Improved brain PET quantification using partial volume correction techniques

Positron emission tomography (PET) suffers from a degradation in quantitative accuracy due to a phenomenon known as the partial volume effect (PVE). The effects are due to the limited spatial resolution of the scanner. Methods that correct for PVEs are known as partial volume correction (PVC) techniques and are either data-driven or make use of anatomical information from other modalities such as magnetic resonance (MR) imaging. This thesis reports investigations into PVC techniques for improving the quantification of brain amyloid PET tracers. These tracers image amyloid plaque aggregation in-vivo, which is a pathological hallmark of Alzheimer’s disease. An extension to existing anatomy-based PVC methods is reported. Region-based voxelwise (RBV) correction has been shown to reduce PVE-induced regional bias and variance when compared to commonly applied PVC techniques. This has been proven in phantom studies and observed in clinical data. In addition, RBV has been used to demonstrate that white matter variability exists in two different amyloid tracers. This finding has implications for the application of PVC in amyloid imaging and also how scans should be normalised. Alternative reference regions were investigated in two amyloid PET tracers. The brain stem, in combination with PVC, was found to result in the strongest agreement between tracers. Anatomy-based PVC techniques rely on parcellations of structural images. These parcellations are not necessarily representative of the PET data. A further extension to RBV is proposed which iteratively modifies the parcellations to find an optimal PVC in terms of the observed PET data. This novel technique reduces quantification errors due to PET-MR mismatch and has the potential to provide an additional parameter of ‘functional volume change’ in longitudinal studies

Optimizing PiB-PET SUVR change-over-time measurement by a large-scale analysis of longitudinal reliability, plausibility, separability, and correlation with MMSE

AbstractQuantitative measurements of change in β-amyloid load from Positron Emission Tomography (PET) images play a critical role in clinical trials and longitudinal observational studies of Alzheimer's disease. These measurements are strongly affected by methodological differences between implementations, including choice of reference region and use of partial volume correction, but there is a lack of consensus for an optimal method. Previous works have examined some relevant variables under varying criteria, but interactions between them prevent choosing a method via combined meta-analysis. In this work, we present a thorough comparison of methods to measure change in β-amyloid over time using Pittsburgh Compound B (PiB) PET imaging.MethodsWe compare 1,024 different automated software pipeline implementations with varying methodological choices according to four quality metrics calculated over three-timepoint longitudinal trajectories of 129 subjects: reliability (straightness/variance); plausibility (lack of negative slopes); ability to predict accumulator/non-accumulator status from baseline value; and correlation between change in β-amyloid and change in Mini Mental State Exam (MMSE) scores.Results and conclusionFrom this analysis, we show that an optimal longitudinal measure of β-amyloid from PiB should use a reference region that includes a combination of voxels in the supratentorial white matter and those in the whole cerebellum, measured using two-class partial volume correction in the voxel space of each subject's corresponding anatomical MR image

Machine learning for image-based classification of Alzheimer's disease

Imaging biomarkers for Alzheimer's disease are important for improved diagnosis and monitoring, as well as drug discovery. Automated image-based classification of individual patients could provide valuable support for clinicians. This work investigates machine learning methods aimed at the early identification of Alzheimer's disease, and prediction of progression in mild cognitive impairment. Data are obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL). Multi-region analyses of cross-sectional and longitudinal FDG-PET images from ADNI are performed. Information extracted from FDG-PET images acquired at a single timepoint is used to achieve classification results comparable with those obtained using data from research-quality MRI, or cerebrospinal fluid biomarkers. The incorporation of longitudinal information results in improved classification performance. Changes in multiple biomarkers may provide complementary information for the diagnosis and prognosis of Alzheimer's disease. A multi-modality classification framework based on random forest-derived similarities is applied to imaging and biological data from ADNI. Random forests provide consistent similarities for multiple modalities, facilitating the combination of different types of features. Classification based on the combination of MRI volumes, FDG-PET intensities, cerebrospinal fluid biomarkers, and genetics out-performs classification based on any individual modality. Multi-region analysis of MRI acquired at a single timepoint is used to show volumetric differences in cognitively normal individuals differing in amyloid-based risk status for the development of Alzheimer's disease. Reduced volumes in temporo-parietal and orbito-frontal regions in high-risk individuals from both ADNI and AIBL could be indicative of early signs of neurodegeneration. This suggests that volumetric MRI can reveal structural brain changes preceding the onset of clinical symptoms. Taken together, these results suggest that image-based classification can support diagnosis in Alzheimer's disease and preceding stages. Future work may lead to more finely meshed prognostic data that may be useful clinically and for research

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods

Positron emission tomography imaging biomarkers of frontotemporal dementia

There are currently no disease modifying treatments available for frontotemporal dementia (FTD). Pathological heterogeneity within and between FTD phenotypes and genotypes makes accurate diagnosis challenging. Biomarkers that can aid diagnosis and monitor disease progression will be critical for clinical trials of potential treatments. Positron emission tomography (PET) imaging provides insights into molecular changes in the brain during life that are otherwise only directly quantifiable at postmortem. In this thesis I aimed to identify potential biomarkers of FTD using PET imaging. In Chapter 3 I use PET imaging of glucose metabolism to identify early neuronal dysfunction in presymptomatic genetic FTD, revealing specific involvement of the anterior cingulate in a subgroup of mutation carriers. In Chapter 4 I evaluate the utility of a PET tracer of tau protein deposition in genetic FTD against volumetric imaging, which appears to provide a more sensitive biomarker of disease than this tau PET tracer in FTD. In Chapter 5 I investigate neuroinflammation via PET imaging and identify different areas of neuroinflammation in different FTD genotypes, suggesting an association between neuroinflammation and protein deposition and that PET imaging of neuroinflammation might provide a sensitive biomarker in MAPT-related FTD. In Chapter 6 I investigate synaptic and mitochondrial dysfunction via PET imaging in FTD, the latter of which has been previously unexplored. I reveal marked differences in both markers in FTD versus controls which suggests both might provide sensitive biomarkers of disease. Furthermore, in Chapter 7 I evaluate the same biomarkers at longitudinal follow up where I find continued reductions in mitochondrial function over time suggesting mitochondrial PET imaging may provide a biomarker of disease progression in FTD. Future replication of the findings in this thesis in larger cohorts might facilitate the advancement of clinical trials in FTD

Choroid plexus enlargement is associated with neuroinflammation and reduction of blood brain barrier permeability in depression.

BACKGROUND: Recent studies have shown that choroid plexuses (CP) may be involved in the neuro-immune axes, playing a role in the interaction between the central and peripheral inflammation. Here we aimed to investigate CP volume alterations in depression and their associations with inflammation. METHODS: 51 depressed participants (HDRS score > 13) and 25 age- and sex-matched healthy controls (HCs) from the Wellcome Trust NIMA consortium were re-analysed for the study. All the participants underwent full peripheral cytokine profiling and simultaneous [11C]PK11195 PET/structural MRI imaging for measuring neuroinflammation and CP volume respectively. RESULTS: We found a significantly greater CP volume in depressed subjects compared to HCs (t(76) = +2.17) that was positively correlated with [11C]PK11195 PET binding in the anterior cingulate cortex (r = 0.28, p = 0.02), prefrontal cortex (r = 0.24, p = 0.04), and insular cortex (r = 0.24, p = 0.04), but not with the peripheral inflammatory markers: CRP levels (r = 0.07, p = 0.53), IL-6 (r = -0.08, p = 0.61), and TNF-α (r = -0.06, p = 0.70). The CP volume correlated with the [11C]PK11195 PET binding in CP (r = 0.34, p = 0.005). Integration of transcriptomic data from the Allen Human Brain Atlas with the brain map depicting the correlations between CP volume and PET imaging found significant gene enrichment for several pathways involved in neuroinflammatory response. CONCLUSION: This result supports the hypothesis that changes in brain barriers may cause reduction in solute exchanges between blood and CSF, disturbing the brain homeostasis and ultimately contributing to inflammation in depression. Given that CP anomalies have been recently detected in other brain disorders, these results may not be specific to depression and might extend to other conditions with a peripheral inflammatory component

Etude multimodale de la maladie d'Alzheimer : forme sporadique prodromale, formes génétiques, et altération du traitement visuel

La maladie d'Alzheimer reste en 2012 un véritable problème de santé publique. Cette pathologie neurodégénérative est au cœur des nombreux projets de recherche scientifique dans des aspects physiopathologiques, neuropsychologique, d'imagerie ou thérapeutiques tant chez l'animal que chez l'homme. Les neurosciences tentent depuis plusieurs décennies de comprendre les mécanismes de son origine et de son évolution, afin d'arriver à freiner le plus précocement possible les atteintes cognitives, comportementales et la perte d'autonomie qui en découlent. Grâce à de nombreux progrès technologiques, en particulier en neuroimagerie, cliniciens et chercheurs disposent d'un panel d'outils de plus en plus performants pour aider au diagnostic et étendre nos connaissances sur la maladie. Dans une première partie, nous verrons comment, à l'aide de l'utilisation combinée de marqueurs cliniques, anatomiques, et biologiques, il nous est possible de mieux caractériser une population de patients atteints de maladie d'Alzheimer prodromale dans les formes sporadiques, et comment ceux-ci nous permettent d'avancer dans la compréhension des processus physiopathologiques à l'origine de la maladie. Nous aborderons ensuite dans une seconde partie le versant génétique de la maladie d'Alzheimer, au travers de deux cas cliniques. Enfin, nous verrons comment, par le biais d'une étude sur le traitement de l'information visuelle, nous pouvons tenter de mieux caractériser certains dysfonctionnements cérébraux impliquant des régions atteintes précocement dans la maladie d'Alzheimer, et ce dans le but d'une meilleure connaissance des réseaux neuronaux atteints.Alzheimer's disease remains in 2012 a real public health issue. This neurodegenerative disease is the focal point of many scientific research projects regarding its physiopathological, neuropsychological, imaging or therapeutic aspects, both in animal or human models. Neuroscience has been trying for decades to understand the mechanisms of its origin and evolution, in order to slow down, at the earliest stages possible, the resulting cognitive and behavioral impairment as well as the autonomy loss. Thanks to numerous technological progresses, in particular in neuroimaging, clinicians and researchers have at their disposal more and more performing tools to help diagnosis and enlarge our knowledge about the disease. In a first part, we will see how, using combined clinical anatomical and biological markers, we can better define a population of patients affected by sporadic prodromal Alzheimer's disease, and how those markers enable us to go ahead with the understanding of the physiopathological processes causing the disease. We will then address, in a second part, the genetic aspect of Alzheimer's disease, through two clinical cases. Finally, we will see how, by means of a study upon visual information processing, we can try to better assess some of the cerebral dysfunctions that involve early affected regions, with the purpose of a better knowledge of the impaired neuronal networks

Dynamics of proteinopathies in Alzheimer’s disease as measured by PET and CSF biomarkers

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by the extracellular aggregation of the amyloid-β (Aβ; amyloid) peptide and the intraneuronal accumulation of the protein tau. Independently, and in concert, these protein opathies lead to the loss of synapses and neurons (neurodegeneration). These processes can be measured in living individuals using positron emission tomography (PET) and cerebrospinal fluid (CSF) based measurements (biomarkers). Biomarkers for AD include the retention in the brain of varied PET ligands (e.g. [11C]PIB and [18F]flutemetamol, Aβ; [18F]THK5317, tau; and [18F]FDG, glucose metabolism, a proxy for synaptic integrity), as well as CSF levels of Aβ1-42, and tau phosphorylated at threonine 181 (p-tau181p), and total-tau (t-tau), reflecting Aβ, the formation tau tangle pathology, and axonal damage, respectively. The aim of this thesis, which comprises five studies, was to obtain new insight into how these biomarkers interrelate in AD, and to examine their potential utility from a clinical standpoint. In study I, agreement between dichotomised (i.e. normal/abnormal) [11C]PIB PET and CSF Aβ1-42 in AD and related disorders was found to persist after controlling for potential methodological confounds tied to CSF, suggesting biological underpinnings to biomarker mismatches. Concordance, however, was substantially improved across patient groups when using Aβ1-42 in ratio with Aβ1-40. In study II, the impact of amyloid imaging with [18F]flutemetamol PET was examined in a cohort of diagnostically unclear patients, drawn from a tertiary memory clinic. [18F]Flutemetamol investigations resulted in substantial changes to pre-amyloid PET diagnoses and an incease in the use of cholinesterase inhibitors, with the greatest impact seen among patients with a pre-[18F]flutemetamol diagnosis of MCI. In study III, the relationship between [18F]THK5317 tau PET and CSF tau, including measures derived from assays capturing novel fragments, was shown to vary by isocortical hypometabolism, suggesting that the relationship between tau biomarkers may vary by disease stage. Novel CSF markers better tracked longitudinal PET, as compared to p-tau181p and t-tau, and improved concordance with [18F]THK5317. Moreover, comparison of cross-sectional and rate of change findings suggest a temporal delay between tau pathology and synaptic impairment. In studies IV and V, perfusion information derived from [18F]THK5317 tau PET scans was shown to strongly correlate with [18F]FDG PET metabolic imaging; though our cross-sectional data support the use of perfusion parameters as a substitute for [18F]FDG, longitudinal findings suggest that the coupling between perfusion and metabolism may vary as a function of disease stage, warranting further studies