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PubMed1993

Correction for head size in brain-imaging measurements.

Structural brain-imaging measurements based on computed tomography (CT) or magnetic resonance imaging (MRI) are often corrected or adjusted for normal variation in head size. Some methods of head-size correction, such as the ventricle-brain ratio (VBR), are based on taking the brain structure size as a proportion of the estimated head size, while other methods have used a regression model to obtain head-size residualized structure measures. Recently, head-size correction was shown to result in less reliable volumetric measures of brain structures (Arndt et al., 1991). In the present study, MRI was used to examine the effects of head-size correction on the interrater reliability of volumetric measures of gray matter, white matter, and cerebrospinal fluid. Four raters independently scored MRI brain images from 26 subjects, generating separate estimates of head size and region of interest (ROI) size. Two methods were used to correct MRI values for differences in head size, one based on proportions and the other based on linear regression. Results confirmed that head-size correction did produce measures with lower reliability; however, further analysis based on classical measurement theory showed that the lower reliability was attributable not only to increased measurement error variance, but also to reduced true score variance. Subsequent analyses of criterion validity compared the raw (uncorrected) and head-size-corrected ROI measures in terms of their correlations with age in a sample of 43 normal control subjects, and in terms of their ability to differentiate schizophrenic patients (n = 22) from normal control subjects (n = 20). Results indicated that head-size correction often improved criterion validity, producing higher correlations with age and with diagnostic status than those produced by the raw measures. These findings suggest that head-size correction removes irrelevant true-score variance which reduces reliability yet improves the correlations with validity criteria such as age and diagnostic status.

Adult↗
PubMed2001

[Brain imaging in depression].

Structural brain imaging studies in major depression have revealed decreased hippocampal volume, decreased frontal lobe volume, decreased basal ganglia volume and increased subcortical hyperintensity lesions(SCH). Decreased hippocampal volume is thought to be related to hypercortisolemia. SCH is related to poor treatment response and clinical symptoms, thus has some value in clinical decision making. Functional brain imaging studies suggested decreased blood flow and metabolism in the frontal lobes and basal ganglia by positron emission tomography and single photon emission tomography, decreased adenosine triphosphate measured by 31P-magnetic resonance spectroscopy(MRS) in the frontal lobes and basal ganglia, and increased choline containing compounds observed by proton MRS.

Brain↗
PubMed1993

A stationary hemispherical SPECT imager for three-dimensional brain imaging.

A completely stationary, hemispherical-coded aperture SPECT imaging system was designed to produce three-dimensional images of the brain. The system consisted of a hemispherical multiple-pinhole coded aperture and 20 small (100 x 100 mm crystal area) digital gamma cameras. Reconstructions and measured performance specifications from two laboratory versions of the imager are presented. The reconstructed field of view of these systems was an ellipsoidal region with semi-diameters of 100 x 100 x 50 mm. The reconstructed spatial resolution for a point source in air at the center of this field was found to be 4.8 mm FWHM and the corresponding system sensitivity was 36 cps/microCi. An analysis using an ideal-observer model indicated that the multiplexed projection data suffered a 21% degradation relative to similar, but nonmultiplexed SPECT data. Therefore, by this measure, the effective sensitivity of the brain imager was 79% of the measured value.

Brain↗
PubMed1985

Functional brain imaging.

Recent advances in brain imaging have allowed a regional examination of brain function using multiple-probe inert gas studies of cerebral blood flow, positron or single photon tomography. Inert gas blood flow methods using inhalation or injection of 133xenon have been used with multiple-probe systems to measure blood flow in 1 to 2 cm regions of lateral cortex. The sensitivity of these systems to neurophysiological stimuli and neurological diseases have been demonstrated in numerous studies of the normal resting state, memory and learning, motor activity and sensory input, dementia, and aphasia, to name some. Positron tomography utilizes cyclotron-produced, short-lived positron-emitting isotopes to label biologically active radiopharmaceuticals. Using positron tomographs capable of quantitative three-dimensional imaging and appropriate tracer-kinetic models, regional metabolic function, including glucose, oxygen, amino acid metabolism, and receptor-binding can be regionally studied throughout the brain. Clinical studies have been performed in dementia, schizophrenia, affective disorders, resting states, and sensory stimulation. Positron tomography offers potentially the greatest variety of studies and highest temporal and spatial resolution of any of the presently available functional brain-imaging modalities. Its principal drawback is the very high cost. Single photon tomography uses gamma-emitting isotopes such as 123iodine and 133xenon to image regional cerebral blood flow and recently receptor function. Although at present it does not have the variety of studies or the technical capabilities of positron tomography, it does provide three-dimensional studies with 1 to 2 cm resolutions throughout the brain at a considerably lower cost than positron tomography. In the future, magnetic resonance studies of blood flow or phosphorus metabolism may add a fourth modality.

Brain↗
PubMed2005

Tissue classification of noisy MR brain images using constrained GMM.

We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of Gaussians, with each brain tissue represented by a large number of the Gaussian components in order to capture the complex tissue spatial layout. The intensity of a tissue is considered a global feature and is incorporated into the model through parameter tying of all the related Gaussians. The EM algorithm is utilized to learn the parameter-tied Gaussian mixture model. A new initialization method is applied to guarantee the convergence of the EM algorithm to the global maximum likelihood. Segmentation of the brain image is achieved by the affiliation of each voxel to a selected tissue class. The presented algorithm is used to segment 3D, T1-weighted, simulated and real MR images of the brain into three different tissues, under varying noise conditions. Quantitative results are presented and compared with state-of-the-art results reported in the literature.

Algorithms↗
PubMedDate not supplied

Accuracy of surface fit registration for PET and MR brain images using full and incomplete brain surfaces.

OBJECTIVE: The accuracy of a surface-fitting image registration technique has been investigated for matching [18F]fluorodeoxyglucose (FDG) and [15O]H2O PET brain images with MR images. Use of partial-brain surfaces (a single hemisphere or a limited number of slices) was investigated to simulate cases in which severe brain defects or limited axial field of view would preclude using the entire brain surface. MATERIALS AND METHODS: Three FDG and three H2O scans were performed on five volunteers, in addition to volume MR studies. Fiducial markers were placed on the subjects' scalps to provide references for registration accuracy. The registration procedure was applied to each PET-MR set, using the surfaces defined by locating the brain edge in multiple slices for each set. RESULTS: The surfaces fit well, with only 1% scaling necessary for the best fit. Errors in fiducial marker positions between MRI and transformed PET were < 2 mm in the transverse directions and < 4.5 mm in the axial direction. Fits based on the partial surfaces worked well and gave results very similar to the full-brain fits. CONCLUSION: The surface-fitting technique is accurate for FDG and H2O PET studies, even when part of the brain surface cannot be used.

Algorithms↗
PubMed1992

An automated method for rotational correction and centering of three-dimensional functional brain images.

The display and analysis of functional brain images often benefit from head rotational correction and centering. An automated method was developed to align brain PET images into a standard three-dimensional orientation. The algorithm performs transverse and coronal rotational correction as well as centering of a brain image set. Optimal rotational correction and centering are determined by maximizing a bilateral hemispheric similarity index, the stochastic sign change criterion. Testing of this algorithm on simulated symmetrical brain image sets showed errors less than 1.0 degree and 0.5 pixels for rotational correction and centering, respectively. With actual PET data, the algorithm results correlated well with those obtained by visual inspection. Testing on asymmetrical brain image sets with simulated lesions indicated that performance of the algorithm is not sensitive to focal asymmetries. This automated method provides objective, reproducible image alignment into a standard orientation and facilitates subsequent data analysis techniques for functional brain images.

Algorithms↗
PubMedDate not supplied

Brain imaging as a predictor of early functional outcome following traumatic brain injury in children, adolescents, and young adults.

OBJECTIVES: A depth of lesion (DOL) model using brain imaging has been proposed to aid in medical decision-making and planning for rehabilitation resource needs. The purpose of this study was to determine the early prognostic value of a DOL classification system for children and young adults following severe traumatic brain injury. METHODS AND OUTCOME MEASURES: CT/MRI brain imaging studies on 92 patients, aged 3 to 21, admitted to the Kluge Children's Rehabilitation Center, University of Virginia, were evaluated to determine DOL. Images were classified according to 5 DOL levels (cortical to brainstem). Functional outcomes in mobility, self-care, and cognition, as rated on the WeeFIM instrument, were compared by DOL levels. RESULTS: Admission WeeFIM scores were significantly different for the DOL levels with the highest score for frontal and/or temporal lesions and the lowest for lesions including the brainstem or cerebellum (P<.001). However, the deeper the lesion, the greater the functional gains (P=.05), resulting in discharge WeeFIM scores that were not significantly different across DOL levels. Patients with deeper lesions tended to have longer lengths of stay in rehabilitation but were able to "catch up" with patients who had more superficial lesions. CONCLUSIONS: While relatively simple and convenient, the DOL classification system is limited in its usefulness as an early prognostic tool. It may not be possible to predict outcome in the early acute phase in the intensive care unit on the basis of standard brain imaging alone. Patients with deeper lesions may enter rehabilitation at a more impaired level but can make remarkable progress, though it may take longer than for less severely injured individuals.

Adolescent↗
PubMed1995

Iterative Principal Axes Registration method for analysis of MR-PET brain images.

Computerized automatic registration of MR-PET images of the brain is of significant interest for multimodality brain image analysis. In this paper, we discuss the Principal Axes Transformation for registration of three-dimensional MR and PET images. A new brain phantom designed to test MR-PET registration accuracy determines that the Principal Axes Registration method is accurate to within an average of 1.37 mm with a standard deviation of 0.78 mm. Often the PET scans are not complete in the sense that the PET volume does not match the respective MR volume. We have developed an Iterative Principal Axes Registration (IPAR) algorithm for such cases. Partial volumes of PET can be accurately registered to the complete MR volume using the new iterative algorithm. The quantitative and qualitative analyses of MR-PET image registration are presented and discussed. Results show that the new Principal Axes Registration algorithm is accurate and practical in MR-PET correlation studies.

Algorithms↗
PubMed2006

What can functional brain imaging studies tell us about typical and atypical cognitive development in children?

Functional brain imaging has been largely reserved for adults. However, in recent years there have been increasing attempts to use functional brain imaging to inform our understanding of child development. These have taken three main forms: (1) Children with known or suspected neurological disorders may undergo brain imaging for medical diagnostic purposes and/or for the purpose of research into the nature of the disorders. (2) There have been a few studies where children, usually over the age of 8, have undergone functional brain imaging. (3) Results from brain imaging studies of adults have influenced theories about children's development. This chapter discusses the impact of brain imaging studies on our understanding of working memory; reading; and arithmetic. The different forms of brain imaging converge in demonstrating that different brain regions show differential activation for different domains and for different components within the domains: e.g. different reading strategies and different components of arithmetic. They show important similarities between children and adults, though it must be remembered that very few studies have involved young children. They also indicate that experience influences brain function, as well as the other way around.

Brain↗
PubMed1976

Value of routine cerebral radionuclide angiography in pediatric brain imaging.

In addition to static brain images, cerebral radionuclide angiograms (CRAGs) were performed in 1,051 children to determine the value of routine radionuclide angiography. The CRAG resulted in a statistically significant increase in detection of abnormalities (p less than 0.01), as it provided the only evidence of confirmed abnormalities in 60 children (5.7%). The CRAG helped detect subdural fluid collections, cerebrovascular disease, and cerebral cysts, but it was of little value in detecting hydrocephalus. For maximum diagnostic yield, a CRAG should be performed with all pediatric brain-imaging studies.

Brain Diseases↗
PubMed2006

A primer on brain imaging in developmental psychopathology: what is it good for?

This primer introduces a Special Section on brain imaging, which includes a commentary and 10 data papers presenting applications of brain imaging to questions on developmental psychopathology. This primer serves two purposes. First, the article summarizes the strength and weaknesses of various brain-imaging techniques typically employed in research on developmental psychopathology. Second, the article places research on brain imaging in a broader context by discussing particular limitations and utilities of imaging. Specifically, while brain imaging is currently of limited clinical utility, work in this area is beginning to shape clinical thinking. Brain-imaging research offers a unique opportunity to constrain theories of pathophysiology based on understandings of brain function. This effect promises to open avenues for novel treatments.

Brain↗
PubMedDate not supplied

An image-processing system for qualitative and quantitative volumetric analysis of brain images.

In this work, we developed, implemented, and validated an image-processing system for qualitative and quantitative volumetric analysis of brain images. This system allows the visualization and quantitation of global and regional brain volumes. Global volumes were obtained via an automated adaptive Bayesian segmentation technique that labels the brain into white matter, gray matter, and cerebrospinal fluid. Absolute volumetric errors for these compartments ranged between 1 and 3% as indicated by phantom studies. Quantitation of regional brain volumes was performed through normalization and tessellation of segmented brain images into the Talairach space with a 3D elastic warping model. Retest reliability of regional volumes measured in Talairach space indicated errors of < 1.5% for the frontal, parietal, temporal, and occipital brain regions. Additional regional analysis was performed with an automated hybrid method combining a region-of-interest approach and voxel-based analysis, named Regional Analysis of Volumes Examined in Normalized Space (RAVENS). RAVENS analysis for several subcortical structures showed good agreement with operator-defined volumes. This system has sufficient accuracy for longitudinal imaging data and is currently being used in the analysis of neuroimaging data of the Baltimore Longitudinal Study of Aging.

Aged↗
PubMed1997

[Brain imaging and its clinical application in psychiatry].

The common structural and functional brain imaging techniques are described from a practical, clinical point of view. The clinical indications for brain imaging in psychiatry are reviewed in relation to the specific limitations and advantages of each technique. The clinical applications of computerized tomography (CT), magnetic resonance imaging (MRI) and single photon emission computerized tomography (SPECT) are discussed in relation to the differential diagnosis between organic and functional psychiatric disorders. In a 55-year-old man with late onset of behavioral changes but without neurological signs the application of structural brain imaging (CT and MRI) in case management was demonstrated. The imaging findings involved the differential diagnosis between depression and focal brain lesions. In a 38-year-old man with personality changes and depression following a traumatic brain injury, time interval repeated functional brain imaging (SPECT) was used. Brain imaging reflected improvement in clinical status following treatment and was able to differentiate between reversible and permanent traumatic brain injuries. The superior yield of time interval repeated functional imaging in diagnosis and management of postconcussion syndrome is discussed.

Adult↗
PubMedDate not supplied

Brain imaging during seizure: ictal brain SPECT.

The role of single photon computed tomography (SPECT) in presurgical localization of medically intractable complex partial epilepsy (CPE) in children is reviewed. 99mTechnetium Neurolite, a newer lipophylic agent with a high first pass brain extraction and little or no redistribution is injected during a seizure, while the child is monitored with a video recording and continuous EEG and SPECT imaging is performed in the next 1-3 hours with the images representing regional cerebral profusion at the time of injection. On SPECT studies performed with radiopharmaceutical injected during a seizure, ictal focus is generally hypervascular. Other findings on ictal brain SPECT include hypoperfusion of adjacent cerebral cortex and white matter, hyperperfusion of contralateral motor cortex, hyperperfusion of ipsilateral basal ganglia and thalamus, brain stem and contralateral cerebellum. Ictal brain SPECT is non-invasive, cost effective and highly sensitive for localization of epileptic focus in patients with intractable CPE.

Brain↗
PubMedDate not supplied

MRI brain image segmentation by multi-resolution edge detection and region selection.

Combining both spatial and intensity information in image, we present an MRI brain image segmentation approach based on multi-resolution edge detection, region selection, and intensity threshold methods. The detection of white matter structure in brain is emphasized in this paper. First, a multi-resolution brain image representation and segmentation procedure based on a multi-scale image filtering method is presented. Given the nature of the structural connectivity and intensity homogeneity of brain tissues, region-based methods such as region growing and subtraction to segment the brain tissue structure from the multi-resolution images are utilized. From the segmented structure, the region-of-interest (ROI) image in the structure region is derived, and then a modified segmentation of the ROI based on an automatic threshold method using our threshold selection criterion is presented. Examples on both T1 and T2 weighted MRI brain image segmentation is presented, showing finer brain tissue structures.

Brain↗