Intimate combination of low- and high-resolution image data: I. Real-space PET and (1)H(2)O MRI, PETAMRI.

Two different types of (co-registered) images of the same slice of tissue will generally have different spatial resolutions. The judicious pixel-by-pixel combination of their data can be accomplished to yield a single image exhibiting properties of both. Here, axial (18)FDG PET and (1)H(2)O MR images of the human brain are used as the low- and high-resolution members of the pair. A color scale is necessary in order to provide for separate intensity parameters from the two image types. However, not all color scales can accommodate this separability. The HSV color model allows one to choose a color scale in which the intensity of the low-resolution image type is coded as hue, while that of the high-resolution type is coded as value, a reasonably independent parameter. Furthermore, the high-resolution image must have high contrast and be quantitative in the same sense as the low-resolution image almost always is. Here, relaxographic MR images (naturally segmented quantitative (1)H(2)O spin-density components) are used. Their essentially complete contrast serves to effect an apparent editing function when encoded as the value of the color scale. Thus, the combination of (18)FDG PET images with gray-matter (GM) relaxographic (1)H(2)O images produces visually "GM-edited" (18)FDG PETAMR (positron emission tomography and magnetic resonance) images. These exhibit the high sensitivity to tracer amounts characteristic of PET along with the high spatial resolution of (1)H(2)O MRI. At the same time, however, they retain the complete quantitative measures of each of their basis images. Magn Reson Med 42:345-360, 1999. Published 1999 Wiley-Liss, Inc.

Measuring reproducibility of regional brain metabolic responses to lorazepam using statistical parametric maps.

UNLABELLED: Statistical parametric mapping (SPM) is a method for localizing differences in brain activation patterns without the need for anatomic predefined constraints. The purpose of this study was to assess the reproducibility of the patterns of activation obtained with SPM for baseline measures and for metabolic changes in response to lorazepam on a test-retest design. The results were compared with those we previously published using region-of-interest (ROI) methods. METHODS: Sixteen healthy right-handed men were scanned twice with PET and [18F]fluorodeoxyglucose (FDG): before placebo and before lorazepam (30 microg/kg). The same double FDG procedure was repeated 6-8 wk later to assess test-retest reproducibility. Image datasets were analyzed by using SPM95 software. Difference images between baseline and lorazepam were compared for the first and second evaluations, both for relative decreases as well as increases in metabolism. Significance level was systematically varied to P < 0.001, P < 0.01 and P < 0.05. RESULTS: There were no differences in the baseline SPM maps obtained for the first and second evaluations. SPM showed similar, although not identical, differences in response to lorazepam between the two evaluations. Both evaluations showed significant decreases in occipital cortex (9.7% and 10%) and significant relative increases in left temporal pole (6.8% and 10.4%). However, the second evaluation showed a decrease in the left frontal cortex (areas 6 and 8), which was not present in the first evaluation. The results were very similar to those we had obtained with ROI methods, except for the activation in the left temporal pole, which we had not observed with ROI analyses. CONCLUSION: Although the overall pattern of lorazepam-induced activation depicted by SPM was reproducible in pattern and magnitude, there were some differences that included a left frontal area of deactivation during the second but not the first evaluation. Results with SPM are similar to those with the ROI method, and, because it systematically analyses the whole brain, SPM can uncover patterns not seen with the ROI method.

MR-PET image coregistration for quantitation of striatal dopamine D2 receptors.

PURPOSE: Our goal was to assess the utility of MR-PET image coregistration to quantify dopamine D2 receptors in striatum. METHOD: Twenty-nine normal subjects were investigated with PET and [11C]raclopride and with MRI. D2 receptors were quantified using the ratio of the distribution volume in striatum to that in cerebellum. Measures obtained using regions selected directly from the PET images were compared with those obtained from MR images and then projected to coregistered PET images. RESULTS: There were no differences between measures selected from the PET images (3.9 +/- 0.5) and those from the MR images (3.9 +/- 0.65). The values for these two measures were significantly correlated and corresponded to r = 0.9, p < 0.0001. CONCLUSION: Regions of interest selected directly from PET images, where there is a large contrast between the region of interest and background, as for the case of dopamine D2 ligands, are almost identical to those obtained from coregistered MR images.

Hypometabolism in olfactory cortical projection areas of male patients with schizophrenia: an initial positron emission tomography study.

Several studies have reported olfactory deficits in schizophrenic patients. This study examines local cerebral metabolic rate within two cortical areas in eight normal men and eight schizophrenic men. A significantly greater degree of hypometabolism was observed in the schizophrenic men in the cortical area of the nondominant hemisphere that receives direct uncrossed olfactory projections.

Three-dimensional anatomical model-based segmentation of MR brain images through Principal Axes Registration.

Model-based segmentation and analysis of brain images depends on anatomical knowledge which may be derived from conventional atlases. Classical anatomical atlases are based on the rigid spatial distribution provided by a single cadaver. Their use to segment internal anatomical brain structures in a high-resolution MR brain image does not provide any knowledge about the subject variability, and therefore they are not very efficient in analysis. We present a method to develop three-dimensional computerized composite models of brain structures to build a computerized anatomical atlas. The composite models are developed using the real MR brain images of human subjects which are registered through the Principal Axes Transformation. The composite models provide probabilistic spatial distributions, which represent the variability of brain structures and can be easily updated for additional subjects. We demonstrate the use of such a composite model of ventricular structure to help segmentation of the ventricles and Cerebrospinal Fluid (CSF) of MR brain images. In this paper, a composite model of ventricles using a set of 22 human subjects is developed and used in a model-based segmentation of ventricles, sulci, and white matter lesions. To illustrate the clinical usefulness, automatic volumetric measurements on ventricular size and cortical atrophy for an additional eight alcoholics and 10 normal subjects were made. The volumetric quantitative results indicated regional brain atrophy in chronic alcoholics.

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.

Principal axes and surface fitting methods for three-dimensional image registration.

We evaluated the effect of the image acquisition parameters on the accuracy of the principal axes and surface-fitting techniques for three-dimensional image registration. Using two types of phantom objects, MR brain image and a mathematically defined ellipsoid, we simulated pairs of scans with known acquisition parameters, including longitudinal coverage, magnitude of mis-registration, number of sections and section thickness. Both methods are sensitive to the systematic deformation of contours. The principal axes method is also sensitive to incomplete scan coverage and to the x-axis and y-axis misangulation. Both methods are insensitive to the number of sections, section thickness and the number of points per section. Surface fitting performed well without user supervision. There is no need for routine inclusion of the scaling factors as search parameters. The results confirm the feasibility of three-dimensional multimodality registration of brain scans with accuracy 1-2 mm, with surface fitting being the method of choice.

Functional importance of ventricular enlargement and cortical atrophy in healthy subjects and alcoholics as assessed with PET, MR imaging, and neuropsychologic testing.

The authors assessed the relationship between ventricular enlargement, cortical atrophy, regional brain glucose metabolism, and neuropsychologic performance in 10 alcoholics and 10 control subjects. Regional brain glucose metabolism was measured with fluorine-18 fluorodeoxyglucose (FDG) and positron emission tomography (PET). Cortical atrophy and ventricular size were evaluated quantitatively with magnetic resonance (MR) imaging. Alcoholics had decreased brain glucose metabolism and more cortical atrophy but did not have significantly greater ventricular size than did control subjects. The degree of ventricular enlargement and of cortical atrophy was associated with decreased metabolism predominantly in the frontal cortices and subcortical structures in both alcoholics and control subjects. There were no significant correlations between neuropsychologic performance and MR imaging structural changes, whereas various subtest scores were significantly correlated with frontal lobe metabolism. These data show that F-18 FDG PET is a sensitive technique for detecting early functional changes in the brain due to alcohol and/or aging before structural changes can be detected with MR imaging.

Spatial low frequency pattern analysis in positron emission tomography: a study between normals and schizophrenics.

Using the two-dimensional Fourier transform and the brain's centroidal principal axis, a method is developed for the analysis of PET metabolic brain images without the use of predefined anatomic regions of interest. We applied the method to images from a group of 11 normal and 12 medicated schizophrenics tested under resting conditions and under a visual task. A cortical/subcortical spatial pattern was found to be significant in two directions; anterior/posterior and chiasmatic (left-anterior/right-posterior). The best individual clinical classification (Jackknife classification) occurred under visual task at two axial brain levels: at the basal ganglia with correct classification rates of 91% and 84%, while the cerebellum had rates of 82% and 92%. These high classification rates were obtained using only the four coefficients of the lowest spatial frequency. These results point to the generalized brain dysfunction of regional glucose metabolism in chronic medicated schizophrenics both at rest and at a visual image-tracking task.

The spectral signature method for the analysis of PET brain images.

We introduce the concept of the metabolic centroid spectrum as the feature space to characterize the distribution of metabolic activity in three-dimensional brains. The method computes the metabolic centroid of a brain subvolume for each increment of metabolic activity occurring in the whole brain. The result is the metabolic spectral signature, a continuous three-dimensional curve whose shape reflects the distribution of metabolic rates in the brain. The method's sensitivity to metabolic distribution asymmetries is greatly increased over that of the metabolic centroid method, while retaining its advantages; it is almost invariant to head size, head positioning, photon scatter, and the positron emission tomography (PET) camera's full width at half-maximum. It does not require magnetic resonance, computed tomography, or x-ray images. To test the method we analyzed the metabolic PET images of 40 normal subjects and 20 schizophrenics. The results show a unification of several metabolic characteristics of schizophrenic brains, such as laterality, hypofrontality, cortical/subcortical abnormalities, and overall brain hypometabolism, which were identified by different laboratories in separate studies using differing methodologies. Here they are presented by a single automatic objective method.

The metabolic centroid method for PET brain image analysis.

The method of centroids is an approach to the analysis of three-dimensional whole-brain positron emission tomography (PET) metabolic images. It utilizes the brain's geometric centroid and metabolic centroid so as to objectively characterize the central tendency of the distribution of metabolic activity in the brain. The method characterizes the three-dimensional PET metabolic image in terms of four parameters: the coordinates of the metabolic centroid and the mean metabolic rate of the whole brain. These parameters are not sensitive to spatially uniform random noise or to the position of the subject's head within a uniform PET camera field of view. The method has been applied to 40 normal subjects, 22 schizophrenics who were treated with neuroleptics, and 20 schizophrenics who were neuroleptic-free. The mean metabolic centroid of the normal subjects was found to be superior to the mean geometric centroid of the brain. The mean metabolic centroid of chronic schizophrenics is lower and more posterior to the mean geometric centroid than is that of normals. This difference is greater in medicated than in unmedicated schizophrenics. The posterior and downward displacement of the mean metabolic centroid is consistent with the concepts of hypofrontality, hyperactivity of subcortical structures, and neuroleptic effect in schizophrenics.

Electrical shock in pregnancy: a case report.

Electrical shock in pregnancy is associated with significant perinatal morbidity and mortality. A case of such an electrical shock in pregnancy is reported. A review of the literature follows. The severity of maternal injury does not correlate with the injury sustained by the fetus. Close fetal surveillance following electrical injury is necessary.