Shizuo Hatashita

Diagnosed Mild Cognitive Impairment Due to Alzheimer’s Disease with PET Biomarkers of Beta Amyloid and Neuronal Dysfunction

The aim of this study is to identify mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) using amyloid imaging of beta amyloid (Aβ) deposition and FDG imaging of reflecting neuronal dysfunction as PET biomarkers. Sixty-eight MCI patients underwent cognitive testing, [11C]-PIB PET and [18F]-FDG PET at baseline and follow-up. Regions of interest were defined on co-registered MRI. PIB distribution volume ratio (DVR) was calculated using Logan graphical analysis, and the standardized uptake value ratio (SUVR) on the same regions was used as quantitative analysis for [18F]-FDG. Thirty (44.1%) of all 68 MCI patients converted to AD over 19.2±7.1 months. The annual rate of MCI conversion was 23.4%. A positive Aβ PET biomarker significantly identified MCI due to AD in individual MCI subjects with a sensitivity (SS) of 96.6% and specificity (SP) of 42.1%. The positive predictive value (PPV) was 56.8%. A positive Aβ biomarker in APOE ε4/4 carriers distinguished with a SS of 100%. In individual MCI subjects who had a prominent impairment in episodic memory and aged older than 75 years, an Aβ biomarker identified MCI due to AD with a greater SS of 100%, SP of 66.6% and PPV of 80%, compared to FDG biomarker alone or both PET biomarkers combined. In contrast, when assessed in precuneus, both Aβ and FDG biomarkers had the greatest level of certainty for MCI due to AD with a PPV of 87.8%. The Aβ PET biomarker primarily defines MCI due to AD in individual MCI subjects. Furthermore, combined FDG biomarker in a cortical region of precuneus provides an added diagnostic value in predicting AD over a short period.

Clinically Different Stages of Alzheimer's Disease Associated by Amyloid Deposition with [ 11C]-PIB PET Imaging

We investigated whether [11C]-PIB PET detects underlying amyloid deposition at clinically different stages of Alzheimers disease (AD) and preclinical dementia. The Japanese cohort of 214 subjects underwent cognitive testing and 60-min dynamic [11C]-PIB PET. [11C]-PIB data were acquired from 35-60 min after injection. Regions of interest were defined on co-registered MRI. Distribution volume ratios (DVR) of PIB retention were determined using Logan graphical analysis. All 56 patients with AD showed a robust increase in PIB retention in cortical areas (typical PIB AD-pattern). A mean DVR value in 11 patients with moderate AD (CDR: 2.1 ± 0.4) showed significantly higher PIB retention (2.38 ± 0.42, p < 0.01) than amyloid-negative healthy control (HC) subjects. The DVR values in 23 patients with very mild AD (CDR: 0.5) and 22 patients with mild AD (CDR: 1.0) were 2.32 ± 0.45 and 2.34 ± 0.42, respectively, similar to moderate AD. In contrast, 28 (48%) of the 58 mild cognitive impairment (MCI) patients (MMSE: 27.3 ± 1.7) showed a typical AD-like pattern with a DVR value of 2.07 ± 0.34. Further, 17 (18%) of 91 HC subjects had a typical AD-like pattern with a DVR value of 2.06 ± 0.28. They did not significantly differ from very mild AD. The prevalence of AD among the 53 amyloid positive patients aged 75 years or older increased greatly to 74% whereas that of amyloid positive HC decreased by only 9% and amyloid positive MCI by 17%. Prodromal AD and AD dementia is identified, based on cognitive function and amyloid deposition by PIB PET imaging. Further, the cortical amyloid deposition could be detected at preclinical stage of AD.

Amyloid-β Deposition and Long-Term Progression in Mild Cognitive Impairment due to Alzheimer’s Disease Defined with Amyloid PET Imaging

The aim was to evaluate brain amyloid-β (Aβ) deposition in patients with mild cognitive impairment (MCI) due to Alzheimers disease (AD) using amyloid PET imaging and clarify the relationship between the annual change in Aβ deposition and disease progression. Forty-eight MCI patients underwent neuropsychological assessment and amyloid PET imaging using [11C]-PIB over a follow-up of 5.7±1.5 years. Thirty-nine MCI patients who had an amyloid-positive scan were defined as MCI due to AD, and 9 MCI patients who had an amyloid-negative scan were included. Regions of interest were defined on co-registered MRI, and the PIB standardized uptake value ratio (SUVR) on the same regions was used over follow-up. Annual change in PIB SUVR was calculated. Patients with MCI due to AD had higher baseline PIB SUVR (1.81±0.32, n = 39, p < 0.01) and a greater annual rate of change in PIB SUVR (0.044±0.027, n = 39, p < 0.01) compared to amyloid-negative MCI patients. Twenty-eight (71.8%) progressed to AD. In patients who progressed during a short duration of 1.7±0.8 years, the annual rate of increase in PIB SUVR was 0.101±0.094 (n = 16, p < 0.05), which was greater compared to patients with long conversion or stable patients. There was a negative correlation between the annual rate of increase in PIB SUVR and duration of progression to AD among individual MCI converters (r = -0.47, n = 28, p < 0.05). The patients defined as MCI due to AD could progress to AD with a shorter period if they have a greater increased annual rate in brain Aβ deposition.

PROGRESSION OF MILD COGNITIVE IMPAIRMENT DUE TO ALZHEIMER'S DISEASE WITH AMYLOID-PET AND FDG-PET IMAGING

Background:The aim is to evaluate the progression of “mild cognitive impairment (MCI) due to Alzheimer’s disease (AD)” using amyloid PET imaging of a beta amyloid (Aß) deposition and FDGPET imaging of hypometabolism among MCI patients. Methods: Fifty patients (age 53-83 years) who met the core clinical criteria for MCI and had a positive amyloid PET with Aß deposition (PIB SUVR > 1.24) were defined as MCI due to AD, and underwent cognitive assessment, [11C]-PIB PET and [18F]-FDG PET at baseline and two or more over follow-up of 5.1361.26 years. Regions of interest were defined on co-registered MRI. A quantitative analysis for [11C]-PIB and [18F]-FDG was used with standardized uptake value ratio (SUVR) on same regions. Results:The cortical PIB SUVR in 50 patients with MCI due to AD was 1.8860.32 at baseline, which significantly increased to 2.0460.31 at followup. An annual increase of PIB SUVR was 0.04860.039 per year, being an increase of 2.7% from baseline. In contrast, the FDG SUVR in 50 patients significantly decreased from 0.9760.06 to 0.9460.07 at follow-up, and 35 (70%) had a hypometabolism (FDG SUVR 0.99) at baseline. An annual change of FDG SUVR was –0.00660.015 per year. There was no significant correlation between increase in PIB SUVR and decrease in FDG SUVR (r1⁄40.14, n1⁄450, p1⁄40.31). Thirty-eight (76%) of 50 MCI due to AD patients progressed to AD over follow-up while 29 (82.8%) of 35 patients with hypometabolism progressed to AD. Sixteen (80%) of 20 patients with high cortical PIB SUVR 1.94) at baseline progressed to AD over the short-term (1.4660.63 years), significantly different from 10 (33.3%) of 30 patients with low PIB SUVR. In addition, when 13 MCI patients with high PIB SUVR had hypometabolism, 12 (92.3%) of them progressed to AD over the short-term while only one did over the long-term. Conclusions: The patients with MCI due to AD have an increase in Aß deposition and a decrease in glucose metabolism over time, both of which does not correlate with each other. The MCI patients with cortical hypometabolism in additon to high Aß deposition could progress to AD dementia in a shorter period of time.

PROGRESSION OF PRECLINICAL ALZHEIMER'S DISEASE ASSOCIATED WITH AMYLOID PET AND FDG PET IMAGING

functional images and performed the standard procedures (slice-time correction, motion estimation, ICBM152-fMRI nonlinear template coregistration, resampling, band-pass filtering (0.01-0.1Hz), 6mm isotropic Gaussian blurring kernel smoothing). A scrubbing method was used to exclude volumes with excessive motion (frame displacement > 0.5). Next, we performed a seed-based correlation analysis using fMRIStat, followed by a cross-sectional group comparison and longitudinal analysis with 6 months follow-ups after the initial assessment, with multistat, correcting for both age and gender.Results: 36 controls (age 7567), 65Mild Cognitive Impairment (MCI, age 7267) patients and 26 AD patients’ (age 73.267) images qualified for the study. The posterior cingulate cortex (PCC) was the region most affected by metabolic deficits in Alzheimer’s Disease patients (Figure 1a). A group comparison shows that AD patients have decreased connectivity between the PCC and the anterior cingulate cortex, the left superior temporal gyrus, the perirhinal cortex and the right caudate nucleus (Figure 1c). Longitudinally, AD patients and controls do not show meaningful changes 6 months after initial assessment (Figure 1df). Conversely, MCI patients show connectivity disruptions in the right insula and the left parietal-occipital juncture, while also increases in the left temporal gyrus and the fusiform gyrus bilaterally (Figure 1e). Conclusions: Conforming to previous studies, AD patients have significant metabolic defects in the posterior cingulate cortex (PCC). As a result, connections between the PCC and other areas of the brain are significantly disrupted. A 6 months follow-up is not sufficient for capturing network changes in controls or dementia patients; however, changes in large scale connectivity observed here do fit the conceptual framework in which brain networks undergo compensatory changes in MCI patients.

Natural history of amyloid deposition in Alzheimer's disease associated with PIB PET imaging

Background: We evaluate the effect of cognitive impairment, age, and apolipoprotein-E (APOE) genotype on amyloid deposition in AD patients, and the natural history of amyloid deposition over time. Methods: 42 AD patients and 10 healthy control (HC) subjects were included in a followup study for 24 months. All subjects underwent cognitive testing, APOE genotype assessment and 60-min dynamic [11C]-PIB PET. Data was acquired from 35-60 min after injection. Regions of interest were defined on co-registered MRI. PIB distribution volume ratios (DVR) were calculated with Logan graphical analysis. The clinical assessments and [11C]-PIB PET were carried at 6, 12 or 24 months after baseline. Relative changes in PIB retention were calculated using the percentage change [(DVR at follow-up DVRat baseline) / (DVR at baseline)]. Results: All AD patients showed increase in PIB retention in cortical regions at baseline. Mean cortical DVR value was 2.26 6 0.43, being significantly higher PIB retention. In precuneus, mean DVR value was the greatest among all cortical regions (2.90 6 0.60), followed by anterior and posterior cingulate, frontal, parietal and lateral temporal cortices. Mean DVR value in APOE e4 carriers did not differ from non-carriers. Individual DVR values among all AD patients were not related with age (r 1⁄4 -0.03, p 1⁄4 0.80). After baseline, mean DVR value in AD patients was 2.15 6 0.35 at 6 months, 2.27 6 0.28 at 12 months and 2.506 0.37 at 24 months, which trended to increase but not significant, while a mean CDR SB score at 24 months (6.8 6 4.1) was significantly higher compared with baseline (4.3 6 2.8). The relative changes in individual DVR values ranged from -11.0% to 25.2% over 24 months. Even in precuneus with highest PIB retention, the DVR value did not increase over time. Relative changes inindividual DVR values at each follow-up time point did not significantly correlated with concurrent changes on CDR SB or MMSE scores. Conclusions: The amyloid deposition does not continue to accumulate in any cortical region during the progression of AD, despite dementia severity, APOEe4 status and age. The precuneus can play a potentially critical role in the pathophysiology of AD.

Progression of Prodromal Alzheimer's disease associated with Amyloid Deposition using PIB PET Imaging

Values calculated by one-tailed independent t-tests. Simon F. Eskildsen, Eric Westman, Femida Gwadry-Sridhar, Per Julin, Niclas Sjögren, Sebastian Muehlboeck, Lars-Olof Wahlund, Magda Tsolaki, Hilkka Soininen, Patrizia Mecocci, Iwona Kloszewska, Bruno Vellas, Simon Lovestone, Andrew Simmons, Christian Spenger AddNeuroMed Consortium, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark; Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; I-THINK Research Lab, Lawson Health Research Institute, London, ON, Canada; AstraZeneca R&D, Södertälje, Sweden; Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden; Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece; Department of Neurology, University and University Hospital of Kuopio, Kuopio, Finland; Institute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy; Department of Old Age Psychiatry & Psychotic Disorders, Medical University of Lodz, Lodz, Poland; Department of Internal and Geriatrics Medicine, Hôpitaux de Toulouse, Toulouse, France; King’s College London, Institute of Psychiatry, London, United Kingdom; NIHR Biomedical Research Centre for Mental Health, London, United Kingdom. Contact e-mail: se@hst.aau.dk

Clinical different stage of Alzheimer's disease associated with amyloid load by [11C] PiB-PET imaging

impairment, non demented elderly (CIND) from a community-based sample. The study of neuropsychiatric syndromes instead of separate neuropsychiatric symptoms may point to a common neurobiological pathogenesis, or may respond to the same treatments. Methods: The dementia epidemiologic study was performed in the urban area of São Paulo. Thirteen patients with AD, 11 with CIND and 13 normal individuals were evaluated. The HMRS was performed in the right temporal, left parietal and medial occipital region studying the metabolits: N-acetylaspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mI). The neuropsychiatric symptoms were assessed with the Neuropsychiatric Inventory (NPI) and classified in neuropsychiatric syndromes (hyperactivity, psychosis, affective symptoms and apathy) in accordance with the results from the European Alzheimer Disease Consortium. The neuropsychiatric syndromes were correlated with the H-MRS metabolities. Results: Parietal mICr was correlated positively with hyperactivity and apathy. Temporal mICr was correlated negatively with psychosis in patients with AD (Spearman’s coefficient; p 0,05). On the other hand, in the CIND group, occipital NAACr was correlated negatively with hyperactivity and psychosis and temporal NAA and mI were correlated negatively with apathy (Spearman’s coefficient; p 0,05). The comparison between the average NPI scores in each group (AD, CIND and normal individuals) showed significantly differences between elderly controls and AD patients on the apathy scores. Conclusions: The results suggest that neuropsychiatric symptoms can be associated with specific metabolic alterations measured by H-MRS in patients with AD and CIND.

IC-P1-027: Imaging of cortical amyloid load and cerebral glucose metabolism in patients with Alzheimer's disease and mild cognitive impairment

Background: The aim is to investigate the deposition of amyloid plaques by carbon 11-labeled Pittsburgh Compound B ([11C]-PIB) in the brains with dementia (Alzheimer’s type, AD) and mild cognitive impairment (MCI). We clarify the association between cerebral amyloid load and glucose metabolism. Methods: Thirty-four patients with dementia, 26 with MCI and 22 healthy control (HC) were studied. All 82 patients underwent 90-min dynamic [11C]PIB PET and 20-min static [18F]-FDG PET. [11C]-PIB data was acquired from 35-60 min after injection. Regions of interest (ROI) were defined on coregistered MRI and used in the analysis of the PET data. PIB distribution volume ratios (DVR) were calculated using Logan graphical analysis (cerebellar gray as reference region). [18F]-FDG PET images were extracted using 3 dimensional stereotactic surface projections (3D-SSP) by a Z-score on a pixel-by-pixel basis. Quantitative analysis for both [11C]-PIB and [18F]-FDG used the standardized uptake value ratio (SUVR) values of cortical regions. Results: A robust increase in PIB binding was observed in the anterior and posterior cingulate, precuneus, frontal, parietal, lateral temporal cortical areas in sixteen of 27 AD patients (typical PIB AD-pattern). The mean value of DVR in these cortical areas was significantly greater than in HC (2.66 0.56 vs 1.32 0.13, P 0.01). Of the 26 MCI patients, twelve showed typical AD-like patterns of amyloid deposition similar to AD. On [18F]-FDG PET 3D-SSP images, eleven of 16 AD patients with typical PIB AD-like pattern showed significant reduction of cortical glucose metabolism in temporo-parietal, frontal, and posterior cingulate cortex and precuneus (classic metabolic AD-pattern). The other 5 patients showed hypometabolism in posteior cingulate gyrus and precuneus, but not in cortical regions. In contrast, three of 12 MCI patients with typical PIB AD-like pattern had the classic metabolic AD-pattern on 3D-SSP images. Only 3 patients showed no hypometabolism in any cortical regions. In patients with typical PIB ADpattern, there was no correlation between PIB and FDG SUVR values in different cortical regions. Conclusions: The [11C]-PIB PET scan could potentially determine characteristic cerebral pattern of amyloid-beta plaque load. This amyloid plaque formation is not directly responsible for cerebral glucose metabolism in cortical regions.