986 resultados para Voxel-based morphometry
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Il presente lavoro è stato svolto presso la struttura di Fisica Medica dell'Azienda Ospedaliera IRCCS "Arcispedale S. Maria Nuova" di Reggio Emilia e consiste nello sviluppo di un sistema per l'ottimizzazione della dose in Radioterapia tramite dose-painting basato sui voxel. Il dose painting è una tecnica di pianificazione del trattamento di radioterapia che si basa sull'assegnazione o ridistribuzione della dose secondo le informazioni biologiche e metaboliche che i moderni sistemi di imaging sono in grado di fornire. La realizzazione del modulo di calcolo BioOPT è stata possibile grazie all'utilizzo dei due software open-source Plastimatch e CERR, specifici per l'elaborazione e la registrazione di immagini mediche di diversi tipi e formati e per la gestione, la modifica e il salvataggio di piani di trattamento di radioterapia creati con la maggior parte dei software commerciali ed accademici. Il sistema sviluppato è in grado di registrare le immagini relative ad un paziente, in generale ottenute da diverse tipologie di imaging e acquisite in tempi diversi ed estrarre le informazioni biologiche relative ad una certa struttura. Tali informazioni verranno poi utilizzate per calcolare le distribuzioni di dose "ottimale" che massimizzano il valore delle funzioni radiobiologiche utilizzate per guidare il processo di redistribuzione della dose a livello dei voxel (dose-painting). In questo lavoro il modulo è stato utilizzato principalmente per l'ottimizzazione della dose in pazienti affetti da Glioblastoma, un tumore cerebrale maligno tra i più diffusi e mortali. L'ottimizzatore voxel-based, infatti, è stato sviluppato per essere utilizzabile all'interno di un progetto di ricerca finanziato dal Ministero della Salute per la valutazione di un programma di terapia che include l'uso di un innovativo acceleratore lineare ad alto rateo di dose per la cura di tumori cerebrali in fase avanzata. Al fine di migliorare il trattamento radiante, inoltre, lo studio include la somministrazione della dose tramite dose-painting con lo scopo di verificarne l'efficacia. I risultati ottenuti mostrano che tramite il modulo sviluppato è possibile ottenere distribuzioni di dose eterogenee che tengono conto delle caratteristiche biologiche intratumore stimate a partire dalle immagini multimodali. Inoltre il sistema sviluppato, grazie alla sua natura 'open', è altamente personalizzabile a scopi di ricerca e consente di simulare distribuzioni di dose basate sui voxel e di confrontarle con quelle ottenute con i sistemi commerciali ad uso clinico, che non consentono questo tipo di ottimizzazioni.
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Preclinical studies using animal models have shown that grey matter plasticity in both perilesional and distant neural networks contributes to behavioural recovery of sensorimotor functions after ischaemic cortical stroke. Whether such morphological changes can be detected after human cortical stroke is not yet known, but this would be essential to better understand post-stroke brain architecture and its impact on recovery. Using serial behavioural and high-resolution magnetic resonance imaging (MRI) measurements, we tracked recovery of dexterous hand function in 28 patients with ischaemic stroke involving the primary sensorimotor cortices. We were able to classify three recovery subgroups (fast, slow, and poor) using response feature analysis of individual recovery curves. To detect areas with significant longitudinal grey matter volume (GMV) change, we performed tensor-based morphometry of MRI data acquired in the subacute phase, i.e. after the stage compromised by acute oedema and inflammation. We found significant GMV expansion in the perilesional premotor cortex, ipsilesional mediodorsal thalamus, and caudate nucleus, and GMV contraction in the contralesional cerebellum. According to an interaction model, patients with fast recovery had more perilesional than subcortical expansion, whereas the contrary was true for patients with impaired recovery. Also, there were significant voxel-wise correlations between motor performance and ipsilesional GMV contraction in the posterior parietal lobes and expansion in dorsolateral prefrontal cortex. In sum, perilesional GMV expansion is associated with successful recovery after cortical stroke, possibly reflecting the restructuring of local cortical networks. Distant changes within the prefrontal-striato-thalamic network are related to impaired recovery, probably indicating higher demands on cognitive control of motor behaviour.
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Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain The underlying structural basis of this functional connectivity pattern is still widely unexplored We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure e 7 underlying default mode connectivity We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data Would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus With lateral temporal lobes, medial temporal lobes, and precuneus This was demonstrated at the p<0001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data Out findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based oil distinct pattern of anatomical connectivity within the cerebral white matter (C) 2009 Elsevier Inc All rights reserved
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Few studies have investigated in vivo changes of the cholinergic basal forebrain in Alzheimer`s disease (AD) and amnestic mild cognitive impairment (MCI), an at risk stage of AD. Even less is known about alterations of cortical projecting fiber tracts associated with basal forebrain atrophy. In this study, we determined regional atrophy within the basal forebrain in 21 patients with AD and 16 subjects with MCI compared to 20 healthy elderly subjects using deformation-based morphometry of MRI scans. We assessed effects of basal forebrain atrophy on fiber tracts derived from high-resolution diffusion tensor imaging (DTI) using tract-based spatial statistics. We localized significant effects relative to a map of cholinergic nuclei in MRI standard space as determined from a postmortem brain. Patients with AD and MCI subjects showed reduced volumes in basal forebrain areas corresponding to anterior medial and lateral, intermediate and posterior nuclei of the Nucleus basalis of Meynert (NbM) as well as in the diagonal band of Broca nuclei (P < 0.01). Effects in MCI subjects were spatially more restricted than in AD, but occurred at similar locations. The volume of the right antero-lateral NbM nucleus was correlated with intracortical projecting fiber tract integrity such as the corpus callosum, cingulate, and the superior longitudinal, inferior longitudinal, inferior fronto-occipital, and uncinate fasciculus (P < 0.05, corrected for multiple comparisons). Our findings suggest that a multimodal MRI-DTI approach is supportive to determine atrophy of cholinergic nuclei and its effect on intracortical projecting fiber tracts in AD. Hum Brain Mapp 32: 1349-1362, 2011. (C) 2010 Wiley-Liss, Inc.
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OBJECTIVE: To examine the relationship between reward sensitivity and self-reported apathy in stroke patients and to investigate the neuroanatomical correlates of both reward sensitivity and apathy. METHODS: In this prospective study, 55 chronic stroke patients were administered a questionnaire to assess apathy and a laboratory task to examine reward sensitivity by measuring motivationally driven behavior ("reinforcement-related speeding"). Fifteen participants without brain damage served as controls for the laboratory task. Negative mood, working memory, and global cognitive functioning were also measured to determine whether reward insensitivity and apathy were secondary to cognitive impairments or negative mood. Voxel-based lesion-symptom mapping was used to explore the neuroanatomical substrates of reward sensitivity and apathy. RESULTS: Participants showed reinforcement-related speeding in the highly reinforced condition of the laboratory task. However, this effect was significant for the controls only. For patients, poorer reward sensitivity was associated with greater self-reported apathy (p < 0.05) beyond negative mood and after lesion size was controlled for. Neither apathy nor reward sensitivity was related to working memory or global cognitive functioning. Voxel-based lesion-symptom mapping showed that damage to the ventral putamen and globus pallidus, dorsal thalamus, and left insula and prefrontal cortex was associated with poorer reward sensitivity. The putamen and thalamus were also involved in self-reported apathy. CONCLUSIONS: Poor reward sensitivity in stroke patients with damage to the ventral basal ganglia, dorsal thalamus, insula, or prefrontal cortex constitutes a core feature of apathy. These results provide valuable insight into the neural mechanisms and brain substrate underlying apathy.
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In humans, touching the skin is known to activate, among others, the contralateral primary somatosensory cortex on the postcentral gyrus together with the bilateral parietal operculum (i.e. the anatomical site of the secondary somatosensory cortex). But which brain regions beyond the postcentral gyrus specifically contribute to the perception of touch remains speculative. In this study we collected structural magnetic resonance imaging scans and neurological examination reports of patients with brain injuries or stroke in the left or right hemisphere, but not in the postcentral gyrus as the entry site of cortical somatosensory processing. Using voxel-based lesion-symptom mapping, we compared patients with impaired touch perception (i.e. hypoaesthesia) to patients without such touch impairments. Patients with hypoaesthesia as compared to control patients differed in one single brain cluster comprising the contralateral parietal operculum together with the anterior and posterior insular cortex, the putamen, as well as subcortical white matter connections reaching ventrally towards prefrontal structures. This finding confirms previous speculations on the 'ventral pathway of somatosensory perception' and causally links these brain structures to the perception of touch.
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Pantomimes of object use require accurate representations of movements and a selection of the most task-relevant gestures. Prominent models of praxis, corroborated by functional neuroimaging studies, predict a critical role for left parietal cortices in pantomime and advance that these areas store representations of tool use. In contrast, lesion data points to the involvement of left inferior frontal areas, suggesting that defective selection of movement features is the cause of pantomime errors. We conducted a large-scale voxel-based lesion-symptom mapping analyses with configural/spatial (CS) and body-part-as-object (BPO) pantomime errors of 150 left and right brain-damaged patients. Our results confirm the left hemisphere dominance in pantomime. Both types of error were associated with damage to left inferior frontal regions in tumor and stroke patients. While CS pantomime errors were associated with left temporoparietal lesions in both stroke and tumor patients, these errors appeared less associated with parietal areas in stroke than in tumor patients and less associated with temporal in tumor than stroke patients. BPO errors were associated with left inferior frontal lesions in both tumor and stroke patients. Collectively, our results reveal a left intrahemispheric dissociation for various aspects of pantomime, but with an unspecific role for inferior frontal regions.
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OBJECTIVE: Previous studies reported that the severity of cognitive deficits in euthymic patients with bipolar disorder (BD) increases with the duration of illness and postulated that progressive neuronal loss or shrinkage and white matter changes may be at the origin of this phenomenon. To explore this issue, the authors performed a case-control study including detailed neuropsychological and magnetic resonance imaging analyses in 17 euthymic elderly patients with BD and 17 healthy individuals. METHODS: Neuropsychological evaluation concerned working memory, episodic memory, processing speed, and executive functions. Volumetric estimates of the amygdala, hippocampus, entorhinal cortex, and anterior cingulate cortex were obtained using both voxel-based and region of interest morphometric methods. Periventricular and deep white matter were assessed semiquantitatively. Differences in cognitive performances and structural data between BD and comparison groups were analyzed using paired t-test or analysis of variance. Wilcoxon test was used in the absence of normal distribution. RESULTS: Compared with healthy individuals, patients with BD obtained significantly lower performances in processing speed, working memory, and episodic memory but not in executive functions. Morphometric analyses did not show significant volumetric or white matter differences between the two groups. CONCLUSIONS: Our results revealed impairment in verbal memory, working memory, and processing speed in euthymic older adults with BD. These cognitive deficits are comparable both in terms of affected functions and size effects to those previously reported in younger cohorts with BD. Both this observation and the absence of structural brain abnormalities in our cohort do not support a progressively evolving neurotoxic effect in BD.
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INTRODUCTION Functional imaging studies of addiction following protracted abstinence have not been systematically conducted to look at the associations between severity of use of different drugs and brain dysfunction. Findings from such studies may be relevant to implement specific interventions for treatment. The aim of this study was to examine the association between resting-state regional brain metabolism (measured with 18F-fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and the severity of use of cocaine, heroin, alcohol, MDMA and cannabis in a sample of polysubstance users with prolonged abstinence from all drugs used. METHODS Our sample consisted of 49 polysubstance users enrolled in residential treatment. We conducted correlation analyses between estimates of use of cocaine, heroin, alcohol, MDMA and cannabis and brain metabolism (BM) (using Statistical Parametric Mapping voxel-based (VB) whole-brain analyses). In all correlation analyses conducted for each of the drugs we controlled for the co-abuse of the other drugs used. RESULTS The analysis showed significant negative correlations between severity of heroin, alcohol, MDMA and cannabis use and BM in the dorsolateral prefrontal cortex (DLPFC) and temporal cortex. Alcohol use was further associated with lower metabolism in frontal premotor cortex and putamen, and stimulants use with parietal cortex. CONCLUSIONS Duration of use of different drugs negatively correlated with overlapping regions in the DLPFC, whereas severity of cocaine, heroin and alcohol use selectively impact parietal, temporal, and frontal-premotor/basal ganglia regions respectively. The knowledge of these associations could be useful in the clinical practice since different brain alterations have been associated with different patterns of execution that may affect the rehabilitation of these patients.
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Introduction: Neuroimaging of the self focused on high-level mechanisms such as language, memory or imagery of the self. Recent evidence suggests that low-level mechanisms of multisensory and sensorimotor integration may play a fundamental role in encoding self-location and the first-person perspective (Blanke and Metzinger, 2009). Neurological patients with out-of body experiences (OBE) suffer from abnormal self-location and the first-person perspective due to a damage in the temporo-parietal junction (Blanke et al., 2004). Although self-location and the first-person perspective can be studied experimentally (Lenggenhager et al., 2009), the neural underpinnings of self-location have yet to be investigated. To investigate the brain network involved in self-location and first-person perspective we used visuo-tactile multisensory conflict, magnetic resonance (MR)-compatible robotics, and fMRI in study 1, and lesion analysis in a sample of 9 patients with OBE due to focal brain damage in study 2. Methods: Twenty-two participants saw a video showing either a person's back or an empty room being stroked (visual stimuli) while the MR-compatible robotic device stroked their back (tactile stimulation). Direction and speed of the seen stroking could either correspond (synchronous) or not (asynchronous) to those of the seen stroking. Each run comprised the four conditions according to a 2x2 factorial design with Object (Body, No-Body) and Synchrony (Synchronous, Asynchronous) as main factors. Self-location was estimated using the mental ball dropping (MBD; Lenggenhager et al., 2009). After the fMRI session participants completed a 6-item adapted from the original questionnaire created by Botvinick and Cohen (1998) and based on questions and data obtained by Lenggenhager et al. (2007, 2009). They were also asked to complete a questionnaire to disclose the perspective they adopted during the illusion. Response times (RTs) for the MBD and fMRI data were analyzed with a 3-way mixed model ANOVA with the in-between factor Perspective (up, down) and the two with-in factors Object (body, no-body) and Stroking (synchronous, asynchronous). Quantitative lesion analysis was performed using MRIcron (Rorden et al., 2007). We compared the distributions of brain lesions confirmed by multimodality imaging (Knowlton, 2004) in patients with OBE with those showing complex visual hallucinations involving people or faces, but without any disturbance of self-location and first person perspective. Nine patients with OBE were investigated. The control group comprised 8 patients. Structural imaging data were available for normalization and co-registration in all the patients. Normalization of each patient's lesion into the common MNI (Montreal Neurological Institute) reference space permitted simple, voxel-wise, algebraic comparisons to be made. Results: Even if in the scanner all participants were lying on their back and were facing upwards, analysis of perspective showed that half of the participants had the impression to be looking down at the virtual human body below them, despite any cues about their body position (Down-group). The other participants had the impression to be looking up at the virtual body above them (Up-group). Analysis of Q3 ("How strong was the feeling that the body you saw was you?") indicated stronger self-identification with the virtual body during the synchronous stroking. RTs in the MBD task confirmed these subjective data (significant 3-way interaction between perspective, object and stroking). fMRI results showed eight cortical regions where the BOLD signal was significantly different during at least one of the conditions resulting from the combination of Object and Stroking, relative to baseline: right and left temporo-parietal junction, right EBA, left middle occipito-temporal gyrus, left postcentral gyrus, right medial parietal lobe, bilateral medial occipital lobe (Fig 1). The activation patterns in right and left temporo-parietal junction and right EBA reflected changes in self-location and perspective as revealed by statistical analysis that was performed on the percentage of BOLD change with respect to the baseline. Statistical lesion overlap comparison (using nonparametric voxel based lesion symptom mapping) with respect to the control group revealed the right temporo-parietal junction, centered at the angular gyrus (Talairach coordinates x = 54, y =-52, z = 26; p>0.05, FDR corrected). Conclusions: The present questionnaire and behavioural results show that - despite the noisy and constraining MR environment) our participants had predictable changes in self-location, self-identification, and first-person perspective when robotic tactile stroking was applied synchronously with the robotic visual stroking. fMRI data in healthy participants and lesion data in patients with abnormal self-location and first-person perspective jointly revealed that the temporo-parietal cortex especially in the right hemisphere encodes these conscious experiences. We argue that temporo-parietal activity reflects the experience of the conscious "I" as embodied and localized within bodily space.
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Aim of the present article was to perform three-dimensional (3D) single photon emission tomography-based dosimetry in radioimmunotherapy (RIT) with (90)Y-ibritumomab-tiuxetan. A custom MATLAB-based code was used to elaborate 3D images and to compare average 3D doses to lesions and to organs at risk (OARs) with those obtained with planar (2D) dosimetry. Our 3D dosimetry procedure was validated through preliminary phantom studies using a body phantom consisting of a lung insert and six spheres with various sizes. In phantom study, the accuracy of dose determination of our imaging protocol decreased when the object volume decreased below 5 mL, approximately. The poorest results were obtained for the 2.58 mL and 1.30 mL spheres where the dose error evaluated on corrected images with regard to the theoretical dose value was -12.97% and -18.69%, respectively. Our 3D dosimetry protocol was subsequently applied on four patients before RIT with (90)Y-ibritumomab-tiuxetan for a total of 5 lesions and 4 OARs (2 livers, 2 spleens). In patient study, without the implementation of volume recovery technique, tumor absorbed doses calculated with the voxel-based approach were systematically lower than those calculated with the planar protocol, with average underestimation of -39% (range from -13.1% to -62.7%). After volume recovery, dose differences reduce significantly, with average deviation of -14.2% (range from -38.7.4% to +3.4%, 1 overestimation, 4 underestimations). Organ dosimetry in one case overestimated, in the other underestimated the dose delivered to liver and spleen. However, both for 2D and 3D approach, absorbed doses to organs per unit administered activity are comparable with most recent literature findings.
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Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer - MT, from healthy subjects (n=96, aged 21-88 years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.
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BACKGROUND: Whether or not cognitive impairment and brain structure changes are trait characteristics of late-life depression is still disputed. Previous studies led to conflicting data possibly because of the difference in the age of depression onset. In fact, several lines of evidence suggest that late-onset depression (LOD) is more frequently associated with neuropsychological deficits and brain pathology than early-onset depression (EOD). To date, no study explored concomitantly the cognitive profile and brain magnetic resonance imaging (MRI) patterns in euthymic EOD and LOD patients. METHOD: Using a cross-sectional design, 41 remitted outpatients (30 with EOD and 11 with LOD) were compared to 30 healthy controls. Neuropsychological evaluation concerned working memory, episodic memory, processing speed, naming capacity and executive functions. Volumetric estimates of the amygdala, hippocampus, entorhinal and anterior cingulate cortex were obtained using both voxel-based and region of interest morphometric methods. White matter hyperintensities were assessed semiquantitatively. RESULTS: Both cognitive performance and brain volumes were preserved in euthymic EOD patients whereas LOD patients showed a significant reduction of episodic memory capacity and a higher rate of periventricular hyperintensities compared to both controls and EOD patients. CONCLUSION: Our results support the dissociation between EOD thought to be mainly related to psychosocial factors and LOD that is characterized by increasing vascular burden and episodic memory decline.
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Detailed knowledge of the anatomy and connectivity pattern of cortico-basal ganglia circuits is essential to an understanding of abnormal cortical function and pathophysiology associated with a wide range of neurological and neuropsychiatric diseases. We aim to study the spatial extent and topography of human basal ganglia connectivity in vivo. Additionally, we explore at an anatomical level the hypothesis of coexistent segregated and integrative cortico-basal ganglia loops. We use probabilistic tractography on magnetic resonance diffusion weighted imaging data to segment basal ganglia and thalamus in 30 healthy subjects based on their cortical and subcortical projections. We introduce a novel method to define voxel-based connectivity profiles that allow representation of projections from a source to more than one target region. Using this method, we localize specific relay nuclei within predefined functional circuits. We find strong correlation between tractography-based basal ganglia parcellation and anatomical data from previously reported invasive tracing studies in nonhuman primates. Additionally, we show in vivo the anatomical basis of segregated loops and the extent of their overlap in prefrontal, premotor, and motor networks. Our findings in healthy humans support the notion that probabilistic diffusion tractography can be used to parcellate subcortical gray matter structures on the basis of their connectivity patterns. The coexistence of clearly segregated and also overlapping connections from cortical sites to basal ganglia subregions is a neuroanatomical correlate of both parallel and integrative networks within them. We believe that this method can be used to examine pathophysiological concepts in a number of basal ganglia-related disorders.
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Computational anatomy with magnetic resonance imaging (MRI) is well established as a noninvasive biomarker of Alzheimer's disease (AD); however, there is less certainty about its dependency on the staging of AD. We use classical group analyses and automated machine learning classification of standard structural MRI scans to investigate AD diagnostic accuracy from the preclinical phase to clinical dementia. Longitudinal data from the Alzheimer's Disease Neuroimaging Initiative were stratified into 4 groups according to the clinical status-(1) AD patients; (2) mild cognitive impairment (MCI) converters; (3) MCI nonconverters; and (4) healthy controls-and submitted to a support vector machine. The obtained classifier was significantly above the chance level (62%) for detecting AD already 4 years before conversion from MCI. Voxel-based univariate tests confirmed the plausibility of our findings detecting a distributed network of hippocampal-temporoparietal atrophy in AD patients. We also identified a subgroup of control subjects with brain structure and cognitive changes highly similar to those observed in AD. Our results indicate that computational anatomy can detect AD substantially earlier than suggested by current models. The demonstrated differential spatial pattern of atrophy between correctly and incorrectly classified AD patients challenges the assumption of a uniform pathophysiological process underlying clinically identified AD.