Academic literature on the topic 'Rs-fMRI'

OBJECTIVEDetermining language laterality in patients with intractable epilepsy is important in operative planning. Wada testing is the gold standard, but it has a risk of stroke. Both Wada and task-based functional MRI (tb-fMRI) require patient cooperation. Recently, resting-state fMRI (rs-fMRI) has been explored for language lateralization. In the present study, the correlation between rs-fMRI and tb-fMRI in language lateralization is estimated in a pediatric population with intractable epilepsy.METHODSrs-fMRI and tb-fMRI language lateralization testing performed as part of epilepsy surgery evaluation was retrospectively reviewed.RESULTSTwenty-nine patients underwent rs-fMRI and tb-fMRI; a total of 38 rs-fMRI studies and 30 tb-fMRI studies were obtained. tb-fMRI suggested left dominance in 25 of 30 cases (83%), right in 3 (10%), and in 2 (7%) the studies were nondiagnostic. In rs-fMRI, 26 of 38 studies (68%) suggested left dominance, 3 (8%) right dominance, 6 (16%) bilateral, and 3 (8%) were nondiagnostic. When tb-fMRI lateralized to the left hemisphere (25 cases), rs-fMRI was lateralized to the left in 23 patients (92%) and it was bilateral/equal in 2 (8%). When tb-fMRI lateralized to the right (3 cases), rs-fMRI lateralized to the right in all cases (100%). The overall concordance rate was 0.93 (95% CI 0.76–0.99) when considering cases with tb-fMRI and rs-fMRI performed within 6 months of each other, and tb-fMRI results were not nondiagnostic.CONCLUSIONSrs-fMRI significantly correlated with tb-fMRI in lateralizing language and suggests the potential role for identifying hemispheric dominance via rs-fMRI. Further investigation and validation studies are warranted.

OBJECTIVEResting-state functional MRI (rs-fMRI) represents a promising and cost-effective alternative to task-based fMRI for presurgical mapping. However, the lack of clinically streamlined and reliable rs-fMRI analysis tools has prevented wide adoption of this technique. In this work, the authors introduce an rs-fMRI processing pipeline (ReStNeuMap) for automatic single-patient rs-fMRI network analysis.METHODSThe authors provide a description of the rs-fMRI network analysis steps implemented in ReStNeuMap and report their initial experience with this tool after performing presurgical mapping in 6 patients. They verified the spatial agreement between rs-fMRI networks derived by ReStNeuMap and localization of activation with intraoperative direct electrical stimulation (DES).RESULTSThe authors automatically extracted rs-fMRI networks including eloquent cortex in spatial proximity with the resected lesion in all patients. The distance between DES points and corresponding rs-fMRI networks was less than 1 cm in 78% of cases for motor, 100% of cases for visual, 87.5% of cases for language, and 100% of cases for speech articulation mapping.CONCLUSIONSThe authors’ initial experience with ReStNeuMap showed good spatial agreement between presurgical rs-fMRI predictions and DES findings during awake surgery. The availability of the rs-fMRI analysis tools for clinicians aiming to perform noninvasive mapping of brain functional networks may extend its application beyond surgical practice.

Background: Resting state functional MRI (rs-fMRI) provides many advantages to task-based fMRI in neurosurgical populations, foremost of which is the lack of the need to perform a task. Many networks can be identified by rs-fMRI in a single period of scanning. Despite the advantages, there is a paucity of literature on rs-fMRI in neurosurgical populations. Methods: Eight patients with tumours near areas traditionally considered as eloquent cortex participated in a five minute rs-fMRI scan. Resting-state fMRI data underwent Independent Component Analysis (ICA) using the Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) toolbox in FSL. Resting state networks (RSNs) were identified on a visual basis. Results: Several RSNs, including language (N=7), sensorimotor (N=7), visual (N=7), default mode network (N=8) and frontoparietal attentional control (n=7) networks were readily identifiable using ICA of rs-fMRI data. Conclusion: These pilot data suggest that ICA applied to rs-fMRI data can be used to identify motor and language networks in patients with brain tumours. We have also shown that RSNs associated with cognitive functioning, including the default mode network and the frontoparietal attentional control network can be identified in individual subjects with brain tumours. While preliminary, this suggests that rs-fMRI may be used pre-operatively to localize areas of cortex important for higher order cognitive functioning.

Resting-state fMRI (rs-fMRI) is a widely used technique to investigate the residual brain functions of patients with Disorders of Consciousness (DoC). Nonetheless, it is unclear how the networks that are more associated with primary functions, such as the sensory–motor, medial/lateral visual and auditory networks, contribute to clinical assessment. In this study, we examined the rs-fMRI lower-order networks alongside their structural MRI data to clarify the corresponding association with clinical assessment. We studied 109 chronic patients with DoC and emerged from DoC with structural MRI and rs-fMRI: 65 in vegetative state/unresponsive wakefulness state (VS/UWS), 34 in minimally conscious state (MCS) and 10 with severe disability. rs-fMRI data were analyzed with independent component analyses and seed-based analyses, in relation to structural MRI and clinical data. The results showed that VS/UWS had fewer networks than MCS patients and the rs-fMRI activity in each network was decreased. Visual networks were correlated to the clinical status, and in cases where no clinical response occurred, rs-fMRI indicated distinctive networks conveying information in a similar way to other techniques. The information provided by single networks was limited, whereas the four networks together yielded better classification results, particularly when the model included rs-fMRI and structural MRI data (AUC = 0.80). Both quantitative and qualitative rs-fMRI analyses yielded converging results; vascular etiology might confound the results, and disease duration generally reduced the number of networks observed. The lower-order rs-fMRI networks could be used clinically to support and corroborate visual function assessments in DoC.

Resting State fMRI (RS-fMRI) represents an emerging and powerful tool to explore brain functional connectivity (FC) changes associated with neurologic disorders. Compared to activation/task-related fMRI, RS-fMRI has the advantages that (i) BOLD fMRI signals are self-generated and independent of subject’s performance during the task and (ii) a single dataset is sufficient to extract a set of RS networks (RSNs) that allows to explore whole brain FC. According to these features RS-fMRI appears particularly suitable for the study of FC changes related to multiple sclerosis (MS). In the present review we will first give a brief description of RS-fMRI methodology and then an overview of most relevant studies conducted so far in MS by using this approach. The most interesting results, in particular, regard the default-mode network (DMN), whose FC changes have been correlated with cognitive status of MS patients, and the visual RSN (V-RSN) whose FC changes have been correlated with visual recovery after optic neuritis. The executive control network (ECN), the lateralized frontoparietal network (FPN), and the sensory motor network (SMN) have also been investigated in MS, showing significant FC rearrangements. All together, RS-fMRI studies conducted so far in MS suggest that prominent RS-FC changes can be detected in many RSNs and correlate with clinical and/or structural MRI measures. Future RS-fMRI studies will further clarify the dynamics and clinical impact of RSNs changes in MS.

Resting state functional magnetic resonance imaging (rs-fMRI) allows studying spontaneous brain activity in absence of task, recording changes of Blood Oxygenation Level Dependent (BOLD) signal. rs-fMRI enables identification of brain networks also called Resting State Networks (RSNs) including the most studied Default Mode Network (DMN). The simplicity and speed of execution make rs-fMRI applicable in a variety of normal and pathological conditions. Since it does not require any task, rs-fMRI is particularly useful for protocols on patients, children, and elders, increasing participant’s compliance and reducing intersubjective variability due to the task performance. rs-fMRI has shown high sensitivity in identification of RSNs modifications in several diseases also in absence of structural modifications. In this narrative review, we provide the state of the art of rs-fMRI studies about physiological and pathological aging processes. First, we introduce the background of resting state; then we review clinical findings provided by rs-fMRI in physiological aging, Mild Cognitive Impairment (MCI), Alzheimer Dementia (AD), and Late Life Depression (LLD). Finally, we suggest future directions in this field of research and its potential clinical applications.

Cognitive impairment is a common disabling symptom in PD. Unlike motor symptoms, the mechanism underlying cognitive dysfunction in Parkinson’s disease (PD) remains unclear and may involve multiple pathophysiological processes. Resting state functional magnetic resonance imaging (rs-fMRI) is a fast-developing research field, and its application in cognitive impairments in PD is rapidly growing. In this review, we summarize rs-fMRI studies on cognitive function in PD and discuss the strong potential of rs-fMRI in this area. rs-fMRI can help reveal the pathophysiology of cognitive symptoms in PD, facilitate early identification of PD patients with cognitive impairment, distinguish PD dementia from dementia with Lewy bodies, and monitor and guide treatment for cognitive impairment in PD. In particular, ongoing and future longitudinal studies would enhance the ability of rs-fMRI in predicting PD dementia. In combination with other modalities such as positron emission tomography, rs-fMRI could give us more information on the underlying mechanism of cognitive deficits in PD.

Rs-fMRI can provide rich information about functional processes in the brain with a large array of imaging parameters and is also suitable for investigating the biological processes in cerebral gliomas. We aimed to propose an imaging analysis method of RP-Rs-fMRIomics by adopting omics analysis on rs-fMRI with exhaustive regional parameters and subsequently estimating its feasibility on the prediction diagnosis of gliomas. In this retrospective study, preoperative rs-fMRI data were acquired from patients confirmed with diffuse gliomas (n = 176). A total of 420 features were extracted through measuring 14 regional parameters of rs-fMRI as much as available currently in 10 specific narrow frequency bins and three parts of gliomas. With a randomly split training and testing dataset (ratio 7:3), four classifiers were implemented to construct and optimize RP-Rs-fMRIomics models for predicting glioma grade, IDH status and Karnofsky Performance Status scores. The RP-Rs-fMRIomics models (AUROC 0.988, 0.905, 0.801) were superior to the corresponding traditional single rs-fMRI index (AUROC 0.803, 0.731, 0.632) in predicting glioma grade, IDH and survival. The RP-Rs-fMRIomics analysis, featuring high interpretability, was competitive for prediction of glioma grading, IDH genotype and prognosis. The method expanded the clinical application of rs-fMRI and also contributed a new imaging analysis for brain tumor research.

Abstract Resting-state fMRI (rs-fMRI) has emerged as an alternative method to study brain function in human and animal models. In humans, it has been widely used to study psychiatric disorders including schizophrenia, bipolar disorder, autism spectrum disorders, and attention deficit hyperactivity disorders. In this review, rs-fMRI and its advantages over task based fMRI, its currently used analysis methods, and its application in psychiatric disorders using different analysis methods are discussed. Finally, several limitations and challenges of rs-fMRI applications are also discussed.

Today, functional magnetic resonance imaging (fMRI) allows to plan surgery based on the topography of functionally important areas of the human brain cortex and tumor. This method can complement the surgical strategy with significant clinical information. The stimulus-dependent fMRI with motor and language paradigms is generally used for preoperative planning. The study outcome depends on the patient's ability to perform tasks paradigm, which is broken in brain tumors. In an attempt to overcome this problem, resting-state fMRI (rs-fMRI) is used for brain mapping. Rs-fMRI is based on the measurement of spontaneous fluctuations of the BOLD signal (blood oxygen level-dependent), representing the functional structure of the brain. In contrast to stimulus-dependent fMRI, rs-fMRI provides more complete information about functional architecture of the brain. rs-fMRI is used in conditions where the results of stimulusdependent fMRI may be falsely positive or in the absence of the possibility of its implementation. In aggregate, both methods significantly expand the efficiency and specificity of preoperative planning.

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) experiments are normally performed separately. The idea of extracting inherently co-registered activation/connectivity maps and diffusion parameters has resulted in efforts to develop methods for simultaneous fMRI and DTI data acquisition. Recently, a 3D echo planar imaging (EPI) acquisition was successfully inserted after each DTI volume to perform real-time motion correction, with the two sequence protocols remaining separate. We examined using a single 3D EPI acquisition, inserted following each DTI volume acquisition (hereafter called the single nav sequence), modified to acquire BOLD resting state fMRI (rs-fMRI) data. We also investigated inserting a second 3D EPI acquisition in the middle of each DTI volume acquisition (hereafter called the double nav sequence) to increase fMRI temporal resolution. Two adult subjects were scanned with the navigated sequences and the standard separate 2D EPI BOLD and DTI acquisitions for comparison. Preprocessing and analysis of data was performed using FATCAT, AFNI , FSL and in-house Python scripts. Four standard resting state networks (RSNs) were visually identified using the navigated diffusion sequences. While RSNs were apparent in the single nav case, they were quite noisy and in some cases entire regions did not show connectivity. The double nav connectivity maps were more similar to the standard BOLD connectivity maps in terms of the spatial extent of the regions showing connectivity to the seed. The whole brain distributions of fractional anisotropy (FA) and mean diffusivity (MD) were similar among the different acquisition protocols. The jackknife standard error was comparable between the navigated and standard protocols. Further comparisons of diffusion data made using probabilistic tractography and connectivity matrices showed overall small differences indicating that connections derived from the standard DTI, single nav and double nav protocols were overall similar. We have therefore shown a significant "proof of concept" of successfully acquiring simultaneous DTI and rs-fMRI data, and therefore for investigating brain structural and functional connectivity simultaneously.

Depression is the most common type of emotional disorder among the world's population. It is characterized by negative sentiments, the feeling of guilt, low self-esteem, a loss of interest, a high-level process of reflection, and in general by a decrease of the individual's psychic functions. The new non-invasive neuroimaging techniques have increased the ability of studying possible variations in patients' brain activity. In concrete, functional magnetic resonance imaging (fMRI) has become the most important method to study human brain functions in the past two decades, being non-invasive and with no risk for human health. Biswal and others in 1995, and later Lowe and his colleagues in 1998, showed the existence of continous spontaneous activity in the brain's activity at rest. These fluctuations have also been verified in other species like macaques (Vicent JL et l, 2007). Studying the brain's activity at rest (rs-fMRI) by means of neuroimaging techniques has become a powerful tool for the investigation of diseases, since it has demonstrated a better signal to noise ratio concerning task-based approaches on one hand, and since certain patients could have difficulties to perform cognitive, language or motor tasks on the other hand. However, it seems that because of certain inconsistencies found among studies, rs-fMRI techniques would not reach a practical clinical use of a personalised monitoring, prognosis or pre-diagnosis in individuals with depression. In this respect, even if Grecius MD exposed in 2008 the benefits of rs-fMRI techniques, he also commented that the signal to noise ratio remains to be improved to be used in a clinical routine. Grecius suggested to lenghthen the time of the temporal series at rest, and to improve analysis procedures. The aim of this thesis is to elucidate if the existence of certain factors or components in the functional signal at rest could be used at the clinical health level. In order to achieve this, we use rs-fMRI data on two sets of samples. In the first set of samples, composed by 27 patients with major depression (MDD) and 27 individuals as controls, we design descriptors that describe both static and dynamic aspects of the resting-state signal for the construction of prediction models. Conversely, with the second type of samples (48 twins), we analyse the relation between possible genetic and environmental factors which could explain certain depressive components in the activity in resting condition. On the one hand, the results show that depression could simultaneously affect different brain networks located in the prefrontal-limbic area, in the DMN, and between the frontoparietal lobes. Besides, it seems that the alterations in these networks could be explained by both static and dynamic aspects existing in the rest signal. Finally, we achieve the creation of models that would partially explain certain clinical phenomenons present in depressive patients by means of global descriptors in these networks. These network descriptors could be used for personalised monitoring in patients with major depression. On the other hand, using the twin sample, we achieve the construction of a risk model from the amygdalar activity which evaluates the risk or predisposition of an individual from analytical components in the activity at rest. The cerebellum of this sample was also analysed, and the environment was found to be possibly modifying the activity in these regions
La depresión es el tipo de trastorno emocional más común en la población mundial. Se caracteriza por sentimientos de culpa o negativos, baja autoestima, pérdida de interés, alto nivel de reflexión y en general una disminución de las funciones psíquicas del individuo. Las nuevas técnicas de neuroimagen no invasivas han incrementado la habilidad para estudiar posibles variaciones de la actividad cerebral en pacientes. En concreto, las imágenes por resonancia funcional magnética (fRMI) se han convertido en las dos últimas décadas el método más importante, no-invasivo sin riesgo para la salud humana, para el estudio de las funciones cerebrales humanas. Biswal y otros en 1995, y posteriormente Lowe y compañía en 1998, demostraron la existencia de actividad espontanea continua en la actividad cerebral en estado de reposo. Estas fluctuaciones también han sido confirmadas en otras especies como en macacos (Vincent JL y compañía, 2007). El estudio mediante técnicas de neuroimagen sobre la actividad cerebral en reposo (rs-fMRI) se ha convertido en una potente herramienta para el estudio de enfermedades, puesto que, por un lado, se ha demostrado tener una mejor relación señal-ruido respecto a enfoques basados en tareas, y por otro lado, ciertos pacientes podrían tener dificultades para realizar algún tipo de tareas cognitivas, de lenguaje o motoras. Sin embargo, parece ser que debido a ciertas inconsistencias encontradas entre estudios, las técnicas de rs-fMRI no estarían llegando a un uso clínico-práctico para el seguimiento, pronóstico o pre-diagnostico personalizado en individuos con depresión. En línea a esto, aunque Grecius MD en 2008 expuso los beneficios de la técnica rs-fMRI también comentó que para poder ser utilizada en la rutina clínica aún se debería mejorar la relación señal-ruido. Propuso alargar los tiempos de las series temporales en estado de reposo y mejorar los procedimientos de análisis. En esta tesis se trabaja para dilucidar si existen ciertos factores o componentes en la señal funcional en estado de reposo que pudieran ser utilizados para su uso en la salud clínica. Por ello, utilizamos datos de rs-fMRI sobre dos conjunto de muestras. En el primer conjunto, 27 pacientes con depresión mayor (MDD) y 27 individuos como control, diseñamos descriptores que describan aspectos estáticos y dinámicos de la señal de reposo para la construcción de modelos de prónostico. En cambio, con el segundo tipo de muestras, 48 gemelos, analizamos la relación de posibles factores genéticos y de entorno que pudieran explicar ciertos componentes depresivos en la actividad en estado de reposo. Por un lado, los resultados muestran que la depresión pudiera estar afectando diferentes redes cerebrales al mismo tiempo localizadas en la parte prefrontal-limbica, en la red DMN, y entre los lóbulos frontoparietales. Además, parece ser que las alteraciones sobre estas redes pudieran ser explicadas tanto por aspectos estáticos y dinámicos existentes en la señal de reposo. Finalmente, conseguimos crear modelos que explicarían parcialmente ciertos fenómenos clínicos presentes en los pacientes depresivos, mediante descriptores globales de estas redes. Estos descriptores de red pudieran ser utilizados para el seguimiento personalizado en pacientes con depresión mayor. Por otro, utilizando la muestra de gemelos, conseguimos construir un modelo de riesgo a partir de la actividad amigdalar que evalúa el riesgo o propensión de un individuo a partir de componentes analíticas en la actividad de reposo. También sobre esta muestra, se analizó el cerebelo encontrando que el entorno pudiera estar modificando la actividad en estas regiones

Il lavoro che ho sviluppato presso l'unità di RM funzionale del Policlinico S.Orsola-Malpighi, DIBINEM, è incentrato sull'analisi dati di resting state - functional Magnetic Resonance Imaging (rs-fMRI) mediante l'utilizzo della graph theory, con lo scopo di valutare eventuali differenze in termini di connettività cerebrale funzionale tra un campione di pazienti affetti da Nocturnal Frontal Lobe Epilepsy (NFLE) ed uno di controlli sani. L'epilessia frontale notturna è una peculiare forma di epilessia caratterizzata da crisi che si verificano quasi esclusivamente durante il sonno notturno. Queste sono contraddistinte da comportamenti motori, prevalentemente distonici, spesso complessi, e talora a semiologia bizzarra. L'fMRI è una metodica di neuroimaging avanzata che permette di misurare indirettamente l'attività neuronale. Tutti i soggetti sono stati studiati in condizioni di resting-state, ossia di veglia rilassata. In particolare mi sono occupato di analizzare i dati fMRI con un approccio innovativo in campo clinico-neurologico, rappresentato dalla graph theory. I grafi sono definiti come strutture matematiche costituite da nodi e links, che trovano applicazione in molti campi di studio per la modellizzazione di strutture di diverso tipo. La costruzione di un grafo cerebrale per ogni partecipante allo studio ha rappresentato la parte centrale di questo lavoro. L'obiettivo è stato quello di definire le connessioni funzionali tra le diverse aree del cervello mediante l'utilizzo di un network. Il processo di modellizzazione ha permesso di valutare i grafi neurali mediante il calcolo di parametri topologici che ne caratterizzano struttura ed organizzazione. Le misure calcolate in questa analisi preliminare non hanno evidenziato differenze nelle proprietà globali tra i grafi dei pazienti e quelli dei controlli. Alterazioni locali sono state invece riscontrate nei pazienti, rispetto ai controlli, in aree della sostanza grigia profonda, del sistema limbico e delle regioni frontali, le quali rientrano tra quelle ipotizzate essere coinvolte nella fisiopatologia di questa peculiare forma di epilessia.

Brain development is a continuous process which, from fetal period to adulthood, introduces changes in the brain both from a structural and functional point of view. The cerebral development in pediatric subjects is an issue of particular interest since substantial modifications in structures and tissues is observed together with the definition of cognitive functions. Magnetic resonance imaging enables to follow this process, by acquiring, in a non invasive way, high resolution images of the brain with several image constrasts (T1, T2, DTI, …). This PhD project has been focused on the implementation and application of advanced image processing methods that can be employed to qualitatively and quantitatively study the changes induced by maturation on brain structures and cerebral connectivity. The first part of the project has been dedicated to the implementation of a method to create brain atlases. The whole pediatric interval (0-17 years old) has been divided in six age ranges to describe the fundamental steps of normal brain development in children. Six brain atlases corresponding to these stages have been created. The availability of specific templates is very important to be used both as a normal reference in diagnostics and for group studies in research. In particular, an adaptive registration method based on Free-form Deformation was implemented. Compared to other approaches already published in literature, this method is characterized by a strong flexibility. In fact, it can be used with different image contrasts and at different age ranges by optimizing registration parameters depending on the image and population characteristics, such as the number of samples and their distance from the mean age of the range. The method has been demonstrated to be consistent, suggesting applications also for different purposes, for example it could be useful for longitudinal evaluation of progressive pathologies. The second part of the project concerned the study of functional magnetic resonance images in Resting State. The study was performed on preterm newborns subjects, in order to analyze the changes in functional connectivity during the very early brain developmental stages. The attention was focused on basic (ex. motor, visual) and high level (ex. cognitive, language) connectivity networks. The implemented method introduces the ability of performing correlation analysis at different resolution levels. The first resolution level is characterized by the study of each network, through image based Seed Correlation Analysis, both at single subject and at group level. The second resolution level consists in the study of the inter-network connections, performing correlation and regression analyses on BOLD signals extracted from brain areas belonging to the networks. This methodology might be employed also for other purposes, for example to provide a support during the diagnostic process of a pathology. Given the complexity of cerebral maturation process, in particular during pediatric period, the implementation of efficient and sophisticated methods for image processing is extremely important. This project fits in this context with the development of techniques for the integration of multiple types of data, which describe different aspects (anatomy, functionality) involved in brain development.

2012/2013
Lo studio delle connessioni anatomiche e funzionali del cervello risulta essere un passo essenziale per comprendere i meccanismi alla base del funzionamento cerebrale. Diverse tecniche di Neuroimmagini sono state sviluppate negli ultimi anni al fine di approfondire la conoscenza della connettività cerebrale umana in vivo. Il presente studio si articola in quattro differenti esperimenti condotti su gruppi di soggetti sani e non, per valutare la validità di differenti tecniche e della loro combinazione nella caratterizzazione della connettività anatomica e funzionale e delle alterazioni che essa subisce nell'ambito di differenti patologie.
XXVI Ciclo
1985

Rationale and objective: The aging HIV seropositive (HIV+) population struggles with the brain functional and structural abnormalities. Consequently, HIV+ individuals can experience decline in neurocognitive performance. The current state of knowledge informs on the neuroinfectious actions of the HIV virus to a limited extent. However, with the new methods of brain imaging, such as resting state functional magnetic resonance imaging (RS-fMRI), we can now better understand the functional brain bases of the clinical neurocognitive portrait in this specific patient population. Up to date, few scientific reports addressed the effects of age and HIV infection on the resting state (RS) of the brain and cognitive functioning. Due to previous inconsistent findings, the issue remains unclear. This study aimed to examine the effects of aging and HIV infection on the RS of the brain in relationship to the cognitive functioning. Methods: This study analyzed data from a final number of 108 participants between 25 and 75 years of age, including 54 HIV+ individuals (age M=41; SD=12 years) and 54 demographically matched HIV-seronegative controls (age M=43; SD=12 years), with the mean of 16 years of education. All HIV+ participants were receiving HAART. The data retained for the current analyses included neuroimaging data of resting state functional magnetic resonance imaging (RS-fMRI), and neurocognitive data from a comprehensive battery of tests assessing attention, executive functions, memory, psychomotor functions, and semantic skills. RS data was analyzed using Regions of Interest-based approach, Independent Component Analysis, and Voxel-based analysis. Cognitive tests outcome T-scores were comprised into Neurocognitive Factor Scores. Between group differences in RS and neurocognitive data was assessed with T-unpaired test. Bivariate correlations examined relationships between age, RS measures, and neurocognitive factors. Multiple Linear Regression Analysis were performed in order to investigate the effects of age and HIV infection on the relationship between RS brain activity and neurocognitive performance. Results: Control group revealed patterns of aging in RS functional connectivity (FC) and neurocognitive decline comparable to the general population. HIV infection was related to decreases and increases in RS-FC and deterioration in attention and sematic skills as compared to controls. Interaction effects of age and HIV infection were exposed in terms of intra- and internetwork remote FC, which was weakening with age in HIV+ group, while strengthening with age in healthy comparators. No age-HIV interaction effects were observed on cognitive factors. Significant relationships were distinguished between RS-FC measures sensitive to age-HIV interaction effects and neurocognitive factors. Age had no significant moderator effects on majority of the revealed relationships in controls. HIV significantly moderated relationship between RS-FC and neurocognitive factors. Age in HIV+ group did not reveal significant moderator effects on the relationship between RS-FC and neurocognitive factors. Conclusions: Current study provides evidence that RS-fMRI is a sensitive technique to reveal not only additive but also interaction effects of age and HIV infection on the functioning of the brain. The results confirm that age and HIV infection lead to brain reorganization and decline in neurocognitive performance. Importantly, the study finds evidence for the employment of brain compensatory mechanisms in aging HIV+ patient population. The current findings support the hypothesis of rather accentuated than accelerated aging in the individuals aging with HIV.
Uzasadnienie i cel: Osoby starzejące się z infekcją HIV (HIV+) zmagają sią z zaburzeniami w strukturze jak i funkcjonowaniu mózgu. W wyniku tego, osoby HIV+ mogą doświadczać deterioracji w funkcjonowaniu neuropoznawczym. Obecny stan wiedzy jest ograniczony na temat neuroinfekcyjnych działań wirusa HIV. Jednak przy użyciu nowych metod neuroobrazowania mózgu, takich jak badanie spoczynkowej aktywności mózgu w funkcjonalnym rezonansie magnetycznym (ang. resting state functional magnetic resonance imaging) możemy coraz lepiej opisać funkcjonalne podstawy mózgu przyczyniających się do klinicznego portretu zaburzeń neuropoznawczych w tej szczególnej grupie pacjentów. Do tej pory niewiele doniesień naukowych skierowanych było na badanie wpływu wieku i zakażenia wirusem HIV na stan spoczynkowy mózgu w odniesieniu do funkcji poznawczych. W związku z niespójnościami dotychczasowych doniesień, zagadnienie to pozostaje niewyjaśnione. To badanie miało na celu zbadanie efektów starzenia się i zakażenia wirusem HIV na stan spoczynkowy mózgu (RS) w stosunku do funkcjonowania poznawczego. Metoda: W badaniu przeanalizowano dane z ostatecznej liczby 108 uczestników między 25 a 75 rokiem życia, w tym 54 osoby HIV+ (średnia wieku = 41 lat; SD = 12 lat) oraz 54 demograficznie dopasowane osoby kontrolne HIV-seronegatywne (średnia wieku = 43 lata; SD = 12 lat), ze średnią 16 lat edukacji. Wszyscy uczestnicy HIV + byli na terapii HAART. Dane przeanalizowane w tym badaniu obejmowały dane spoczynkowego neuroobrazowania stanu mózgu (RS-fMRI) i dane neuropoznawcze z kompleksowego zestawu testów oceniających funkcje uwagi, funkcje wykonawcze, pamięć, funkcje psychomotoryczne i umiejętności semantyczne. Dane analizowano stosując podejście oparte na mózgowych regionach zainteresowania badawczego (ang. Regions of Interest-based analysis), analizy niezależnych komponentów (ang. Independent Component Analysis), i analizy opartej na wokselach (ang. Voxel-based analysis). Na podstawie wyników przekształconych (T) z testów poznawczych zostały skomponowane czynniki neuropoznawcze. Różnice pomiędzy grupami w RS i funkcjonowaniu poznawczym oceniano testem t. Dwuwymiarowe korelacje były użyte do zbadania relacji między wiekiem, RS, a czynnikami neuropoznawczymi. Wielokrotna analiza regresji liniowej przeprowadzona została w celu zbadania wpływu wieku i zakażenia wirusem HIV na relacje między spoczynkowa aktywnością mózgu (RS) a neuropoznawczą wydajnością. Wyniki: Grupa kontrolna, w zakresie połączeń funkcjonalnych (FC) w spoczynkowej aktywności mózgu oraz deterioracji funkcji neuropoznawczych, wykazała wzorce starzenia się porównywalne do ogólnej zdrowej populacji. Zakażenie wirusem HIV związane było z obniżeniem jak i z podwyższeniem RS-FC oraz pogorszeniem uwagi i umiejętności semantycznych w porównaniu z grupą kontrolną. Efekty interakcji wieku i zakażenia HIV były wykazane dla FC wewnątrz-sieciowych oraz między-sieciowych, które słabły wraz z wiekiem w grupie HIV+, a wzmacniały się wraz z wiekiem u zdrowych niezakażonych. Brak efektów interakcji wieku i wirusa HIV był wykazany dla czynników poznawczych. Wykazane zostały istotne relacje pomiędzy mocą połączeń RS-FC, które wykazały wrażliwość na skutki interakcji wieku i wirusa HIV, a wartością czynników neuropoznawczych. Wiek nie miał znaczącego wpływu jako moderator dla większości wykazanych relacji w grupie kontrolnej. Zakażenie wirusem HIV znacznie wpływało na związek między RS-FC a czynniki neuropoznawcze. Natomiast wiek w grupie HIV+ nie miał znaczących skutków jako moderator na relacje między RS-FC a czynnikami neuropoznawczymi. Wnioski: Obecne badanie dostarcza dowodów na to, że RS-fMRI jest czułą techniką mogącą ujawnić nie tylko efekty niezależne, ale również efekty interakcji wieku i zakażenia wirusem HIV na funkcjonowanie mózgu podczas braku jawnych procesów poznawczych. Wyniki tego badania dalej potwierdzają, że wiek i zakażenie wirusem HIV prowadzą do reorganizacji funkcjonalnej mózgu i spadku wydajności funkcji neuropoznawczych. Co ważne, badania to donosi o dowodach na wdrożenie kompensacyjnych mechanizmów mózgowych w populacji pacjentów starzejących się z wirusem HIV. Wyniki tego badania dowodzą o przeważającej słuszności hipotezy natężonego/skoncentrowanego (ang. accentuated) nad hipotezą przyspieszonego (ang. accelerated) starzenia się u osób żyjących z infekcją HIV.

Data acquisition for Magnetic Resonance Imaging (MRI) is usually expensive and time-consuming. Multi-site study enables pooling more data with less cost. However, the reliability of multi-site study is not guaranteed since the data acquired from different sites always introduces site related variations. Further, these variation can not be fully resolved even using the same imaging protocols. In this thesis, we propose a seed-based image processing and statistical analyzing pipeline which mitigates the variations brought by sites to a statistically insignificant level. We collect data from a same group of subjects on two different scanners where each subject undergoes two imaging session on each site. Seed-based correlations of BOLD timeseries are used to access the connectivity between the human brain regions and seed region. The results imply that images collected from the four visits generate similar results of seed-based connectivity. The variance brought by site-related factors, machine, visit and interaction are proved to be insignificant by ANOVA test. Moreover, principle component analysis (PCA) are performed in a manner that data are reconstructed where subject identifiability is maximized. It is shown that reconstructed data introduces less variance from interaction of machine and visit.

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2017
Imagiologia por ressonância magnética funcional (fMRI) tem-se afirmado como uma das técnicas mais relevantes ao nível do estudo da função cerebral. A elevada resolução espacial que caracteriza a generalidade das técnicas MRI tem motivado o uso da fMRI no mapeamento da resposta hemodinâmica cerebral. A resposta hemodinâmica é estimada pela fMRI através da aquisição dinâmica do contraste imagiológico dependente do nível de oxigenação do sangue (BOLD). A relação intrínseca entre a resposta hemodinâmica cerebral e a atividade neuronal tem levado ao uso das oscilações do sinal BOLD como ferramenta na análise da dinâmica espácio-temporal da função cerebral. O procedimento experimental em fMRI tem considerado a atividade cerebral espontânea que se verifica num estado de repouso, envolvendo por parte dos sujeitos testados a inibição consciente de qualquer tipo de esforço físico e mental. A aplicação da fMRI em estado de repouso (rs-fMRI) tem permitido investigar o modo como a atividade cerebral espontânea está organizada em redes neuronais do estado de repouso (RSNs), que por sua vez têm sido interpretadas como unidades funcionais da função cerebral. Neste contexto, o sinal BOLD gerado sob um estado de repouso (rs-BOLD) tem sido aplicado no estudo da conectividade funcional (FC) no ser humano, tendo permitido determinar as regiões de interesse (ROIs) que estabelecem as ligações internas e externas das RSNs. Técnicas de neuroimagiologia como a fMRI têm sido utilizadas de forma a compreender o desenvolvimento da função cerebral no ser humano. Particularmente, a investigação tem associado a adolescência a alterações significativas nos padrões espácio-temporais da atividade cerebral, que por sua vez tem sido interpretados como um efeito da maturação de RSNs associadas a estados cognitivos, emocionais e comportamentais. Num contexto clínico, o conhecimento do funcionamento saudável do cérebro adolescente tem sido motivado pela necessidade de diagnosticar distúrbios mentais ou desvios no decurso natural do desenvolvimento que tipicamente se manifestam durante esse período, como é o caso da esquizofrenia. Apesar do papel relevante dos métodos de FC, iniciativas ao nível da investigação em fMRI têm investido em soluções alternativas para análise da função cerebral. Um dos casos que demonstra esse esforço é a exploração das propriedades oscilatórias locais do sinal BOLD (BOLD-LOPs), que tem possibilitado a investigação da atividade intrínseca de cada ROI. As primeiras tentativas bem-sucedidas de análise das BOLD-LOPs basearam-se em medidas representativas da amplitude do sinal BOLD (BOLD-amp), como a média ou a variância. Efetivamente, a variância do sinal BOLD (BOLD-var) induzido pela execução de uma certa ação, tal como a rs-BOLD-var, têm demonstrado ser biomarcadores representativos da atividade intrínseca das RSNs. Adicionalmente, a investigação das BOLD-LOPs tem sido realizada através de análises ao poder espectral do sinal rs-BOLD (rs-BOLD-SPAs). As rs-BOLD-SPAs têm sido particularmente aplicadas com o objetivo de demonstrar que o poder espectral do sinal BOLD (BOLD-PS) é representado por um padrão independente da dimensão espacial considerada, corroborando a manifestação de propriedades livres de escala ao nível da atividade cerebral. A distribuição da lei da potência, que reflete as propriedades livres de escala de uma forma geral, tem sido utilizada na modelação do BOLD-PS. O expoente da lei da potência estimado para o sinal BOLD (BOLD-PLE) tem sido adotado como biomarcador da atividade intrínseca das RSNs, tendo contribuído para a relevância do estado de repouso na função cerebral. Ambos os biomarcadores representativos das rs-BOLD-LOPs, nomeadamente a rs-BOLD-amp e o rs-BOLD-PLE, têm sido analisados no contexto do desenvolvimento humano. No entanto, os ditos biomarcadores não têm sido considerados em estudos centrados nas alterações funcionais do cérebro adolescente. Nesse sentido, a dissertação de tese de mestrado aqui apresentada comprometeu-se a testar três medidas representativas das rs-BOLD-LOPs como biomarcadores do desenvolvimento da função cerebral ao longo da adolescência. O estágio realizado no âmbito desta dissertação de tese de mestrado teve lugar no Neuroimaging Research Group, sediado no Departamento de Psiquiatria do UMC Utrecht. A investigação levada a cabo teve em conta o largo conjunto de dados adquiridos pelo projecto BrainSCALE, que tem resultado de uma colaboração a longo prazo entre o Neuroimaging Research Group e o Netherlands Twin Register, VU University, Amesterdão. O objetivo do projeto BrainSCALE consiste em descrever o desenvolvimento cerebral ao nível cognitivo, estrutural e funcional que ocorre entre a infância e a fase adulta. O estágio realizado teve em consideração os dados longitudinais de MRI adquiridos na sequência do projeto BrainSCALE, para além das classificações do quociente de inteligência (IQ). Por definição, um estudo longitudinal caracteriza-se pela formação de uma amostra consistida num grupo de indivíduos periodicamente submetido a um certo protocolo experimental. Desta forma, é conferido um aumento de poder estatístico que advém da deteção de diferenças etárias ao nível de cada individuo da amostra. Concretamente, o projeto de tese de mestrado teve em consideração uma amostra formada por dois grupos de oitenta e um indivíduos, representando as fases do inicio da puberdade e da adolescência, respetivamente. Em relação à análise de dados, os três métodos foram desenhados de forma abranger dimensões distintas ao nível do espaço cerebral representado nos dados MRI. Desta forma, foi possível testar as medidas de rs-BOLD-LOP associadas à matéria cinzenta (GM) de uma forma geral, tal como a análise de medidas referentes a uma representação especifica das RSNs corticais e das ROIs individuais que as integram. O primeiro método teve como hipótese testar eventuais diferenças entre medidas de rs-BOLD-amp estimadas para os dois grupos da amostra. As comparações entre grupos foram realizadas através do uso de dois tipos de medidas de rs-BOLD-amp, estimadas para sinal BOLD obtido previamente e após a remoção de ruído, respetivamente. Apesar de se assumir a não fiabilidade da rs-BOLD-amp sem a dita remoção, seria uma vantagem do ponto de vista técnico tirar partido do poder estatístico conferido pelo largo de conjunto de dados longitudinais aqui testado. Contando com os artefactos associados à comparação de grupos etários distintos, diferenças significativas ao nível da rs-BOLD-amp com e sem ruído contribuiria para a evidência de um fundamento biológico nos resultados obtidos, não havendo uma influência maioritária de tipos de ruído que não advém dos sujeitos testados. Ao contrário do primeiro método, os dois métodos restantes focaram-se exclusivamente no sinal rs-BOLD resultante da remoção de ruído. Concretamente, o segundo método consistiu numa rs-BOLD-SPA, que foi desenhada no sentido de comparar rs-BOLD-PLEs estimados para os dois grupos da amostra, de forma a corroborar a influência do desenvolvimento ao longo da adolescência nesta medida. A estimação dos rs-BOLD-PLEs para cada ROI e cada sujeito da amostra envolveu o escalamento da distribuição dos rs-BOLD-PSs com base na distribuição da lei da potência. Posteriormente, os rs-BOLD-PLEs correspondentes às duas faixas etárias foram comparados com a finalidade de demonstrar diferenças entre grupos nas distribuições dos rs-BOLD-PSs, especificamente ao nível das frequências mais baixas do espectro de oscilações de sinal rs-BOLD de interesse. Por último, o terceiro método teve como motivação analisar a relação entre as rs-BOLD-LOPs e a função cognitiva em desenvolvimento. Concretamente, foi testada a correlação entre a rs-BOLD-var e o IQ de performance (PIQ) nos dois grupos da amostra, tendo sido realizada a estimação da rs-BOLD-var com base exclusiva nas séries temporais de rs-BOLD obtidas após a remoção de ruído. Considerando o PIQ como uma variável representativa do potencial de um individuo na execução de certas ações, pretendia-se que este método evidenciasse a significância das correlações testadas durante a adolescência. Quanto aos resultados, a análise da rs-BOLD-amp indicou a presença de diferenças entre grupos ao nível de medidas com e sem remoção de ruido. Nos dois casos, as comparações entre grupos destacaram alterações na GM de uma forma geral, e mais especificamente ao nível da rede límbica (LN). Em relação à rs-BOLD-SPA, foram verificadas diferenças significativas nos rs-BOLD-PLEs representativos da LN, das redes frontoparietal (FPN) e default mode (DMN), verificando-se um efeito do desenvolvimento ao longo da adolescência nas alterações de rs-BOLD-PS de frequências mais baixas. Relativamente à correlação entre a rs-BOLD-var e o PIQ, a evidência de uma tendência de correlação negativa verificou-se durante a adolescência na GM e a vários níveis do espaço cortical. Especificamente, a população adolescente foi associada a correlações com relativa significância na rede de atenção ventral (VAN), na LN e na DMN. No cômputo geral, os métodos de análise de dados, implementados nesta dissertação de tese de mestrado, promoveram o papel das rs-BOLD-LOPs na investigação do desenvolvimento da função cerebral ao longo da adolescência.
Resting-state functional magnetic resonance imaging (rs-fMRI) has played a significant role in the understanding of brain functioning. Mapping brain hemodynamic response, which is estimated by the blood-oxygenation-level-dependent (BOLD) contrast acquired in the fMRI acquisition, has been widely applied to the description of human development. However, there is up to date a lack of developmental rs-fMRI research testing functional changes represented in local oscillatory properties of resting-state BOLD signal (rs-BOLD-LOP), which are thought to reflect spontaneous brain activity intrinsic to regions of interest (ROIs). Thus, the study here reported aimed to test measures based on rs-BOLD-LOPs as suitable developmental biomarkers, which potentially represent brain functional changes throughout adolescence. A longitudinal sample and the respective rs-fMRI data were considered in three methods of data analysis, each one implemented so as to validate developmental biomarkers representative of intrinsic activity at distinct dimensional levels within the whole-brain gray matter (GM). Firstly, we tested age differences in rs-BOLD amplitude (rs-BOLD-amp) measures provided by a large dataset for two processing stages, which preceded and followed rs-fMRI data denoising, respectively. Secondly, scale-free properties in brain functioning were considered in a rs-BOLD spectral power analysis (rs-BOLD-SPA), which involved the fitting of the denoised rs-BOLD power spectrum (rs-BOLD-PS) to the power-law distribution. Age differences in rs-BOLD power-law exponents (rs-BOLD-PLEs) were investigated so as to find developmental changes in low-frequency rs-BOLD-PSs. Thirdly, we aimed to investigate whether rs-BOLD-LOPs are associated with cognitive functioning, by establishing the correlation between denoised rs-BOLD variance (rs-BOLD-var) and performance intelligence quotient (PIQ), which was assumed to represent general cognitive performance. The correlations obtained by the two age groups, which composed the longitudinal sample here tested, were thought to provide relevant information regarding development throughout adolescence. Age differences were confirmed after comparing rs-BOLD-amp measures, which were found both before and after denoising. Whole-brain GM and limbic network (LN) were reported as the ROIs that presented significant differences in rs-BOLD-amp measures for both processing stages. Further, the rs-BOLD-SPA here carried out detected age-group-differences in the LN, frontoparietal network (FPN) and default mode network (DMN) rs-BOLD-PLEs. Findings obtained by rs-BOLD-SPA were interpreted as a developmental alteration in the proportion of low-frequency rs-BOLD-PSs throughout adolescence. Finally, testing the correlation between rs-BOLD-var and PIQ led to evidence of a negative trend that was generally manifested in the whole-brain GM. With special emphasis on the resting-state network (RSN) level, the negative correlations in the ventral attention network (VAN), LN, and DMN were significant during adolescence. All the approaches here tested demonstrated the influence of human development on rs-BOLD-LOPs, which has strengthened the role of this kind of measures in investigating the functional brain throughout adolescence.

New paradigms are developed in magnetic resonance imaging for the advanced diagnosis of neurodegenerative diseases. In particular, multiple sclerosis (MS) and amyotrophic lateral sclerosis (ALS) preclinical research poorly focuses on functional connectivity in brain. Available animal models of MS and ALS are extensively used for analysis such drug testing and discovery of underlying mechanisms of pathogenesis. These diseases present, since neuronal lesions formation and neuroinflammation, a multilevel heterogeneity in mechanism of neurodegeneration and brain connectivity still not well understood. Moreover, they play a key role in pharmacological research, from the identification of a therapy target to the in vivo validation of the efficacy. More recently alterations in synchronized brain activity at rest in MS patients have been reported. At the best of our knowledge, functional imaging has not been applied yet in the assessment of new therapies in the preclinical models for MS and ALS. In this study, we aim to develop an innovative platform based on functional MRI in the resting state (rsfMRI), for the pre-clinical evaluation of new markers in MS and ALS. Moreover, the advancing in MRI techniques could assess new criteria of sensitivity and specificity in diagnosis; an additional analysis on diffusion MRI outcomes in MS preclinical models is added to this study.