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Статті в журналах з теми "MRI, Diffusion, MEG"

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Lambregts, Doenja M. J., Milou H. Martens, Raymond C. W. Quah, Katerina Nikiforaki, Luc A. Heijnen, Cornelis H. C. Dejong, Geerard L. Beets, Kostas Marias, Nickolas Papanikolaou, and Regina G. H. Beets-Tan. "Whole-liver diffusion-weighted MRI histogram analysis." European Journal of Gastroenterology & Hepatology 27, no. 4 (April 2015): 399–404. http://dx.doi.org/10.1097/meg.0000000000000316.

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Deslauriers-Gauthier, Samuel, Isa Costantini, and Rachid Deriche. "Non–invasive inference of information flow using diffusion MRI, functional MRI, and MEG." Journal of Neural Engineering 17, no. 4 (July 10, 2020): 045003. http://dx.doi.org/10.1088/1741-2552/ab95ec.

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Trojsi, Francesca, Pierpaolo Sorrentino, Giuseppe Sorrentino, and Gioacchino Tedeschi. "Neurodegeneration of brain networks in the amyotrophic lateral sclerosis–frontotemporal lobar degeneration (ALS–FTLD) continuum: evidence from MRI and MEG studies." CNS Spectrums 23, no. 6 (October 27, 2017): 378–87. http://dx.doi.org/10.1017/s109285291700075x.

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Анотація:
Brain imaging techniques, especially those based on magnetic resonance imaging (MRI) and magnetoencephalography (MEG), have been increasingly applied to study multiple large-scale distributed brain networks in healthy people and neurological patients. With regard to neurodegenerative disorders, amyotrophic lateral sclerosis (ALS), clinically characterized by the predominant loss of motor neurons and progressive weakness of voluntary muscles, and frontotemporal lobar degeneration (FTLD), the second most common early-onset dementia, have been proven to share several clinical, neuropathological, genetic, and neuroimaging features. Specifically, overlapping or mildly diverging brain structural and functional connectivity patterns, mostly evaluated by advanced MRI techniques—such as diffusion tensor and resting-state functional MRI (DT–MRI, RS–fMRI)—have been described comparing several ALS and FTLD populations. Moreover, though only pioneering, promising clues on connectivity patterns in the ALS–FTLD continuum may derive from MEG investigations. We will herein overview the current state of knowledge concerning the most advanced neuroimaging findings associated with clinical and genetic patterns of neurodegeneration across the ALS–FTLD continuum, underlying the possibility that network-based approaches may be useful to develop novel biomarkers of disease for adequately designing and monitoring more appropriate treatment strategies.
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Lee, Yun Jeong. "Advanced neuroimaging techniques for evaluating pediatric epilepsy." Clinical and Experimental Pediatrics 63, no. 3 (March 15, 2020): 88–95. http://dx.doi.org/10.3345/kjp.2019.00871.

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Accurate localization of the seizure onset zone is important for better seizure outcomes and preventing deficits following epilepsy surgery. Recent advances in neuroimaging techniques have increased our understanding of the underlying etiology and improved our ability to noninvasively identify the seizure onset zone. Using epilepsy-specific magnetic resonance imaging (MRI) protocols, structural MRI allows better detection of the seizure onset zone, particularly when it is interpreted by experienced neuroradiologists. Ultra-high-field imaging and postprocessing analysis with automated machine learning algorithms can detect subtle structural abnormalities in MRI-negative patients. Tractography derived from diffusion tensor imaging can delineate white matter connections associated with epilepsy or eloquent function, thus, preventing deficits after epilepsy surgery. Arterial spin-labeling perfusion MRI, simultaneous electroencephalography (EEG)-functional MRI (fMRI), and magnetoencephalography (MEG) are noinvasive imaging modalities that can be used to localize the epileptogenic foci and assist in planning epilepsy surgery with positron emission tomography, ictal single-photon emission computed tomography, and intracranial EEG monitoring. MEG and fMRI can localize and lateralize the area of the cortex that is essential for language, motor, and memory function and identify its relationship with planned surgical resection sites to reduce the risk of neurological impairments. These advanced structural and functional imaging modalities can be combined with postprocessing methods to better understand the epileptic network and obtain valuable clinical information for predicting long-term outcomes in pediatric epilepsy.
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Allen, Christopher, Lukas Rier, Lauren Gascoyne, Robert Dineen, Roshan DasNair, Matthew Brookes, and Nikos Evangelou. "164 The role of MEG in assessment and diagnosis in mTBI." Journal of Neurology, Neurosurgery & Psychiatry 93, no. 9 (August 12, 2022): e2.122. http://dx.doi.org/10.1136/jnnp-2022-abn2.208.

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IntroductionThis MRC Confidence in Concept funded study (Clinical Trials reference:NCT03867513) combined magnetoencephalography (MEG) with ultrahigh field 7T MRI, to look for functional and struc- tural abnormalities in mild traumatic brain injury (mTBI).ObjectivesCan those with mTBI be differentiated from non-head injured orthopaedic trauma controls by measuring brain wave activity.MethodsWe scanned 40 participants within two weeks of an emergency department visit and they underwent resting state and task specific MEG followed by 7T MRI including structural, susceptibility, and diffusion sequences. Questionnaire assessment was completed at baseline, three, and six months.ResultsWhilst most individuals with mTBI recover a significant proportion have persistent difficulties. Using a Hidden Markov Model in the mTBI cohort, we were able to demonstrate reduced beta band connec- tivity results from a loss in the temporal coincidence of bursts of activity in spatially distinct regions. This replicates our findings in a distinct sub-acute mTBI cohort. Susceptibility weight imaging revealed only two mTBI participants with microhaemorrhages, their clinical care, markers of injury severity, and recovery did not differentiate them from others in the mTBI cohort.ConclusionsOur results suggests that mTBI may impair the dynamic coordination of neural network activity and this requires further exploration.
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Richards, Todd L. "Functional Magnetic Resonance Imaging and Spectroscopic Imaging of the Brain: Application of fmri and fmrs to Reading Disabilities and Education." Learning Disability Quarterly 24, no. 3 (August 2001): 189–203. http://dx.doi.org/10.2307/1511243.

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This tutorial/review covers functional brain-imaging methods and results used to study language and reading disabilities. Although the main focus is on functional MRI and functional MR spectroscopy, other imaging techniques are discussed briefly such as positron emission tomography (PET), electroencephalography (EEG), magnetoencepholography (MEG), and MR diffusion imaging. These functional brain-imaging studies have demonstrated that dyslexia is a brain-based disorder and that serial imaging studies can be used to study the effect of treatment on functional brain activity.
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Sidiropoulos, Christos, Susan M. Bowyer, Andrew Zillgitt, Peter A. LeWitt, Hassan Bagher-Ebadian, Esmaeil Davoodi-Bojd, Jason M. Schwalb, Richard Rammo, Ellen Air, and Hamid Soltanian-Zadeh. "Multimodal Imaging in a Patient with Hemidystonia Responsive to GPi Deep Brain Stimulation." Case Reports in Neurological Medicine 2017 (2017): 1–4. http://dx.doi.org/10.1155/2017/9653520.

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Background. Dystonia is a syndrome with varied phenomenology but our understanding of its mechanisms is deficient. With neuroimaging techniques, such as fiber tractography (FT) and magnetoencephalography (MEG), pathway connectivity can be studied to that end. We present a hemidystonia patient treated with deep brain stimulation (DBS). Methods. After 10 years of left axial hemidystonia, a 45-year-old male underwent unilateral right globus pallidus internus (GPi) DBS. Whole brain MEG before and after anticholinergic medication was performed prior to surgery. 26-direction diffusion tensor imaging (DTI) was obtained in a 3 T MRI machine along with FT. The patient was assessed before and one year after surgery by using the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS). Results. In the eyes-closed MEG study there was an increase in brain coherence in the gamma band after medication in the middle and inferior frontal region. FT demonstrated over 50% more intense ipsilateral connectivity in the right hemisphere compared to the left. After DBS, BFMDRS motor and disability scores both dropped by 71%. Conclusion. Multimodal neuroimaging techniques can offer insights into the pathophysiology of dystonia and can direct choices for developing therapeutics. Unilateral pallidal DBS can provide significant symptom control in axial hemidystonia poorly responsive to medication.
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Kamada, Kyousuke, Kiyohiro Houkin, Fumiya Takeuchi, Nobuaki Ishii, Jun Ikeda, Yutaka Sawamura, Shinya Kuriki, Kawaguchi, and Yoshinobu Iwasaki. "Visualization of the eloquent motor system by integration of MEG, functional, and anisotropic diffusion-weighted MRI in functional neuronavigation." Surgical Neurology 59, no. 5 (May 2003): 352–60. http://dx.doi.org/10.1016/s0090-3019(03)00018-1.

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Renga, Vijay. "Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis." Neurology Research International 2022 (February 7, 2022): 1–20. http://dx.doi.org/10.1155/2022/1838682.

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Анотація:
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no effective treatment or cure. ALS is characterized by the death of lower motor neurons (LMNs) in the spinal cord and upper motor neurons (UMNs) in the brain and their networks. Since the lower motor neurons are under the control of UMN and the networks, cortical degeneration may play a vital role in the pathophysiology of ALS. These changes that are not apparent on routine imaging with CT scans or MRI brain can be identified using modalities such as diffusion tensor imaging, functional MRI, arterial spin labelling (ASL), electroencephalogram (EEG), magnetoencephalogram (MEG), functional near-infrared spectroscopy (fNIRS), and positron emission tomography (PET) scan. They can help us generate a representation of brain networks and connectivity that can be visualized and parsed out to characterize and quantify the underlying pathophysiology in ALS. In addition, network analysis using graph measures provides a novel way of understanding the complex network changes occurring in the brain. These have the potential to become biomarker for the diagnosis and treatment of ALS. This article is a systematic review and overview of the various connectivity and network-based studies in ALS.
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Aqil, Marco, Selen Atasoy, Morten L. Kringelbach, and Rikkert Hindriks. "Graph neural fields: A framework for spatiotemporal dynamical models on the human connectome." PLOS Computational Biology 17, no. 1 (January 28, 2021): e1008310. http://dx.doi.org/10.1371/journal.pcbi.1008310.

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Tools from the field of graph signal processing, in particular the graph Laplacian operator, have recently been successfully applied to the investigation of structure-function relationships in the human brain. The eigenvectors of the human connectome graph Laplacian, dubbed “connectome harmonics”, have been shown to relate to the functionally relevant resting-state networks. Whole-brain modelling of brain activity combines structural connectivity with local dynamical models to provide insight into the large-scale functional organization of the human brain. In this study, we employ the graph Laplacian and its properties to define and implement a large class of neural activity models directly on the human connectome. These models, consisting of systems of stochastic integrodifferential equations on graphs, are dubbed graph neural fields, in analogy with the well-established continuous neural fields. We obtain analytic predictions for harmonic and temporal power spectra, as well as functional connectivity and coherence matrices, of graph neural fields, with a technique dubbed CHAOSS (shorthand for Connectome-Harmonic Analysis Of Spatiotemporal Spectra). Combining graph neural fields with appropriate observation models allows for estimating model parameters from experimental data as obtained from electroencephalography (EEG), magnetoencephalography (MEG), or functional magnetic resonance imaging (fMRI). As an example application, we study a stochastic Wilson-Cowan graph neural field model on a high-resolution connectome graph constructed from diffusion tensor imaging (DTI) and structural MRI data. We show that the model equilibrium fluctuations can reproduce the empirically observed harmonic power spectrum of resting-state fMRI data, and predict its functional connectivity, with a high level of detail. Graph neural fields natively allow the inclusion of important features of cortical anatomy and fast computations of observable quantities for comparison with multimodal empirical data. They thus appear particularly suitable for modelling whole-brain activity at mesoscopic scales, and opening new potential avenues for connectome-graph-based investigations of structure-function relationships.
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Дисертації з теми "MRI, Diffusion, MEG"

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Philippe, Anne-Charlotte. "Régularisation du problème inverse MEG par IRM de diffusion." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00939159.

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La magnéto-encéphalographie (MEG) mesure l'activité cérébrale avec un excellent décours temporel mais sa localisation sur la surface corticale souffre d'une mauvaise résolution spatiale. Le problème inverse MEG est dit mal-posé et doit de ce fait être régularisé. La parcellisation du cortex en régions de spécificité fonctionnelle proche constitue une régularisation spatiale pertinente du problème inverse MEG. Nous proposons une méthode de parcellisation du cortex entier à partir de la connectivité anatomique cartographiée par imagerie de diffusion. Au sein de chaque aire d'une préparcellisation, la matrice de corrélation entre les profils de connectivité des sources est partitionnée. La parcellisation obtenue est alors mise à jour en testant la similarité des données de diffusion de part et d'autre des frontières de la préparcellisation. C'est à partir de ce résultat que nous contraignons spatialement le problème inverse MEG. Dans ce contexte, deux méthodes sont développées. La première consiste à partitionner l'espace des sources au regard de la parcellisation. L'activité corticale est alors obtenue sur un ensemble de parcelles. Afin de ne pas forcer les sources à avoir exactement la même intensité au sein d'une parcelle, nous développons une méthode alternative introduisant un nouveau terme de régularisation qui, lorsqu'il est minimisé, tend à ce que les sources d'une même parcelle aient des valeurs de reconstruction proches. Nos méthodes de reconstruction sont testées et validées sur des données simulées et réelles. Une application clinique dans le cadre du traitement de données de sujets épileptiques est également réalisée.
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PASQUINI, JACOPO. "Multimodal Magnetic Resonance Imaging for the identification of early Multiple System Atrophy biomarkers." Doctoral thesis, Università degli Studi di Milano, 2022. http://hdl.handle.net/2434/890787.

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Background. Multiple system atrophy (MSA) is a rare, sporadic disease characterized by autonomic failure and a various combination of parkinsonism and cerebellar dysfunction. Currently, development of new treatment strategies in MSA is hampered by the lack of reliable diagnostic and disease-progression biomarkers. The aim of this study was to investigate brain microstructural abnormalities in MSA through diffusion and neuromelanin-sensitive magnetic resonance imaging (MRI) and their relationship with clinical manifestations. Methods. Clinical evaluation and MRI were performed on 11 MSA patients, 19 Parkinson’s Disease (PD) and 18 healthy controls (HC). MRI scans included structural, diffusion (dMRI) and neuromelanin-sensitive sequences. dMRI was applied through a novel technique, neurite orientation dispersion and density imaging (NODDI). Compared to previous dMRI techniques, NODDI allows the simultaneous evaluation of the integrity of the intracellular and extracellular compartments, while gathering information on the orientation of axons and dendrites. Neuromelanin-sensitive MRI was used to quantitively investigate the integrity of substantia nigra (SN) and locus coeruleus (LC). Results. Median duration of symptoms in MSA patients was 3 years (range 1-6). Age was not significantly different across subgroups. Compared to PD, MSA patients had reduced neurite density index (NDI) in the middle cerebellar peduncle (MCP) and in the pons (Mann-Whitney U=44.0, p=0.019 and U=52.0, p=0.050), indicating white matter degeneration in these locations, and increased free water fraction (FWF), indicating grey matter loss, in the putamen, caudate and cerebellar lobule VI grey matter (U=146.0, p=0.019; U=145.0, p=0.021; U=154.0, p=0.006 respectively). Neuromelanin content was not different in SN and LC between PD and MSA, although this was reduced in the posterior SN and intermediate part of LC compared to HCs (Kruskal Wallis H=11.363, p=0.003 and H=13.788, p=0.001), indicating similar, significant degeneration of these nuclei in both conditions. No significant correlations were found between motor scores and MRI parameters in the SN, putamen, and MCP and pons. LC neuromelanin loss in the rostral and/or intermediate sections was significantly associated with greater cognitive, depressive and REM sleep behaviour disorder (RBD) symptoms scores in MSA. Symptoms of dysautonomia were not associated with diffusion or neuromelanin content measures. Conclusion. Multimodal MRI with diffusion and neuromelanin evaluation may help define structural abnormalities in the early stages of MSA. NODDI seems a promising technique to simultaneously evaluate multiple microstructural parameters in critical locations of MSA pathology, such as the basal ganglia, cerebellum, and pons. Neuromelanin content evaluation is useful for defining SN and LC degeneration, although this occurs similarly in MSA and PD. In MSA, LC degeneration is associated with greater depressive, cognitive and RBD symptoms. Longitudinal investigations are needed to establish whether these MRI parameters may serve as disease-progression biomarkers.
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LAPUCCI, CATERINA. "ADVANCED SUSCEPTIBILITY AND DIFFUSION WEIGHTED IMAGING IN THE DIAGNOSIS OF MULTIPLE SCLEROSIS: FROM RESEARCH TO CLINICAL APPLICATIONS." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1088218.

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Rational and Objectives In 2015, the Institute of Medicine described the need to study the phenomenon of misdiagnosis as a “moral, professional, and public health imperative”. Despite the periodic updates of diagnostic criteria for MS, the risk of diagnosing as having MS patients with other disease involving the Central Nervous System (CNS) remains still not negligible. Indeed, diagnosis of MS may be straightforward, but a rapid and accurate diagnosis of MS can also be an issue, particularly due to the lack of specific biomarkers. Alongside developments that enabled earlier diagnosis of MS, the introduction of disease-modifying therapies (DMTs) for MS provided increasing evidence that earlier treatment is associated with better long-term outcomes. This evidence leads to an increasing pressure for the physician to make a diagnosis of MS as early as possible. This pressure, in turn, creates a tension between the benefits of an early MS diagnosis and the risk of an inaccurate diagnosis that may cause serious, sometimes life-threatening, health and financial consequences. Among MS mimics, migraine (alone or in combination with additional diagnoses) has been reported as the most common alternative diagnosis in patients misdiagnosed with MS (reported in 22% of misdiagnosed patients). Interestingly, in the patients with migraine, it was reported that often migraineurs symptoms mistaken for demyelinating attacks were incorrectly used to satisfy Dissemination in Time (DIT) criteria for MS. On the other side, migraine-associated white matter (WM) hyperintensity were often considered in the fulfilment of Dissemination in Space (DIS) imaging criteria for MS. Nevertheless, the differential diagnosis between MS and its mimics is not the only challenge. In a treatment era when also the only evidence of radiological disease activity in clinically stable patients may be the trigger to escalate MS therapy, the presence of comorbidities in a patient with MS introduces an extra challenge, represented by the need to distinguish whether a new T2 lesion is due to MS or to comorbidities. The high prevalence of small vessel disease (SVD)-related white matter hyperintensities in people over 50 years of migraine in general population including MS patients and the similar features shared with MS in conventional MRI sequences regardless of their different histopathological substrates, makes this issue not negligible. The identification of specific and sensitive biomarkers able to distinguishes MS from other diseases represent an unmet need. Several cerebrospinal fluid and serum biomarkers of MS have been studied, but no tests with high specificity and sensitivity are now available. Another issue is represented by the fact that many proposed biomarkers have only been explored in the context of cross-sectional studies, while their longitudinal evaluation is essential. As concerns MRI biomarkers, the “Central Vein Sign” inside WM lesions has been proposed as a very promising biomarker of inflammatory demyelination and, thus, may aid the diagnosis of MS and differentiation from its mimics. On the other hand, multi-compartments diffusion models have been demonstrated their potential in investigating tissue abnormalities inside MS lesions and Normal Appearing White Matter (NAWM), as demyelination, fibre loss and axonal degeneration. The work described in this thesis aimed at investigating the application of the Central Vein Sign detected on advanced susceptibility weighted images to differentiate MS from migraine and then, at applying the Central Vein Sign associated with advanced diffusion weighted images, to explore the impact of ageing and comorbidities on WM lesions architecture in MS. Overview of the Thesis • Chapter 2 includes a description of multiple sclerosis, with a final focus on MS mimics and their challenging differentiation from MS. • In the chapter 2 an overview of the state of the art of advanced susceptibility and diffusion weighted imaging methods used to investigate brain structure is provided, together with a summary of previous studies that used these techniques in MS. • In the chapter 3 the first study, aiming at investigating the performance of the Central Vein Sign (CVS) in the differential diagnosis between MS and migraine is described. • The chapter 4 illustrates the second study, exploring the performance of the CVS and spherical Mean Technique (SMT) model in differentiating MS lesions from white matter hyperintensities related to ageing, concomitant small vessel disease and migraine in a cohort of patients with MS. The chapters 3 and 4 contain sections including the background, aims, methods and discussion specific for each study.
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PIAGGIO, NICCOLO'. "MICROSTRUCTURAL WHITE MATTER PROPERTIES IN MULTIPLE SCLEROSIS: ANATOMICAL SPATIAL MAPPING VIA NODDI MODELLING TO BETTER UNDERSTAND THE MECHANISM OF INJURY." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1046511.

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Introduction. Plenty of literature focused on the topography of multiple sclerosis (MS) injury localization within brain. Various theories were proposed to explain this pattern, calling into question two main hypothesis: 1- preexistent tissue-intrinsic microstructural susceptibility factors 2- cerebrospinal-fluid (CSF)-borne soluble inflammatory factors diffusing through the brain surfaces (inner-ependymal-ventricular and outer-pial-cortical), thence affecting the parenchyma with a decreasing distribution along a distance-from-CSF gradient. However, despite more than one hundred years of efforts, the etio-physio-pathological basis of the onset and development of the MS plaque has not been completely unveiled yet. Recent technological advances in magnetic resonance imaging (MRI) and data post-processing, enabling an in-vivo definition of the local microstructure of the white matter (WM), give new perspectives for untangling the secrets of this complex disease. Materials & Methods. With a novel algorithm to analyze diffusion weighted MRI images, “NODDI”, we created detailed atlases of the microstructural characteristics of the normal WM in a healthy population; parallelly, we defined the topography of the lesions for a MS-affected population. By superposition of the patients lesion maps onto the healthy atlas, we could then test if any of the microstructural NODDI parameters is predictive of development of a T1-visible lesion. We then tested at which deepness of the gradient of distance from CSF, the a-priori microstructural susceptibility factor was more responsible of the T1-visible lesion development. Finally, we computed the mean distance from the CSF of the T1-lesioned tissue, compared to the T1-spared one. Results. In the corresponding areas where the patients developed T1-visible lesions, we found significant higher values of Neurite Density (ND) on the healthy population atlas, if compared to the areas where no lesion was visible on T1 imaging. The a-priori tissue property of high ND was found to have its greatest influence on T1-visible lesion formation especially in the deep WM layer (the furthest from the pial and ventricular surfaces). The NODDI microstructural parameter Orientation Dispersion Index (ODI) showed to have no influence at any level on the tissue proneness to develop a T1-visible lesion. The average distance of the T1-lesioned tissue from the ventricles was higher than the one of the T1-spared tissue. Conclusion. Our results suggest that an higher density of neurites seem to play a role on the probability of development of a T1-visible WM lesion in MS, while the orientation dispersion of the axons does not appear to have any impact on these pathological events. An higher coherence and compactness of structure in the myelin-rich WM areas could constitute a facilitating factor for the auto-inflammatory immune process against myelin antigens. It is interesting to see that this effect, which appears already significant when considered the whole brain, looks to be even more prominent in the “deep WM layer”, which is the furthest-from-CSF part of WM. Conversely, the lesion-promoting effect of high ND seems to be attenuated or neutralized in the WM layers neighboring the CSF: this fact brings to speculate the existence of some underlying interaction between inflammatory soluble factors and tissue structure, at different WM deepness levels.
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Marizzoni, M. "DEVELOPMENT OF IMAGING MARKERS TO TRACK ALZHEIMER¿S DISEASE PROGRESSION IN HUMANS AND MOUSE MODELS." Doctoral thesis, Università degli Studi di Milano, 2013. http://hdl.handle.net/2434/217458.

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La Malattia di Alzheimer (AD) è la forma più comune di demenza nella popolazione anziana e affligge più 35 milioni di persone nel mondo. Ad oggi, le uniche terapie approvate per la sua cura sono dirette a ridurre i sintomi. Lo sviluppo di nuovi farmaci è lungo e costoso. Il processo di scoperta è arduo in quanto i trial clinici coinvolgono un ampio campione di pazienti e implicano dei follow-up troppo lunghi. Inoltre il valore predittivo dei modelli sperimentali è limitato a causa della mancanza di marcatori omologhi nell’uomo e nei modelli animali. Questo lavoro si inserisce in Pharmacog, un progetto europeo che vede la collaborazione di università ed industrie allo scopo di identificare biomarcatori affidabili e sensibili alla progressione di malattia in pazienti affetti da decadimento cognitivo lieve (MCI) e modelli animali di AD allo scopo di colmare il vuoto tra risultati clinici e preclinici. Nell’uomo, i marcatori di neuroimmagine sono tra i più promettenti candidati nel tracciare la progressione di malattia. Innovazioni nelle tecniche di risonanza magnetica (MRI) rendono possibile l’identificazione di marcatori omologhi nell’uomo e nel topo. Prima dello studio di neuroimmagine nei pazienti MCI, è necessario verificare che eventuali cambiamenti individuati siano dovuti all’effettiva progressione di malattia e non causati dalla variabilità intra e tra i diversi scanner utilizzati nel progetto. Il primo scopo di questo lavoro è lo studio dei cambiamenti morfometrici e di diffusione in tre diversi modelli murini di Malattia Alzheimer (TASTPM, TauPS2APP e PDAPP da 3 a 22 mesi) tramite l’utilizzo di tecniche MRI. A nove mesi abbiamo trovato una significativa riduzione rispetto ai controlli del volume del caudato-putamen e della corteccia frontale nei TASTPM e nei TauPS2APP (p< 0.001). L’assottigliamento della corteccia entorinale era significativo alla stessa età in tutte e tre i modelli (p< 0.001). Abbiamo inoltre individuato delle anormalità dipendenti dall’età anche in diverse regione di sostanza bianca. Quelle più precoci erano nella commissura anteriore e nel corpo calloso dei TASTPM di 13 mesi (p< 0.001). I danni dei TASTPM sono associabili al pesante carico di amiloide ed alla marcata attivazione della glia e degli astrociti. Il secondo scopo dello studio è la valutazione e la comparazione della riproducibilità di misure volumetriche e di spessore tra test e retest ottenute utilizzando due diversi metodi di processazione esistenti (Freesurfer sulla singola acquisizione o Freesurfer longitudinale). Inoltre abbiamo saggiato la riproducibilità di un’analisi per le immagini di diffusione messa a punto nel nostro laboratorio. A questo scopo ognuno degli otto centri europei coinvolti nel progetto e con diversi scanner a 3T ha arruolato un gruppo di 5 volontari sani e anziani sottoponendoli a 2 acquisizioni di risonanza ad almeno una settimana di distanza l’una dall’altra. Abbiamo trovato che la variabilità intra e tra i diversi centri nei volumi estratti da queste acquisizioni era inferiore al 3% per le strutture più grandi (come il talamo) e minore del 6% per quelle più piccole (es. amigdala). La variabilità degli spessori era meno del 6% e le variazioni dei parametri di diffusione erano prevalentemente nell’intervallo del 2-3%. In conclusione, abbiamo identificato nei modelli analizzati dei marcatori di immagine sensibili alla progressione dell’AD simili a quelli visti nell’uomo e questo apre la strada al possibile utilizzo di una “distintiva collezione” di marcatori murini di immagine nei trial clinici. I dati collezionati nella parte umana mostrano un più altra riproducibilità dei risultati morfometrici ottenuti con l’analisi longitudinale rispetto a quella sulla singola acquisizione (p< 0.01). Infine, abbiamo dimostrato che l’analisi delle immagini di diffusione messa a punto nel nostro laboratorio dà risultati ugualmente riproducibili a quelli riportati in letteratura.
Alzheimer’s disease (AD) is the most common form of dementia in elderly population, affecting more than 35 million people worldwide. To date, the only approved therapies for AD focus on symptomatic relief. The development of new therapeutic agents is time consuming and costly. Drug discovery process is arduous because clinical trials are currently involving too wide sample of patients and long follow-up. Moreover, the predicting value of experimental models used nowadays is limited due to the lack of homologous markers in humans and animals. This work is a branch of Pharmacog, an industry-academic European project aimed at identifying reliable biomarkers that are sensitive to disease progression in patients with Mild Cognitive Impairment (MCI) and in AD animal models in order to bridge the gap between preclinical and clinical outcomes. Human neuroimaging markers are among the most promising candidates to track disease progression. In addition, advanced magnetic resonance imaging (MRI) allow the identification of homologous biomarkers in humans and mice. Prior to investigate neuroimaging biomarkers on MCI patients, we have to test that there is no significant effect of within and across MRI sites variability on brain AD-related longitudinal changes. The first aim of this work is the study of the morphometric and diffusion changes in three different AD mouse model (TASTPM, TauPS2APP and PDAPP from 3 to 22 months of age) through MRI. We found significant volume reduction starting at 9 months in the caudate-putamen and frontal cortex of TASTPM and TauPS2APP (p< 0.001) compared to non transgenic mice. The decrease in the enthorinal cortex thickness was significantly lower in all the strains (p< 0.001). We also found age-related diffusion abnormalities in different white matter regions of TASTPM. The earlier changes were found in the corpus callosum and anterior commissure of 13 months old mice (p< 0.001). In TASTPM, deficits detected with MRI are related to heavy amyloid pathology, marked gliosis and astrocitosys. The second aim of this study is the evaluation and comparison of test-retest reproducibility of brain volumes and thicknesses by two existing Freesurfer pipelines (longitudinal and cross-sectional). Moreover, we assessed the reliability of a diffusion pipeline developed in our lab. Eight different 3T MRI sites in Europe enrolled a group of 5 healthy elderly subjects scanned twice at least a week apart. We found that the within and across sites variability of volumes was less than 3% for larger brain structures (such as thalamus) and less than 6% for smaller regions (i.e., hippocampus). The thickness variability was less than 6% and diffusion indices variations were mostly within the range 2-3%. In conclusion, the present data identify imaging biomarkers of disease progression in mice similar to that seen in humans and pave the way of a murine “imaging signature” usefulness in clinical trials. Human data show significantly higher reproducibility of brain morphometry using the longitudinal pipeline than using the cross-sectional one (p< 0.01). Finally, we demonstrated that the reliability of the analysis of brain diffusion we implemented in our lab is comparable to data reported in the literature.
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6

Silvia, Obertino. "Studying brain connectivity: a new multimodal approach for structure and function integration ​." Doctoral thesis, 2019. http://hdl.handle.net/11562/995190.

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Il cervello è un sistema che integra organizzazioni anatomiche e funzionali. Negli ultimi dieci anni, la comunità neuroscientifica si è posta la domanda sulla relazione struttura-funzione. Essa può essere esplorata attraverso lo studio della connettività. Nello specifico, la connettività strutturale può essere definita dal segnale di risonanza magnetica pesato in diffusione seguito dalla computazione della trattografia; mentre la correlazione funzionale del cervello può essere calcolata a partire da diversi segnali, come la risonanza magnetica funzionale o l’elettro-/magneto-encefalografia, che consente la cattura del segnale di attivazione cerebrale a una risoluzione temporale più elevata. Recentemente, la relazione struttura-funzione è stata esplorata utilizzando strumenti di elaborazione del segnale sui grafi, che estendono e generalizzano le operazioni di elaborazione del segnale ai grafi. In specifico, alcuni studi utilizzano la trasformata di Fourier applicata alla connettività strutturale per misurare la decomposizione del segnale funzionale in porzioni che si allineano (“aligned”) e non si allineano (“liberal”) con la sottostante rete di materia bianca. Il relativo allineamento funzionale con l’anatomia è stato associato alla flessibilità cognitiva, sottolineando forti allineamenti di attività corticali, e suggerendo che i sistemi sottocorticali contengono più segnali liberi rispetto alla corteccia. Queste relazioni multimodali non sono, però, ancora chiare per segnali con elevata risoluzione temporale, oltre ad essere ristretti a specifiche zone cerebrali. Oltretutto, al giorno d'oggi la ricostruzione della trattografia è ancora un argomento impegnativo, soprattutto se utilizzata per l'estrazione della connettività strutturale. Nel corso dell'ultimo decennio si è vista una proliferazione di nuovi modelli per ricostruire la trattografia, ma il loro conseguente effetto sullo strumento di connettività non è ancora chiaro. In questa tesi, ho districato i dubbi sulla variabilità dei trattogrammi derivati da diversi metodi di trattografia, confrontandoli con un paradigma di test-retest, che consente di definire la specificità e la sensibilità di ciascun modello. Ho cercato di trovare un compromesso tra queste, per definire un miglior metodo trattografico. Inoltre, ho affrontato il problema dei grafi pesati confrontando alcune possibili stime, evidenziando la sufficienza della connettività binaria e la potenza delle proprietà microstrutturali di nuova generazione nelle applicazioni cliniche. Qui, ho sviluppato un modello di proiezione che consente l'uso dei filtri aligned e liberal per i segnali di encefalografia. Il modello estende i vincoli strutturali per considerare le connessioni indirette, che recentemente si sono dimostrate utili nella relazione struttura-funzione. I risultati preliminari del nuovo modello indicano un’implicazione dinamica di momenti più aligned e momenti più liberal, evidenziando le fluttuazioni presenti nello stato di riposo. Inoltre, viene presentata una relazione specifica di periodi più allineati e liberali per il paradigma motorio. Questo modello apre la prospettiva alla definizione di nuovi biomarcatori. Considerando che l’encefalografia è spesso usata nelle applicazioni cliniche, questa integrazione multimodale applicata su dati di Parkinson o di ictus potrebbe combinare le informazioni dei cambiamenti strutturali e funzionali nelle connessioni cerebrali, che al momento sono state dimostrate individualmente.
The brain is a complex system of which anatomical and functional organization is both segregated and integrated. A longstanding question for the neuroscience community has been to elucidate the mutual influences between structure and function. To that aim, first, structural and functional connectivity need to be explored individually. Structural connectivity can be measured by the Diffusion Magnetic Resonance signal followed by successive computational steps up to virtual tractography. Functional connectivity can be established by correlation between the brain activity time courses measured by different modalities, such as functional Magnetic Resonance Imaging or Electro/Magneto Encephalography. Recently, the Graph Signal Processing (GSP) framework has provided a new way to jointly analyse structure and function. In particular, this framework extends and generalizes many classical signal-processing operations to graphs (e.g., spectral analysis, filtering, and so on). The graph here is built by the structural connectome; i.e., the anatomical backbone of the brain where nodes represent brain regions and edge weights strength of structural connectivity. The functional signals are considered as time-dependent graph signals; i.e., measures associated to the nodes of the graph. The concept of the Graph Fourier Transform then allows decomposing regional functional signals into, on one side, a portion that strongly aligned with the underlying structural network (“aligned"), and, on the other side, a portion that is not well aligned with structure (“liberal"). The proportion of aligned-vs-liberal energy in functional signals has been associated with cognitive flexibility. However, the interpretation of these multimodal relationships is still limited and unexplored for higher temporal resolution functional signals such as M/EEG. Moreover, the construction of the structural connectome itself using tractography is still a challenging topic, for which, in the last decade, many new advanced models were proposed, but their impact on the connectome remains unclear. In the first part of this thesis, I disentangled the variability of tractograms derived from different tractography methods, comparing them with a test-retest paradigm, which allows to define specificity and sensitivity of each model. I want to find the best trade-off between specificity and sensitivity to define the best model that can be deployed for analysis of functional signals. Moreover, I addressed the issue of weighing the graph comparing few estimates, highlighting the sufficiency of binary connectivity, and the power of the latest-generation microstructural properties in clinical applications. In the second part, I developed a GSP method that allows applying the aligned and liberal filters to M/EEG signals. The model extends the structural constraints to consider indirect connections, which recently demonstrated to be powerful in the structure/function link. I then show that it is possible to identify dynamic changes in aligned-vs-liberal energy, highlighting fluctuations present motor task and resting state. This model opens the perspective of novel biomarkers. Indeed, M/EEG are often used in clinical applications; e.g., multimodal integration in data from Parkinson’s disease or stroke could combine changes of both structural and functional connectivity.
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7

CAPORALE, ALESSANDRA. "A novel mechanism of contrast in MRI: pseudo super-diffusion of water molecules unveils microstructural details in biological tissues." Doctoral thesis, 2017. http://hdl.handle.net/11573/942463.

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The goal of this work is to investigate the properties of the contrast provided by Anomalous Diffusion (AD) γ-imaging technique and to test its potential in detecting tissue microstructure. The collateral purpose is to implement this technique by optimizing data acquisition and data processing, with the long term perspective of adoption in massive in vitro, in vivo and clinical studies. The AD γ-imaging technique is a particular kind of Diffusion Weighted- Magnetic Resonance Imaging (DW-MRI). It represents a refinement of conventionally used DW-MRI methods, sharing with them the advantage of being non invasive, since it uses water as an endogenous contrast agent. Besides, it is more suitable to the study of complex tissues, because it is based on a theoretical model that overcomes the simplistic Gaussian assumption. While the Gaussian assumption predicates the linearity between the average molecular displacement of water and the diffusing time, as in case of diffusion in isotropic, homogeneous and infinite environments, a number of experiments performed in vitro and in vivo on both animals and humans showed an anomalous behavior of water molecules, with a non linear relation between the distance travelled and the elapsed time. In particular, the γ-parameter quantifies water pseudo super-diffusion, a peculiarity due to the fact that water diffusion occurs in multi-compartments and it is probed by means of MRI. In fact, a restricted diffusion is rather predicted for water diffusing in biological tissues. Recently, the trick that allows to make the traditional DW-MRI acquisition sequence suitable for pseudo super-diffusion quantification has been unveiled, and in short it consists in performing DW experiments varying the diffusion gradient strengths, at a constant diffusive time. The γ-parameter is extracted by fitting DW-data to a stretched-exponential function. Finally, probing water diffusion in different directions allows to reconstruct a γ-tensor, with scalar invariants that quantify the entity of AD and its anisotropy in a given volume element. In vitro results on inert materials revealed that γ correlates with internal gradients arising from magnetic susceptibility differences (Δ) between neighboring compartments, and that it reflects the multi-compartmentalization of the space explored by diffusing molecules. Furthermore, values of γ compatible with a description of super-diffusive motion were found. This anomaly can be explained considering that the presence of Δ induce an additional attenuation to the signal, simulating a pseudo super-diffusion. Finally, In vivo results on human brain showed that γ is more effective in discriminating among different brain regions compared to conventional DWMRI parameters. These studies suggest that the contrast provided by AD γ-imaging is influenced by an interplay of two factors, Δ -effects on one hand, multicompartmentalization on the other hand, through which γ could reflect tissue microstructure. With the aim to shed some light on this issue I performed AD γ-imaging in excised mouse spinal cord (MSC) at 9.4 T and healthy human brain at 3.0 T. The adoption of MSC was motivated by its current use in studies of demyelination due to an induced pathology that mimics Multiple Sclerosis alterations, and by its simplified geometry. I acquired DW-data with parameters optimized for the particular system chosen: the MSC was scanned along 3 orthogonal directions, thus an apparent γ was derived; for the in vivo studies I used more directions and I extracted a γ-tensor. I found that γ and its anisotropy reflected the microstructure of spinal cord tracts (such as the axon diameters and the axonal density). I investigated both in MSC and human brain the relation between γ and the rate of relaxation (R2*), a parameter well-known to reflect Δ, and found significant linear correlations. Because of this γ was able to differentiate white matter regions on the basis of their spatial orientation, and gray matter regions on the basis of their intrinsic iron content in human brain imaged at 3.0 T. These results suggest that AD γ-imaging could be an alternative or complementary technique to DW-MRI in the field of neuroscience. Indeed it could be useful for the assessment of the bulk susceptibility inhomogeneity, which reflects iron deposition, the hallmark of several neurodegenerative diseases. The part of this thesis work concerning the in vivo experiment in human brain gave rise to a paper published on NeuroImage, a relevant scientific journal in the field of MRI applied to brain investigation.
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8

HUANG, XIU-WEN, and 黃綉紋. "Research on Electronic word-of-mouth diffusion path of social marketing: A Case Study of I-MEI Milk Tea." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/9jr729.

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碩士
東吳大學
巨量資料管理學院碩士學位學程
107
The use of social media has become an irreversible phenomenon in the world. The new social media platforms are emerging one after another. The number of social media users has also grown year by year. Due to the rise of social media and the diversification of information dissemination, consumers can obtain the information through multiple channels. This phenomenon has greatly changed the behavior of consumers and their decision-making process of purchasing, and prompted companies to change their marketing strategy. Enterprises must think about how to market with consumers in interaction, let consumers understand company’s brand value and be influenced through interaction, stand out from the huge amount of information to attract consumers' attention, and how to rotate in information, finding effective marketing channels in fast and noisy online communities. In the mentioned research questions, to the best of our knowledge, previous studies major focus on single social media platform. To remedy this research gap, this study proposed a method to find the most influence path of word-of-mouth for marketing that maximize the information diffusion. This method also identifies the key nodes that cause the diffusion benefit from the path to see if there is a specific media or organization that assists the brand owner in operating the word-of-mouth operation business. In the future, enterprises can refer to the results of this study to formulate a word-of-mouth marketing strategy.
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9

Chen, Hsin-Chun, and 陳信君. "Studies on Diffusion Extraction of Soluble Constituents and Volatile Components in Mei (Prunus mume Sieb. et Zucc.) Liqueur during Maceration with Rice Wine." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/92527037420808059514.

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碩士
國立臺灣大學
園藝學研究所
90
This research is to study on diffusion extractions of soluble constituents and volatile components in Mei (Prunus mume Sieb. Et Zucc.) liqueur during maceration with rice wine. Samples were from mei fruit (250g) with different cultivars (Ta-Ching and Yen-Chih), and different ripening (90, 100, 110 days after anthesis) soaked in 35 vol % alcohol with different amount of sugar (150g). The maceration times were 0, 30, 90, 180 and 360 days. Within these days, compositions were regularly sampled and analyzed. Results showed that total soluble solid and pH value were different with cultivars, process and maceration time. However, total phenol and tannin content in mei liqueur increased with the increasing of maceration time. The capacity of the scavenging effect from mei liqueur on DPPH radical was up to 78%. The volatile flavor compounds in the mei liqueur were adsorped by a Amberlite XAD-2 resin and analyzed with GC and GC/MS. Total of thirty compounds were identified, including 11 esters, 7 alcohols, 2 aldehydes, 3 acids and 1 aromatic hydrocarbons compounds. Among the volatile flavor compounds in the mei liqueur, the content of isoamyl alcohol was found with the highest (33.50%), and benzaldehyde was found with the second (21.06%). The comparision of volatile compounds amounts in mei liqueur during the maceration with various mei cultivars harvested after anthesis for various periods was also studied. In the Ta-Ching cultivar, added suger after 180 days on the amounts in mei liqueur during maceration with Ta-Ching mei harvested after anthesis for 90-days was the highest, while Yen-Chih cultivar of added suger after 270 days on the amounts in mei liqueur during maceration with Yen-Chih mei harvested after anthesis for 100-days was the highest.
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10

Meddour, Miriam. "MR-tomographische Darstellung intracerebraler Blutungen mit und ohne Therapie." Doctoral thesis, 2011. http://hdl.handle.net/11858/00-1735-0000-0006-B180-D.

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Книги з теми "MRI, Diffusion, MEG"

1

jia, Fen, and Zeng ying. Mei you dui shou de jing zheng. Bei jing: Qun yan chu ban she, 2008.

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2

Jones, PhD, Derek K., ed. Diffusion MRI. Oxford University Press, 2012. http://dx.doi.org/10.1093/med/9780195369779.001.0001.

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Since its initial development in the mid-1980s, and wide accessibility to perform diffusion MRI on all MRI scanners, the use of diffusion MRI has become widespread across the last 30 years. This online resource discusses the importance of ensuring that the hardware is performing optimally, the pulse sequence is carefully designed, the acquisition is optimal, the data quality is maximized while artifacts are minimized, the appropriate post-processing is used, and, where appropriate, the appropriate statistical testing is used, and the data are interpreted correctly. The author is a world authority on diffusion MRI, and has assembled most of the world's leading scientists and clinicians developing and applying diffusion MRI to produce a definitive, didactic and essential reference work for those working with diffusion MRI.
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3

Glockner, James F., Kazuhiro Kitajima, and Akira Kawashima. Magnetic resonance imaging. Edited by Christopher G. Winearls. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0015_update_001.

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Magnetic resonance imaging (MRI) provides excellent anatomic detail and soft tissue contrast for the evaluation of patients with renal disease. MRI needs longer scan time than computed tomography (CT); however, no radiation is involved. Gadolinium-based contrast agents (GBCAs) are used to help provide additional image contrast during MRI. MRI is indicated for characterization of renal mass, staging of malignant renal neoplasms, and determination of vena cava involvement by the renal tumour. Magnetic resonance (MR) angiography is widely accepted as a non-invasive imaging work-up of renal artery stenosis. MR urography is an alternative to CT urography to assess the upper urinary tract but does not identify urinary calculi. Diffusion-weighted imaging is a functional MR technique being used to characterize parenchymal renal disease and renal tumours. Nephrogenic systemic fibrosis is a rare but debilitating and potentially life-threatening condition which has been linked to exposure of GBCAs in patients with severe renal insufficiency. The risk versus benefit must be assessed before proceeding.
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4

Das, Raj, Susan Heenan, and Uday Patel. Magnetic resonance imaging in urology. Edited by Michael Weston. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199659579.003.0134.

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Magnetic resonance imaging is essential for urological imaging. It offers excellent soft tissue contrast and resolution, allowing manipulation of tissue contrast with different image weighting and sequences. The multiplanar aspect of MRI allows image acquisition in different planes and degrees of obliquity to best exhibit pathology. The basic physics of MRI is explored initially with explanation of image weighting, sequences, and diffusion-weighted imaging. The chapter is then divided into renal, bladder, and prostate MRI imaging. The paragraphs on renal MRI outline renal mass analysis and include characterization and assessment of cystic and fat-containing lesions. Staging of renal carcinoma with MRI is also discussed, along with its advantages compared with CT staging. Throughout the text, the key diagnostic MRI features with each disease and organ, and the pitfalls and caveats of MRI imaging are emphasized.
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5

Konrad, Kerstin, Adriana Di Martino, and Yuta Aoki. Brain volumes and intrinsic brain connectivity in ADHD. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198739258.003.0006.

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Neuroimaging studies have increased our understanding of the neurobiological underpinnings of ADHD. Structural brain imaging studies demonstrate widespread changes in brain volumes, in particular in frontal-striatal-cerebellar networks. Based on the widespread nature of structural and functional brain abnormalities, approaches able to capture the organizing principles of large-scale neural systems have been used in ADHD. These include diffusion magnetic resonance imaging (MRI) and resting state functional MRI (R-fMRI). Complementary to findings of volumetric studies, diffusion investigations have reported structural connectivity abnormalities in frontal-striatal-cerebellar networks. In parallel, R-fMRI studies point towards abnormalities in the interaction of multiple networks, extending the functional territory of explorations beyond cognitive and motor control. In the future, a deep phenotypic characterization beyond diagnostic categories combined with longitudinal study designs and novel analytical approaches will accelerate the pace towards clinical translations of neuroimaging to improve the detection and prediction of neural trajectories and treatment response in ADHD.
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6

Bandettini, Peter A., and Hanzhang Lu. Magnetic Resonance Methodologies. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0008.

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Magnetic resonance imaging is a noninvasive tool for assessing brain anatomy, perfusion, metabolism, and function with precision. In this chapter, the basics and the most cutting edge examples of MRI-based measures are described. The first is measurement of cerebral perfusion, including the latest techniques involving spin-labelling as well as the tracking of exogenous contrast agents. Functional MRI is then discussed, along with some of the cutting edge methodology that has yet to make it into routine clinical practice. Next, resting state fMRI is described, a powerful technique whereby the entire brain connectivity can be established. Diffusion-based MRI techniques are useful for diagnosing brain trauma as well as understanding the structural connections in healthy and pathological brains. Spectroscopy is able to make spatially specific and metabolite-specific assessment of brain metabolism. The chapter ends with an overview of structural imaging with MRI, highlighting the developing field of morphometry and its potential for differentially assessing individual brains.
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7

Gorman, Jack M. Brain Imaging. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190850128.003.0005.

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The blood–brain barrier vigorously limits what can get into and out of the brain, making our ability to understand brain function much more difficult than with any other organ in the body. The modern era of brain imaging began about a half-century ago with the introduction of computed axial tomography (CAT) and magnetic resonance imaging (MRI). Although CAT scanning shows brain structure in great detail and revolutionized the precision of medical diagnosis, including of brain disorders, it has had relatively little impact on psychiatry because most psychiatric illnesses do not involve visible abnormalities of the size, shape, or volume of brain structures. Similarly, although we have gained some insights from structural MRI, it primarily shows us the anatomy of the brain. Three other variants of MRI, however, have been extremely useful in studying psychiatric issues: functional magnetic resonance imaging, diffusion tensor imaging, and magnetic resonance spectroscopy.
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8

Cohen-Inbar, Or, Daniel M. Trifiletti, and Jason P. Sheehan. Stereotatic Radiosurgery and Microsurgery for Brain Metastases. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190696696.003.0024.

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This chapter describes the case of a patient with brain metastases due to metastatic breast cancer. MRI is the best imaging modality for visualizing brain metastases, and advanced techniques such as perfusion imaging and diffusion weighted imaging may provide important additional information beyond standard anatomic imaging. Patients with brain metastases due to systemic cancer may benefit from targeted therapies such as surgery and stereotactic radiosurgery. Understanding the differences between radiation modalities such as stereotactic radiosurgery and whole brain radiotherapy is important for counseling patients.
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9

Krause-Utz, Annegret, Inga Niedtfeld, Julia Knauber, and Christian Schmahl. Neurobiology of Borderline Personality Disorder. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199997510.003.0006.

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In this chapter, neuroimaging findings in BPD are discussed referring to the three core domains of BPD psychopathology: disturbed emotion processing and emotion dysregulation (including dissociation and altered pain processing), behavioral dysregulation and impulsivity, and interpersonal disturbances. Experimental approaches investigating BPD psychopathology on the subjective, behavioral, and neurobiological levels have become increasingly important for an improved understanding of BPD. Over the past decades, neuroimaging has become one of the most important tools in clinical neurobiology. Neuroimaging includes a broad spectrum of methods such as positron emission tomography (PET), structural and functional magnetic resonance imaging (fMRI), MR spectroscopy, and diffusion tensor imaging (DTI).
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Частини книг з теми "MRI, Diffusion, MEG"

1

Catani, Marco. "The Functional Anatomy of White Matter: From Postmortem Dissections to In Vivo Virtual Tractography." In Diffusion MRI, 5–18. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0001.

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2

Filley, Christopher M. "Neurobiology of White Matter Disorders." In Diffusion MRI, 19–30. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0002.

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Axer, Hubertus. "Invasive Methods for Tracing White Matter Architecture." In Diffusion MRI, 31–42. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0003.

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4

Callaghan, Paul T. "Physics of Diffusion." In Diffusion MRI, 45–56. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0004.

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Le Bihan, Denis. "Magnetic Resonance Diffusion Imaging: Introduction and Concepts." In Diffusion MRI, 57–78. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0005.

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Basser, Peter J., and Evren Özarslan. "Anisotropic Diffusion: From the Apparent Diffusion Coefficient to the Apparent Diffusion Tensor." In Diffusion MRI, 79–91. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0006.

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Beaulieu, Christian. "What Makes Diffusion Anisotropic in the Nervous System?" In Diffusion MRI, 92–109. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0007.

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Ackerman, Joseph J. H., and Jeffrey J. Neil. "Biophysics of Diffusion in Cells." In Diffusion MRI, 110–24. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0008.

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Cohen, Yoram, and Yaniv Assaf. "Extracting Geometric Properties of White Matter with q-Space Diffusion MRI (QSI)." In Diffusion MRI, 125–51. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0009.

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Kiselev, Valerij G. "The Cumulant Expansion: An Overarching Mathematical Framework For Understanding Diffusion NMR." In Diffusion MRI, 152–68. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780195369779.003.0010.

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Тези доповідей конференцій з теми "MRI, Diffusion, MEG"

1

Kojcic, Ivana, Theodore Papadopoulo, Rachid Deriche, and Samuel Deslauriers-Gauthier. "Incorporating Transmission Delays Supported By Diffusion Mri In Meg Source Reconstruction." In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI). IEEE, 2021. http://dx.doi.org/10.1109/isbi48211.2021.9433861.

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2

Fukushima, Makoto, Okito Yamashita, Thomas R. Knosche, and Masa-aki Sato. "MEG source reconstruction constrained by diffusion MRI based whole brain dynamical model." In 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013). IEEE, 2013. http://dx.doi.org/10.1109/isbi.2013.6556646.

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3

Philippe, Anne-Charlotte, Maureen Clerc, Theodore Papadopoulo, and Rachid Deriche. "A nested cortex parcellation combining analysis of MEG forward problem and diffusion MRI tractography." In 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012). IEEE, 2012. http://dx.doi.org/10.1109/isbi.2012.6235599.

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4

Belaoucha, Brahim, Jean-Marc Lina, Maureen Clerc, and Theodore Papadopoulo. "MEM-diffusion MRI framework to solve MEEG inverse problem." In 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE, 2015. http://dx.doi.org/10.1109/eusipco.2015.7362709.

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Dantas, Pedro da Cunha, Lucas Pablo Almendro, Ana Caroline Fonseca Silva, and André Douglas Marinho da Silva. "Magnetic resonance and its diagnostic accuracy of glioblastoma: narrative review." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.294.

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Анотація:
Introduction: Glioblastoma (GBM) is the most common and lethal Central Nervous System (CNS) malignant cancer, and the exclusion of differential diagnoses - eg primary central nervous system lymphoma (PCNSL) - often occurs via various Magnetic Resonance Imaging (MRI) methodologies. Objective: To describe which best image sequences are critical for greater accuracy in the diagnosis of GBM and for their distinction from other CNS tumors. Methods: This is a literature narrative review, initiated by research in Pubmed database, using associated Key words: “Glioblastoma” and “Magnetic Resonance”; and filters: systematic reviews + last 5 years publications. Productions that didn’t meet the objective were discarded. Results: MRI has accuracy for diagnosing GBM using the combination T2 + FLAIR + T1 with pre and post-gadolinic contrast. Diffusion and perfusion-weighted MRI association show an improvement in specificity. Computed tomography is used when MRI is unviable, identifying calcifications or hemorrhages and determining the lesion location and surgical potential. Also, spectroscopic MRI, diffusion tensor imaging and PET 18F-FDG, and 11C-MET were reported as important additional diagnostic criteria. Diffusion MRI (DWI) is a non-invasive, convenient, economical, and quick procedure when compared to GBM biopsy. Therefore, adding reliable evidence for moderate differentiation between GBM and PCNSL through DWI. Conclusion: Reliable methods are needed for GBM accurate diagnosis and its differential diagnoses, using at least T2 + FLAIR + T1, and physiological exams to enhance specificity.
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Delgado-Goni, Teresa, Slawomir Wantuch, Teresa Casals-Galobart, Udai Banerji, Nina Tunariu, Simon P. Robinson, Martin O. Leach, and Mounia Beloueche-Babari. "Abstract 4108: Longitudinal diffusion-weighted MRI assessment of NRAS mutant melanoma response to dual RAF-MEK inhibition reveals differences associated with collagen deposition." In Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.am2018-4108.

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Beloueche-Babari, Mounia, Yann Jamin, Vaitha Arunan, Simon Walker-Samuel, Paul D. Smith, John C. Waterton, Jane Halliday, Paul Workman, Martin O. Leach, and Simon P. Robinson. "Abstract LB-48: Non-invasive imaging of response to MEK Inhibition with AZD6244 (ARRY-142886) in a human melanoma xenograft monitored by diffusion-weighted MRI." In Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC. American Association for Cancer Research, 2010. http://dx.doi.org/10.1158/1538-7445.am10-lb-48.

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8

Duport, Laurent J. "Georges Candilis (1913-1995) architecte pour le plus grand nombre." In LC2015 - Le Corbusier, 50 years later. Valencia: Universitat Politècnica València, 2015. http://dx.doi.org/10.4995/lc2015.2015.664.

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Анотація:
Résumé: Né à Bakou en 1913 Georges Candilis est un architecte d’origine grecque qui étudie à l’Ecole Supérieure Polytechnique d’Athènes où il rencontre Le Corbusier en 1933 lors du 4e congrès des CIAM. Arrivé à Paris en 1945 il intègre l’Atelier de Le Corbusier où il travaille exclusivement sur les études et le chantier de l’Unité d’Habitation de Marseille. Après avoir été chargé de représenter Le Corbusier au 7e CIAM à Bergamo en 1949 Candilis va se rendre au Maroc où il va construire des nombreuses opérations en qualité de directeur de l’ATBAT Afrique et de membre du groupe GAMMA. Il va se révéler un des acteurs du Team X assurant le passage des CIAM au Team X dont il organisera 5 réunions entre 1960 et 1977. De retour en France en 1955 Candilis va s’associer avec les architectes Woods et Josic. L’équipe va remporter le concours Million et construire près de 4000 logements à Bagnols sur Cèze, Toulouse et en région parisienne. D’autres concours vont suivre en France et à l’étranger, l’équipe construira ainsi l’université libre de Berlin. Par la suite Candilis assure seul la mission d’architecte en chef de la station de Leucate Barcares (1962-1976) et entre 1970 et 1978 il est chargé de plusieurs projets au Moyen Orient. Parallèlement Candilis est impliqué dans la diffusion de l’architecture dès 1953 comme membre du comité de rédaction de revues et dans l’enseignement en qualité de professeur à partir de 1963. Il s’éteint à Paris le 10 mai 1995. Abstract: Born in Baku in 1913 Georges Candilis is an architect of Greek origin who studied at the Polytechnic School of Athens where he met Le Corbusier in 1933 at the 4th Congress of CIAM. Arrived in Paris in 1945 he joined the Atelier of Le Corbusier where he works exclusively on studies and the site of the Unité d’habitation in Marseilles. After being appointed to represent Le Corbusier at the 7th CIAM in Bergamo in 1949 Candilis will travel to Morocco where he will build many operations as Director of ATBAT Africa and a member of the GAMMA group. It will be one of the actors of Team X and ensure the transition from CIAM to Team X for which he will hold 5 meetings between 1960 and 1977. Back in France in 1955 Candilis will partner with architects Alexis Josic and Shadrach Woods. The team will win the Million competition and build nearly 4,000 housing units in Bagnols sur Cèze, Toulouse and around Paris. Other competitions will follow in France and abroad, the team will thus build the Free University in Berlin. Subsequently Candilis assumes alone the chief architect mission of Leucate Barcares station (1962-1976) and between 1970 and 1978 he was responsible for several projects in the Middle East. In parrallel Candilis is involved in the diffusion of architecture since 1953 as an editorial board member of reviews and in architectural education with a grade of Professor since 1963. He died in Paris on May 10, 1995. Mots-clés: CIAM, Team X, Enseignement, Habitat, Tige, Web. Keywords: CIAM, Team X, Education, Housing, Stem, Web. DOI: http://dx.doi.org/10.4995/LC2015.2015.664
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