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Academic literature on the topic 'Magnetic Resonance Imaging Biomarkers'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Magnetic Resonance Imaging Biomarkers"

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Kurhanewicz, J. "Magnetic Resonance Imaging Biomarkers of Prostate Cancer." AACR Education book 2008, no. 1 (April 12, 2008): 523–26. http://dx.doi.org/10.1158/aacr.edb-08-8146.

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Candiota, Ana Paula, and Carles Arús. "Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives." Metabolites 12, no. 3 (March 14, 2022): 243. http://dx.doi.org/10.3390/metabo12030243.

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This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.
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Mills, S. J., G. Thompson, and A. Jackson. "Advanced magnetic resonance imaging biomarkers of cerebral metastases." Cancer Imaging 12, no. 1 (2012): 245–52. http://dx.doi.org/10.1102/1470-7330.2012.0012.

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Bragin, A. G. "Prevention of epileptogenesis as a future strategy for the treatment of epilepsy." Almanac of Clinical Medicine 47, no. 7 (December 22, 2019): 614–22. http://dx.doi.org/10.18786/2072-0505-2019-47-028.

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Epilepsy affects more than 70 million people worldwide. From 30 to 40% of the patients are resistant to existing medication. This paper describes the current state of the treatment of epilepsy and proposes a future approach to preventative treatment at earlier stages of epileptogenesis. For preventative treatment biomarkers are needed that predict the development of epilepsy at its earlier stages. Pathological high frequency oscillations are the only acceptable biomarker of epileptogenesis. However, the main limitation of this biomarker is the necessity of implanting of recording electrodes. The search for noninvasive biomarkers of epileptogenesis is one of the hot topics in epilepsy research. There are two potentially interesting directions in this area: search for inflammatory biomarkers in the peripheral blood and analysis of different parameters of imaging methods. In this paper we present approaches for identification of potential epileptogenesis biomarkers by magnetic resonance imaging. Some of magnetic resonance imaging parameters correlate with the existence of pathological high frequency oscillations, may indirectly reflect ongoing inflammation process in the brain and be potential biomarkers of epileptogenesis.
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Moura Cunha, Guilherme, Patrick J. Navin, Kathryn J. Fowler, Sudhakar K. Venkatesh, Richard L. Ehman, and Claude B. Sirlin. "Quantitative magnetic resonance imaging for chronic liver disease." British Journal of Radiology 94, no. 1121 (May 1, 2021): 20201377. http://dx.doi.org/10.1259/bjr.20201377.

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Chronic liver disease (CLD) has rapidly increased in prevalence over the past two decades, resulting in significant morbidity and mortality worldwide. Historically, the clinical gold standard for diagnosis, assessment of severity, and longitudinal monitoring of CLD has been liver biopsy with histological analysis, but this approach has limitations that may make it suboptimal for clinical and research settings. Magnetic resonance (MR)-based biomarkers can overcome the limitations by allowing accurate, precise, and quantitative assessment of key components of CLD without the risk of invasive procedures. This review briefly describes the limitations associated with liver biopsy and the need for non-invasive biomarkers. It then discusses the current state-of-the-art for MRI-based biomarkers of liver iron, fat, and fibrosis, and inflammation.
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Kollewe, Katja, Sonja Körner, Reinhard Dengler, Susanne Petri, and Bahram Mohammadi. "Magnetic Resonance Imaging in Amyotrophic Lateral Sclerosis." Neurology Research International 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/608501.

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Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disorder which is incurable to date. As there are many ongoing studies with therapeutic candidates, it is of major interest to develop biomarkers not only to facilitate early diagnosis but also as a monitoring tool to predict disease progression and to enable correct randomization of patients in clinical trials. Magnetic resonance imaging (MRI) has made substantial progress over the last three decades and is a practical, noninvasive method to gain insights into the pathology of the disease. Disease-specific MRI changes therefore represent potential biomarkers for ALS. In this paper we give an overview of structural and functional MRI alterations in ALS with the focus on task-free resting-state investigations to detect cortical network failures.
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Kamagata, Koji, Christina Andica, Ayumi Kato, Yuya Saito, Wataru Uchida, Taku Hatano, Matthew Lukies, et al. "Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases." International Journal of Molecular Sciences 22, no. 10 (May 14, 2021): 5216. http://dx.doi.org/10.3390/ijms22105216.

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There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.
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Song, Jae W., Athanasios Pavlou, Jiayu Xiao, Scott E. Kasner, Zhaoyang Fan, and Steven R. Messé. "Vessel Wall Magnetic Resonance Imaging Biomarkers of Symptomatic Intracranial Atherosclerosis." Stroke 52, no. 1 (January 2021): 193–202. http://dx.doi.org/10.1161/strokeaha.120.031480.

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Background and Purpose: Intracranial atherosclerotic disease is a common cause of stroke worldwide. Intracranial vessel wall magnetic resonance imaging may be able to identify imaging biomarkers of symptomatic plaque. We performed a meta-analysis to evaluate the strength of association of imaging features of symptomatic plaque leading to downstream ischemic events. Effects on the strength of association were also assessed accounting for possible sources of bias and variability related to study design and magnetic resonance parameters. Methods: PubMed, Scopus, Web of Science, EMBASE, and Cochrane databases were searched up to October 2019. Two independent reviewers extracted data on study design, vessel wall magnetic resonance imaging techniques, and imaging end points. Per-lesion odds ratios (OR) were calculated and pooled using a bivariate random-effects model. Subgroup analyses, sensitivity analysis, and evaluation of publication bias were also performed. Results: Twenty-one articles met inclusion criteria (1750 lesions; 1542 subjects). Plaque enhancement (OR, 7.42 [95% CI, 3.35–16.43]), positive remodeling (OR, 5.60 [95% CI, 2.23–14.03]), T1 hyperintensity (OR, 2.05 [95% CI, 1.27–3.32]), and surface irregularity (OR, 4.50 [95% CI, 1.39–8.57]) were significantly associated with downstream ischemic events. T2 signal intensity was not significant ( P =0.59). Plaque enhancement was significantly associated with downstream ischemic events in all subgroup analyses and showed stronger associations when measured in retrospectively designed studies ( P =0.02), by a radiologist as a rater ( P <0.001), and on lower vessel wall magnetic resonance imaging spatial resolution sequences ( P =0.02). Conclusions: Plaque enhancement, positive remodeling, T1 hyperintensity, and surface irregularity emerged as strong imaging biomarkers of symptomatic plaque in patients with ischemic events. Plaque enhancement remained significant accounting for sources of bias and variability in both study design and instrument. Future studies evaluating plaque enhancement as a predictive marker for stroke recurrence with larger sample sizes would be valuable.
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Barnes, Josephine, Jo Foster, and Nick C. Fox. "Structural magnetic resonance imaging-derived biomarkers for Alzheimer’s disease." Biomarkers in Medicine 1, no. 1 (June 2007): 79–92. http://dx.doi.org/10.2217/17520363.1.1.79.

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Reeder, Scott B. "Emerging quantitative magnetic resonance imaging biomarkers of hepatic steatosis." Hepatology 58, no. 6 (October 11, 2013): 1877–80. http://dx.doi.org/10.1002/hep.26543.

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Dissertations / Theses on the topic "Magnetic Resonance Imaging Biomarkers"

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Stephen, Renu M. "Magnetic Resonance Imaging Biomarkers For Targeted Cancer Therapies." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/194845.

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In 2007, there will be an estimated 178,480 new cases of breast cancer diagnosed in women in the United States. The elucidation of the vast heterogeneity of individual tumors has led to a paradigm shift from a one-size fits all treatment strategy to more individualized treatment based on the molecular profile of the tumor. Identifying biomarkers that respond to or predict the action of drugs is important in identifying efficacious targets and drugs that will improve clinical outcome. To examine this, we first identified two breast cancer cell lines (ACC-3199 and ACC-3171) from a panel of low passage breast cells lines that were capable of growing serially as tumor xenografts. This was followed by the in vivo molecular characterization of these two cell lines. In ACC-3199 tumors, we identified a gain of pAKT expression compared to cultured cells. Based on this finding, we investigated the role of diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) as potential imaging biomarkers in identifying early response to PX-866, a PI3K inhibitor, in ACC-3199 tumors as represented by changes in tumor cellularity and hemodynamic parameters, respectively. Our results indicated that DW-MRI was able to identify an early response to PX-886 in ACC-3199 tumors as defined by an increase in the apparent diffusion coefficient (ADC) value of the tumors prior to changes in tumor volumes. Using DCE-MRI, we were able to conclude that PX-866 was not an effective anti-angiogenic agent as indicated by an increase in tumor permeability following therapy. Based on the VEGFR2 expression observed in ACC-3171 tumor xenografts, we examined the response of MDA-MB-231/GFP and ACC-3171 tumor xenografts to the anti-angiogenic agent, sunitinib, using the same imaging modalities. DW-MRI was able to detect increases in ADC values as early as 12 h post-treatment in both MDA-MB-231/GFP and ACC-3171 tumors. Thus, it appears that DW-MRI may be a useful clinical test in predicting the early response to PI3K and anti-angiogenic inhibitors. These imaging approaches, in addition to the further molecular characterization of breast tumors may lead to the improvement and development of medical therapies for breast cancer patients.
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Johnston, Edward William. "Developing multiparametric and novel magnetic resonance imaging biomarkers for prostate cancer." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/10039809/.

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Whilst biomarker research is gaining momentum within the cancer sciences, disappointingly few biomarkers are successfully translated into clinical practice, which is partly due to lack of rigorous methodology. In this thesis, I aim to systematically study several quantitative magnetic resonance imaging (MRI) biomarkers (QIBs), at various stages of biomarker development for use as tools in the assessment of local and metastatic prostate cancer according to clinical need. I initially focus on QIBs derived from conventional multiparametric (mp) prostate MRI sequences, namely T2 weighted (T2W), apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE). Firstly, by optimising analytical methods used throughout the thesis, deciding which approach is more reliable between single-slice region-of-interest vs. contouring the whole tumour volume using two different software packages. I then consider whether metric reproducibility can be improved by normalisation to different anatomical structures, and assess whether it is preferable to use statistics derived from imaging histograms rather than the current convention of using mean values. I combine multiple QIBs in a logistic regression model to predict a Gleason 4 component in known prostate cancer, which represents an unmet clinical need, as noninvasive tools to distinguish these more aggressive tumours do not currently exist. I subsequently ‘technically validate’ a novel microstructural diffusion-weighted MRI technique called VERDICT (Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours) to detect aggressive prostate cancer as part of a prospective cohort study. I assess the image quality, contrast-to-noise ratio, repeatability and performance of quantitative parametric VERDICT maps to discriminate between Gleason grades vs. the current best performing, but still imperfect tool of ADC. In the final two results chapters, motivated by the limited diagnostic accuracy of the prostate cancer staging modalities in current clinical use, I investigate the ability of mp whole-body (WB) MRI to stage aggressive cancer outside the prostate in patients with a high risk of metastases at primary diagnosis, and in biochemical failure following prostatectomy.
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Latifoltojar, Arash. "Developing whole-body magnetic resonance imaging biomarkers for the assessment of haematological malignancies." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10055800/.

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Whole body magnetic resonance imaging (WB-MRI) is being recognised as an alternative to conventional computed tomography, isotope bone scan and PET-CT scan. Advances in MR imaging have enabled sophisticated whole body protocols interrogating and imaging different facets of tumour biology. Furthermore, these multi-sequence WB-MRI protocols can be applied within patient friendly examination times. Qualitative and quantitative evaluation of WB-MRI examinations can now readily be performed, and form the focus of ongoing research into clinical utility for disease staging and response assessment. Quantitative WB-MRI research has mainly concentrated on diffusion weighted imaging (DWI) derived apparent diffusion coefficient (ADC), a parameter broadly representative of tumour cellularity. This thesis focuses on evaluating WB-MRI in the setting of lymphoma and multiple myeloma (haematological malignancies) through a series of translational imaging biomarker developmental studies. The first study retrospectively evaluates the diagnostic accuracy of WB-MRI (performed at 1.5 T) for the staging of paediatric Hodgkin’s lymphoma (HL) (Chapter 3) and determines ADC quantitative thresholds for disease detection (Chapter 4). Following this, a clinical trial of WB-MRI with prospective application of quantitative ADC thresholds for staging and response assessment of paediatric HL is described (Chapter 5). The final 3 chapters describe the WB-MRI studies conducted at 3.0 T – exploring the potential value of higher field strengths, and the reliability of novel quantitative imaging biomarkers for the diagnosis and response assessment of lymphoma and multiple myeloma.
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Rahman, Rifaquat M. "Magnetic Resonance Imaging for Prediction and Assessment of Treatment Response in Bevacizumab-Treated Recurrent Glioblastoma." Thesis, Harvard University, 2014. http://etds.lib.harvard.edu/hms/admin/view/65.

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Glioblastoma is the most common primary brain tumor in adults, and it is associated with a dismal prognosis with a median survival of 15 months. Despite treatment with chemotherapy, radiation therapy and surgery, patients inevitably have disease recurrence. Bevacizumab is a monoclonal humanized antibody that inhibits vascular endothelial growth factor signaling, and it has been shown to be effective in recurrent glioblastoma with respect to prolonging progression-free survival (PFS). The use of bevacizumab and other anti-angiogenic agents in recurrent glioblastoma have created novel challenges in interpreting magnetic resonance imaging (MRI) of patients. Furthermore, since only some patients appear to have a durable benefit from bevacizumab, there is a need for imaging biomarkers that can reliably identify this subgroup of patients. Partly due to the challenges created by anti-angiogenic agents, the Response Assessment in Neuro-Oncology (RANO) was proposed to address some of the limitations with traditional response assessment criteria. In the first part of this project, we attempted to validate the RANO criteria by performing a comparative analysis of the RANO criteria vs. the Macdonald criteria using imaging from the phase II BRAIN trial. As we hypothesized, the RANO criteria yielded a significantly decreased PFS by identifying a subset of patients who had progression of nonenhancing tumor evident on T2-weighted imaging. Additionally, response and progression as defined by the RANO criteria correlated with subsequent overall survival (OS) in landmark analyses. While this supports the implementation of RANO criteria for response assessment in glioma clinical trials, future research will be necessary to further improve response assessment by incorporating advanced techniques such as volumetric anatomic assessment, perfusion-weighted MR (PWI-MR), diffusion-weighted MR (DWI-MR), MR spectroscopy (MRS) and positron emission tomography (PET). Advanced imaging techniques are becoming increasingly recognized for their ability to provide objective, non-invasive assessment of treatment response but also to serve as predictive and prognostic biomarkers allowing for stratification of patient subgroups with better treatment outcome. In the second part of the project, we attempted to perform volumetric analysis of tumor size based on conventional MRI, as well as a histogram analysis of apparent diffusion coefficients (ADC) derived from diffusion-weighted MRI, to evaluate imaging parameters as predictors for PFS and OS in a single institution database of recurrent glioblastoma patients initiated on bevacizumab. Volumetric percentage change and absolute early post-treatment volume (3-6 weeks after initiation) of enhancing tumor can stratify survival for patients with recurrent glioblastoma receiving bevacizumab therapy. ADC histogram analysis using a multi-component curve-fitting technique within both enhancing and nonenhancing components of tumor prior to the initiation of bevacizumab can also be used to stratify OS in recurrent glioblastoma patients. While prospective studies are necessary to validate findings, future studies will increasingly incorporate multiparametric approaches to elucidate biomarkers that combine the value of conventional MRI with advanced techniques such as DWI-MR, PWI-MR, MRS and PET to obtain better predictors for PFS and OS in recurrent glioblastoma.
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Hiscox, Lucy Victoria. "Early characterisation of neurodegeneration with high-resolution magnetic resonance elastography." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31198.

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This thesis contributes to recent interest within medical imaging regarding the development and clinical application of magnetic resonance elastography (MRE) to the human brain. MRE is a non-invasive phase-contrast MRI technique for measurement of brain mechanical properties in vivo, shown to reflect the composition and organisation of the complex tissue microstructure. MRE is a promising imaging biomarker for the early characterisation of neurodegeneration due to its exquisite sensitivity to variation among healthy and pathological tissue. Neurodegenerative diseases are debilitating conditions of the human nervous system for which there is currently no cure. Novel biomarkers are required to improve early detection, differential diagnosis and monitoring of disease progression, and could also ultimately improve our understanding of the pathophysiological mechanisms underlying degenerative processes. This thesis begins with a theoretical background of brain MRE and a description of the experimental considerations. A systematic review of the literature is then performed to summarise brain MRE quantitative measurements in healthy participants and to determine the success of MRE to characterise neurological disorders. This review further identified the most promising acquisition and analysis methods within the field. As such, subsequent visits to three brain MRE research centres, within the USA and Germany, enabled the acquisition of exemplar phantom and brain data to assist in discussions to refine an experimental protocol for installation at the Edinburgh Imaging Facility, QMRI (EIF-QMRI). Through collaborations with world-leading brain MRE centres, two high-resolution - yet fundamentally different - MRE pipelines were installed at the EIF-QMRI. Several optimisations were implemented to improve MRE image quality, while the clinical utility of MRE was enhanced by the novel development of a Graphical User Interface (GUI) for the optimised and automatic MRE-toanatomical coregistration and generation of MRE derived output measures. The first experimental study was performed in 6 young and 6 older healthy adults to compare the results from the two MRE pipelines to investigate test-retest agreement of the whole brain and a brain structure of interest: the hippocampal formation. The MRE protocol shown to possess superior reproducibility was subsequently applied in a second experimental study of 12 young and 12 older cognitively healthy adults. Results include finding that the MRE imaging procedure is very well tolerated across the recruited population. Novel findings include significantly softer brains in older adults both across the global cerebrum and in the majority of subcortical grey matter structures including the pallidum, putamen, caudate, and thalamus. Changes in tissue stiffness likely reflect an alteration to the strength in the composition of the tissue network. All MRE effects persist after correcting for brain structure volume suggesting changes in volume alone were not reflective of the detected MRE age differences. Interestingly, no age-related differences to tissue stiffness were found for the amygdala or hippocampus. As for brain viscosity, no group differences were detected for either the brain globally or subcortical structures, suggesting a preservation of the organisation of the tissue network in older age. The third experiment performed in this thesis finds a direct structure-function relationship in older adults between hippocampal viscosity and episodic memory as measured with verbal-paired recall. The source of this association was located to the left hippocampus, thus complementing previous literature suggesting unilateral hippocampal specialisation. Additionally, a more significant relationship was found between left hippocampal viscosity and memory after a new procedure was developed to remove voxels containing cerebrospinal fluid from the MRE analysis. Collectively, these results support the transition of brain MRE into a clinically useful neuroimaging modality that could, in particular, be used in the early characterisation of memory specific disorders such as amnestic Mild Cognitive Impairment and Alzheimer's disease.
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Royle, Natalie Anne. "Quantifying structural changes in the ageing brain from magnetic resonance imaging." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/15835.

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Understanding the ageing process is of increasing importance to an ageing society and one aspect of this is investigating what role the brain has in this process. Cognitive ability declines as we age and it is one of the most distressing aspects of getting older. Brain tissue deterioration is a significant contributor to lower cognitive ability in late life but the underlying biological mechanisms in the brain are not yet fully understood. One reason for this is the difficulty in obtaining accurate measures of potential ageing-related brain biomarkers. The chapters in this thesis explore the difficulties of quantifying brain changes in the ageing brain from Magnetic Resonance Imaging (MRI), and how the changes identified are related to cognition in later life. The data was acquired as part of the second wave of the longitudinal Lothian Birth Cohort 1936 study in which 866 people aged 73 years, returned for cognitive and medical assessment. At this stage of the study 702 underwent MR imaging resulting in 627 complete datasets across all testing. The entire data, a randomly chosen subset of 150 and 416 freely available data were used to investigate global and regional measurement methods in older brains and how the resultant measurements related to cognitive performance. Furthermore the presence of early life cognitive data in the form of a general intelligence test sat at age 11, served as an indicator of cognitive ability prior to the potential influence of the ageing process. The chapters concerning global measures at first establish, that a measure of intracranial volume (ICV) serves as both a way of correcting for individual differences in brain size between participants and as a proxy premorbid measure of brain size. The analysis, utilising freely available cross-sectional MRI data (http://www.oasis-brains.org) revealed that ICV differed very little between 18-28 year olds and 84-96 year olds where as total brain tissue volume (TBV) differed by 14.1% between the two groups, which was more than twice the standard deviation across the entire age range (18-96 years). Second a validated, reliable method for measuring ICV was investigated using 150 people randomly chosen from the LBC1936 study. Automated and semi-automated methods were validated against reference measurements the results of which showed that common ageing features make automated and semi-automated methods that do not have an additional manual editing step, ineffective at producing accurate ICV measurements. This analysis also highlighted the need to employ additional spatial overlap assessment to volumetric comparison of measurement methods to reduce the effect of false-positives and false-negatives skewing apparent discrepancies between methods. Using the information gained here ICV and TBV from the entire LBC1936 cohort were analysed in a structural equation model, alongside cognitive ability measures at both age 11 and age 73. We found that TBV was a stronger predictor of later life cognitive ability, after accounting for early life ability, but that a modest association remained between ICV and late life cognition. This suggests that early life factors pay a role in how well we age, though the relationship is complex. The regional measures chapters look at two brain regions commonly associated with ageing, the hippocampus and the frontal lobes. Measuring either of these brain regions in large samples of healthy older adults is challenging for many reasons. The hippocampus is small and as with all brain regions shows greater variation in older age, this makes employing automated methods that have the advantage of being fast and reproducible difficult. Following the results of our systematic review of automated methods for measuring the hippocampus, the two most commonly used and available automated methods were validated against reference standard measurements. The results indicated that although automated methods present an attractive alternative to laborious manual measurements they still require manual editing to produce accurate measurements in older adults. The modified strategy employed across the LBC1936 was to use an automated method and then manually edit the output; these segmentations were used to investigate the potential of multimodal image analysis in clarifying associations between the hippocampus and cognitive ability in old age. The analysis focused on associations between longitudinal relaxation time (T1), magnetization transfer ratio (MTR), fractional anisotropy (FA) and mean diffusivity (MD) in the hippocampus and general factors of fluid intelligence, cognitive processing speed and memory. The findings show that multi-modal MRI assessments were more sensitive than volumetric measurements at detecting associations with cognitive measures. The difficulty with producing a relevant frontal lobe measure was made apparent when the result of a large systematic review looking at the manual protocols used revealed 19 methods and 15 different landmarks had been employed. This resulted in an analysis that took the 5 most common boundaries reported and applied them to 10 randomly selected participants from the LBC1936. The results showed significant differences between the resultant volumes, with the smallest measurement when using the genu as the posterior marker representing only 35% of the measurement acquired using the central sulcus. The results from the studies presented in this thesis strongly highlight the need to develop age specific methods when using brain MRI to study ageing. Furthermore the implications of using unstandardised protocols, making assumptions about a methods performance based on validation in younger samples and the need to account for early life factors in this area of research have been made clearer. Studies building on these findings will be beneficial in elucidating the role of the brain in ageing.
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Heise, Verena. "How can magnetoencephalography and magnetic resonance imaging improve our understanding of genetic susceptibility to Alzheimer's disease?" Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:a3c670f3-aef5-4f34-b983-37f21d0019ad.

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The Apolipoprotein E (APOE) ε4 allele is the best-established genetic risk factor for sporadic Alzheimer's disease (AD) while the ε2 allele confers a reduced risk compared with the most common ε3 allele. Neuroimaging studies using magnetic resonance imaging (MRI) have shown that APOE genotype affects brain structure and function. The aims of the research presented in this DPhil thesis were twofold: 1) to investigate the effect of APOE genotype on brain function in healthy adults using magnetoencephalography (MEG), which is a direct measure of neuronal activity and 2) to explore interactions between the AD risk factors APOE ε4 allele, age and female gender and their effects on brain structure and function using resting-state functional MRI and diffusion tensor imaging. MEG revealed similar neuronal activity at rest for APOE ε2 and ε4 carriers, i.e. those with opposite AD risk, indicating a more general effect on the functional architecture of the brain that is not directly linked to AD risk. However, differences between APOE ε2 and ε4 carriers became apparent when reactivity to stimuli was explored using the excellent temporal resolution of MEG. APOE ε4 carriers showed faster sensory pro- cessing and APOE genotype effects were found for functional networks associated with attention. In the second part of this project, female APOE ε4 carriers showed overall significantly reduced functional connectivity between the hippocampus and precuneus and a significant age-related decrease in connectivity of these regions. Increased vulnerability of this connection might be one reason for increased AD risk and interventions targeting hippocampal connectivity might be especially effective in at-risk populations. The research presented in this DPhil thesis showed a complex pattern of APOE genotype effects on brain structure and function. While global APOE genotype effects on functional and structural connectivity do not follow patterns of AD risk, more specific measures of connectivity and task-related brain function could be of use in the development of preclinical markers for AD development.
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Jia, Guang. "MR imaging biomarkers for benign prostatic hyperplasia pharmacotherapy." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1164686290.

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Chaney, Aisling. "Investigating imaging biomarkers of neuroinflammation and neurodegeneration in rodent models of Alzheimer's disease." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/investigating-imaging-biomarkers-of-neuroinflammation-and-neurodegeneration-in-rodent-models-of-alzheimers-disease(16750cf1-eb30-49c5-b9eb-9f01d4a0560f).html.

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Alzheimer’s disease (AD) is a progressive neurodegenerative disease resulting in alterations in memory, language, executive function and emotional behaviour. Although it can be characterised by symptoms, by the time they arise significant pathological alterations have already emerged in the central nervous system, namely increased amyloid plaques, neurofibrillary tangles and neuronal loss. Despite known pathological hallmarks the exact aetiology of AD is poorly understood and no current treatments are available. However, there is growing interest in the role of neuroinflammation in AD, with increases observed in the early stages of disease and with disease progression. Moreover, it has been suggested that peripheral inflammation can influence neuroinflammation and worsen neurodegeneration. Using Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRS) we can non-invasively measure biomarkers of neuroinflammation and degeneration allowing multi-modal investigation of its role in normal aging and AD. Considering this the objectives of this study were to (i) Use PET and MRS to investigate neuroinflammatory and metabolite alterations in transgenic (TG) models of AD and their wildtype (WT) animals. (ii) Assess rates of cognitive decline in these models using memory based tests. (iii) Investigate relatively new TgF344AD rat as an AD model by characterising younger time-points than previously reported. (iv) Investigate the contribution of peripheral inflammation on AD progression. PET and MRS imaging was carried out longitudinally in the APPswe×PS1de9 mouse. Neuroinflammation was confirmed ex vivo and cognitive ability was assessed by behavioural tests. Results revealed significantly increase hippocampal and thalamic neuoinflammation in old TG mice as assessed by [18F]DPA-714 PET and supported by immunohistochemistry. Reduced neuronal marker N-acetlyaspartate was seen with age and was exacerbated in the TG mice. Accelerated cognitive decline was also seen in TG mice. PET and MRS imaging was carried out at 6 and 12 months in the TgF344AD model, which expresses amyloid and tau pathology as well as neuronal loss. No cognitive decline was observed in TG rats; however increased anxiety behaviour was seen. Increased [18F]DPA-714 PET was observed as an effect of gene in the thalamus at 6 months and the hypothalamus at 12 months. Increases in glutamate were seen with age in the TG rats but not the WTs. Increased inflammation and metabolite alterations were seen with aging. The effect of peripheral urinary tract infection (UTI) on cognition and imaging out was assessed. Imaging was carried out prior to and after re-current UTI. Infection induced cognitive decline in infected TG but not WT rats. Infection had an increasing effect on hypothalamic neuroinflammation in WT rats but a decreasing effect on TG rats, which masked the original gene differences. This thesis is set out in the alternative format with each experimental study represented as a chapter. Results in this thesis implicate neuroinflammation in AD development and progression. In addition, we report systemic infection-CNS interactions accelerating cognitive decline in AD and highlight the importance of understanding the effects of comorbidities in disease.
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Wright, Caroline. "Magnetic Resonance Imaging (MRI) biomarkers of placental structure and function in normal and growth restricted pregnancy." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/magnetic-resonance-imaging-mri-biomarkers-of-placental-structure-and-function-in-normal-and-growth-restricted-pregnancy(288b4214-b346-4a31-8bdd-1d4afaf65178).html.

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Fetal growth restriction (FGR) is a serious complication of human pregnancy where the fetus fails to reach its genetically pre-determined growth potential. It is a common condition, affecting 5 -15% of all pregnancies (Gardosi 2009) and is linked to a third of all antepartum deaths (CEMACH 2008). An ongoing problem for obstetricians is the difficulty in diagnosing and predicting FGR and those at highest risk of poor outcomes. Placental insufficiency is a major cause of FGR and specific abnormalities in placental morphology and function occur in this condition; constituting an abnormal FGR placental phenotype (Sibley, Turner et al. 2005). Magnetic Resonance Imaging (MRI) is a powerful tool that allows quantitative analysis of several indices relating to tissue structure and function and, therefore, is of potential use in identifying this phenotype. We hypothesised that a range of MR indices would be feasible in the placenta at 1.5 T, that these indices would be altered in FGR and that there would be correlations with relevant parameters of placental morphology. Ultimately, we aimed to assess whether these indices could be used in the assessment of FGR in utero.Using MRI we estimated placental volume, widths, length and depths in groups of women with normal and FGR pregnancies. We also measured placental relaxation times, T1 and T2, which relate to tissue composition and assessed parameters relating to blood flow using Intra-Voxel Incoherent Motion (IVIM) and Arterial Spin Labelling (ASL). We demonstrated an FGR placental phenotype that was reduced in volume but increased in depth, by around 10mm, with a shorter T2 relaxation time and lower values of D (the diffusion coefficient) measured by IVIM. A trend for reduced perfusion measured by ASL was observed in pregnancies with birthweights less than 10th centile (Gardosi, Chang et al. 1992). T2 and D also correlated with stereological indices of placental morphology.In conclusion, the studies in this thesis illustrate these MRI indices show great potential asbiomarkers for identifying the FGR placenta
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Books on the topic "Magnetic Resonance Imaging Biomarkers"

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Leon, Partain C., ed. Magnetic resonance imaging. 2nd ed. Philadelphia, Pa: Saunders, 1988.

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Prasad, Pottumarthi V., ed. Magnetic Resonance Imaging. Totowa, NJ: Humana Press, 2006. http://dx.doi.org/10.1385/1597450103.

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Zuurbier, Ria, Johan Nahuis, Sija Geers-van Gemeren, José Dol-Jansen, and Tom Dam, eds. Magnetic Resonance Imaging. Houten: Bohn Stafleu van Loghum, 2017. http://dx.doi.org/10.1007/978-90-368-1934-3.

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Sigal, Robert, D. Doyon, Ph Halimi, and H. Atlan. Magnetic Resonance Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73037-5.

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Brown, Robert W., Yu-Chung N. Cheng, E. Mark Haacke, Michael R. Thompson, and Ramesh Venkatesan, eds. Magnetic Resonance Imaging. Chichester, UK: John Wiley & Sons Ltd, 2014. http://dx.doi.org/10.1002/9781118633953.

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Vlaardingerbroek, Marinus T., and Jacques A. den Boer. Magnetic Resonance Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03800-0.

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Vlaardingerbroek, Marinus T., and Jacques A. den Boer. Magnetic Resonance Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05252-5.

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Vlaardingerbroek, Marinus T., and Jacques A. den Boer. Magnetic Resonance Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-03258-9.

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Feigenbaum, Ernest. Magnetic resonance imaging (MRI). Rockville, MD: U.S. Dept. of Health and Human Services, Public Health Service, National Center for Health Services Research and Health Care Technology Assessment, 1985.

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Smith, Robert C. Understanding magnetic resonance imaging. Boca Raton, Fla: CRC Press, 1998.

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Book chapters on the topic "Magnetic Resonance Imaging Biomarkers"

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Tost, Heike, Shabnam Hakimi, and Andreas Meyer-Lindenberg. "Magnetic Resonance Imaging Biomarkers in Schizophrenia Research." In The Handbook of Neuropsychiatric Biomarkers, Endophenotypes and Genes, 123–44. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-9831-4_6.

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Madsen, Per Lav. "Biomarkers of Myocardial Fibrosis in Diabetes, Echocardiography, and Magnetic Resonance Imaging." In Biomarkers in Diabetes, 1–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81303-1_45-1.

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Madsen, Per Lav. "Biomarkers of Myocardial Fibrosis in Diabetes, Echocardiography, and Magnetic Resonance Imaging." In Biomarkers in Diabetes, 821–47. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08014-2_45.

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Holiga, Stefan, Ahmed Abdulkadir, Stefan Klöppel, and Juergen Dukart. "Functional Magnetic Resonance Imaging in Alzheimer’ Disease Drug Development." In Biomarkers for Alzheimer’s Disease Drug Development, 159–63. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7704-8_10.

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Kou, Ph.D., Zhifeng, Randall R. Benson, M.D.,, and E. Mark Haacke, Ph.D. "Chapter 2. Magnetic Resonance Imaging Biomarkers of Mild Traumatic Brain Injury." In Biomarkers for Traumatic Brain Injury, 19–44. Cambridge: Royal Society of Chemistry, 2012. http://dx.doi.org/10.1039/9781849734745-00019.

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Tsarouchi, Marialena I., Georgios F. Vlachopoulos, Anna N. Karahaliou, and Lena I. Costaridou. "Diffusion Weighted Magnetic Resonance Imaging Texture Biomarkers for Breast Cancer Diagnosis." In IFMBE Proceedings, 301–5. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31635-8_36.

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Ramos Delgado, Paula, Ekkehard Küstermann, André Kühne, Jason M. Millward, Thoralf Niendorf, Andreas Pohlmann, and Martin Meier. "Hardware Considerations for Preclinical Magnetic Resonance of the Kidney." In Methods in Molecular Biology, 131–55. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_8.

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AbstractMagnetic resonance imaging (MRI) is a noninvasive imaging technology that offers unparalleled anatomical and functional detail, along with diagnostic sensitivity. MRI is suitable for longitudinal studies due to the lack of exposure to ionizing radiation. Before undertaking preclinical MRI investigations of the kidney, the appropriate MRI hardware should be carefully chosen to balance the competing demands of image quality, spatial resolution, and imaging speed, tailored to the specific scientific objectives of the investigation. Here we describe the equipment needed to perform renal MRI in rodents, with the aim to guide the appropriate hardware selection to meet the needs of renal MRI applications.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This chapter on hardware considerations for renal MRI in small animals is complemented by two separate publications describing the experimental procedure and data analysis.
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Meyer, Sandra, Dieter Fuchs, and Martin Meier. "Ultrasound and Photoacoustic Imaging of the Kidney: Basic Concepts and Protocols." In Methods in Molecular Biology, 109–30. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_7.

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AbstractNoninvasive, robust, and reproducible methods to image kidneys are provided by different imaging modalities. A combination of modalities (multimodality) can give better insight into structure and function and to understand the physiology of the kidney. Magnetic resonance imaging can be complemented by a multimodal imaging approach to obtain additional information or include interventional procedures. In the clinic, renal ultrasound has been essential for the diagnosis and management of kidney disease and for the guidance of invasive procedures for a long time. Adapting ultrasound to preclinical requirements and for translational research, the combination with photoacoustic imaging expands the capabilities to obtain anatomical, functional, and molecular information from animal models. This chapter describes the basic concepts of how to image kidneys using different and most appropriate modalities.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.
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Grist, James T., Esben Søvsø Hansen, Frank G. Zöllner, and Christoffer Laustsen. "Sodium (23Na) MRI of the Kidney: Basic Concept." In Methods in Molecular Biology, 257–66. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_15.

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AbstractThe handling of sodium by the renal system is a key indicator of renal function. Alterations in the corticomedullary distribution of sodium are considered important indicators of pathology in renal diseases. The derangement of sodium handling can be noninvasively imaged using sodium magnetic resonance imaging (23Na MRI), with data analysis allowing for the assessment of the corticomedullary sodium gradient. Here we introduce sodium imaging, describe the existing methods, and give an overview of preclinical sodium imaging applications to illustrate the utility and applicability of this technique for measuring renal sodium handling.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.
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Zöllner, Frank G., Walter Dastrù, Pietro Irrera, Dario Livio Longo, Kevin M. Bennett, Scott C. Beeman, G. Larry Bretthorst, and Joel R. Garbow. "Analysis Protocol for Dynamic Contrast Enhanced (DCE) MRI of Renal Perfusion and Filtration." In Methods in Molecular Biology, 637–53. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_38.

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AbstractHere we present an analysis protocol for dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data of the kidneys. It covers comprehensive steps to facilitate signal to contrast agent concentration mapping via T1 mapping and the calculation of renal perfusion and filtration parametric maps using model-free approaches, model free analysis using deconvolution, the Toft’s model and a Bayesian approach.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concept and experimental procedure.
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Conference papers on the topic "Magnetic Resonance Imaging Biomarkers"

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Nogueira, Cristiana Bello Dultra, João Gustavo dos Anjos Morais Oliveira, and Alexandre Martins Lopes Filho. "The use of biomarkers in Duchenne muscular dystrophy – a literature review." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.330.

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Background: Biomarkers are indicators associated with a disease, used for diagnosis, monitoring progression and prognosis. In Duchenne Muscular Dystrophy (DMD), they are very important. Although the literature describes various types of biomarkers for it, there is no consensus of their appropriate use. Objective: Describe the use of biomarkers associated with DMD. Methods: This literature review used articles searched in PubMed using the formula: (“Duchenne Muscular Dystrophy”) AND (“Biomarkers”). Those that corroborate with the objective of this review were included. Model’s studies and studies that evaluated biomarkers in other diseases were excluded. Results: Cohort and case-control studies propose a staging score that evaluate the infiltration of fat into the muscles and the edema in magnetic resonance imaging (MRI) sequences. Other studies indicate that the relation between volume and cross-sectional can be a prognostic biomarker. Some clinical trials already use these MRI markers to evaluate the effectiveness of their therapies. Creatine Kinase, a serum marker, has been shown in clinical trials to be a good biomarker in diagnosis’ moment. However, due to its low specificity, it is not used in prognosis. In model studies, miRNAs have been shown to be useful in various spheres, and can be used as biomarkers in muscular dystrophies, helping with diagnosis, staging and treatment. Conclusions: The use of biomarkers in DMD is not well defined, for financial reasons and lack of more concrete evidence. Therefore, further studies are needed.
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Kaplan, Ozge Can, Dilek Betul Arslan, Sevim Cengiz, Ani Kıcik, Emel Erdogdu, Gokce Hale Hatay, Zeynep Tufekcioglu, et al. "Determination of Diffusion Weighted Magnetic Resonance Imaging Based Biomarkers of Mild Cognitive Impairment in Parkinson’s Disease." In 2017 21st National Biomedical Engineering Meeting (BIYOMUT). IEEE, 2017. http://dx.doi.org/10.1109/biyomut.2017.8479249.

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Choida, Varvara, Tim Bray, Anna Radziszewska, Corinne Fisher, Coziana Ciurtin, Debajit Sen, and Margaret Hall-Craggs. "AB0950 CORRELATION OF QUANTITATIVE MAGNETIC RESONANCE IMAGING BIOMARKERS AND AXIAL PAIN IN ENTHESITIS-RELATED ARTHRITIS PATIENTS." In Annual European Congress of Rheumatology, EULAR 2019, Madrid, 12–15 June 2019. BMJ Publishing Group Ltd and European League Against Rheumatism, 2019. http://dx.doi.org/10.1136/annrheumdis-2019-eular.7742.

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Cortes, Daniel H., Lachlan J. Smith, Sung M. Moon, Jeremy F. Magland, Alexander C. Wright, and Dawn M. Elliott. "Magnetic Resonance Elastography for the Measurement of Annulus Fibrosus Material Properties." In ASME 2011 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2011. http://dx.doi.org/10.1115/sbc2011-53436.

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Intervertebral disc degeneration is characterized by a progressive cascade of structural, biochemical and biomechanical changes affecting the annulus fibrosus (AF), nucleus pulposus (NP) and end plates (EP). These changes are considered to contribute to the onset of back pain. It has been shown that mechanical properties of the AF and NP change significantly with degeneration [1,2]. Therefore, mechanical properties have the potential to serve as a biomarker for diagnosis of disc degeneration. Currently, disc degeneration is diagnosed based on the detection of structural and compositional changes using MRI, X-ray, discography and other imaging techniques. These methods, however, do not measure directly the mechanical properties of the extracellular matrix of the disc. Magnetic Resonance Elastography (MRE) is a technique that has been used to measure in vivo mechanical properties of soft tissue by applying a mechanical vibration and measuring displacements with a motion-sensitized MRI pulse sequence [3]. The mechanical properties (e.g., the shear modulus) are calculated from the displacement field using an inverse method. Since the applied displacements are in the order of few microns, fibers may not be stretched enough to remove crimping. Therefore, it is unknown if the anisotropy of the AF due to the contribution of the fibers is detectable using MRE. The objective of this study is twofold: to measure shear properties of AF in different orientations to determine the degree of AF anisotropy observable by MRE, and to identify the contribution of different AF constituents to the measured shear modulus by applying different biochemical treatments.
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Beri, Sonali, and Arun Khosla. "ASD Diagnoses using Deep Learning and Neuroimaging as A Biomarker: A Review." In International Conference on Women Researchers in Electronics and Computing. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.114.52.

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Autism Spectrum Disorder (ASD) is a commonly occurring neurodevelopmental disorder characterized by problems occurring in social communication and the presence of restricted and repetitive behavior and interests. Up to now, ASD is being diagnosed considering clinical interview, behavior and developmental factors. Early diagnosis of it can help the autistic people to deal well in their lives. For this early detection different biomarker like Neuro-imaging data can be used which includes structural and functional magnetic resonance imaging. In order to explore the functional and structural differences in between TC and autistic group deep learning methods can be used. These deep learning methods will help in efficient classification and thus can help in autism diagnosis as well. In this paper studies related to various Deep Learning techniques used to diagnose autism are being looked at.
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Tsourkas, Andrew. "Highly Paramagnetic Tumor-Targeted Contrast Agents." In ASME 2010 First Global Congress on NanoEngineering for Medicine and Biology. ASMEDC, 2010. http://dx.doi.org/10.1115/nemb2010-13225.

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The noninvasive imaging of cell surface markers could provide a powerful technique for the early identification of cancer as well as allow for repetitive measurements to monitor the efficacy of therapeutic treatments. Magnetic resonance (MR) is a particularly attractive platform for molecular imaging due to the ability to acquire high-resolution anatomical images in conjunction with measures of biomarker expression; however, the sensitivity of MR contrast agents is often too low to detect the relatively low number of cell receptors per imaging voxel at the targeted site. To generate the level of sensitivity required for imaging molecular markers of disease, novel approaches must be established to amplify the MR signal. In this talk, we will describe how nanoparticulate carriers can be designed to carry extremely high gadolinium (Gd) payloads in order to compensate for the low MR signal enhancement generated by individual Gd ions. Further, we will show that Gd-labeled nanoparticles that have been functionalized with targeting ligands can be used for the highly sensitive detection of human tumor xenografts in mice.
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Lourenço, Rafael, and Marcio Balthazar. "CONECTOME COMPARISON IN MILD COGNITIVE IMPAIRMENT: AD CONTINUUM X SNAP." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda063.

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Background: Studies on functional magnetic resonance imaging of prodromal Alzheimer´s disease can help understanding on how it affects the brain. Objective: We seek for potential differences in brain resting state functional connectivity (FC) of subjects with Mild cognitive impairment with biomarkers: Alzheimer’s disease continuum (MCI-DA) and Suspected non-Alzheimer pathology (MCI-SNAP). Methods: MCI and controls were defined by the Clinical Dementia Rating, neuropsychological measures and cerebrospinal fluid data, resulting in 32 MCI-DA, 25 MCI-SNAP and 35 controls. An analysis ROI-to-ROI was performed inter and intra-networks involving the default mode (DMN), salience (SN), visuospatial (VN) and executive networks. FC was estimated by Pearson’s correlation coefficients converted into Z-Scores. Groups were compared by T tests. Alpha was set to 0.05, FDR correction. Results: Between MCI-DA and controls, intra-network decrease of FC in the SN and inter-network between SN and VN was observed. There was maintenance of the anti-correlation between DMN and VN, which may indicate an indirect dysfunction of the DMN. Between MCI-SNAP and controls, there was an increase in FC between one ROI of DMN and one ROI of VN. Conclusion: MCI-AD showed marked differences in FC compared to MCI-SNAP, mainly in salience network and indirectly in DMN. MCI-SNAP showed milder impairment in resting state networks.
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Marks, SD, F. Nery, M. Cutajar, C. Clark, D. Thomas, and I. Gordon. "21 Renal blood flow measurements by magnetic resonance imaging using arterial spin labelling as a novel non-invasive biomarker in paediatric renal transplant recipients." In Great Ormond Street Hospital Conference. BMJ Publishing Group Ltd and Royal College of Paediatrics and Child Health, 2017. http://dx.doi.org/10.1136/archdischild-2017-084620.46.

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Du, Yaodong, Ming Zhang, Garrett Stonis, and Shan Juan. "Topological Data Analysis on Magnetic Resonance Image Biomarkers." In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2019. http://dx.doi.org/10.1109/bibm47256.2019.8983312.

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Fullerton, Ph.D., Gary D. "Imaging with magnetic resonance." In The fourth mexican symposium on medical physics. AIP, 2000. http://dx.doi.org/10.1063/1.1328942.

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Reports on the topic "Magnetic Resonance Imaging Biomarkers"

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Haacke, E. M. Development of Magnetic Resonance Imaging Biomarkers for Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, July 2013. http://dx.doi.org/10.21236/ada601794.

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Haacke, Ewart M. Development of Magnetic Resonance Imaging Biomarkers for Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada601883.

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Russek, Stephen E. Magnetic Resonance Imaging Biomarker Calibration Service:. Gaithersburg, MD: National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.sp.250-100.

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Boss, Michael A., Andrew M. Dienstfrey, Zydrunas Gimbutas, Kathryn E. Keenan, Anthony B. Kos, Jolene D. Splett, Karl F. Stupic, and Stephen E. Russek. Magnetic resonance imaging biomarker calibration service: proton spin relaxation times. Gaithersburg, MD: National Institute of Standards and Technology, May 2018. http://dx.doi.org/10.6028/nist.sp.250-97.

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Schweizer, M. Developments in boron magnetic resonance imaging (MRI). Office of Scientific and Technical Information (OSTI), November 1995. http://dx.doi.org/10.2172/421332.

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Schmidt, D. M., and M. A. Espy. Low-field magnetic resonance imaging of gases. Office of Scientific and Technical Information (OSTI), November 1998. http://dx.doi.org/10.2172/674672.

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Bronskill, Michael J., Paul L. Carson, Steve Einstein, Michael Koshinen, Margit Lassen, Seong Ki Mun, William Pavlicek, et al. Site Planning for Magnetic Resonance Imaging Systems. AAPM, 1986. http://dx.doi.org/10.37206/19.

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Budakian, Raffi. Nanometer-Scale Force Detected Nuclear Magnetic Resonance Imaging. Fort Belvoir, VA: Defense Technical Information Center, January 2013. http://dx.doi.org/10.21236/ada591583.

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Haslam, Philip. Multiparametric magnetic resonance imaging of the prostate gland. BJUI Knowledge, March 2021. http://dx.doi.org/10.18591/bjuik.0731.

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Schmidt, D. M., J. S. George, S. I. Penttila, and A. Caprihan. Nuclear magnetic resonance imaging with hyper-polarized noble gases. Office of Scientific and Technical Information (OSTI), October 1997. http://dx.doi.org/10.2172/534499.

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