Dissertations / Theses on the topic 'Alzheimer's disease – Diagnosis'
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Wang, Xueli. "Organic molecules for diagnosis and therapy of Alzheimer's disease." HKBU Institutional Repository, 2020. https://repository.hkbu.edu.hk/etd_oa/883.
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Alzheimer's disease has become one of the most common diseases jeopardizing the health of the human being. The main pathological feature of AD is the accumulation of Aβ in the brain to form senile plaques. Therefore, it is of great significance to develop new and efficient drugs targeting at amyloid-β for the detection, diagnosis and therapeutics for Alzheimer's disease. Xanthohumol (Xn) naturally presents in hops (Humulus lupulus L). Studies have shown that it has anti-lipoperoxidative, anti-inflammatory, anti-proliferative activities, antiangiogenic and antioxidant effects, which further illustrates its potential therapeutic for AD. However, the bio-incompatibility and blood-brain barrier impermeability of Xanthohumol hindered it in vivo efficacy potential for treating Alzheimer's disease. Thus, we designed and prepared a series of Xanthohumol derivatives, namely, Xn-n, (n = 1-9) and its chalcone derivatives C-n, (n = 1-10) to enhance the desirable physical, biological and pharmacological properties, especially the blood-brain barrier permeability for intervention of AD. As an effective technique for in vivo visualization, Near-infrared fluorescence imaging based on organic small molecule probes has a promising application in the diagnosis of Alzheimer's disease. However, most of the reported imaging probes can only visualize Aβ-plaques but do not have therapeutic potential such as neuroprotection against Aβ induced toxicity. Herein, we designed and synthesized a series of oligomeric Aβ targeted near infrared (NIR) fluorescent probes for the diagnosis and therapeutics of Alzheimer's disease, namely DBAN-SLM, DBAN-SLOH, DBAN-OSLM which showed remarkably effective inhibitory effect on Aβ aggregation, significant neuroprotection effect against the Aβ-induced toxicities, and suppression on Aβ-induced ROS generation. indicating its great promise as a useful theragnostic agent for the early diagnosis and therapy of AD. Dual-modal imaging is an important approach to overcome the limitations of single imaging technology in the diagnosis of AD disease. Therefore, based on the dual-modal, we designed and synthesized the NIR/MR dual-modal detection and theragnostic probes namely Dyad-1, Dyad-2, Dyad-3 and NP@SiO2@F-SLOH. More surprising is that the two NIR/MR dual-modal probes show excellent biological properties, including the ability to inhibit Aβ aggregation to a certain extent, neuroprotective effects on cytotoxicity caused by different forms of Aβ species, blood-brain barrier (BBB) permeability, and high stability. All of these newly designed and synthesized molecules were characterized with 1H NMR, 13C NMR, and HRMS and found to show good agreement with the desired structures. The photophysical properties and biological properties of these novel designed and synthesized fluorescent probe such as UV-vis absorption, fluorescence emission, dissociation constant determined by fluorescence titration, cytotoxicity assay, neuroprotection, and inhibition of Aβ aggregation were investigated
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Andreasen, Niels. "Search for reliable diagnostic markers for Alzheimer's disease /." Stockholm, 2000. http://diss.kib.ki.se/2000/91-628-4039-8/.
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Haigh, Anne-Marie Francoise. "The Alzheimer's Disease Life Events Study." Thesis, Oxford Brookes University, 2009. http://radar.brookes.ac.uk/radar/items/9c1acdb7-0df9-4046-ec50-810f9122e1d0/1.
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The Alzheimer's Disease Life Events study examines whether there is a relationship between life events and Alzheimer's disease (AD). The ADLE study uses a mixed methods approach to answer the central research question:Are life events a risk factor for Alzheimer's disease? The central research question uses the following theory questions to examine:1. Is there a difference between the number of life events between patients and controls, using the Life Events and Difficulties Schedule (LEDS)(Brown and Harris, 1978) as a measurement tool?2. Is there a difference in the way (i.e. positive, neutral and negative) life events are discussed and in the range of emotions expressed when discussing life events between the patients and controls? 3. Are there any differences in the narrative constructions of life events, as interpreted by the Biographic Narrative Interpretive Method (BNIM)(Wengraf, 2001, 2008) between the patient and control groups? 4. Can the differences, between the patient and control groups, in the narratives be developed into a diagnostic marker? 5. Can the Emotion Word Coding (EWC)(Danner et aI., 2000) be used as a diagnostic marker by being applied to text collected from patients and controls over a period of decades? The ADLE study found that the patient group had experienced more life events in comparison with the control group as defined by the LEOS (Brown and Harris, 1978), and that the patient group had experienced more bereavements under the age of 51 years. The evidence supports the association between life events and AD.Even though there were significantly more life events experienced by the patients, the EWC (Danner et aI., 2001) found significantly fewer discussions expressing emotion bythe patients, particularly the negatively described ones. The range of negative and positive words used to describe the life events was significantly fewer too. This implies that the ways the patients express emotions about life events is substantially different from the controls. This finding was mirrored in the thematic field analysis of the BNIM interviews (Wengraf, 2001, 2008), which found differences in the content and structure of the narratives, and the emotional expression in the narratives about life events. A tool has been constructed using the differences between patients and controls to contribute to the early diagnosis of AD. In addition, the ADLE study has contributed to a gap in the knowledge about life events and AD.
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Bogdanovic, Nenad. "Alzheimer's disease : towards a multifaceted approach in neuropathological diagnosis /." Stockholm, 1998. http://diss.kib.ki.se/1998/91-628-2846-0.
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Sayeed, Abdul. "Positron emission tomography analysis of Alzheimer's disease." Thesis, University of Surrey, 2001. http://epubs.surrey.ac.uk/842834/.
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Alzheimer's Disease (AD) is a major concern for the elderly population, currently affecting over 670,000 people in the UK. With the continual increase in the age of the population the problem is expected to rise. There is no known cure to the condition and a definite diagnosis cannot be made in life. Clinical diagnosis is considered to be approximately 80% - 90% accurate, sometimes taking up to a year to assess. Early detection could aid in the care and possible development of better treatments or even a cure. AD has been shown to alter the structure and global texture of the brain. Studies using Magnetic Resonance imaging (MRI) and Computerised Tomography (CT) have been used to detect these changes with some success by some researchers. Positron Emission Tomography (PET) imaging is a functional imaging modality and in theory before structural changes are evident functional changes should be apparent. Therefore we utilise PET images for this study. This thesis will exploit the fact that AD alters the global texture of the brain. Texture features extracted from fluoro-deoxy-glucose (FDG) PET images and sinograms of the brain will be used. Most texture feature extraction methods fail, due to poor signal to noise ratio so we will use a novel texture feature extraction method known as the Trace transform - triple features, which can extract features directly from raw data acquired by PET scanners. Classifiers will be used to aid in the separation of the two groups, namely AD patients and normal controls. The Trace transform - triple feature method has proven its potential as a good feature extraction technique. It enabled us to achieve classification accuracy of up to 93% on raw sinogram data using a combination of five features. This result is very good compared with the clinical accuracy of 80% reported by most researcher. It is comparable to results obtained by Kippenhan et al [52, 53, 51, 50], who used regional metabolic activity using PET and a neural network classifier. Monomial features extracted from images achieved accuracies as high as 87%. These features are good discriminators, however, they suffer from lack of scaling invariance. This is problematic as brain sizes do vary considerably. The use of registration and extraction of regional information failed to produce fruitful results. This is principally due to poor registration. The registration failed primarily because a very small cross section of the brain was available. Also the effect of AD alters the structure of the brain. Since the registration relies on matching structure, it becomes questionable whether one can actually register automatically a very degraded AD brain. Gender and age are crucial to the progress of Alzheimer's disease. Age and gender matching is not sufficient to get the best results. This thesis has shown that performance gains of up to 11% can be attained by simply incorporating age and/or gender into the classification model. However, the maximum classification accuracy was not improved any further.
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Casson, Roland James. "Making sense of a diagnosis of Alzheimer's disease : partners' experiences." Thesis, University of Hertfordshire, 2004. http://hdl.handle.net/2299/14242.
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Objectives This study aimed to explore the personal experiences and meanings that people develop in response to their partner being diagnosed with Alzheimer's disease, and how these inform the ways in which they cope with and manage their situation in the early stages. Method In-depth interviews were conducted with four women whose partners had received a diagnosis of early-stage Alzheimer's disease from specialist services within the past six months. Interpretative Phenomenological Analysis was used to identify themes running within their accounts. Results Three key themes emerged from the analysis: `Receiving confirmation of a diagnosis of Alzheimer's disease', `Making sense of the diagnosis' and "Staying on an even keel'. `Receiving confirmation of a diagnosis ofAlzheinzer's disease' came at the end of a chain of events for participants. By the time they had been through the process of searching for an explanation for their husband's cognitive difficulties and consulted with professionals, most had half-expecteda diagnosis, although it provoked some strong emotional responsesT. hey described a range of strategies to 'make sense of the diagnosis', including making social comparisons, interpreting professional and social discourses about Alzheimer's disease, making comparisons with previous phases of their life, and attempting to understand and empathise with their partner's experience. The core theme that emerged from participants' accounts was an emphasis on 'staying on an even keel' and protecting their partners' sense of competence and selfhood. They engaged in a range of idiosyncratic intra-personal and interpersonal adjustments to achieve this goal, including re-evaluating their life story and redefining themselves or their partners as `old', re-defining social boundaries to avoid social stigma, and subtly taking on an increasingly powerful position within the relationship in a way that their partners would not be aware of. Conclusions The results are discussed in relation to current clinical debates about the ethics and practicalities of diagnostic disclosure as well as how services can better engage with and respond to the psychosocial needs of family caregivers in the early stages of dementia.
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Gonzalez, Murcia Josue David. "Diagnosis and the Role of Chemokine Receptors in Alzheimer's Disease." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8888.
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Alzheimer’s disease (AD) is the most common neurodegenerative disorder and is the main cause of dementia in the elderly population. AD is pathologically characterized by the accumulation of amyloid plaques and neurofibrillary tangles that results in neurodegeneration and loss of memory function. However, diagnosis of AD and characterization of biological mechanisms that lead to pathology and modulate risk for disease has proven to be extremely difficult. Cerebrospinal fluid (CSF) contains critical biomarkers for AD such as levels of amyloid beta (Aβ) phosphorylated-tau (p-tau), total-tau (t-tau), and neurofilament light chain (NfL). The CSF levels of these biomarkers are useful in determining AD status in a patient, but data collection can be time consuming, technically difficult, and expensive. While still subject to the limitations of obtaining CSF, cell free single stranded DNA (cfssDNA) is much cheaper and more reliably measured than these biomarkers. We investigated cfssDNA as a biomarker for AD status. We observed an association between low levels of concentration isolated from CSF as a potential biomarker for diagnosis of AD. Inflammation is a vital process in the immune system. Acute inflammation plays an essential role in the normal response to tissue injury. This inflammatory response initiates a cascade of cellular activation signals in innate immune cells resulting in increased production of proinflammatory cytokines and chemokines. These chemokines are essential to the recruitment and activation of other cells in the innate and adaptive immune system. Deviations from the normal production of these chemokines can result in disease status. Recently published work has identified genetic variants that show strong associations with AD-related chemokine levels in CSF and plasma. We attempted to characterize the biological mechanisms that underlie the reported associations between the ACKR2-V41A variant and CCL2 levels and the CCRL2-V180M variant and CCL4 levels. Our data demonstrate that the ACKR2-V41A receptor has a lower CCL2 binding affinity, scavenging efficiency, and receptor upregulation compared to ACKR2-WT. For CCRL2-V180M our data demonstrate higher binding affinity with chemerin and CCL19 than CCRL2-WT. Our data also show that while CCRL2-V180M and CCRL2-WT do not directly bind with CCL4, interactions between CCRL2-V180M and CCL19 alter the secretion of CCL4 from leukocytes. These findings provide evidence for a novel biomarker for AD diagnosis, mechanistic insights into the functional impact of common genetic variants on chemokine levels, and highlight a potential role of atypical chemokines in altering the risk for AD.
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Fedotova, M. S. "Current issues in the diagnosis and treatment of Alzheimer's disease." Thesis, БДМУ, 2021. http://dspace.bsmu.edu.ua:8080/xmlui/handle/123456789/18901.
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Smith, André P. "Medicalizing intersubjectivity : diagnostic practices and the self in Alzheimer's disease." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36792.
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Alzheimer's disease (AD) is a condition marked by progressive intellectual decline and memory loss, which typically affects individuals over the age of 60. Its origins are unknown but genetic factors are suspected in some cases. There is limited information about the subjective experience of AD although it is often described as a calamity that inevitably destroys the self irrespective of its victims' social circumstances. This dissertation offers an alternative to this nihilistic portrayal that draws on a critical phenomenological framework. It explores the loss of self as an intersubjective phenomenon that is mediated by three contexts: (1) Western representations of the self as autonomous and individualistic; (2) the public description of AD; and (3) the biomedical practices that construct AD as a diagnostic object.The dissertation examines the experiences of 16 patients and 37 family members who participated in a multi-disciplinary assessment at a dementia clinic. The participants also include 14 clinicians and staff members from the clinic. The findings are derived from a prospective study that includes in-depth, at-home interviews and observations of clinical assessment activities and research-based genetic counseling. The dissertation examines how memory trouble interferes with the intersubjective fabric of everyday life in families as affected participants lose the ability to meaningfully reciprocate on the basis of their individualistic identities. The analysis emphasizes the role of the clinical assessment, diagnosis, and public description in restoring intersubjective order. A salient aspect of this process is the way in which medicalized interpretations of memory trouble facilitate reinterpretation of the eroding self as being animated by pathology. The self is thus rendered meaningful again as it is being indexed to lay descriptions of what people do and say in AD. The analysis also considers how this process extends to participants who came to perceive themselves as victims of AD although they were assessed as not having a dementia disorder. The dissertation finally considers the impact of acquiring genetic knowledge about AD on interpretations of the self. Overall, the research underscores the loss of self in AD as a phenomenological process that is mediated by familial and institutional contexts.
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Kixmiller, Jeffrey S. "Subtyping patients with Senile Dementia of the Alzheimer type using cluster analysis." Virtual Press, 1992. http://liblink.bsu.edu/uhtbin/catkey/833474.
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The purpose of this study was to determine if distinct subgroups of patients with Senile Dementia of the Alzheimer Type (SDAT) could be identified using seven scales of the Cognitive Behavior Rating Scale (CBRS). Ward's method of cluster analysis was used to group 104 patients with a probable diagnosis of SDAT into subtypes.The following three clusters were identified: (a) Moderately Impaired, (b) Severely Impaired, and (c) Emotionally Intact which displayed differences in symptom severity. Clusters could be partially defined by the amount of time they had been diagnosed with the disease. Differences in the cluster's configuration of scores had little/no descriptive utility. Subsequent discrimination analyses indicated that patient demographics were not as useful as the CBRS in classification of patients.This study provided evidence for the CBRS's ability to differentially portray SDAT patients' profiles. Results provide partial support for a stage model of SDAT. Implications of existing subgroups in SDAT are discussed as they pertain to patient management issues.Department of Counseling Psychology and Guidance Services
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Goranson, Tamara Elaine. "On diagnosing Alzheimer's disease, assessing abstract thinking and reasoning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/NQ62516.pdf.
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Garrison, Lisa Rae. "The syntactic comprehension deficit observed in Alzheimer's patients using an object manipulation task." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/27927.
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In the present study, the syntactic deficit of Alzheimer's patients was investigated, using an object manipulation task. Four case studies were presented, using data from test batteries devised by Caplan (pers. comm.) and the author. Subjects responded by acting out stimulus sentences presented in aural and written modes, using a set of small figurines. Responses were evaluated following criteria described by Caplan (1986, pers. comm.). Data from the four subjects were compared with each other, and with data obtained from a similar battery administered to aphasic patients. An impairment in the ability to interpret certain syntactic structures was found for all subjects, indicating that Alzheimer's patients do suffer from a syntactic comprehension deficit in the early stages of the disease. Several syntactic structures which caused errors in the responses of the Alzheimer's subjects, also caused errors for the aphasic patients, suggesting that the parsing model underlying the design of the stimuli, described by Caplan (in press) is a valid description of normal language function. Results of the present investigation are examined in relation to a model of syntactic comprehension suggested by Caplan (in press). Contradictions to hypotheses proposed are noted. The limitations and diagnostic use of the object manipulation test, are discussed.Medicine, Faculty of
Audiology and Speech Sciences, School of
Graduate
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Dooley, Jemima Mary Beatrice. "Communicating a diagnosis of dementia." Thesis, University of Exeter, 2016. http://hdl.handle.net/10871/27939.
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Background: There has been a rise in dementia awareness, with policy changes leading to increased diagnosis rates. However, the stigma of dementia is likely to cause challenges in diagnostic communication. This is complicated by the effect of dementia on cognitive functioning. The aims of this study were to (1) identify how diagnoses of dementia are communicated, (2) identify how people with dementia respond to the diagnosis, and (3) explore doctors’ perspectives on dementia diagnosis delivery. Methodology: A systematic literature review was conducted. Twenty doctors from 9 memory clinics across 4 NHS trusts participated. Eighty-one dementia diagnosis feedback meetings were video-recorded. Conversation analysis was used to identify patterns in diagnosis delivery. Four focus groups with the participating doctors were analysed using thematic analysis (inter-rater reliability 0.89). Findings: The literature review highlighted the dilemma of communicating both sensitively and honestly with people with dementia, as well as challenges stemming from cognitive impairment. This was also evident in diagnostic communication. Prior to diagnosis doctors elicited patient orientation to the meeting purpose (“do you know why you’re here?) and perspective into symptoms (“how is your memory?”). The majority of patients displayed some confusion as to the meeting purpose and offered non-medicalised explanations for their symptoms. Doctors attempted to address this through repeated explication of test results and statements of the clinic purpose. Dementia was always explicitly named. Diagnoses were often delivered indirectly (“that is dementia”), a practice to manage patient resistance and negative responses. However, over 40% were delivered directly (“you have dementia”), especially when patients were more cognitively impaired. Doctors pursued non-minimal responses to diagnosis, apparently to obtain perspective before progressing to treatment. However, resistance was not always addressed and prognosis was often avoided. Doctors highlighted pressure to make diagnoses and an aim to emphasise “living well” rather than discussing prognosis. Conclusion: The findings of this study highlighted the delicate balance between minimising likely resistance and distress and maximising understanding in the context of cognitive impairment. Instilling hope is evidently a priority for doctors. The diagnosis meeting is just one part of the journey of the person with dementia, and sufficient pre- and post-diagnosis support is integral.
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Cardona, Francisco Miguel Ribeiro. "Synthesis of new Aβ-ligands useful in diagnosis of Alzheimer's disease." Doctoral thesis, Universidade de Aveiro, 2013. http://hdl.handle.net/10773/12243.
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Doutoramento em QuímicaAlzheimer’s disease is a chronic progressive neurodegenerative disease and is the most common form of dementia (estimated 50−60% of all cases), associated with loss of memory (in particular episodic memory), cognitive decline, and behavioural and physical disability, ultimately leading to death. Alzheimer’s disease is a complex disease, mostly occurring sporadically with no apparent inheritance and being the age the main risk factor. The production and accumulation of amyloid-beta peptide in the central nervous system is a key event in the development of Alzheimer’s disease. This project is devoted to the synthesis of amyloid-beta ligands, fluorophores and blood brain barrier-transporters for diagnosis and therapy of Alzheimer’s disease. Different amyloid-beta ligands will be synthesized and their ability to interact with amyloid-beta plaques will be studied with nuclear magnetic resonance techniques and a process of lead optimization will be performed. Many natural and synthetic compounds able to interact as amyloid-beta ligands have been identified. Among them, a set of small molecules in which aromatic moieties seem to play a key role to inhibit amyloid-beta aggregation, in particular heteroaromatic polycyclic compounds such as tetracyclines. Nevertheless tetracyclines suffer from chemical instability, low water solubility and possess, in this contest, undesired anti-bacterial activity. In order to overcome these limitations, one of our goals is to synthesize tetracyclines analogues bearing a polycyclic structure with improved chemical stability and water solubility, possibly lacking antibacterial activity but conserving the ability to interact with amyloid-beta peptides. Known tetracyclines have in common a fourth cycle without an aromatic character and with different functionalisations. We aim to synthesize derivatives in which this cycle is represented by a sugar moiety, thus bearing different derivatisable positions or create derivatives in which we will increase or decrease the number of fused rings. In order to generate a potential drug-tool candidate, these molecules should also possess the correct chemical-physical characteristics. The glycidic moiety, not being directly involved in the binding, it assures further possible derivatizations, such as conjugation to others molecular entities (nanoparticles, polymeric supports, etc.), and functionalization with chemical groups able to modulate the hydro/lipophilicity. In order to be useful such compounds should perform their action within the brain, therefore they have to be able to cross the blood brain barrier, and to be somehow detected for diagnostic purposes.
A doença de Alzheimer é uma doença crónica neurodegenerativa e uma das formas mais comuns de demência. Está associada à perda de memória, declínio cognitivo, incapacidade física e comportamental, e, em última análise, pode levar à morte. A doença de Alzheimer é uma doença complexa, ocorrendo na maioria dos casos esporadicamente, sendo a idade o principal fator de risco. A produção e acumulação do péptido beta-amilóide no sistema nervoso central é um facto importante no desenvolvimento da doença de Alzheimer. O principal objetivo deste projeto consiste na síntese de ligandos beta-amilóide, de compostos fluoróforos e transportadores de fármacos através da barreira hematoencefálica para o diagnóstico e tratamento da doença de Alzheimer. Serão sintetizados diversos ligandos do péptido beta-amilóide e estudada a capacidade destes compostos interatuarem com as placas beta-amilóides através de espectroscopia de ressonância magnética nuclear. Será também realizado um estudo de otimização do composto líder. Já foram identificados muitos compostos naturais e sintéticos capazes de interagir com o péptido beta-amilóide, entre eles um conjunto de pequenas moléculas nas quais se constata que a parte aromática possui um papel importante na inibição da sua agregação, nomeadamente compostos hetero-aromáticos policíclicos, tais como as tetraciclinas. Porém as tetraciclinas apresentam instabilidade química, baixa solubilidade em água e possuem atividade antibacteriana, a qual é neste contexto indesejada. De modo a ultrapassar estas limitações, um dos objectivos deste trabalho é sintetizar compostos análogos de tetraciclinas, possuindo uma estrutura policíclica com uma melhor estabilidade química e solubilidade em água e possivelmente não possuindo atividade antibacteriana, mas conservando a capacidade de interação com o péptido beta-amilóide. As tetraciclinas possuem em comum um quarto ciclo sem carácter aromático e possuindo diferentes grupos funcionais. Com este projeto pretende-se sintetizar derivados nos quais este quarto ciclo é constiuído por uma entidade glucídica, portanto, possuindo diferentes posições funcionalizáveis ou criar derivados nos quais se irá acrescentar ou diminuir o número de anéis fundidos. De modo a criar um potencial fármaco, estas moléculas deverão também possuir as corretas propriedades físico-químicas. A entidade glucídica, não estando diretamente envolvida na interação com o péptido beta-amilóide, assegura possíveis derivatizações, tais como a conjugação a outras entidades moleculares (nanopartículas, suportes poliméricos, etc.) e a funcionalização com outros grupos funcionais capazes de modularem as propriedades lipofílicas e hidrofílicas. Estes compostos só serão úteis se atravessarem a barreira hematoencefálica e serem de algum modo detetados para fins de diagnóstico.
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Jobst, Kim Anthony. "Neuroimaging in Alzheimer's disease : a longitudinal prospective clinicopathological study." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318899.
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Creegan, Rhona. "Identification of plasma lipid biomarkers in Alzheimer's disease." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2014. https://ro.ecu.edu.au/theses/1340.
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Alzheimer’s disease (AD), the commonest form of dementia, is a chronic, progressive neurodegenerative disease which manifests clinically as a slow global decline in cognitive function, including deterioration of memory, reasoning, abstraction, language and emotional stability, culminating in a patient with end-stage disease, totally dependent on custodial care. With an ageing population, there is predicted to be a marked increase in the number of people diagnosed with AD in the coming decades, making this a significant challenge to socio-economic policy and aged care. Currently there is no cure for AD and while current therapies may temporarily ameliorate symptoms, death usually occurs approximately 8 years after diagnosis. Attention is now being directed to the discovery of biomarkers that may not only facilitate pre-symptomatic diagnosis but provide an insight into aberrant biochemical pathways that may reveal potential therapeutic targets. AD pathogenesis develops over many years before clinical symptoms appear, providing the opportunity to develop therapy that could slow or stop disease progression well before any clinical manifestations develop.
Research and understanding of AD pathology has been driven in recent years by advances in technologies, enabling the precise investigation of the lipidome; the repertoire of lipid species present in cells and tissues that reflect the net effect of gene and protein expression, which in turn are influenced by the cellular environment. Lipidomic studies have identified abnormal lipid metabolism as a key component of the pathological processes which lead to the development of AD. Therefore, lipidomic studies are crucial for advancing the understanding of AD pathology and for identifying potential therapeutic targets; these studies may also facilitate biomarker discovery. Many studies have reported abnormal lipid profiles in both AD plasma and brain tissue.
This thesis investigated plasma lipid species using a “shotgun” lipidomics approach by electrospray ionisation tandem mass spectrometry (ESI/MS/MS). Additionally, Phospholipid Transfer Protein (PLTP); a protein involved in lipid metabolism was assayed using a commercial kit. The utility of these analytes as potential AD biomarkers was investigated by testing plasma samples from the highly characterised Australian Imaging, Biomarkers and Lifestyle (AIBL) study. The study cohort comprised over 1000 participants at inception who were classified as either healthy control (n=733), mild cognitive impairment (MCI, n=125) or AD (n=204): Samples from the baseline and 18 month follow-up time points were utilised. Plasma PLTP activity levels were measured in a subset of the baseline samples (n=259). Lipid and PLTP measurements were analysed in conjunction with supplementary neuroimaging and blood biomarker data collected as part of the AIBL study.
The thesis identified significant differences in several plasma lipids between clinical classification groups, including several ceramide, sphingomyelin (SM), phosphatidylethanolamine (PE), phosphatidylcholine (PC) and plasmalogen species. Additionally, a panel of lipids was identified which could distinguish AD participants from healthy controls with a sensitivity and specificity of 80%. Plasma PLTP activity was significantly lower in AD and MCI groups compared to healthy controls, and levels correlated with plasma Aβ in all groups and cerebral Aβ in the healthy controls.
The results of this thesis validate and extend previous findings reported in the literature. The current findings provide evidence to indicate that several lipid species and PLTP show promise as potential blood biomarkers of AD. Further investigation using a targeted lipidomics platform and prospective longitudinal follow-up is warranted.
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Jones, Phyllis L. (Phyllis Lee). "Caregivers' Appraisal of Alzheimer's Disease Symptoms and the Relationship to Decisions About Care." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278991/.
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The purpose of the present study was to compare 42 community-dwelling spouse and child Alzheimer's Disease caregivers with 38 community-dwelling potential caregivers on salience of illness symptoms, and accuracy of judging symptoms of illnesses.
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Jackson, Stanita. "Caregivers' Perceptions of an Early Diagnosis of Alzheimer's Disease in African Americans." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2290.
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Alzheimer's disease (AD) is significantly more prevalent among African Americans than within the general population, but rates of early detection are lower in the African American community. Researchers have demonstrated that both pessimistic Alzheimer's-directed health beliefs, and negative perceptions of the effectiveness and the accessibility of medical care act as barriers to care seeking by African American family members of individuals with the disease. Recent research into causal judgments made by potential caregivers about individuals with undiagnosed AD suggests that gender bias and errors in attribution may constitute covert barriers to both lay and professional interpretations regarding the need for cognitive assessment. This study used grounded theory to investigate whether African American family caregivers hold integrated, gender-distinct beliefs about causal attributions of their family member's cognitive decline which may contribute to a delay in care-seeking behaviors. The health belief model was used in conjunction with the attribution theory as the conceptual framework for understanding the data. Purposive sampling of geriatric and memory clinics, and a church was used to recruit eight family caregivers who participated in in-depth interviews. The results indicated that there is a significant lack of caregivers' knowledge and understanding of AD regardless of gender, and that this lack is linked to delays in diagnosis. These results may be used to support the development of a new theory of family caregivers' knowledge and understanding of AD. The social change implications include decreasing delayed diagnosis through increased educational awareness, community outreach programs, and universal mandatory cognitive testing of AD for at-risk individuals.
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Daniels, Katherine Jean. "Couples' construction of meaning of an Alzheimer's disease diagnosis : a systemic approach." Diss., Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/1057.
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Ben, Ahmed Olfa. "Features-based MRI brain classification with domain knowledge : application to Alzheimer's disease diagnosis." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0002/document.
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Les outils méthodologiques en indexation et classification des images par le contenu sont déjà assez matures et ce domaine s’ouvre vers les applications médicales. Dans cette thèse,nous nous intéressons à l'indexation visuelle, à la recherche et à la classification des images cérébrales IRM par le contenu pour l'aide au diagnostic de la maladie d'Alzheimer (MA). L'idée principale est de donner au clinicien des informations sur les images ayant des caractéristiques visuelles similaires. Trois catégories de sujets sont à distinguer: sujets sains (NC), sujets à troubles cognitifs légers (MCI) et sujets atteints par la maladie d'Alzheimer(AD). Nous représentons l’atrophie cérébrale comme une variation de signal dans des images IRM (IRM structurelle et IRM de Tenseur de Diffusion). Cette tâche n'est pas triviale,alors nous nous sommes concentrés uniquement sur l’extraction des caractéristiques à partir des régions impliquées dans la maladie d'Alzheimer et qui causent des changements particuliers dans la structure de cerveau : l'hippocampe le Cortex Cingulaire Postérieur. Les primitifs extrais sont quantifiés en utilisant l'approche sac de mots visuels. Cela permet de représenter l’atrophie cérébrale sous forme d’une signature visuelle spécifique à la MA.Plusieurs stratégies de fusion d’information sont appliquées pour renforcer les performances de système d’aide au diagnostic. La méthode proposée est automatique (sans l’intervention de clinicien), ne nécessite pas une étape de segmentation grâce à l'utilisation d'un Atlas normalisé. Les résultats obtenus apportent une amélioration par rapport aux méthodes de l’état de l’art en termes de précision de classification et de temps de traitementContent-Based Visual Information Retrieval and Classification on Magnetic Resonance Imaging (MRI) is penetrating the universe of IT tools supporting clinical decision making. A clinician can take profit from retrieving subject’s scans with similar patterns. In this thesis, we use the visual indexing framework and pattern recognition analysis based on structural MRIand Tensor Diffusion Imaging (DTI) data to discriminate three categories of subjects: Normal Controls (NC), Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD). The approach extracts visual features from the most involved areas in the disease: Hippocampusand Posterior Cingulate Cortex. Hence, we represent signal variations (atrophy) inside the Region of Interest anatomy by a set of local features and we build a disease-related signature using an atlas based parcellation of the brain scan. The extracted features are quantized using the Bag-of-Visual-Words approach to build one signature by brain/ROI(subject). This yields a transformation of a full MRI brain into a compact disease-related signature. Several schemes of information fusion are applied to enhance the diagnosis performance. The proposed approach is less time-consuming compared to the state of thearts methods, computer-based and does not require the intervention of an expert during the classification/retrieval phase
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Jelic, Vesna. "Early diagnosis of Alzheimer's disease : focus on quantitative EEG in relation to genetic, biochemical and neuroimaging markers /." Stockholm, 1999. http://diss.kib.ki.se/1999/91-628-3431-2/.
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Everitt, Alaina. "Differential Scoring Patterns on the Clock Drawing Test: a Comparison of Vascular Dementia and Alzheimer's Dementia." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5283/.
Full textAbstract:
This study examined differences in scoring patterns among those diagnosed with Alzheimer's dementia and vascular dementia on the clock-drawing test. Archival clock drawing data was retrieved on 279 patients presenting at a county hospital-based memory clinic. Analysis of drawings was based on frequency of qualitative errors, as well as an overall quantitative score. Mean comparisons found those patients with Alzheimer's dementia to perform worse on both quantitative and qualitative scoring measures. However, Pearson's chi-squared test revealed a significantly higher rate of spacing errors among subjects with vascular dementia. Such lends support to my hypothesis that impaired executive functioning in vascular dementia patients would lead to poor qualitative performance. Logistic regression found significant predictive ability for the qualitative criteria in diagnosis (χ2 = 25.49, p < .001), particularly the rate of omission (z = 8.96, p = .003) and addition errors (z = 7.58, p = .006). Such findings hold important implications for the use of qualitative criteria in cognitive screening assessments.
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Schafer, Nicole D. "Targeting Tau Aggregation for the Diagnosis and Treatment of Alzheimer’s Disease." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366219959.
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Davis, Tommy E. Jr. "The Effectiveness of the Geriatric Depression Scale to Distinguish Apathy From Depression in Alzheimer's Disease and Related Dementias." Thesis, University of North Texas, 2008. https://digital.library.unt.edu/ark:/67531/metadc9109/.
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Early detection of Alzheimer's disease (AD) and related dementias in the elderly is critical for improving treatment methods and is a necessary component for improving public health interventions. One of the earliest and most common behavioral syndromes of AD is apathy and is associated with executive dysfunction. Apathy in AD is often misdiagnosed as depression due to an overlap in symptoms. Studies that have found depression to be associated with executive dysfunction have not always controlled for the presence of apathy. The Geriatric Depression Scale (GDS) is a widely used instrument designed to assess depression in the elderly. This study utilized the GDS and a set of standard neuropsychological instruments to investigate the relationship between apathy, depression, and executive functions in individuals with AD and related dementias. The first objective of this study was to determine if apathy has a greater impact on executive functions compared to depression in AD and related dementias. The second objective was to determine the effectiveness of the GDS as a screen for apathy. The results of the analyses did not support the hypotheses. However, exploratory analyses suggested a possible non-linear relationship with apathy and various levels of dementia severity. Exploratory analysis also suggested mean levels of endorsement for apathy varied by diagnosis. Further research is warranted to investigate this relationship and the GDS endorsement patterns for caregivers regarding their impression of the demented individual.
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Teo, Arnold, and Daniel Tsada Yosief. "Influence of T1 and T2 weighted MRI images on automated diagnosis of Alzheimer's disease." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301735.
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Alzheimer’s Disease (AD) is the most common form of dementia and according to the World Health Organization it contributes to 60-70% of the approximately 50 million total worldwide dementia cases. While AD is easy to diagnose from a patient’s symptoms alone, due to AD atrophying brain tissue, a Magnetic Resonance Imaging (MRI) scan can strengthen the diagnosis. Computer-Aided Diagnosis (CAD) refers to the use of machine learning methods for assistance with diagnosis. The main purpose of CAD is to assist, primarily radiologists, with a second opinion in a diagnosis and reduce the amount of false diagnosis. In some cases CAD can also aid in accurate early detection of AD and therefore allowing the patient the possibility to deploy preventive measures. This study investigates the influence of T1 or T2 weighted MRI images on the automated diagnosis of AD using the VGG-16 Deep Neural Network (DNN). Previous studies have researched classification accuracy of different algorithms or artificial neural networks on MRI images for automated diagnosis of AD. However, the choice of MRI weighting varies in these studies and reasoning for choosing said weightings are not explicitly given. This study thus aims to answer whether choice of MRI weighting can affect the classification accuracy of AD using automated diagnosis, and if so, how significantly? Two of the most common MRI weightings were chosen for the study, T1 and T2. 149 images of each weighting were manually collected from the ADNI database and used for training and validation of the VGG-16 DNN. The resulting difference in classification accuracy was significant, with T1 having an average accuracy of 59.41% and T2 an average of 74.71%. The obtained conclusion was that the selection of T1 or T2 weighted images could have a significant influence on the classification accuracy of a chosen CAD method. More research needs to be done however to see if the results of this study are repeated for other algorithms and/ or for larger datasets.Alzheimers sjukdom (AD) är den vanligaste formen av demens och enligt Världshälsoorganisationen bidrar den till 60-70% av de approximativt 50 miljoner totala globala demensfallen. Medan AD är lätt att diagnostisera enbart utifrån en patients symptom, på grund av att AD atrofierar hjärnvävnad, kan en Magnetisk Resonanstomografisk (MR) undersökning stärka diagnosen. Datorassisterad diagnostisering (CAD) avser användningen av maskininlärningsmetoder för hjälp med diagnostisering. Huvudsyftet med CAD är att hjälpa, främst radiologer, med en andra åsikt vid en diagnos och minska mängden falska diagnoser. I vissa fall kan CAD också hjälpa med tidig upptäckt av AD och därmed ge patienten möjlighet att vidta förebyggande åtgärder. Denna studie undersöker påverkan av T1- eller T2-viktade MR-bilder på automatiska diagnostiseringen av AD med hjälp av Djupa Neurala Nätverket (DNN) VGG-16. Tidigare studier har undersökt klassificeringsnoggrannheten för olika algoritmer eller artificiella neurala nätverk på MR-bilder för automatisk diagnostisering av AD. Valet av MR-viktning varierar i dessa studier och resonemang för valet av viktning ges inte uttryckligen. Denna studie syftar således till att svara på om valet av MR-viktning kan påverka klassificeringsnoggrannheten på AD vid användning av automatiserad diagnos, och i så fall hur betydande? Två av de vanligaste MR-vikterna valdes för studien, T1 och T2. 149 bilder av vardera viktning samlades manuellt från ADNI-databasen och användes för träning och validering av VGG-16 DNN. Den resulterande skillnaden i klassificeringsnoggrannheten var betydlig, där T1 hade en genomsnittlig noggrannhet på 59.41% och T2 ett genomsnitt på 74.71%. Den erhållna slutsatsen var att valet av T1- eller T2-viktade bilder kan ha ett betydande inflytande på klassificeringsnoggrannheten för en vald CAD-metod. Mer forskning behöver dock göras för att se om resultaten av denna studie upprepas för andra algoritmer och/ eller för större datamängder.
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Pan, Xiaoxi. "Towards FDG-PET image characterization and classification : application to Alzheimer's disease computer-aided diagnosis." Thesis, Ecole centrale de Marseille, 2019. http://www.theses.fr/2019ECDM0008.
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La maladie d’Alzheimer (MA) est la maladie neurodégénérative--incurable et irréversible pour le moment--la plus répandue chez les personnes âgées. On s’attend à ce qu’elle soit diagnostiquée à son stade précoce, Mild Cognitive Impairment (MCI), pour pouvoir intervenir et retarder son apparition. La tomographie par émission de positons au fluorodésoxyglucose (TEP-FDG) est considérée comme une modalité efficace pour diagnostiquer la MA et la phase précoce correspondante, car elle peut capturer les changements métaboliques dans le cerveau, indiquant ainsi des régions anormales. Cette thèse est consacrée à identifier et distinguer, sur des images TEP, les sujets atteints de MA de ceux qui sont sains. Ce travail vise également à prédire la conversion de MCI sous la modalité d’imagerie TEP-FDG. A cette fin, trois nouvelles méthodes indépendantes sont proposées.La première méthode est axée sur le développement de connectivités entre les régions anatomiques impliquées dans les images au TEP-FDG, qui sont rarement abordées dans les méthodes déjà publiées. Ces connectivités sont représentées par des similarités ou des mesures graphiques entre régions. Combinées ensuite aux propriétés de chaque région, ces caractéristiques sont intégrées dans un cadre de classification d’ensemble conçu pour résoudre les problèmes de diagnostic MA et de prédiction de conversion MCI.La seconde méthode étudie les caractéristiques permettant de caractériser les images au TEP-FDG à partir de gradients spatiaux, ce qui permet de lier les caractéristiques couramment utilisées, voxel ou régionales. Le gradient spatial est quantifié par un histogramme 2D d’orientation et exprimé sous forme multi-échelle. Les résultats sont obtenus en intégrant différentes échelles de gradients spatiaux dans différentes régions.La troisième méthode applique le Convolutional Neural Network (CNN) sur les trois axes des données 3D de TEP-FDG, proposant ainsi la principale architecture CNN à vues multiples. Une telle architecture peut faciliter les opérations de convolution, de la 3D à la 2D, tout en tenant compte des relations spatiales, qui bénéficient d’une nouvelle couche de cartographie. Ensuite, le traitement sur les trois axes sont combinées et prennent une décision conjointement.Les expériences menées sur des ensembles de données publics montrent que les trois méthodes proposées peuvent atteindre des performances significatives et, de surcroît, dépasser les approches les plus avancéesAlzheimer's disease (AD) is becoming the dominant type of neurodegenerative brain disease in elderly people, which is incurable and irreversible for now. It is expected to diagnose its early stage, Mild Cognitive Impairment (MCI), then interventions can be applied to delay the onset. Fluorodeoxyglucose positron emission tomography (FDG-PET) is considered as a significant and effective modality to diagnose AD and the corresponding early phase since it can capture metabolic changes in the brain thereby indicating abnormal regions. Therefore, this thesis is devoted to identify AD from Normal Control (NC) and predict MCI conversion under FDG-PET modality. For this purpose, three independent novel methods are proposed. The first method focuses on developing connectivities among anatomical regions involved in FDG-PET images which are rarely addressed in previous methods. Such connectivities are represented by either similarities or graph measures among regions. Then combined with each region's properties, these features are fed into a designed ensemble classification framework to tackle problems of AD diagnosis and MCI conversion prediction. The second method investigates features to characterize FDG-PET images from the view of spatial gradients, which can link the commonly used features, voxel-wise and region-wise features. The spatial gradient is quantified by a 2D histogram of orientation and expressed in a multiscale manner. The results are given by integrating different scales of spatial gradients within different regions. The third method applies Convolutional Neural Network (CNN) techniques to three views of FDG-PET data, thereby designing the main multiview CNN architecture. Such an architecture can facilitate convolutional operations, from 3D to 2D, and meanwhile consider spatial relations, which is benefited from a novel mapping layer with cuboid convolution kernels. Then three views are combined and make a decision jointly. Experiments conducted on public dataset show that the three proposed methods can achieve significant performance and moreover, outperform most state-of-the-art approaches
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Gibson, Allison K. "Examining the Experiences of Caregivers During the Diagnosis of Alzheimer’s Disease and Related Dementias." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275071723.
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Cisek, Katryna. "Rational Optimization of Small Molecules for Alzheimer’s Disease Premortem Diagnosis." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338325484.
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Tarantello, Concetta. "The role of subjective memory complaints in predicting cognitive impairment associated with future Alzheimer’s disease: a community based study." Thesis, The University of Sydney, 2009. http://hdl.handle.net/2123/6190.
Full textAbstract:
In recent years there has been a substantial increase in research examining the role of subjective memory complaints (SMC) in cognitive function and Alzheimer’s disease. These studies have related SMC to many different cognitive outcomes, such as retaining normal cognitive function, a fluctuating cognitive performance and the development of Alzheimer’s disease. Most of these studies have focused on older populations and have employed a limited assessment of cognitive function. This limits the available evidence regarding the clinical utility of SMC. The literature on the role of SMC in younger subjects is scarce. It is not known whether memory complaints are useful in predicting future cases of Alzheimer’s disease in younger community-based subjects. Aims: The main aim of the present study was to determine whether SMC predict the development of cognitive impairment in a younger cohort of subjects, many of whom were under the age of 70 years (73%), based on their risk profile and neuropsychological assessment. A further aim was to ascertain whether the DRS or 7MS are sensitive screening tools for MCI and examine whether the presence of SMC affects the 3-year cognitive outcome of subjects. To address these aims, this study consisted of two parts: a cross-sectional design and a longitudinal follow-up component. Methods: This study was carried out with 86 community-dwelling subjects recruited via advertisement within the catchment area of Central Sydney Area Health Service. The mean age of the subjects was 63.1 years (SD=8.4). Subjective memory complaints were assessed using a single question. Cognitive function was assessed using a comprehensive battery of tests, selected on the basis of their sensitivity to identifying cognitive impairment typically associated with Alzheimer’s disease. After the initial analysis between those with SMC and without SMC, subjects were further classified according to their performance on an episodic memory task (i.e., delayed verbal recall, Rey, 1964) as having normal memory function, SMC or aMCI. Results: Part 1 - Subjective memory complaints (SMC) were reported by 63% of the sample. The initial analysis between subjects with SMC (n=54) and without SMC (n=32) suggested an initial relationship between SMC and cognitive functioning. Subjects with SMC had impaired global cognitive functioning on two brief screening tests (7MS and DRS), working memory, verbal recall and visuomotor speed. However, subsequent screening with the delayed verbal recall test showed that 12 of the 54 subjects with SMC demonstrated significant cognitive impairment, scoring 2 SD below the control group mean. After these subjects were removed to form the aMCI group, the cognitive differences between subjects with SMC and without SMC were no longer apparent. Subjects with aMCI showed evidence of multiple cognitive deficits (below 1 SD of control group mean) with a high percentage of subjects demonstrating impairment on tests of verbal learning, verbal recall, verbal ability and visuomotor speed. Further analysis showed a significant association between age and subjects identified as having SMC (r=-.581, p<.001) and aMCI (r=.692, p<.001). From the age of 60 onwards, both the SMC and aMCI groups demonstrated a more rapid cognitive decline with increasing age in several cognitive domains. Part 2 - After a mean interval of 3.2 years, 43 subjects were followed up. Subjects with aMCI showed evidence of greater decline on both screening tests (7MS; DRS), whilst the SMC group had significantly higher scores. This trend was also apparent with other neuropsychological testing. The analysis of change over time in cognitive function showed that the majority of subjects (both SMC aMCI) either remained stable or improved their cognitive performance. It is likely that the small sample size and short follow-up interval of the present study contributed to the present observation of no change in cognitive function over time. Discussion: The present findings suggest that subjective memory complaints are a poor predictor of cognitive function. In isolation, SMC are unlikely to be useful for identifying cases with significant cognitive impairment. This is particularly relevant for subjects under the age of 70 years. However, for subjects over the age of 70 years, SMC are likely to identify significant cases with neuropsychological assessment (such as animal fluency and delayed recall). Conclusion: The present study showed that SMC are a poor predictor of cognitive function in subjects under the age of 70 years. This study provided evidence that selected and relatively quick to administer formal neuropsychological tests of cognitive function (in particular tests of animal fluency and delayed recall) are better able to identify those at risk of developing cognitive impairment associated with Alzheimer’s disease, at an earlier age. This would thus allow exposure to earlier treatment options, such as donepezil, aricept, vitamin E, and memantine”.
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Tarantello, Concetta. "The role of subjective memory complaints in predicting cognitive impairment associated with future Alzheimer’s disease: a community based study." University of Sydney, 2009. http://hdl.handle.net/2123/6190.
Full textAbstract:
Doctor of Philosophy(PhD)In recent years there has been a substantial increase in research examining the role of subjective memory complaints (SMC) in cognitive function and Alzheimer’s disease. These studies have related SMC to many different cognitive outcomes, such as retaining normal cognitive function, a fluctuating cognitive performance and the development of Alzheimer’s disease. Most of these studies have focused on older populations and have employed a limited assessment of cognitive function. This limits the available evidence regarding the clinical utility of SMC. The literature on the role of SMC in younger subjects is scarce. It is not known whether memory complaints are useful in predicting future cases of Alzheimer’s disease in younger community-based subjects. Aims: The main aim of the present study was to determine whether SMC predict the development of cognitive impairment in a younger cohort of subjects, many of whom were under the age of 70 years (73%), based on their risk profile and neuropsychological assessment. A further aim was to ascertain whether the DRS or 7MS are sensitive screening tools for MCI and examine whether the presence of SMC affects the 3-year cognitive outcome of subjects. To address these aims, this study consisted of two parts: a cross-sectional design and a longitudinal follow-up component. Methods: This study was carried out with 86 community-dwelling subjects recruited via advertisement within the catchment area of Central Sydney Area Health Service. The mean age of the subjects was 63.1 years (SD=8.4). Subjective memory complaints were assessed using a single question. Cognitive function was assessed using a comprehensive battery of tests, selected on the basis of their sensitivity to identifying cognitive impairment typically associated with Alzheimer’s disease. After the initial analysis between those with SMC and without SMC, subjects were further classified according to their performance on an episodic memory task (i.e., delayed verbal recall, Rey, 1964) as having normal memory function, SMC or aMCI. Results: Part 1 - Subjective memory complaints (SMC) were reported by 63% of the sample. The initial analysis between subjects with SMC (n=54) and without SMC (n=32) suggested an initial relationship between SMC and cognitive functioning. Subjects with SMC had impaired global cognitive functioning on two brief screening tests (7MS and DRS), working memory, verbal recall and visuomotor speed. However, subsequent screening with the delayed verbal recall test showed that 12 of the 54 subjects with SMC demonstrated significant cognitive impairment, scoring 2 SD below the control group mean. After these subjects were removed to form the aMCI group, the cognitive differences between subjects with SMC and without SMC were no longer apparent. Subjects with aMCI showed evidence of multiple cognitive deficits (below 1 SD of control group mean) with a high percentage of subjects demonstrating impairment on tests of verbal learning, verbal recall, verbal ability and visuomotor speed. Further analysis showed a significant association between age and subjects identified as having SMC (r=-.581, p<.001) and aMCI (r=.692, p<.001). From the age of 60 onwards, both the SMC and aMCI groups demonstrated a more rapid cognitive decline with increasing age in several cognitive domains. Part 2 - After a mean interval of 3.2 years, 43 subjects were followed up. Subjects with aMCI showed evidence of greater decline on both screening tests (7MS; DRS), whilst the SMC group had significantly higher scores. This trend was also apparent with other neuropsychological testing. The analysis of change over time in cognitive function showed that the majority of subjects (both SMC aMCI) either remained stable or improved their cognitive performance. It is likely that the small sample size and short follow-up interval of the present study contributed to the present observation of no change in cognitive function over time. Discussion: The present findings suggest that subjective memory complaints are a poor predictor of cognitive function. In isolation, SMC are unlikely to be useful for identifying cases with significant cognitive impairment. This is particularly relevant for subjects under the age of 70 years. However, for subjects over the age of 70 years, SMC are likely to identify significant cases with neuropsychological assessment (such as animal fluency and delayed recall). Conclusion: The present study showed that SMC are a poor predictor of cognitive function in subjects under the age of 70 years. This study provided evidence that selected and relatively quick to administer formal neuropsychological tests of cognitive function (in particular tests of animal fluency and delayed recall) are better able to identify those at risk of developing cognitive impairment associated with Alzheimer’s disease, at an earlier age. This would thus allow exposure to earlier treatment options, such as donepezil, aricept, vitamin E, and memantine”.
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Stepenosky, Nicholas. "Data fusion of complementary information from parietal and occipital event related potentials for early diagnosis of Alzheimer's disease /." Full text available online, 2006. http://www.lib.rowan.edu/find/theses.
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Perry, Richard James. "Attention and executive function in the differential diagnosis of Alzheimer's disease and other cortical dementias." Thesis, Imperial College London, 2005. http://hdl.handle.net/10044/1/8825.
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Beckett, Christina. "VARIANCE OF THE AMYLOID BETA PEPTIDE AS A METRIC FOR THE DIAGNOSIS OF ALZHEIMER'S DISEASE." UKnowledge, 2016. http://uknowledge.uky.edu/medsci_etds/6.
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Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder associated with aging. AD is by far the best understood and most studied neurodegenerative disease. Substantial advances have been made over the last decade, however it is debatable how much closer we are to a clinically useful therapy. A long standing goal in the AD field has been to improve the accuracy of early detection, with the assumption that the ability to intervene earlier in the disease process will lead to a better clinical outcome. Major facets of this effort have been the continued development and improvement of AD biomarkers, with a strong focus on developing imaging modalities. AD is accompanied by two pathological hallmarks in the brain: extracellular neuritic plaques composed of the beta-amyloid peptide (Aβ) and intracellular neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau protein. Evidence of Aβ as the driving force behind the progression of AD (the amyloid cascade hypothesis) was first published by Hardy & Higgins in 1992, and this peptide has been the focus of therapeutic and diagnostic testing for decades. Significant technological advances in recent years now allow imaging of amyloid pathology in vivo. These methods evaluate Aβ burden in a living person, and could potentially serve as both a biomarker, and as a diagnostic tool to detect disease. Pittsburgh Compound B (PiB) is currently the best studied of these imaging agents, however, our current knowledge of the quantitative relationship between PiB binding and amyloid pathology in the brain is limited. A better understanding of how these variables relate to one another is essential for the continued development of reliable diagnostic biomarkers for AD. We analyzed increasingly insoluble pools of Aβ to quantify their relative contributions to the overall Aβ burden, and to determine if any of these measures could be used to predict disease status. We found that the amount of PiB binding in a cortical region of the brain could distinguish cases of mild cognitive impairment (MCI) when corrected to the amount of PiB binding in the cerebellum. As the Aβ peptide ages, the amino acid aspartate may spontaneously convert to an isoaspartate residue through a succinimide intermediary. The presence of iso-Asp Aβ has been used to indicate the presence of aged plaques in AD and Down syndrome cases. We sought to investigate the potential relationship between levels of ‘aged’ Aβ in the plasma as indicated by iso-Asp Aβ and disease state, as a potential biomarker for the presence of AD pathology. We found that AD cases had lower levels of all forms of Aβ in plasma when standardized to the group average, and that plasma levels of Aβ and iso-Asp Aβ were reversed between disease groups. A follow up study is required, however, these initial data are a promising step towards utilizing aged iso-Asp Aβ plasma levels as a potential biomarker to indicate disease state.
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Anand, Swati. "Discovery of Low-Molecular Weight Novel Serum Biomarkers for Diagnosing Preeclampsia and Alzheimer's Disease." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6200.
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Preeclampsia (PE), a life threatening pregnancy-related disorder, is characterized mainly by new onset of hypertension and proteinuria after 20 weeks of gestation. Currently, PE cannot be predicted prior to onset of symptoms and there is no cure for the disease. There is a clear value in having biomarkers able, early in a pregnancy, to identify women at risk for PE so that proper treatment therapies could be developed. Although a number of serum candidate markers have been proposed to be altered in PE patients, their use is limited due to poor sensitivity and specificity. Therefore, there is ongoing need for better set of novel biomarkers predicting PE. Consequently, for my first project, we used a serum proteomic approach involving reversed phase capillary-liquid chromatography-electrospray ionization-quadrupole-time of flight mass spectrometry (cLC-ESI-QTOF). Our approach focuses on the less abundant (nM or lower), lower molecular weight peptides and lipids predicting PE. We got previously collected sera from pregnant women at 12–14 weeks gestation. There were 24 controls, having term uncomplicated pregnancies and 24 cases, which developed PE later in the same pregnancy. Many statistically significant serum PE biomarker candidates were found comparing cases and controls. In addition, multimarker combinations having high detection sensitivity and specificity (AUC >0.9) were developed using logistic regression analysis. For my second project, serum lipidomic analysis of sera from pregnant women was undertaken to determine if useful PE lipid biomarkers exist. A discovery study involving a shotgun lipidomic approach was performed using sera collected at 12-14 weeks of pregnancy from 27 controls with uncomplicated pregnancies and 29 cases that later developed PE. Lipids were extracted using organic solvent and analyzed by direct infusion into a time-of-flight mass spectrometer. Statistically significant lipid markers were found and reevaluated in a second confirmatory study having 43 controls and 37 PE cases. The initial study detected 45 potential PE markers. Of these, 23 markers continued to be statistically significant in the second confirmatory set. Several multi-marker panels with AUC >0.85 and high predictive values were developed from these markers. My third project also involved the above mentioned approach for detection of novel lipid biomarkers for Alzheimer's disease. Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common cause of age-related dementia. Currently, there are no methods to detect Alzheimer's at an early stage when treatment therapies could be applied. Therefore, there is need for detection of panel of biomarkers for detecting patients at risk to AD at an early stage. In the initial discovery set, sera from 29 different stage AD cases and 32 controls were analyzed using direct infusion mass spectrometry (ESI-TOF). This study yielded 89 potential lipid biomarkers which were evaluated in another confirmation study. Of these, 35 markers continued to be statistically significant in the second confirmatory set. Using the confirmed markers, several multi-marker panels with AUC > 0.87 were developed for any stage AD cases vs controls. Multi-marker panels with AUCs > 0.90 were developed for each specific CDR vs controls, including the earliest stage of AD. These lipidomic biomarkers are likely to distinguish AD cases regardless of the stage from controls. In conclusion, we successfully detected, validated and identified low molecular weight novel biomarkers for PE and lipid biomarkers for AD.
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Moren, Mark G. "Predictive utility of neuropsychological measures and single photon emission computed tomography (SPECT) in the classification of cerebral perfusion deficits in dementia of the Alzheimer type (DAT)." Virtual Press, 1995. http://liblink.bsu.edu/uhtbin/catkey/1001181.
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The general purpose of this study was to investigate the relationship between neuropsychological tests scores and perfusion deficits, based upon measures of regional cerebral blood flow (rCBF) taken from the single photon emission computed tomography (SPECT) scans of patients suffering from dementia of the Alzheimer type (DAT). The study was designed to determine if DAT patients categorized as having left hemisphere, right hemisphere, diffuse, or an absence of perfusion deficits, as measured by SPECT, would be accurately grouped into their respective categories, and if they would exhibit the corresponding neuropsychological deficiencies usually associated with lateral hemispheric asymmetries.Selected subjects were 80 right handed, DAT patients from the North Broward Medical Center - Memory Disorder Center, in Pompono Beach, Florida, who had been administered a neuropsychological test battery, and a SPECT scan.Through several ANOVA's that were calculated for each of the neuropsychological variables, it was concluded that DAT patients who suffered from perfusion deficits exhibited significantly lower levels of neuropsychological functioning than DAT patients without perfusion deficits.These analyses revealed significantly lower levels of neuropsychological performance in the perfusion deficit group on the combination of left hemisphere WAIS-R subtests (Information, Similarities & Vocabulary), WMS - Logical Story (p < .01), WRAT-R Reading, WRAT-R Mathematics, WMS Paired Associates, and the Rey Complex Figure (p < .05).A separate step-wise discriminant function analysis indicated that a combination of the neuropsychological variables could not accurately classify the DAT patients into their respective right hemisphere, left hemisphere, diffuse, or absence of perfusion deficit groups. The discriminant function classified only 32.5% of the grouped cases accurately. Of the original thirteen neuropsychological variables, only Paired Associates immediate recall of the WMS entered the discriminant analysis equation. This accounted for only 23% of the total variability that could be explained by differences between the perfusion deficit groups. In several post hoc ANOVA's using the Bonferroni method of multiple comparisons, it was revealed that the absence of perfusion deficit group scored significantly higher than the other groups on the majority of the left hemisphere neuropsychological measures. However, none of the right hemisphere neuropsychological measures attained significance.Department of Educational Psychology
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Topalis, Apostolos. "Multiresolution wavelet analysis of event-related EEG potentials using ensemble of classifier data fusion techniques for early diagnosis of Alzheimer's disease /." Full text available online, 2006. http://www.lib.rowan.edu/find/theses.
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Begnoche, Normand B. "Effectiveness of the Neurobehavioral Cognitive Status Examination in Assessing Alzheimer's Disease." Thesis, University of North Texas, 1996. https://digital.library.unt.edu/ark:/67531/metadc278136/.
Full textAbstract:
Accurate, early diagnosis of Alzheimer's Disease is becoming increasingly important in light of its growing prevalence among the expanding older-aged adult population. Due to its ability to assess multiple domains of cognitive functioning and provide a profile of impairment rather than a simple global score, the Neurobehavioral Cognitive Status Examination (NCSE) is suggested to better assess such patterns of cognitive deficit for the purpose of diagnosis. The performance of the NCSE was compared with that of the Mini-Mental State Examination (MMSE) for diagnostic sensitivity in a sample of patients diagnosed as having probable Alzheimer's Disease. The strength of correlation between severity of cognitive impairment on these tests and report of behavior problems on the Memory and Behavior Problems Checklist (MBPC) was also explored, as was performance on the NCSE and report of behavior problems using the MBPC in predicting Single Photon Emission Computed Tomography (SPECT) scan results.
The NCSE was found to exhibit greater sensitivity to physician diagnosis of probable Alzheimer's Disease relative to two versions (Serial 7's or WORLD) of the MMSE (.90, .77 and .68, respectively). While both measures were found to correlate significantly with the report of behavior problems, only a moderate proportion (NCSE = .22 and MMSE = .33) of the explained variance was accounted for by either test. Severity of cognitive impairment on the NCSE was found to be significant, though small in estimate of its effect size, for predicting the absence/presence of pathognomic findings on SPECT scans. In contrast, the report of behavior problems on the MBPC did not significantly predict SPECT scan outcomes.
The NCSE would appear to be a sensitive tool for the identification of the extent and severity of cognitive impairment found among demented individuals; however, it may be "over"-sensitive to such diagnosis. Although relationships between cognitive impairment and behavior problems and/or neuroradiological findings are observed, their meaningfulness remains with the need for further, more detailed, study using standardized criteria for comparison purposes.
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McGonigal, G. "The epidemiology of presenile Alzheimer's disease in Scotland (1974-1988) : diagnosis, incidence rate and natural history." Thesis, University of Glasgow, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.517823.
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Lindau, Maria. "Clinical differentiation between frontotemporal dementia and Alzheimer's disease : psychometric, behavioral, neuroimaging and neurophysiological information /." Stockholm, 2002. http://diss.kib.ki.se/2002/91-7349-430-5/.
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Kolanowski, Mikael, and David Stevens. "A Comparative Study of the Effect of Features on Neural Networks within Computer-Aided Diagnosis of Alzheimer's Disease." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-255260.
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Alzheimer’s disease is a neurodegenerative disease that affects approximately 6% of the global population aged over 65 and is forecasted to become even more prevalent in the future. Accurately diagnosing the disease in an early stage can play a large role in improving the quality of life for the patient. One key development for performing this diagnosis is applying machine learning to perform computer-aided diagnosis. Current research in the field has been focused on removing assumptions about the used data sets, but in doing so they have often discarded objective metadata such as the patient’s age, sex or priormedical history. This study aimed to investigate the effect of including such metadata as additional input features to neural networks used for diagnosing Alzheimer’s disease through binary classification of magnetic resonance imaging scans. Two similar neural networks were developed and compared, one with these additional features and the other without them. Including the metadata led to significant improvements in the network’s classification accuracy, and should therefore be considered in future computer-aided diagnostic systems for Alzheimer’s disease.Alzheimers sjukdom är en form av demens som påverkar ungefär 6% av den globala befolkningen som är äldre än 65 och förutspås bli ännu vanligare i framtiden. Tidig diagnos av sjukdomen är viktigt för att säkerställa högre livskvalitet för patienten. En viktig utveckling inom fältet är datorstödd diagnos av sjukdomen med hjälp av maskininlärning. Dagens forskning fokuserar på att ta bort subjektiva antaganden om datamängden som används, men har ofta även förkastat objektiv metadata såsom patientens ålder, kön eller tidigare medicinska historia. Denna studier ämnade därför undersöka om inkluderandet av denna metadata ledde till bättre prestanda hos neuronnät som används för datorstödd diagnos av Alzheimers genom binär klassificering av bilder tagna med magnetisk resonanstomografi. Två snarlika neuronnät utvecklades och jämfördes, med skillnaden att den ena även tog metadata om patienten som indata. Inkluderandet av metadatan ledde till en markant ökning i neuronnätets prestanda, och bör därför övervägas i framtida system för datorstödd diagnos av Alzheimers sjukdom.
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Dhiman, Kunal. "Utility of CSF biomarkers for the diagnosis, prognosis and assessment of cognitive decline in Alzheimer’s disease." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2020. https://ro.ecu.edu.au/theses/2284.
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Alzheimer’s disease (AD) is a slow and progressive neurodegenerative disorder.With new treatment strategies failing in clinical trials, there is a need to initiate a targeted treatment strategy, by administering the right medication, to the right individual, at the right stage. This concept of precision medicine not only requires diagnosis at the preclinical stage, but a thorough understanding of the stage-associated neuropathological changes that occur along the continuum of AD. Pathophysiological biomarkers indicative of neuropathological changes in the brain are needed to identify the preclinical stage of AD, as well as track the extent of cognitive deficit that occurs with the evolution of such changes.
The current study was conducted to assess the diagnostic and prognostic potential of cerebrospinal fluid (CSF) biomarkers in AD, associated with neurodegeneration (neurofilament light chain protein, NfL; visinin-like protein-1, VILIP-1; fatty acid binding protein 3, FABP3), neuroinflammation (YKL-40) and synaptic dysfunction (neurogranin, growth-associated protein 43, GAP-43; synaptosomal-associated protein 25, SNAP-25; synaptotagmin-1). CSF samples of participants (n = 221) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing were used in the study. The study participants were clinically classified as healthy controls (HC, n = 159), mild cognitive impairment (MCI, n = 34) and AD (n = 28). The study aimed to assess the diagnostic potential of CSF biomarkers, their preclinical diagnostic utility, prediction of disease onset and progression, association with central AD pathology, as well as their ability to predict baseline cognition, brain atrophy and amyloid accumulation.
The CSF biomarkers NfL, VILIP-1, FABP3, YKL-40, neurogranin, GAP-43 and SNAP-25 distinguished AD participants from HC with a fairly high area under the receiver operating characteristic curve (AUC). CSF biomarkers of neurodegeneration (NfL and FABP3) predicted disease onset among HC who converted from Clinical Dementia Rating (CDR) 0 to CDR ≥ 0.5, over a follow-up period of 4.5 years. CSF biomarkers predicted disease progression among patients (MCI and AD), assessed through the annual change in cognitive scores in patients, divided into tertiles based on 33rd and 66th percentile of CSF measures. CSF levels of NfL significantly increase in the earlier stages of the disease, but not in the later stages, indicating that the brain reaches a stage of irreversible neurodegeneration in late AD, with not much further evolution. CSF biomarkers significantly correlated with core CSF biomarkers total tau (T-tau) and phosphorylated tau (P-tau); classified study participants according to the A/T/N classification (based on biomarker of amyloid deposition, A; tau pathology, T and neurodegeneration, N) and predicted baseline cognition and brain atrophy. All CSF biomarkers were weak predictors of baseline amyloid load, and did not distinguish amyloid positives from negatives with a high sensitivity. This makes it apparent that neurodegeneration, neuroinflammation and synaptic dysfunction, all run independent of amyloid pathology along the disease continuum, but amyloid beta (Aβ) accumulation does contribute to the disruption of spines or neuritis, and inflammatory response.
These biomarkers and the pathologies they drive conglomerate at one stage or the other to constitute the AD neuropathology, and demonstrate an excellent diagnostic accuracy in combination. Neurodegeneration and neuroinflammation evolve in synchronisation at all stages, along the disease continuum. Neurodegeneration and synaptic dysfunction are synchronised as well, but not in an advanced stage of the disease continuum. These biomarkers give a clear picture of the pathological changes that occur along the disease continuum, and can be used as endpoint measures in clinical trials.
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Long, Xiaojing. "Image Classification using Pair-wise Registration and Machine Learning with Applications to Neuroimaging." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/40396.
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Alzheimer's disease~(AD) is the most frequent neurodegenerative dementia and a growing health problem. Early and accurate diagnosis and prediction of AD is crucial because treatment may be most efficacious if introduced as early as possible. Neuropsychological testing, which is clinically used, sometimes fails to recognize probable dementia, especially to recognize the disease at an early time point such as the mild cognitive impairment~(MCI), which is the prodromal stage of AD.
Recently, there has been a realization that magnetic resonance imaging~(MRI) may help diagnoses of AD and MCI. In this dissertation, we introduce an MRI-analysis based algorithm to help diagnose the illness before irreversible neuronal loss has set in, and to help detect brain changes between MCI patients who may convert and may not convert to AD. Given a set of brain MR images, the algorithm first calculates the distance between each pair of images via a registration process. Then images are projected from a high dimensional Euclidean space to a low dimensional Euclidean subspace based on the calculated distances, with a dimension reduction method. Finally classical supervised classification approaches are employed to assign images to appropriate groups in the low dimensional space. The classification accuracy rates we obtained in our experiments are higher than, or at least comparable to, those reported in recently published papers.
Moreover, this algorithm can be extended to explore the pathology distribution of AD. Exploring the distribution of AD pathology is of great importance to reveal AD related regional atrophy at specific stages of the disease and provide insight into longitudinal sequence of disease progression. Calculating distances between different brain structures produces different classification accuracy. Those structures yielding higher classification accuracy are considered as pathological regions. Our experimental results on pathology localization are also compared with the reproduced results using other existing popular algorithms; the observations are consistent.Ph. D.
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Simons, Samantha M. "Analysis of brain signals with advanced signal processing techniques to help in the diagnosis of Alzheimer's disease." Thesis, University of Surrey, 2017. http://epubs.surrey.ac.uk/813461/.
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Alzheimer’s disease (AD) is the most prevalent form of dementia in the world. Symptoms include progressive memory, cognitive and behavioural changes before death, caused by amyloid plaques and hyperphosphorated tau in the brain. The cause of AD is currently unknown and current interventions only slow the decline. Diagnosis is based on patient and familial history, interviews with close family and friends, cognitive, mental and physical tests. The electroencephalogram (EEG) records the electrical signals of the brain, which AD, as a cortical dementia, is known to directly affect. Non-linear signal processing has shown that these changes in the EEG can be identified with complementary findings to linear methods. This thesis aimed to explore these changes with novel univariate and bivariate methods using both synthetic signals and resting, eyes-closed EEGs recorded from 22 subjects, 11 AD patients (MMSE=13.1±5.9 (mean SD)) and 11 age-matched controls (30±0). Permutation entropy showed statistically significant increased complexity in control EEGs for electrodes at the front of the head. Bivariate analysis was novel for this EEG database so coherence was used to create a comparison results set. With the success of Lempel-Ziv Complexity (LZC), distance based bivariate forms were applied (dLZC03). Novel normalisation methods based on that for univariate LZC showed a greater representation of the signal patterns in the results. Volume conduction was shown to significantly impact the results, both of coherence and dLZC03, though this was greater with coherence. Lastly, volume conduction mitigated, bandwidth based pre filtering with dLZC03 was calculated, producing the most significant p values ever recorded with this EEG database. Thus this PhD shows increased distinction between the two subject groups with dLZC03 over LZC and increased distinction with limited but targeted bandwidths from those subject signals.
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Kjellberg, Gustav, and Henrik Kälvegren. "A comparison of classification accuracy between MRI and PET datasets in computer aided diagnosis of Alzheimer's disease." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229704.
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The number of people suffering from Alzheimer’s disease (AD) is expected to increase rapidly in the coming years. Diagnosing the disease early is key to giving those affected a chance to maintain a higher quality of life. One of the most common ways to detect AD is to visually inspect scans of the patients’ brains. Computer aided diagnosis (CAD)can assist a physician’s judgement when searching for the disease in the brain scans, making the assessment more accurate. Progress has been made in this field throughout the years. This paper compares the machine learning classification accuracy of AD on images from two different brain scanning procedures - Magnetic resonance imaging (MRI) and Positron emission tomography (PET). Both the MRI and PET datasets contained 60 images. 30 of the images were AD cases and 30 were normal cases in each of the datasets. The images were processed into 1-dimensional signals using Discrete wavelet transform (DWT). The classification accuracy of Support vector machine (SVM), Random forest (RF) and Naive Bayes (NB) was obtained and then evaluated using 6-fold cross validation (CV). This study showed that PET images are more suitable than MR images for diagnosing AD using machine learning classifiers. The highest accuracy for PET and MRI from 6-fold CV was 100% and 90% respectively. The lowest accuracy was 60% for PET and 40% for MRI.Antalet människor drabbade av Alzheimers sjukdom (AD) förväntas öka kraftigt de kommande åren. Att kunna diagnostisera sjukdomen tidigt är nyckeln till att ge dem insjukna en chans att leva ett liv av högre kvalitet. Ett av de vanligaste sätten att upptäcka AD är att visuellt undersöka bilder från hjärnskanningar av patienter. Datorassisterad diagnostisering (CAD) kan hjälpa en läkare i sitt omdöme vid undersökning för sjukdomen i hjärnbilderna, vilket ökar omdömets pålitlighet. Framsteg har gjorts inom området genom åren. Den här studien undersöker bedömningssäkerheten av maskinlärningsmetoder i klassifiering av AD på bilder från två olika skanningsmetoder för hjärnan - Magnetisk resonanstomografi (MRI) och Positronemissionstomografi (PET). Både PET- och MRI-datamängderna innehöll 60 bilder. 30 av bilderna var AD-fall och 30 var normala fall i varje datamängd. Bilderna processerades till endimensionella signaler med Discrete wavelet transform (DWT). Klassifieringssäkerheten av Support vector machine (SVM), Random forest (RF) och Naive bayes (NB) framtogs och utvärderades därefter med 6-delad korsvalidering (CV). Studien visade att PET-bilder är att föredra vid diagnostisering av AD med maskininlärningsklassifierare framför MR-bilder. Den högsta bedömningssäkerheten för PET och MRI utifrån 6-delad CV var 100 % och 90 % respektive. Den lägsta säkerheten var 60 % för PET and 40 % för MRI.
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Chan, Cho-cheong, and 陳楚莊. "Magnetic resonance elastography: neuronal andmuscular studies, and a novel acoustic shear wave generator." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38643868.
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Kleiren, Emilie. "Towards an early diagnosis of Alzheimer's disease: development of an ATR-FTIR biosensor for the detection of Abeta toxic conformations." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209415.
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As the most prevalent cause of dementia worldwide, Alzheimer’s disease (AD) has become a global issue of public health. By current criteria, diagnosis of this neurodegenerative disorder requires both clinical confirmation of dementia and post-mortem detection of the so-called neurofibrillary tangles and senile plaques in the brain. Yet the main proteinaceous component of these plaques, the amyloid beta peptide (Abeta) is now widely believed to initiate a cascade of events that ultimately leads to Alzheimer’s disease. Besides, extensive evidence supports a pathogenic role of soluble oligomers formed upon Abeta aggregation in the onset of the disease, which, unlike Abeta fibrils, present distinct neurotoxic properties and correlate well with disease progression. Their detrimental effects have been suggested to appear decades before the first signs of cognitive impairment, making them biomarkers of choice in the study of the pathology. Given that present guidelines for AD diagnosis are increasingly considered as ill-defined, reliable and early-stage detection methods taking into account the presence of toxic Abeta species are highly awaited by the medical community. In this regard, this thesis work describes the development of a sensing device aiming at the specific detection of the amyloid beta peptide in solution via recognition by antibodies grafted at the surface of functionalized germanium crystals. This new type of BIA-ATR (Biospecific Interaction Analysis - Attenuated Total Reflection) biosensor resorts on ATR-FTIR (Attenuated Total Reflection - Fourier Transform Infrared) spectroscopy, which is extremely sensitive to the secondary structure of proteins. The ATR mode uses germanium as optical transduction element combined to the evanescent wave principle to allow selective online monitoring of peptide-antibody binding events.
In the first part of this work, evaluation of the photochemistry on germanium optical elements have been the subject of intense research focus. Our investigations led to the elaboration of a quality control of functionalization efficiency based on infrared spectroscopy. We also set up in the lab an original ELISA method for selecting antibodies in terms of their true affinity for the Abeta peptide.
Thereafter binding experiments were carried out on the BIA-ATR sensor using different antibodies and Abeta isoforms, leading to the establishing of a standardized protocol for the detection of molecules of interest. Our results showed that Abeta detected on the biosensor corresponded precisely to antibody-bound peptide, whereas Abeta assemblies, and especially Abeta 1-42 oligomeric conformations, could be discriminated with respect to their spectral signature. This point, which was later confirmed by unsupervised statistical analysis, could be considered as particularly interesting and innovative, since to our knowledge, such conformation-sensitivity has never been observed with existing AD diagnostic methods. Moreover, effective recycling of the functionalized crystals has been demonstrated, which confers thereby a second major advantage to the biosensor.
In parallel to these experiments, a structural characterization study of Abeta species was undertaken in order to generate a database of IR spectra, as reference for future comparative analysis of physiological fluids on the biosensor. ATR-FTIR measurements revealed a strong dependency on the ratio between oligomers and fibrils within a mixture and their relative ratio in antiparallel and parallel beta-sheet content. Interestingly, separation trials of oligomeric entities demonstrated a specific effect of Cu2+ ions on Abeta aggregation. Stabilization of small oligomeric aggregates at equimolar Cu2+:Abeta ratios, which had never been clearly evidenced so far, could help to unravel some aspects of the complex role of copper in AD development.
These investigations illustrate the applicability of the so-called BIA-ATR methodology to online detection of different forms of the Abeta peptide in solution and the potential of this new sensor technology to fulfill current pitfalls in providing a reliable and comprehensive approach of AD diagnosis.
Doctorat en Sciences agronomiques et ingénierie biologique
info:eu-repo/semantics/nonPublished
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Gu, Jiamin [Verfasser], Boris [Akademischer Betreuer] Schmidt, and Katja [Akademischer Betreuer] Schmitz. "Design, synthesis and evaluation of fluorescent probes for the diagnosis of Alzheimer's disease and Parkinson's disease / Jiamin Gu. Betreuer: Boris Schmidt ; Katja Schmitz." Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2013. http://d-nb.info/1106454146/34.
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Clarnette, Roger M. "Predictors of cognitive decline in those with subjective memory complaint." University of Western Australia. School of Psychiatry and Clinical Neurosciences, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0245.
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[Truncated abstract] Background: Dementia, largely due to Alzheimer's disease (AD), is a major public health problem. The early identification of disease is an important challenge for clinicians because treatment of AD is now available. A simple and accurate means of stratifying risk for AD and identifying early disease is needed so that risk factor modification and treatment can occur optimally. To date, despite many attempts, an accurate means of standardising an approach to the assessment of subtle cognitive symptoms has not been developed. A subjective complaint of poor memory has been identified as a possible marker for underlying brain disease. This study examines the utility of neuropsychological scores, homocysteine levels, APOE genotyping and brain imaging as predictors of cognitive decline in individuals with subjective memory complaint (SMC). Method Eighty subjects with SMC were recruited from memory clinics and the community (MC: 1). Forty-two control subjects were also examined (MC: 0). CAMDEX was used to describe baseline clinical features. The CAMCOG was used as a global test of cognition and was administered annually for four years. At baseline, neuropsychological testing was administered. Cranial CT scanning, measurement of plasma homocysteine and APOE genotyping were completed. Categorical variables were analysed using chi-square according to Pearson's method. Continuous data was analysed using Student's t-tests and Mann-Whitney tests. A logistic regression model was used to identify independent contributors to the presence of memory complaint. Participants were then matched for age, gender and time to follow-up (up for three years) to determine longitudinal predictors of cognitive decline. ... Baseline CAMCOG scores were greater in the control group (MC:0 = 98.3 ? 2.8, MC:1 94.2 ? 5.5, Z ?4.46, p 0.000). There were no differences in neuropsychological scores, concentration of total plasma homocysteine, APOE genotype or brain scan measurements. Using the Wald stepwise selection method, logistic regression could not be established due to non-convergence regardless of whether or not the continuous variables were re-coded into dichotomous variables. A matching process that created 32 pairs of controls/subjects allowed follow-up analysis. The controls showed significant improvement with time on the CAMCOG unlike subjects (mean ? SD, controls 1.5 ?-3.0, Z - 2.61, p 0.01, subjects 0.2 ? 3.2, Z ? 0.24, p 0.81). The logistic regression analysis showed that group membership could not be defined by any single independent variable. When group membership was abandoned and those with stable scores were compared to those who declined no clear meaningful independent predictors of decline apart from age were identified. Conclusions: Methodological issues such as small sample size and inadequate follow up duration were identified that may have precluded identification of predictive factors for cognitive decline. The results indicate that complaints of memory problems are not associated with established risk factors for Alzheimer's disease and fail to predict objective cognitive decline over three years. Future studies should continue trying to identify robust predictors of cognitive decline in later life.
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Jensen, Jordan Royce. "Development of Tau-Selective Imaging Agents for Improved Diagnosis of Alzheimer’s Disease and Other Tauopathies." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306441097.
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Clague, Fiona. "The early diagnosis of Alzheimer's disease and related dementias using tests of people naming and cross-modal associative learning." Thesis, University of Cambridge, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615022.
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