Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain

Because the human brain consumes a disproportionate fraction of the resting body’s energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMRglc) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMRglc with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMRglc alterations compared to control were detected in all conditions except in congenitally blind where regional CMRglc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMRglc changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMRglc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMRglc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMRglc data in health and disease

JULIDE: A Software Tool for 3D Reconstruction and Statistical Analysis of Autoradiographic Mouse Brain Sections

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool

Cerebral F18 -FDG PET CT in Children: Patterns during Normal Childhood and Clinical Application of Statistical Parametric Mapping

The first aim was to recruit and analyse a high quality dataset of cerebral FDG PET CT scans in neurologically normal children. Using qualitative, semi-quantitative and statistical parametric mapping (SPM) techniques, the results showed that a pattern of FDG uptake similar to adults does not occur by one year of age as was previously believed, but the regional FDG uptake changes throughout childhood driven by differing age related regional rates of increasing FDG uptake. The second aim was to use this normal dataset in the clinical analysis of cerebral FDG PET CT scans in children with epilepsy and Neurofibromatosis type 1 (NF1). The normal dataset was validated for single-subject-versus-group SPM analysis and was highly specific for identifying the epileptogenic focus likely to result in a good post-operative outcome in children with epilepsy. Qualitative, semi-quantitative and group-versus-group SPM analyses were applied to FDG PET CT scans in children with NF1. The results showed reduced metabolism in the thalami and medial temporal lobes compared to neurologically normal children. This thesis has produced novel findings that advance the understanding of childhood brain development and has developed SPM techniques that can be applied to cerebral FDG PET CT scans in children with neurological disorders

Surface compositional mapping by spectral ratioing of ERTS-1 MSS data in the Wind River Basin and Range, Wyoming

The author has identified the following significant results. ERTS data collected in August and October 1972 were processed on digital and special purpose analog recognition computers using ratio enhancement and pattern recognition. Ratios of band-averaged laboratory reflectances of some minerals and rock types known to be in the scene compared favorably with ratios derived from the data by ratio normalization procedures. A single ratio display and density slice of the visible channels of ERTS MSS data, Channel 5/Channel 4 (R5,4), separated the Triassic Chugwater formation (redbeds) from other formations present and may have enhanced iron oxide minerals present at the surface in abundance. Comparison of data sets collected over the same area at two different times of the year by digital processing indicated that spectral variation due to environmental factors was reduced by ratio processing

Content based retrieval of PET neurological images

Medical image management has posed challenges to many researchers, especially when the images have to be indexed and retrieved using their visual content that is meaningful to clinicians. In this study, an image retrieval system has been developed for 3D brain PET (Position emission tomography) images. It has been found that PET neurological images can be retrieved based upon their diagnostic status using only data pertaining to their content, and predominantly the visual content. During the study PET scans are spatially normalized, using existing techniques, and their visual data is quantified. The mid-sagittal-plane of each individual 3D PET scan is found and then utilized in the detection of abnormal asymmetries, such as tumours or physical injuries. All the asymmetries detected are referenced to the Talairarch and Tournoux anatomical atlas. The Cartesian co- ordinates in Talairarch space, of detected lesion, are employed along with the associated anatomical structure(s) as the indices within the content based image retrieval system. The anatomical atlas is then also utilized to isolate distinct anatomical areas that are related to a number of neurodegenerative disorders. After segmentation of the anatomical regions of interest algorithms are applied to characterize the texture of brain intensity using Gabor filters and to elucidate the mean index ratio of activation levels. These measurements are combined to produce a single feature vector that is incorporated into the content based image retrieval system. Experimental results on images with known diagnoses show that physical lesions such as head injuries and tumours can be, to a certain extent, detected correctly. Images with correctly detected and measured lesion are then retrieved from the database of images when a query pertains to the measured locale. Images with neurodegenerative disorder patterns have been indexed and retrieved via texture-based features. Retrieval accuracy is increased, for images from patients diagnosed with dementia, by combining the texture feature and mean index ratio value

Incorporating accurate statistical modeling in PET: reconstruction for whole-body imaging

Tese de doutoramento em Biofísica, apresentada à Universidade de Lisboa através da Faculdade de Ciências, 2007The thesis is devoted to image reconstruction in 3D whole-body PET imaging. OSEM ( Ordered Subsets Expectation maximization ) is a statistical algorithm that assumes Poisson data. However, corrections for physical effects (attenuation, scattered and random coincidences) and detector efficiency remove the Poisson characteristics of these data. The Fourier Rebinning (FORE), that combines 3D imaging with fast 2D reconstructions, requires corrected data. Thus, if it will be used or whenever data are corrected prior to OSEM, the need to restore the Poisson-like characteristics is present. Restoring Poisson-like data, i.e., making the variance equal to the mean, was achieved through the use of weighted OSEM algorithms. One of them is the NECOSEM, relying on the NEC weighting transformation. The distinctive feature of this algorithm is the NEC multiplicative factor, defined as the ratio between the mean and the variance. With real clinical data this is critical, since there is only one value collected for each bin the data value itself. For simulated data, if we keep track of the values for these two statistical moments, the exact values for the NEC weights can be calculated. We have compared the performance of five different weighted algorithms (FORE+AWOSEM, FORE+NECOSEM, ANWOSEM3D, SPOSEM3D and NECOSEM3D) on the basis of tumor detectablity. The comparison was done for simulated and clinical data. In the former case an analytical simulator was used. This is the ideal situation, since all the weighting factors can be exactly determined. For comparing the performance of the algorithms, we used the Non-Prewhitening Matched Filter (NPWMF) numerical observer. With some knowledge obtained from the simulation study we proceeded to the reconstruction of clinical data. In that case, it was necessary to devise a strategy for estimating the NEC weighting factors. The comparison between reconstructed images was done by a physician largely familiar with whole-body PET imaging

The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification

A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of b-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging.</p

ADVANCEMENTS IN QUANTITATIVE PERFUSION MAGNETIC RESONANCE IMAGING (MRI) OF DEMENTIA

Alzheimer's disease (AD) affects a considerable, and increasing, part of the population. Early diagnosis of AD is very important to permit effective therapy, and minimize AD's social and economic burden. The goal of our research is to evaluate the changes of cerebral perfusion (i.e., blood flow) in the early stages of AD and the effects from hypertension.We studied volunteers with Mild Cognitive Impairment (MCI) and early AD from the Pittsburgh cohort of the Cardiovascular Health Study (CHS) Cognitive Study during a four-year follow-up. Previously, studies used referral patients who typically have more advanced AD. No perfusion data concerning the early and transitional disease stages are currently available from population studies (i.e., subjects who have been monitored longitudinally in time). There are no common techniques for perfusion quantification and image analysis so that inconsistencies are observed between/within studies, modalities, and researchers. Several advancements were achieved in preparation for the cohort study. First, we improved the accuracy and speed of brain perfusion quantification. Second, we improved the accuracy of image registration to a reference brain using quantitative validation of a registration method and performance comparison with a popular registration method. Third, we improved the method of statistical analysis for evaluating the changes of perfusion between groups. Fourth, we evaluated the changes of cerebral perfusion between cognitive groups (controls, MCIs, ADs), and hypertension and normo-tensive subgroups.Individual perfusion maps were improved by measuring and incorporating individual arrival time, saturation effects, and individual inversion efficiency. A fully deformable registration technique was shown to be more accurate than standard techniques like statistical parametric mapping to detect local perfusion changes. All of the published literature for perfusion up-to-date reported decreased perfusion in AD, but we found hyperperfusion in some regions. The regional findings imply that a hemodynamic process, at the capillary level, accompanied the neurodegenerative process. Hypertensive normal cognitive controls demonstrated hypoperfusion in regions usually involved in AD pathology. However, the effect of hypertension was attenuated after the onset of the pathological cognitive process

Asymmetric Cerebral Blood Flow in Patients with Mild Cognitive Impairment: Possible Relationship to Further Cognitive Deterioration

To explore patterns of cerebral blood flow in patients with mild cognitive impairment (MCI), who (1) eventually deteriorate into overt dementia, with no particular focus on the type of dementia, or (2) do not appear to further deteriorate in their cognitive functions