (76%) volumes had an error between 0-1 mm for the AC and 55 (59%) for the PC. The mean errors were 1.0 mm (AC) and 1.0 mm (PC). The accuracy has improved twice due to fine stage processing. The algorithm took about 1 second for coarse and 4 seconds for fine processing on P4, 2.5 GHz. CONCLUSION: The use of anatomical and radiological knowledge including variability in algorithm formulation aids in localization of structures more accurately and robustly. This fully automatic algorithm is potentially useful in clinical setting and for research.     

Region-growing segmentation of brain vessels: an atlas-based automatic approach

PURPOSE: To propose an atlas-based method that uses both phase and magnitude images to integrate anatomical information in order to improve the segmentation of blood vessels in cerebral phase-contrast magnetic resonance angiography (PC-MRA). MATERIAL AND METHODS: An atlas of the whole head was developed to store the anatomical information. The atlas divides a magnitude image into several vascular areas, each of which has specific vessel properties. It can be applied to any magnitude image of an entire or nearly entire head by deformable matching, which helps to segment blood vessels from the associated phase image. The segmentation method used afterwards consists of a topology-preserving, region-growing algorithm that uses adaptive threshold values depending on the current region of the atlas. This algorithm builds the arterial and venous trees by iteratively adding voxels that are selected according to their grayscale value and the variation of values in their neighborhood. The topology preservation is guaranteed because only simple points are selected during the growing process. RESULTS: The method was performed on 40 PC-MRA images of the brain. The results were validated using maximum-intensity projection (MIP) and three-dimensional surface rendering visualization, and compared with results obtained with two non-atlas-based methods. CONCLUSION: The results show that the proposed method significantly improves the segmentation of cerebral vascular structures from PC-MRA. These experiments tend to prove that the use of vascular atlases is an effective way to optimize vessel segmentation of cerebral images.     

Boundary-based warping of brain MR images

The goal of this work was to develop a warping technique for mapping a brain image to another image or atlas data, with minimum user interaction and independent of gray level information. We have developed and tested three different methods for warping magnetic resonance (MR) brain images. We utilize a deformable contour to extract and warp the boundaries of the two images. A mesh-grid coordinate system is constructed for each brain, by applying a distance transformation to the resulting contours, and scaling. In the first method (MGC), the first image is mapped to the second image based on a one-to-one mapping between different layers defined by the mesh-grid. In the second method (IDW), the corresponding pixels in the two images are found using the above mesh-grid system and a local inverse-distance weights interpolation. In the third proposed method (TSB), a subset of grid points is used for finding the parameters of a spline transformation, which defines the global warping. The warping methods were applied to clinical MR consisting of diffusion-weighted and T2-weighted images of the human brain. The IDW and TSB methods were superior in ranking of diagnostic quality of the warped MR images to the MGC (P < 0.01) as defined by a neuroradiologist. The deformable contour warping produced excellent diagnostic quality for the diffusion-weighted images coregistered and warped to T2 weighted images. J. Magn. Reson. Imaging 2000;12:417-429.     

A computerized adjustable brain atlas

A computerized brain atlas, adjustable to the patients anatomy, has been developed. It is primarily intended for use in positron emission tomography, but may also be employed in other fields utilizing neuro imaging, such as stereotactic surgery, transmission computerized tomography (CT) and magnetic resonance imaging (MRI). The atlas is based on anatomical information obtained from a digitized cryosectioned brain. It can be adjusted to fit a wide range of images from individual brains with normal anatomy. The corresponding transformation is chosen so that the modified atlas agrees with a set of CT or NMR images of the patient. The computerized atlas can be used to improve the quantification and evaluation of PET data by: Aiding and improving the selection of regions of interests. Facilitating comparisons of functional image data from different individuals or groups of individuals. Facilitating the comparison of different examinations of the same patient, thus reducing the need of reproducible fixation systems. Providing external a priori anatomical information to be used in the image reconstruction. Improving the attenuation and scatter corrections. Aiding in selecting a suitable patient orientation during the PET study. By applying the inverse atlas transformation to PET data set it is possible to relate the PET information to the anatomy of the reference atlas. Thus reformatted PET data from different patients can be averaged, and averages from different categories of patients can be compared. This procedure will facilitate the identification of statistically significant differences in the PET information from different groups of patients.     

Automatic method for tracing regions of interest in rat brain magnetic resonance imaging studies

Purpose

To automatically extract regions of interest (ROIs) and simultaneously preserve the anatomical characteristics of each individual, we developed a new atlas‐based method utilizing a pair of coregistered brain template and digital atlas.

Materials and Methods

Unlike the previous atlas‐based method, this method treats each individual as the target image, and the template and atlas are each transformed to register with the individual. To evaluate the accuracy of this method we implemented it in extracting the hippocampus from two groups of T₂‐weighted structural images with different spatial resolutions and a group of T₂*‐weighted functional images. Furthermore, the results were compared against a manually segmented hippocampus and an atlas‐derived hippocampus.

Results

Jaccard similarity (JS) reached 84.7%–90.5%, and relative error in volume (RV) was 4.8%–12.7%. The consistency observed between the results of the proposed method and manual drawing was therefore considerable.

Conclusion

We developed a new atlas‐based method for ROI extraction that can automatically extract ROI and simultaneously preserve each individual's unique anatomical characteristics. J. Magn. Reson. Imaging 2010;32:830–835. © 2010 Wiley‐Liss, Inc.     

国人脑解剖结构的磁共振三维重建初探

目的：通过磁共振对国人脑进行三维重建以便清晰显示脑内解剖结构,以便建立脑部解剖的数字化图像。方法筛选25例中国中青年无脑部疾病的健康志愿者,利用1.5 T磁共振采集其脑部的影像数据,在计算机后处理工作站采用MATLAB、SPM及Mango等多种图像处理软件进行标准化和三维重建处理,以便立体显示脑深部解剖结构。结果采集的MRI脑图经过一系列校正处理后,对大脑皮质、髓质、脑室、基底核、脑干、小脑等主要结构进行提取并存入数据库,经过多步骤重建处理显示脑三维立体形态,在此基础上确定脑内三维坐标,再把解剖名称按一定顺序与脑部结构进行相应标注,从而通过多功能浏览器用鼠标点击不同层面的脑深部结构,即可实时显示其三维坐标及相应的中英文双语解剖名称,可进行交互式的操作,方便使用者浏览和学习脑部解剖。结论 MRI三维脑图谱对脑神经科学研究及教学具有重大意义,其在计算机辅助手术、影像指导手术及微创手术等领域起着很大作用。     

Global spatial normalization of human brain using convex hulls.

Global spatial normalization transforms a brain image so that its principal global spatial features (position, orientation and dimensions) match those of a standard or atlas brain, supporting consistent analysis and referencing of brain locations. The convex hull (CH), derived from the brain's surface, was selected as the basis for automating and standardizing global spatial normalization. The accuracy and precision of CH global spatial normalization of PET and MR brain images were evaluated in normal human subjects. METHODS: Software was developed to extract CHs of brain surfaces from tomographic brain images. Pelizzari's hat-to-head least-square-error surface-fitting method was modified to fit individual CHs (hats) to a template CH (head) and calculate a nine-parameter coordinate transformation to perform spatial normalization. A template CH was refined using MR images from 12 subjects to optimize global spatial feature conformance to the 1988 Talairach Atlas brain. The template was tested in 12 additional subjects. Three major performance characteristics were evaluated: (a) quality of spatial normalization with anatomical MR images, (b) optimal threshold for PET and (c) quality of spatial normalization for functional PET images. RESULTS: As a surface model of the human brain, the CH was shown to be highly consistent across subjects and imaging modalities. In MR images (n = 24), mean errors for anterior and posterior commissures generally were <1 mm, with SDs < 1.5 mm. Mean brain-dimension errors generally were <1.3 mm, and bounding limits were within 1-2 mm of the Talairach Atlas values. The optimal threshold for defining brain boundaries in both 18F-fluorodeoxyglucose (n = 8) and 15O-water (n = 12) PET images was 40% of the brain maximum value. The accuracy of global spatial normalization of PET images was shown to be similar to that of MR images. CONCLUSION: The global features of CH-spatially normalized brain images (position, orientation and size) were consistently transformed to match the Talairach Atlas in both MR and PET images. The CH method supports intermodality and intersubject global spatial normalization of tomographic brain images.     

Human brain iron mapping using atlas‐based T2 relaxometry

Several in vivo quantitative MRI techniques have been proposed as surrogate measures to map iron content in the human brain. The majority of in vivo quantitative MRI iron mapping methods used the age‐dependent iron content data based on postmortem data. In this work, we fused atlas‐based human brain volumetry obtained on a large cohort of healthy adults using FreeSurfer with T₂ relaxation time measurements. We provide a brain atlas‐based T₂ relaxation time map, which was subsequently used along with published postmortem iron content data to obtain a map of iron content in subcortical and cortical gray matter. We have also investigated the sensitivity of the linear model relating transverse relaxation rate with published iron content to the number of regions used. Our work highlights the challenges encountered on using the simple model along with postmortem data to infer iron content in several brain regions where postmortem iron data are scant (e.g., corpus callosum, amygdale). Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.     

A computerized brain atlas: construction, anatomical content, and some applications

An adjustable computerized atlas of the human brain has been developed, which can be adapted to fit individual anatomy. It is primarily intended for positron emission tomography (PET) but may also be used for single photon emission CT, transmission CT, magnetic resonance imaging, and neuroimaging-based procedures, such as stereotactic surgery and radiotherapy. The atlas is based on anatomical information obtained from brains fixed in situ soon after death. All structures have been drawn in on digitized photos of slices from one cryosectioned brain. The definition and classification of the anatomical structures and divisions are in agreement with the standard textbooks of anatomy, and the nomenclature is that of the Nomina Anatomica of 1965. The boundaries of the cortical cytoarchitectonic areas (Brodmann areas) have been determined using information from several sources, since three-dimensional literature data on their distribution are incomplete, scarce, and partly contradictory. However, no analysis of the cytoarchitectonics of the atlas brain itself has been undertaken. At present the data base contains three-dimensional representations of the brain surface, the ventricular system, the cortical gyri and sulci, as well as the Brodmann cytoarchitectonic areas. The major basal ganglia, the brain stem nuclei, the lobuli of the vermis, and the cerebellar hemispheres are also included. The computerized atlas can be used to improve the quantification and evaluation of PET data in several ways. For instance, it can serve as a guide in selecting regions of interest. It may also facilitate comparisons of data from different individuals or groups of individuals, by applying the inverse atlas transformation to PET data volume, thus relating the PET information to the anatomy of the reference atlas rather than to the patient's anatomy. Reformatted PET data from individuals can thus be averaged, and averages from different categories or different functional states of patients can be compared.