Biyomedikal Mühendisliği Enstitüsü

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Browsing Biyomedikal Mühendisliği Enstitüsü by Subject "Alzheimer's disease."

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    A correlational stydy between serum cytokine measures, volumetric MR measures and global cognitive changes in Alzheimer's disease
    (Thesis (M.S.)-Bogazici University. Institute of Biomedical Engineering, 2010., 2010.) Tardu, Mehmet.; Ademoğlu, Ahmet.; Gürvit, Hakan.
    Earlier detection and diagnosis of Alzheimer's disease (AD) would permit earlier intervention, which conceivably could delay progression of this dementing disorder. In order to accomplish this goal, reliable and speci c biomarkers are needed. Unfortunately, there is no yet such a universally accepted biomarker. In this study, we aimed to analyze the association between volumetric MR measurements and possible AD related serum cytokine biomarkers and to determine biological and clinical predictors for patients at high risk to develop AD. 28 AD patients and 16 healthy controls were participated to the study. For this study biochemical markers (IL-1 , IL-1 , IL-10, TNF- ) which were considered to play a pivotal role in the in ammation process during AD were chosen. Additionally, volumetric MR measurements were done to determine atrophic regions in the brain of AD patients. For this purpose, a fully automated software (FreeSurfer) was used. First of all, our ELISA measurements indicated that patients with AD produce increased quantities of pro-in ammatory cytokines (IL-1 and TNF- ) than normal subjects and these results supporting the hypothesis that a pro-in ammatory phenotype contributes to AD. ROC curve analysis showed that IL-1 and TNF- serum levels could not be used as a diagnostic test tool. However, serum IL-1 level might be a better candidate to make a better diagnostic decision. Secondly, regression analysis revealed that serum IL-1 level had a signi cant linear relation with the volume changes of cerebral white matter and amygdala/hippocampus. Additionally, the Mini-Mental State Examination (MMSE) score was used as a scale of AD severity. Regression analysis emphasized that serum cytokine levels did not have a signi cant relation with the severity of cognitive impairment.|Keywords: Alzheimer's Disease, Biomarker, Serum, In ammation, IL-1alpha , IL-1beta , IL- 10, TNF-alpha , Volumetric MR, FreeSurfer, Mini-Mental State Examination
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    Functional connectivity network analysis of alzheimer and mild cognitive impairment patients
    (Thesis (M.S.)-Bogazici University. Institute of Biomedical Engineering, 2014., 2014.) Şahin, Duygu.; Ademoğlu, Ahmet.
    In our era, while the life span is expanding, neurodegenerative diseases, such as Alzheimer's disease (AD), pose a great threat upon the quality of life. In such a case, the best course of action would be to detect, modify or treat the pathologies before they become too severe. Since the main cause of AD is still unknown, further studies for possible biomarkers are needed. Therefore, in this study, the objective is to nd a distinctive agent for AD and mild cognitive impairment (MCI) from an optimized auditory oddball task fMRI data via functional connectivity analysis. In order to achieve that, a group ICA approach using temporal concatenation of the subject data is adopted. Since, there are no studies investigating functional connectivity of AD and MCI during an oddball task, especially via group ICA, this study can enrich the literature. As the results are concerned, in group comparisons, no signi cant di erences are found in spatial maps. On the other hand, there are promising ndings in temporal course analysis of the components such as the multiple regression outcomes. Therefore, our next aim will be to perform a longutidinal study including both resting state and task related data for nding a better biomarker.|Keywords : fMRI, Alzheimer's disease, mild cognitive impairment, independent component analysis, oddball paradigm.
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    Reliability improvement of computer aided diagnostic system using mutual information
    (Thesis (M.S.)-Bogazici University. Institute of Biomedical Engineering, 2016., 2016.) Polat, Esra.; Güveniş, Albert.
    Computer aided diagnosis (CAD) is one of the most important topic in recent years since the systems are able to provide a second reliable opinion to physicians and early diagnosis with these systems are possible. In this study we aim to construct a system for the detection of Alzheimer's disease (AD) using PET images from a database. The CAD system includes a database consisting of a 3D PET image for every query. Via using a similarity metric namely mutual information(MI), every query compares to all other query in database. According to their similarity results, a decision index is calculated. The decision index demonstrate presence or absence of AD. The system was developed and evaluated using two di erent databases extracted from Alzheimer's disease Neuroimaging Initiative (ADNI) database. All normal and Alzheimer's images are stored and ordered in database. First database consists of 259 normal and 138 AD patient whereas second database consists of 102 normal and 95 AD patient. Main di erence of two database is registration. Images in second database are warped with talairach atlas. CAD performance was evaluated using Receiver Operating Characteristic analysis. For every query, a decision index was calculated. According to our results we observed that accuracy and speed of the CAD system is a ected by certain parameters. The method proposed in the article is adequate to distinguish the disease. The mutual information method is very simple, applicable and fast enough to use in clinic area.|Keywords : Computer Aided Diagnosis, Mutual Information, Alzheimer Disease.
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    Similarity - based analysis of FDG-PET images of alzheimer's disesase patients :|a method for automated diagnosis and severity prediction with the aim of therapy response monitoring
    (Thesis (M.S.)-Bogazici University. Institute of Biomedical Engineering, 2022., 2022.) Yüksel, Ceren.; Güveniş, Albert.
    This study aimed to evaluate 18-Fluorodeoxyglucose positron emission tomog raphy (18F-FDG-PET) images of the brain for the computer-aided characterization detection of Alzheimer’s disease (AD) intuitive image similarity-measure-based ap proach. The first objective was to diagnose AD automatically. The second objective was to determine the association between the similarity measure and neuropsycholog ical assessments. Therefore, we aimed to develop a new AD evaluation algorithm that can give an early diagnosis of the disease and define an objective severity index that correlates with well-known neuropsychological tests. 125 patients with AD, 132 Cog nitively Normal (CN), and a total of 257, FDG-PET data were obtained from ADNI. We then found a distance value indicative of the similarity between any 3D image to available CN and AD patient images in the database using the mutual information method. The diagnosis was based on a threshold value for the distance value. Then, the Mini Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) results of all patients and the distance values obtained from FDG-PET were analyzed using an analysis of variance. The algorithm achieved an AUC ROC of 0,969 using a leave-one-out method for the original dataset (n=197) and 0,873 using the independent testing dataset (n=60). The correlation was 0,642 between MMSE scores and imaging scores, and for CDR global test correlation between imaging and testing was 0,677. A simple and intuitive similarity-based algorithm can be used for the early detection of AD using molecular imaging as well as determining an objective severity index. No ROI and feature computations should be performed.|Keywords : Alzheimer’s disease, 18F-FDG-PET, Similarity Index, Neuropsychological Assessments, Severity Index.
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    Surface based morphometry in Alzheimer's disease
    (Thesis (M.S.)-Bogazici University. Institute of Biomedical Engineering, 2019., 2019.) Uluğ, Esma Ece.; Ademoğlu, Ahmet.
    Alzheimer’s disease( AD) is aneurodegenerativedisorderespeciallyaffectingthe elderlypopulationwhichisgrowingworldwide. Inthisstudy, surface-basedmorphometry analysis was performed on anatomical MR images of patients with Alzheimer’s Disease (AD) and healthy control (HC) subjects using a computational anatomy toolbox called CAT(Computational Anatomy Toolbox) on SPM (Statistical Parameter Mapping) platform. MR images were obtained from a database named Minimal Interval Resonance Imaging in Alzheimer’s Disease (MIRIAD) consisting of 46 AD patients and 23 HC subjects. The cortical thickness measurements were performed over 34 different regions on each hemisphere defined by Desikan-Killiany anatomical atlas. The t-statistics parameters of the cortical thickness values were found to be decreased in 24 regions in AD patients compared with the HC subjects. Additionally, the linear correlation values between the MMSE scores and cortical thickness values of AD and HC individuals were estimated for each atlas region. Accordingly, 28 regions exhibited a significant correlation between MMSE(Mini Mental State Examination) scores and cortical thickness values. Significant regions that were affected by AD were observed to be as parietal, temporal, frontal, cingulate and occipital lobes as reported in previous studies.|Keywords : Alzheimer’s Disease, Magnetic Resonans Imaging, Surface Based Morphometry, Cortical Thickness, Computational Anatomy Toolbox, Desikan-Killiany Atlas, Mini Mental State Examination.