Alzheimer Disease: Hammers A

Yakushev I, Landvogt C, Buchholz HG, Fellgiebel A, Hammers A, Scheurich A, Schmidtmann I, Gerhard A, Schreckenberger M, Bartenstein P. · Department of Nuclear Medicine, University of Mainz, Mainz, Germany. · Psychiatry Res. · Pubmed #18930634 No free full text.

Abstract: At present, there is still no consensus on the choice of the reference area in positron emission tomography (PET) studies of Alzheimer's disease (AD). In this study, PET scans with fluorodeoxyglucose-F18 were carried out in the following groups of subjects: 47 patients with probable AD, 8 patients with mild cognitive impairment, and 15 age-similar healthy subjects. Scans normalized to the cerebral global mean (CGM), cerebellum (CBL), and the primary sensorimotor cortex (SMC). We evaluated the effect of the different count normalization procedures on the accuracy of (18)F-FDG PET to detect AD-specific metabolic abnormalities (voxel-based group comparison) and to differentiate between patients and healthy subjects (ROI-based discriminant analysis) with regard to the degree of clinical deterioration. Metabolic reductions in groups of very mildly, mildly and moderate-to-severely affected patients appeared, respectively, 2.2, 2.6, and 2.7 times greater in spatial extent when tracer uptake was normalized to SMC rather than to CGM. The overall accuracy of discrimination was 94%, 91%, and 80% after normalization to SMC, CBL, and CGM, respectively. In general, normalization to SMC was somewhat superior to cerebellar normalization, allowing the detection of more pronounced metabolic deficits and the more accurate discrimination of patients from non-patients. Normalization to CGM should be used with great caution not only in advanced stages of dementia, but also in very mild AD cases.

Shidahara M, Tsoumpas C, Hammers A, Boussion N, Visvikis D, Suhara T, Kanno I, Turkheimer FE. · Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, Japan. · Neuroimage. · Pubmed #18852055 No free full text.

Abstract: PURPOSE: Positron Emission Tomography (PET) has the unique capability of measuring brain function but its clinical potential is affected by low resolution and lack of morphological detail. Here we propose and evaluate a wavelet synergistic approach that combines functional and structural information from a number of sources (CT, MRI and anatomical probabilistic atlases) for the accurate quantitative recovery of radioactivity concentration in PET images. When the method is combined with anatomical probabilistic atlases, the outcome is a functional volume corrected for partial volume effects. METHODS: The proposed method is based on the multiresolution property of the wavelet transform. First, the target PET image and the corresponding anatomical image (CT/MRI/atlas-based segmented MRI) are decomposed into several resolution elements. Secondly, high-resolution components of the PET image are replaced, in part, with those of the anatomical image after appropriate scaling. The amount of structural input is weighted by the relative high frequency signal content of the two modalities. The method was validated on a digital Zubal phantom and clinical data to evaluate its quantitative potential. RESULTS: Simulation studies showed the expected relationship between functional recovery and the amount of correct structural detail provided, with perfect recovery achieved when true images were used as anatomical reference. The use of T1-MRI images brought significant improvements in PET image resolution. However improvements were maximized when atlas-based segmented images as anatomical references were used; these results were replicated in clinical data sets. CONCLUSION: The synergistic use of functional and structural data, and the incorporation of anatomical probabilistic information in particular, generates morphologically corrected PET images of exquisite quality.

Edison P, Archer HA, Gerhard A, Hinz R, Pavese N, Turkheimer FE, Hammers A, Tai YF, Fox N, Kennedy A, Rossor M, Brooks DJ. · MRC Clinical Sciences Centre, Cyclotron Building Hammersmith Hospital, Imperial College London, UK. · Neurobiol Dis. · Pubmed #18786637 No free full text.

Abstract: [11C](R)PK11195-PET is a marker of activated microglia while [11C]PIB-PET detects raised amyloid load. Here we studied in vivo the distributions of amyloid load and microglial activation in Alzheimer's disease (AD) and their relationship with cognitive status. Thirteen AD subjects had [11C](R)PK11195-PET and [11C]PIB-PET scans. Ten healthy controls had [11C](R)PK11195-PET and 14 controls had [11C]PIB-PET scans. Region-of-interest analysis of [11C](R)PK11195-PET detected significant 20-35% increases in microglial activation in frontal, temporal, parietal, occipital and cingulate cortices (p<0.05) of the AD subjects. [11C]PIB-PET revealed significant two-fold increases in amyloid load in these same cortical areas (p<0.0001) and SPM (statistical parametric mapping) analysis confirmed the localisation of these increases to association areas. MMSE scores in AD subjects correlated with levels of cortical microglial activation but not with amyloid load. The inverse correlation between MMSE and microglial activation is compatible with a role of microglia in neuronal damage.

Yakushev I, Hammers A, Fellgiebel A, Schmidtmann I, Scheurich A, Buchholz HG, Peters J, Bartenstein P, Lieb K, Schreckenberger M. · Department of Nuclear Medicine, University of Mainz, Mainz, Germany. · Neuroimage. · Pubmed #18691659 No free full text.

Abstract: Statistical comparisons of [(18)F]FDG PET scans between healthy subjects and patients with Alzheimer's disease (AD) or amnestic mild cognitive impairment (aMCI) using Statistical Parametric Mapping (SPM) usually require normalization of regional tracer uptake via ROIs defined using additional software. Here, we validate a simple SPM-based method for count normalization. FDG PET scans of 21 mild, 15 very mild AD, 11 aMCI patients and 15 age-matched controls were analyzed. First, we obtained relative increases in the whole patient sample compared to controls (i.e. areas relatively preserved in patients) with proportional scaling to the cerebral global mean (CGM). Next, average absolute counts within the cluster with the highest t-value were extracted. Statistical comparisons of controls versus three patients groups were then performed using count normalization to CGM, sensorimotor cortex (SMC) as standard, and to the cluster-derived counts. Compared to controls, relative metabolism in aMCI patients was reduced by 15%, 20%, and 23% after normalization to CGM, SMC, and cluster-derived counts, respectively, and 11%, 21%, and 25% in mild AD patients. Logistic regression analyses based on normalized values extracted from AD-typical regions showed that the metabolic values obtained using CGM, SMC, and cluster normalization correctly classified 81%, 89% and 92% of aMCI and controls; classification accuracies for AD groups (very mild and mild) were 91%, 97%, and 100%. The proposed algorithm of fully SPM-based count normalization allows for a substantial increase of statistical power in detecting very early AD-associated hypometabolism, and very high accuracy in discriminating mild AD and aMCI from healthy aging.

Heckemann RA, Hammers A, Rueckert D, Aviv RI, Harvey CJ, Hajnal JV. · Division of Neurosciences and Mental Health, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK. · BMC Med Imaging. · Pubmed #18500985 links to  free full text

Abstract: BACKGROUND: Diagnostic decisions in clinical imaging currently rely almost exclusively on visual image interpretation. This can lead to uncertainty, for example in dementia disease, where some of the changes resemble those of normal ageing. We hypothesized that extracting volumetric data from patients' MR brain images, relating them to reference data and presenting the results as a colour overlay on the grey scale data would aid diagnostic readers in classifying dementia disease versus normal ageing. METHODS: A proof-of-concept forced-choice reader study was designed using MR brain images from 36 subjects. Images were segmented into 43 regions using an automatic atlas registration-based label propagation procedure. Seven subjects had clinically probable AD, the remaining 29 of a similar age range were used as controls. Seven of the control subject data sets were selected at random to be presented along with the seven AD datasets to two readers, who were blinded to all clinical and demographic information except age and gender. Readers were asked to review the grey scale MR images and to record their choice of diagnosis (AD or non-AD) along with their confidence in this decision. Afterwards, readers were given the option to switch on a false-colour overlay representing the relative size of the segmented structures. Colorization was based on the size rank of the test subject when compared with a reference group consisting of the 22 control subjects who were not used as review subjects. The readers were then asked to record whether and how the additional information had an impact on their diagnostic confidence. RESULTS: The size rank colour overlays were useful in 18 of 28 diagnoses, as determined by their impact on readers' diagnostic confidence. A not useful result was found in 6 of 28 cases. The impact of the additional information on diagnostic confidence was significant (p < 0.02). CONCLUSION: Volumetric anatomical information extracted from brain images using automatic segmentation and presented as colour overlays can support diagnostic decision making.

Anderson AN, Pavese N, Edison P, Tai YF, Hammers A, Gerhard A, Brooks DJ, Turkheimer FE. · Department of Clinical Neuroscience, Division of Neuroscience and Mental Health, Imperial College London, UK. · Neuroimage. · Pubmed #17398120 No free full text.

Abstract: [(11)C]-(R)-PK11195 is presently the most widely used radiotracer for the monitoring of microglia activity in the central nervous system (CNS). Microglia, the resident immune cells of the brain, play a critical role in acute and chronic diseases of the central nervous system and in host defence against neoplasia. The purpose of this investigation was to evaluate the reliability and sensitivity of five kinetic modelling methods for the formation of parametric maps from dynamic [(11)C]-(R)-PK11195 studies. The methods we tested were the simplified reference tissue model (SRTM), basis pursuit, a simple target-to-reference ratio, the Logan plot and a wavelet based Logan plot. For the reliability assessment, the test-retest data consisted of four Alzheimer's patients that were scanned twice at approximately a six-week interval. For the sensitivity assessment, comparison of [(11)C]-(R)-PK11195 binding in Huntington's disease (HD) patients and normal subjects was performed using a group contrast to localize significant increases in mean pixel volume of distribution (VD) in HD. In all instances, a reference region kinetic extracted by a supervised clustering technique was used as input function. Reliability was assessed by use of the intra-class correlation coefficient (ICC) across a wide set of anatomical regions and it was found that the wavelet-based Logan plot, basis pursuit and SRTM gave the highest ICC values on average. The same methods produced the highest z-scores resulting from increases in mean striatal VD in HD patients compared with controls. The reference-to-target ratio and the Logan graphical approach were significantly less reliable and less sensitive.

Edison P, Archer HA, Hinz R, Hammers A, Pavese N, Tai YF, Hotton G, Cutler D, Fox N, Kennedy A, Rossor M, Brooks DJ. · MRC Clinical Sciences Centre and Division of Neuroscience, Hammersmith Hospital, Imperial College London, London, UK. · Neurology. · Pubmed #17065593 No free full text.

Abstract: OBJECTIVE: To investigate the association between brain amyloid load in Alzheimer disease (AD) measured by [11C]PIB-PET, regional cerebral glucose metabolism (rCMRGlc) measured by [18F]FDG-PET, and cognition. METHODS: Nineteen subjects with AD and 14 controls had [11C]PIB-PET and underwent a battery of psychometric tests. Twelve of those subjects with AD and eight controls had [18F]FDG-PET. Parametric images of [11C]PIB binding and rCMRGlc were interrogated with a region-of-interest atlas and statistical parametric mapping. [11C]PIB binding and rCMRGlc were correlated with scores on psychometric tests. RESULTS: AD subjects showed twofold increases in mean [11C]PIB binding in cingulate, frontal, temporal, parietal, and occipital cortical areas. Higher cortical amyloid load correlated with lower scores on facial and word recognition tests. Two patients fulfilling the clinical criteria for AD had normal [11C]PIB at baseline. Over 20 months this remained normal in one but increased in the cingulate of the other. Mean levels of temporal and parietal rCMRGlc were reduced by 20% in AD and these correlated with mini mental scores, immediate recall, and recognition memory test for words. Higher [11C]PIB uptake correlated with lower rCMRGlc in temporal and parietal cortices. CONCLUSION: [11C]PIB-PET detected an increased amyloid plaque load in 89% of patients with clinically probable Alzheimer disease (AD). The high frontal amyloid load detected by [11C]PIB-PET in AD in the face of spared glucose metabolism is of interest and suggests that amyloid plaque formation may not be directly responsible for neuronal dysfunction in this disorder.