Characterizing the emergence of amyloid and tau burden in Down syndrome.

INTRODUCTION: Almost all individuals with Down syndrome (DS) will develop neuropathological features of Alzheimer's disease (AD). Understanding AD biomarker trajectories is necessary for DS-specific clinical interventions and interpretation of drug-related changes in the disease trajectory. METHODS: A total of 177 adults with DS from the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) underwent positron emission tomography (PET) and MR imaging. Amyloid-beta (Aß) trajectories were modeled to provide individual-level estimates of Aß-positive (A+) chronicity, which were compared against longitudinal tau change. RESULTS: Elevated tau was observed in all NFT regions following A+ and longitudinal tau increased with respect to A+ chronicity. Tau increases in NFT regions I-III was observed 0-2.5 years following A+. Nearly all A+ individuals had tau increases in the medial temporal lobe. DISCUSSION: These findings highlight the rapid accumulation of amyloid and early onset of tau relative to amyloid in DS and provide a strategy for temporally characterizing AD neuropathology progression that is specific to the DS population and independent of chronological age. HIGHLIGHTS: Longitudinal amyloid trajectories reveal rapid Aß accumulation in Down syndrome NFT stage tau was strongly associated with A+ chronicity Early longitudinal tau increases were observed 2.5-5 years after reaching A.

MISPEL: A supervised deep learning harmonization method for multi-scanner neuroimaging data.

Large-scale data obtained from aggregation of already collected multi-site neuroimaging datasets has brought benefits such as higher statistical power, reliability, and robustness to the studies. Despite these promises from growth in sample size, substantial technical variability stemming from differences in scanner specifications exists in the aggregated data and could inadvertently bias any downstream analyses on it. Such a challenge calls for data normalization and/or harmonization frameworks, in addition to comprehensive criteria to estimate the scanner-related variability and evaluate the harmonization frameworks. In this study, we propose MISPEL (Multi-scanner Image harmonization via Structure Preserving Embedding Learning), a supervised multi-scanner harmonization method that is naturally extendable to more than two scanners. We also designed a set of criteria to investigate the scanner-related technical variability and evaluate the harmonization techniques. As an essential requirement of our criteria, we introduced a multi-scanner matched dataset of 3T T1 images across four scanners, which, to the best of our knowledge is one of the few datasets of this kind. We also investigated our evaluations using two popular segmentation frameworks: FSL and segmentation in statistical parametric mapping (SPM). Lastly, we compared MISPEL to popular methods of normalization and harmonization, namely White Stripe, RAVEL, and CALAMITI. MISPEL outperformed these methods and is promising for many other neuroimaging modalities.

Direct Comparison of the Tau PET Tracers 18F-Flortaucipir and 18F-MK-6240 in Human Subjects.

Tau PET tracers exhibit varying levels of specific signal and distinct off-target binding patterns that are more diverse than amyloid PET tracers. This study compared 2 frequently used tau PET tracers, 18F-flortaucipir and 18F-MK-6240, in the same subjects. Methods:18F-flortaucipir and 18F-MK-6240 scans were collected within 2 mo in 15 elderly subjects varying in clinical diagnosis and cognition. FreeSurfer, version 5.3, was applied to 3-T MR images to segment Braak pathologic regions (I-VI) for PET analyses. Off-target binding was assessed in the choroid plexus, meninges, and striatum. SUV ratio (SUVR) outcomes were determined over 80-100 min (18F-flortaucipir) or 70-90 min (18F-MK-6240) normalized to cerebellar gray matter. Masked visual interpretation of images was performed by 5 raters for both the medial temporal lobe and the neocortex, and an overall (majority) rating was determined. Results: Overall visual ratings showed complete concordance between radiotracers for both the medial temporal lobe and the neocortex. SUVR outcomes were highly correlated (r2 > 0.92; P ≪ 0.001) for all Braak regions except Braak II. The dynamic range of SUVRs in target regions was approximately 2-fold higher for 18F-MK-6240 than for 18F-flortaucipir. Cerebellar SUVs were similar for 18F-MK-6240 and 18F-flortaucipir, suggesting that differences in SUVRs are driven by specific signals. Apparent off-target binding was observed often in the striatum and choroid plexus with 18F-flortaucipir and most often in the meninges with 18F-MK-6240. Conclusion: Both 18F-MK-6240 and 18F-flortaucipir are capable of quantifying signal in a common set of brain regions that develop tau pathology in Alzheimer disease; these tracers perform equally well in visual interpretations. Each also shows distinct patterns of apparent off-target binding. 18F-MK-6240 showed a greater dynamic range in SUVR estimates, which may be an advantage in detecting early tau pathology or in performing longitudinal studies to detect small interval changes.

MULTI-DOMAIN LEARNING BY META-LEARNING: TAKING OPTIMAL STEPS IN MULTI-DOMAIN LOSS LANDSCAPES BY INNER-LOOP LEARNING.

We consider a model-agnostic solution to the problem of Multi-Domain Learning (MDL) for multi-modal applications. Many existing MDL techniques are model-dependent solutions which explicitly require nontrivial architectural changes to construct domain-specific modules. Thus, properly applying these MDL techniques for new problems with well-established models, e.g. U-Net for semantic segmentation, may demand various low-level implementation efforts. In this paper, given emerging multi-modal data (e.g., various structural neuroimaging modalities), we aim to enable MDL purely algorithmically so that widely used neural networks can trivially achieve MDL in a model-independent manner. To this end, we consider a weighted loss function and extend it to an effective procedure by employing techniques from the recently active area of learning-to-learn (meta-learning). Specifically, we take inner-loop gradient steps to dynamically estimate posterior distributions over the hyperparameters of our loss function. Thus, our method is model-agnostic, requiring no additional model parameters and no network architecture changes; instead, only a few efficient algorithmic modifications are needed to improve performance in MDL. We demonstrate our solution to a fitting problem in medical imaging, specifically, in the automatic segmentation of white matter hyperintensity (WMH). We look at two neuroimaging modalities (T1-MR and FLAIR) with complementary information fitting for our problem.

ROBUST WHITE MATTER HYPERINTENSITY SEGMENTATION ON UNSEEN DOMAIN.

Typical machine learning frameworks heavily rely on an underlying assumption that training and test data follow the same distribution. In medical imaging which increasingly begun acquiring datasets from multiple sites or scanners, this identical distribution assumption often fails to hold due to systematic variability induced by site or scanner dependent factors. Therefore, we cannot simply expect a model trained on a given dataset to consistently work well, or generalize, on a dataset from another distribution. In this work, we address this problem, investigating the application of machine learning models to unseen medical imaging data. Specifically, we consider the challenging case of Domain Generalization (DG) where we train a model without any knowledge about the testing distribution. That is, we train on samples from a set of distributions (sources) and test on samples from a new, unseen distribution (target). We focus on the task of white matter hyperintensity (WMH) prediction using the multi-site WMH Segmentation Challenge dataset and our local in-house dataset. We identify how two mechanically distinct DG approaches, namely domain adversarial learning and mix-up, have theoretical synergy. Then, we show drastic improvements of WMH prediction on an unseen target domain.

Multi-scanner Harmonization of Paired Neuroimaging Data via Structure Preserving Embedding Learning.

Combining datasets from multiple sites/scanners has been becoming increasingly more prevalent in modern neuroimaging studies. Despite numerous benefits from the growth in sample size, substantial technical variability associated with site/scanner-related effects exists which may inadvertently bias subsequent downstream analyses. Such a challenge calls for a data harmonization procedure which reduces the scanner effects and allows the scans to be combined for pooled analyses. In this work, we present MISPEL (Multi-scanner Image harmonization via Structure Preserving Embedding Learning), a multi-scanner harmonization framework. Unlike existing techniques, MISPEL does not assume a perfect coregistration across the scans, and the framework is naturally extendable to more than two scanners. Importantly, we incorporate our multi-scanner dataset where each subject is scanned on four different scanners. This unique paired dataset allows us to define and aim for an ideal harmonization (e.g., each subject with identical brain tissue volumes on all scanners). We extensively view scanner effects under varying metrics and demonstrate how MISPEL significantly improves them.

A multi-scanner neuroimaging data harmonization using RAVEL and ComBat.

Modern neuroimaging studies frequently combine data collected from multiple scanners and experimental conditions. Such data often contain substantial technical variability associated with image intensity scale (image intensity scales are not the same in different images) and scanner effects (images obtained from different scanners contain substantial technical biases). Here we evaluate and compare results of data analysis methods without any data transformation (RAW), with intensity normalization using RAVEL, with regional harmonization methods using ComBat, and a combination of RAVEL and ComBat. Methods are evaluated on a unique sample of 16 study participants who were scanned on both 1.5T and 3T scanners a few months apart. Neuroradiological evaluation was conducted for 7 different regions of interest (ROI's) pertinent to Alzheimer's disease (AD). Cortical measures and results indicate that: (1) RAVEL substantially improved the reproducibility of image intensities; (2) ComBat is preferred over RAVEL and the RAVEL-ComBat combination in terms of regional level harmonization due to more consistent harmonization across subjects and image-derived measures; (3) RAVEL and ComBat substantially reduced bias compared to analysis of RAW images, but RAVEL also resulted in larger variance; and (4) the larger root mean square deviation (RMSD) of RAVEL compared to ComBat is due mainly to its larger variance.

Characterization of point-spread function specification error on Geometric Transfer Matrix partial volume correction in [11C]PiB amyloid imaging.

PURPOSE: Partial-volume correction (PVC) using the Geometric Transfer Matrix (GTM) method is used in positron emission tomography (PET) to compensate for the effects of spatial resolution on quantitation. We evaluate the effect of misspecification of scanner point-spread function (PSF) on GTM results in amyloid imaging, including the effect on amyloid status classification (positive or negative). METHODS: Twenty-nine subjects with Pittsburgh Compound B ([11C]PiB) PET and structural T1 MR imaging were analyzed. FreeSurfer 5.3 (FS) was used to parcellate MR images into regions-of-interest (ROIs) that were used to extract radioactivity concentration values from the PET images. GTM PVC was performed using our "standard" PSF parameterization [3D Gaussian, full-width at half-maximum (w) of approximately 5 mm]. Additional GTM PVC was performed with "incorrect" parameterizations, taken around the correct value. The result is a set of regional activity values for each of the GTM applications. For each case, activity values from various ROIs were combined and normalized to produce standardized uptake value ratios (SUVRs) for nine standard [11C]PiB quantitation ROIs and a global region. GTM operating-point characteristics were determined from the slope of apparent SUVR versus w curves. RESULTS: Errors in specification of w on the order of 1 mm (3D) mainly produce only modest errors of up to a few percent. An exception was the anterior ventral striatum in which fractional errors of up to 0.29 per millimeter (3D) of error in w were observed. CONCLUSION: While this study does not address all the issues regarding the quantitative strengths and weakness of GTM PVC, we find that with reasonable caution, the unavoidable inaccuracies associated with PSF specification do not preclude its use in amyloid quantitation.

Imaging beta-amyloid (Aß) burden in the brains of middle-aged individuals with alcohol-use disorders: a [11C]PIB PET study.

No in vivo human studies have examined the prevalence of Alzheimer's disease (AD) neuropathology in individuals with alcohol-use disorder (AUD), although recent research suggests that a relationship between the two exists. Therefore, this study used Pittsburgh Compound-B ([11C]PiB) PET imaging to test the hypothesis that AUD is associated with greater brain amyloid (Aß) burden in middle-aged adults compared to healthy controls. Twenty healthy participants (14M and 6F) and 19 individuals with AUD (15M and 4F), all aged 40-65 years, underwent clinical assessment, MRI, neurocognitive testing, and positron emission tomography (PET) imaging. Global [11C]PiB standard uptake value ratios (SUVRs), cortical thickness, gray matter volumes (GMVs), and neurocognitive function in subjects with AUD were compared to healthy controls. These measures were selected because they are considered markers of risk for future AD and other types of neurocognitive dysfunction. The results of this study showed no significant differences in % global Aß positivity or subthreshold Aß loads between AUD and controls. However, relative to controls, we observed a significant 6.1% lower cortical thickness in both AD-signature regions and in regions not typically associated with AD, lower GMV in the hippocampus, and lower performance on tests of attention as well as immediate and delayed memory in individuals with AUD. This suggest that Aß accumulation is not greater in middle-aged individuals with AUD. However, other markers of neurodegeneration, such as impaired memory, cortical thinning, and reduced hippocampal GMV, are present. Further studies are needed to elucidate the patterns and temporal staging of AUD-related pathophysiology and cognitive impairment. Imaging ß-amyloid in middle age alcoholics as a mechanism that increases their risk for Alzheimer's disease; Registration Number: NCT03746366 .

Validation of amyloid PET positivity thresholds in centiloids: a multisite PET study approach.

BACKGROUND: Inconsistent positivity thresholds, image analysis pipelines, and quantitative outcomes are key challenges of multisite studies using more than one ß-amyloid (Aß) radiotracer in positron emission tomography (PET). Variability related to these factors contributes to disagreement and lack of replicability in research and clinical trials. To address these problems and promote Aß PET harmonization, we used [18F]florbetaben (FBB) and [18F]florbetapir (FBP) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to derive (1) standardized Centiloid (CL) transformations and (2) internally consistent positivity thresholds based on separate young control samples. METHODS: We analyzed Aß PET data using a native-space, automated image processing pipeline that is used for PET quantification in many large, multisite AD studies and trials and made available to the research community. With this pipeline, we derived SUVR-to-CL transformations using the Global Alzheimer's Association Interactive Network data; we used reference regions for cross-sectional (whole cerebellum) and longitudinal (subcortical white matter, brain stem, whole cerebellum) analyses. Finally, we developed a FBB positivity threshold using an independent young control sample (N=62) with methods parallel to our existing FBP positivity threshold and validated the FBB threshold using a data-driven approach in ADNI participants (N=295). RESULTS: The FBB threshold based on the young sample (1.08; 18 CL) was consistent with that of the data-driven approach (1.10; 21 CL), and the existing FBP threshold converted to CL with the derived transformation (1.11; 20 CL). The following equations can be used to convert whole cerebellum- (cross-sectional) and composite- (longitudinal) normalized FBB and FBP data quantified with the native-space pipeline to CL units: [18F]FBB: CLwhole cerebellum = 157.15 × SUVRFBB - 151.87; threshold=1.08, 18 CL [18F]FBP: CLwhole cerebellum = 188.22 × SUVRFBP - 189.16; threshold=1.11, 20 CL [18F]FBB: CLcomposite = 244.20 × SUVRFBB - 170.80 [18F]FBP: CLcomposite = 300.66 × SUVRFBP - 208.84 CONCLUSIONS: FBB and FBP positivity thresholds derived from independent young control samples and quantified using an automated, native-space approach result in similar CL values. These findings are applicable to thousands of available and anticipated outcomes analyzed using this pipeline and shared with the scientific community. This work demonstrates the feasibility of harmonized PET acquisition and analysis in multisite PET studies and internal consistency of positivity thresholds in standardized units.

Alzheimer's disease pathology in a community-based sample of older adults without dementia: The MYHAT neuroimaging study.

A true understanding of the distribution and functional correlates of Alzheimer's disease pathology in dementia-free older adults requires a population-based perspective. Here we report initial findings from a sample of 102 cognitively unimpaired participants (average age 77.2 years, 54.9% women, 13.7% APOE*4 carriers) recruited for neuroimaging from a larger representative population-based cohort participating in an ongoing longitudinal study of aging, the Monongahela-Youghiogheny Healthy Aging Team (MYHAT). All participants scored < 1.0 on the Clinical Dementia Rating (CDR) Scale, with 8 participants (7.8%) scoring CDR = 0.5. Participants completed a positron emission tomography scan using the tracers [C-11]Pittsburgh Compound-B (PiB) and [F-18]AV-1451 to estimate amyloid and tau deposition. PiB positivity was defined on a regional basis using established standardized uptake value ratio cutoffs (SUVR; cerebellar gray matter reference), with 39 participants (38.2%) determined to be PiB(+). Health history, lifestyle, and cognitive abilities were assessed cross-sectionally at the nearest annual parent MYHAT study visit. A series of adjusted regression analyses modeled cognitive performance as a function of global PiB SUVR and [F-18]AV-1451 SUVR in Braak associated regions 1, 3/4, and 5/6. In comparison to PiB(-) participants (n = 63), PiB(+) participants were older, less educated, and were more likely to be APOE*4 carriers. Global PiB SUVR was significantly correlated with [F-18]AV-1451 SUVR in all Braak-associated regions (r = .38-0.53, p < .05). In independent models, higher Global PiB SUVR and Braak 1 [F-18]AV-1451 SUVR were associated with worse performance on a semantic interference verbal memory test. Our findings suggest that brain amyloid is common in a community-based setting, and is associated with tau deposition, but both pathologies show few associations with concurrent cognitive performance in a dementia-free sample.

Influence of apolipoprotein-E genotype on brain amyloid load and longitudinal trajectories.

To characterize the influence of apolipoprotein-E (APOE) genotype on cerebral Aß load and longitudinal Aß trajectories, [11C]Pittsburgh compound-B (PiB) positron emission tomography (PET) imaging was used to assess amyloid load in a clinically heterogeneous cohort of 428 elderly participants with known APOE genotype. Serial [11C]PiB data and a repeated measures model were used to model amyloid trajectories in a subset of 235 participants classified on the basis of APOE genotype. We found that APOE-ε4 was associated with increased Aß burden and an earlier age of onset of Aß positivity, whereas APOE-ε2 appeared to have modest protective effects against Aß. APOE class did not predict rates of Aß accumulation. The present study suggests that APOE modifies Alzheimer's disease risk through a direct influence on amyloidogenic processes, which manifests as an earlier age of onset of Aß positivity, although it is likely that other genetic, environmental, and lifestyle factors are important.

Associations between NIH Toolbox Cognition Battery and in vivo brain amyloid and tau pathology in non-demented older adults.

INTRODUCTION: The National Institutes of Health (NIH) Toolbox Cognition Battery (NIHTB-CB) was developed to be a common assessment metric across a broad array of research studies. We investigated associations between NIHTB-CB and brain amyloid and tau deposition in cognitively unimpaired older adults. METHODS: One hundred eighteen community-based volunteers completed magnetic resonance imaging (MRI), Pittsburgh compound B (PiB)-PET (positron emission tomography) and AV-1451-PET neuroimaging, a neuropsychological evaluation, NIHTB-CB, and the Clinical Dementia Rating (CDR) scale. Demographically adjusted regression models evaluated cognition-biomarker associations; standardized effect sizes allowed comparison of association strength across measures. RESULTS: No NIHTB-CB measures were associated with amyloid deposition. NIHTB-CB measures of fluid cognition, including Pattern Comparison Processing Speed, Dimensional Change Card Sort, and Fluid Cognition Composite, were associated with tau deposition in higher Braak regions. Pattern Comparison Processing Speed was the most robust association with sensitivity analyses. DISCUSSION: NIHTB-CB tasks of processing speed and executive functions may be sensitive to pathologic tau deposition on imaging in normal aging.

Amyloid accumulation in Down syndrome measured with amyloid load.

INTRODUCTION: Individuals with Down syndrome (DS) show enhanced amyloid beta (Aß) deposition in the brain. A new positron emission tomography (PET) index of amyloid load (AßL ) was recently developed as an alternative to standardized uptake value ratios (SUVrs) to quantify Aß burden with high sensitivity for detecting and tracking Aß change.1. METHODS: AßL was calculated in a DS cohort (N = 169, mean age ± SD = 39.6 ± 8.7 years) using [C-11]Pittsburgh compound B (PiB) PET imaging. DS-specific PiB templates were created for Aß carrying capacity (K) and non-specific binding (NS). RESULTS: The highest values of Aß carrying capacity were found in the striatum and precuneus. Longitudinal changes in AßL displayed less variability when compared to SUVrs. DISCUSSION: These results highlight the utility of AßL for characterizing Aß deposition in DS. Rates of Aß accumulation in DS were found to be similar to that observed in late-onset Alzheimer's disease (AD; ≈3% to 4% per year), suggesting that AD progression in DS is of earlier onset but not accelerated.

[18F]FDG, [11C]PiB, and [18F]AV-1451 PET Imaging of Neurodegeneration in Two Subjects With a History of Repetitive Trauma and Cognitive Decline.

Background: Trauma-related neurodegeneration can be difficult to differentiate from multifactorial neurodegenerative syndromes, both clinically and radiographically. We have initiated a protocol for in vivo imaging of patients with suspected TBI-related neurodegeneration utilizing volumetric MRI and PET studies, including [18F]FDG indexing cerebral glucose metabolism, [11C]PiB for Aß deposition, and [18F]AV-1451 for tau deposition. Objective: To present results from a neuroimaging protocol for in vivo evaluation of TBI-related neurodegeneration in patients with early-onset cognitive decline and a history of TBI. Methods: Patients were enrolled in parallel TBI studies and underwent a comprehensive neuropsychological test battery as well as an imaging protocol of volumetric MRI and PET studies. Findings from two patients were compared with two age-matched control subjects without a history of TBI. Results: Both chronic TBI patients demonstrated cognitive deficits consistent with early-onset dementia on neuropsychological testing, and one patient self-reported a diagnosis of probable early-onset AD. Imaging studies demonstrated significant [18F]AV-1451 uptake in the bilateral occipital lobes, substantial [11C]PiB uptake throughout the cortex in both TBI patients, and abnormally decreased [18F]FDG uptake in the posterior temporoparietal areas of the brain. One TBI patient also had subcortical volume loss. Control subjects demonstrated no appreciable [18F]AV-1451 or [11C]PiB uptake, had normal cortical volumes, and had normal cognition profiles on neuropsychological testing. Conclusions: In the two patients presented, the [11C]PiB and [18F]FDG PET scans demonstrate uptake patterns characteristic of AD. [11C]PiB PET scans showed widespread neocortical uptake with less abnormal uptake in the occipital lobes, whereas there was significant [18F]AV-1451 uptake in both occipital lobes.

Comparison of longitudinal Aß in nondemented elderly and Down syndrome.

Down syndrome (DS) predisposes individuals to early Alzheimer's disease (AD). Using Pittsburgh Compound B ([11C]PiB), a pattern of striatal amyloid beta (Aß) that is elevated relative to neocortical binding has been reported, similar to that of nondemented autosomal dominant AD mutation carriers. However, it is not known whether changes in striatal and neocortical [11C]PiB retention differ over time in a nondemented DS population when compared to changes in a nondemented elderly (NDE) population. The purpose of this work was to assess longitudinal changes in trajectories of Aß in a nondemented DS compared to an NDE cohort. The regional trajectories for anterior ventral striatum (AVS), frontal cortex, and precuneus [11C]PiB retention were explored over time using linear mixed effects models with fixed effects of time, cohort, and time-by-cohort interactions and subject as random effects. Significant differences between DS and NDE cohort trajectories for all 3 region of interests were observed (p < 0.05), with the DS cohort showing a faster accumulation in the AVS and slower accumulation in the frontal cortex and precuneus compared to the NDE cohort. These data add to the previously reported distinct pattern of early striatal deposition not commonly seen in sporadic AD by demonstrating that individuals with DS may also accumulate Aß at a rate faster in the AVS when compared to NDE subjects.

The use of Centiloids for applying [11C]PiB classification cutoffs across region-of-interest delineation methods.

INTRODUCTION: Centiloid standardization was developed to establish a quantitative outcome measure of amyloid burden that could accommodate the integration of different amyloid positron emission tomography radiotracers or different methods of quantifying the same tracer. The goal of this study was to examine the use of Centiloids for establishing amyloid classification cutoffs for differing region-of-interest (ROI) delineation schemes. METHODS: Using ROIs from hand-drawn delineation in native space as the gold standard, we compared standard uptake value ratios obtained from the 6 hand-drawn ROIs that determine amyloid-positivity classification with standard uptake value ratio obtained from 3 different automated techniques (FreeSurfer, Statistical Parametric Mapping, and superimposed hand-drawn ROIs in Pittsburgh Compound B template space). We tested between-methods reliability using repeated measures models and intraclass correlation coefficients. RESULTS: We found high reliability between the hand-drawn standard method and other methods for almost all the regions considered. However, small differences in standard uptake value ratio were found to lead to unreliable classifications when the hand-drawn native space-derived cutoffs were used across other ROI delineation methods. DISCUSSION: The use of Centiloid standardization greatly improved the agreement of Pittsburgh Compound B classification across methods and may serve as an alternative method for applying cutoffs across methodologically different outcomes.

Impact of partial volume correction on the regional correspondence between in vivo [C-11]PiB PET and postmortem measures of Aß load.

The positron emission tomography (PET) radiotracer Pittsburgh Compound B ([C-11]PiB) demonstrates a high affinity for fibrillary amyloid-beta (Aß) aggregates. However, [C-11]PiB's in vivo sensitivity and specificity is an ongoing area of investigation in correlation studies with postmortem measures of Aß pathology. One potential confound in PET-to-postmortem correlation studies is the limited spatial resolution of PET and resulting partial volume effects (PVEs). In this work, we evaluated the impact of three partial volume correction (PVC) techniques - the Meltzer, the modified Müller-Gärtner, and the Region-Based Voxel-Wise - on correlations between region-matched in vivo [C-11]PiB standardized uptake value ratios (SUVRs) and postmortem measures of Aß pathology in a unique cohort of nine subjects. Postmortem Aß pathology was assessed histologically as percent area coverage of 6-CN-PiB positive and Aß immunoreactive (4G8 antibody) deposits. The application of all three PVC techniques resulted in minimally reduced PET-to-postmortem correlations relative to no PVC. However, correlations to both 6-CN-PiB and 4G8 percent area across all PVC techniques and no PVC were statistically significant at p < 0.01, suggesting that PVC is of minimal importance in understanding the relationship between Aß PET and neuropathologically assessed Aß. Thus, the utility of PVC in Aß PET imaging should continue to be examined on an application-specific basis.

Image-Based 2D Re-Projection for Attenuation Substitution in PET Neuroimaging.

PURPOSE: In dual modality positron emission tomography (PET)/magnetic resonance imaging (MRI), attenuation correction (AC) methods are continually improving. Although a new AC can sometimes be generated from existing MR data, its application requires a new reconstruction. We evaluate an approximate 2D projection method that allows offline image-based reprocessing. PROCEDURE: 2-Deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) brain scans were acquired (Siemens HR+) for six subjects. Attenuation data were obtained using the scanner's transmission source (SAC). Additional scanning was performed on a Siemens mMR including production of a Dixon-based MR AC (MRAC). The MRAC was imported to the HR+ and the PET data were reconstructed twice: once using native SAC (ground truth); once using the imported MRAC (imperfect AC). The re-projection method was implemented as follows. The MRAC PET was forward projected to approximately reproduce attenuation-corrected sinograms. The SAC and MRAC images were forward projected and converted to attenuation-correction factors (ACFs). The MRAC ACFs were removed from the MRAC PET sinograms by division; the SAC ACFs were applied by multiplication. The regenerated sinograms were reconstructed by filtered back projection to produce images (SUBAC PET) in which SAC has been substituted for MRAC. Ideally SUBAC PET should match SAC PET. Via coregistered T1 images, FreeSurfer (FS; MGH, Boston) was used to define a set of cortical gray matter regions of interest. Regional activity concentrations were extracted for SAC PET, MRAC PET, and SUBAC PET. RESULTS: SUBAC PET showed substantially smaller root mean square error than MRAC PET with averaged values of 1.5 % versus 8.1 %. CONCLUSIONS: Re-projection is a viable image-based method for the application of an alternate attenuation correction in neuroimaging.

Dynamic PET imaging reveals heterogeneity of skeletal muscle insulin resistance.

PURPOSE: Skeletal muscle insulin resistance (IR) often precedes hyperglycemia and type 2 diabetes. However, variability exists within different skeletal muscle types and can be influenced by 3 primary steps of control: glucose delivery, transport, and phosphorylation. We performed dynamic positron emission tomography imaging studies to determine the extent to which heterogeneity in muscle type and control of insulin action contribute to IR. METHODS: Thirteen volunteers from normal weight to obese underwent dynamic positron emission tomography imaging of [15O]H2O, [11C]3-O-methylglucose, and [18F]fluorodeoxyglucose, measuring delivery, transport, and phosphorylation rates, respectively, in soleus and tibialis anterior muscle during a hyperinsulinemic-euglycemic clamp. Subjects were classified as insulin-sensitive (IS) or insulin-resistant (IR) based on the median systemic glucose infusion rate needed to maintain euglycemia. RESULTS: In soleus, transport kinetic rates were significantly higher (P<.05) in IS (0.126±0.028 min(-1)) vs IR (0.051±0.008 min(-1)) subjects. These differences were not as evident in tibialis anterior. These differences were paralleled in overall insulin-stimulated tissue activity, higher in IS (0.017±0.001 mL·cm3·min(-1)) vs IR (0.011±0.002 mL·cm3·min(-1)) in soleus (P<.05), without significant differences in tibialis anterior. No significant differences were observed for either muscle in delivery or phosphorylation. Both muscle types displayed a control shift from an even distribution among the steps in IS to transport exerting greater control of systemic insulin sensitivity in IR. CONCLUSION: Lower glucose transport rates are the major feature underlying IR preceding type 2 diabetes, although substantial heterogeneity in insulin action across muscle types highlight the complexity of skeletal muscle IR.