Recent advances in diffusion weighted image acquisition and processing allow for the construction of anatomically highly precise structural connectomes. In this study, we introduce a method to compute high-resolution whole-brain structural connectome. Our method relies on cortical and subcortical triangulated surface models, and on a large number of fiber tracts generated using a probabilistic tractography algorithm. Each surface triangle is a node of the structural connectivity graph while edges are fiber tract densities across pairs of nodes. Surface-based registration and downsampling to a common surface space are introduced for group analysis whereas connectome surface smoothing aimed at improving whole-brain network estimate reliability. Based on 10 datasets acquired from a single healthy subject, we evaluated the effects of repeated probabilistic tractography, surface smoothing, surface registration and downsampling to the common surface space. We show that, provided enough fiber tracts and surface smoothing, good to excellent intra-acquisition reliability could be achieved. Surface registration and downsampling efficiently established triangle-to-triangle correspondence across acquisitions and high inter-acquisition reliability was obtained. Computational time and disk/memory usages were monitored throughout the steps. Although further testing on large cohort of subjects is required, our method presents the potential to accurately model whole-brain structural connectivity at high-resolution.
Objective: Patients with temporal lobe epilepsy (TLE) have impaired theory of mind (ToM). However, ToM involves a variety of processes, such as understanding a person's intentions ("cognitive" ToM) and emotional states ("affective" ToM). The objectives of the present study were to characterize ToM disorders in TLE patients, identify patients at risk of ToM disorders, and study the relationships between psychobehavioral and quality of life factors and ToM disorders. Method: Fifty TLE patients and 50 controls performed ToM tasks assessing their understanding of verbal clumsiness (faux pas), sarcastic remarks, and mentalistic actions. Demographic, cognitive, and psychobehavioral data, and (for TLE patients) clinical and quality of life factors, were recorded. Results: Compared with controls, TLE patients showed impairments in all ToM tasks: 84% misunderstood faux pas, and around 50% misunderstood sarcasm. A long duration of epilepsy and young age at onset were risk factors for ToM impairments. In TLE patients, ToM impairments were associated with impaired empathy and anhedonia. Their affective states were less positively and more negatively valenced than in controls. Low positive affectivity was predictive of greater cognitive and affective ToM impairments for the faux pas task, and high negative affectivity was predictive of greater cognitive ToM abilities for the sarcasm task. The lack of social support was correlated with impaired ToM but was not a predictive factor. Conclusions: Both cognitive and affective ToM processes are impaired in TLE patients. Impaired ToM has an impact on empathy abilities and is related to affective disturbances in TLE patients. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm(3), b = 700 s/mm(2), 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.
Simultaneous recording of electroencephalogram and functional MRI (EEG-fMRI) is a powerful tool for localizing epileptic networks via the detection of hemodynamic changes correlated with interictal epileptic discharges (IEDs). fMRI can be used to study the long-lasting effect of epileptic activity by assessing stationary functional connectivity during the resting-state period [especially, the connectivity of the default mode network (DMN)]. Temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) are associated with low responsiveness and disruption of DMN activity. A dynamic functional connectivity approach might enable us to determine the effect of IEDs on DMN connectivity and to better understand the correlation between DMN connectivity changes and altered consciousness.
Large-scale longitudinal multi-site MRI brain morphometry studies are becoming increasingly crucial to characterize both normal and clinical population groups using fully automated segmentation tools. The test-retest reproducibility of morphometry data acquired across multiple scanning sessions, and for different MR vendors, is an important reliability indicator since it defines the sensitivity of a protocol to detect longitudinal effects in a consortium. There is very limited knowledge about how across-session reliability of morphometry estimates might be affected by different 3T MRI systems. Moreover, there is a need for optimal acquisition and analysis protocols in order to reduce sample sizes. A recent study has shown that the longitudinal FreeSurfer segmentation offers improved within session test-retest reproducibility relative to the cross-sectional segmentation at one 3T site using a nonstandard multi-echo MPRAGE sequence. In this study we implement a multi-site 3T MRI morphometry protocol based on vendor provided T1 structural sequences from different vendors (3D MPRAGE on Siemens and Philips, 3D IR-SPGR on GE) implemented in 8 sites located in 4 European countries. The protocols used mild acceleration factors (1.5-2) when possible. We acquired across-session test-retest structural data of a group of healthy elderly subjects (5 subjects per site) and compared the across-session reproducibility of two full-brain automated segmentation methods based on either longitudinal or cross-sectional FreeSurfer processing. The segmentations include cortical thickness, intracranial, ventricle and subcortical volumes. Reproducibility is evaluated as absolute changes relative to the mean (%), Dice coefficient for volume overlap and intraclass correlation coefficients across two sessions. We found that this acquisition and analysis protocol gives comparable reproducibility results to previous studies that used longer acquisitions without acceleration. We also show that the longitudinal processing is systematically more reliable across sites regardless of MRI system differences. The reproducibility errors of the longitudinal segmentations are on average approximately half of those obtained with the cross sectional analysis for all volume segmentations and for entorhinal cortical thickness. No significant differences in reliability are found between the segmentation methods for the other cortical thickness estimates. The average of two MPRAGE volumes acquired within each test-retest session did not systematically improve the across-session reproducibility of morphometry estimates. Our results extend those from previous studies that showed improved reliability of the longitudinal analysis at single sites and/or with non-standard acquisition methods. The multi-site acquisition and analysis protocol presented here is promising for clinical applications since it allows for smaller sample sizes per MRI site or shorter trials in studies evaluating the role of potential biomarkers to predict disease progression or treatment effects.
Interstitial photodynamic therapy is becoming an interesting modality to treat some early stage prostate cancers. A light-sensitive drug is injected to the patient and activated by light using optical fibres inserted inside the prostate. In this work, we were interested in the characterization of the light action model for the WST11 (Tookad® Soluble) drug. A retrospective analysis was performed on results from 28 patients enrolled in phase I and II trials with the WST11 drug. A drug dose of 4 mg/kg patient, dose light of 200 J cm(-1) and wavelength of 753 nm were used. Correlation between the illuminated volume and the obtained necrosis, measured at day 7 MR images, was clearly established. This result suggests that photodynamic therapy planning is possible based on this model.
18F-fluorodeoxyglucose positron emission tomography (18FDG PET) has become an essential technique in oncology. Accurate segmentation and uptake quantification are crucial in order to enable objective follow-up, the optimization of radiotherapy planning, and therapeutic evaluation. We have designed and evaluated a new, nearly automatic and operator-independent segmentation approach. This incorporated possibility theory, in order to take into account the uncertainty and inaccuracy inherent in the image. The approach remained independent of PET facilities since it did not require any preliminary calibration. Good results were obtained from phantom images [percent error =18.38% (mean) ± 9.72% (standard deviation)]. Results on simulated and anatomopathological data sets were quantified using different similarity measures and showed the method was efficient (simulated images: Dice index =82.18% ± 13.53% for SUV =2.5 ). The approach could, therefore, be an efficient and robust tool for uptake volume segmentation, and lead to new indicators for measuring volume of interest activity.
To assess the extent of brain involvement during focal epileptic activity, we studied patterns of cortical and subcortical metabolic changes coinciding with interictal epileptic discharges (IEDs) using group analysis of simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) scans in patients with focal epilepsy.
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