Striosomes and matrix are two compartments that comprise the striatum, each having its own distinct immunohistochemical properties, function, and connectivity. It is currently not clear whether prodromal or early manifest Parkinson's disease (PD) is associated with any striatal matrix or striosomal abnormality. Recently, a method of striatal parcellation using probabilistic tractography has been described and validated, using the distinct connectivity of these two compartments to identify voxels with striosome- and matrix-like connectivity. The goal of this study was to use this approach in tandem with DAT-SPECT, a method used to quantify the level of nigrostriatal denervation, to analyze the striatum in populations of de novo diagnosed, treatment-naïve patients with PD, isolated REM behavioral disorder (iRBD) patients, and healthy controls. We discovered a shift in striatal connectivity, which showed correlation with nigrostriatal denervation. Patients with PD exhibited a significantly higher matrix-like volume and associated connectivity than healthy controls and higher matrix-associated connectivity than iRBD patients. In contrast, the side with less pronounced nigrostriatal denervation in PD and iRBD patients showed a decrease in striosome-like volume and associated connectivity indices. These findings could point to a compensatory neuroplastic mechanism in the context of nigrostriatal denervation and open a new avenue in the investigation of the pathophysiology of Parkinson's disease.
- Publication type
- Journal Article MeSH
The human brain represents a complex computational system, the function and structure of which may be measured using various neuroimaging techniques focusing on separate properties of the brain tissue and activity. We capture the organization of white matter fibers acquired by diffusion-weighted imaging using probabilistic diffusion tractography. By segmenting the results of tractography into larger anatomical units, it is possible to draw inferences about the structural relationships between these parts of the system. This pipeline results in a structural connectivity matrix, which contains an estimate of connection strength among all regions. However, raw data processing is complex, computationally intensive, and requires expert quality control, which may be discouraging for researchers with less experience in the field. We thus provide brain structural connectivity matrices in a form ready for modelling and analysis and thus usable by a wide community of scientists. The presented dataset contains brain structural connectivity matrices together with the underlying raw diffusion and structural data, as well as basic demographic data of 88 healthy subjects.
INTRODUCTION: Despite substantial clinical and pathophysiological differences, the characteristics of tremor in Parkinson's disease (PD) and essential tremor (ET) patients bear certain similarities. The presented study delineates tremor-related structural networks in these two disorders. METHODS: 42 non-advanced PD patients (18 tremor-dominant, 24 without substantial tremor), 17 ET, and 45 healthy controls underwent high-angular resolution diffusion-weighted imaging acquisition to reconstruct their structural motor connectomes as a proxy of the anatomical interconnections between motor network regions, implementing state-of-the-art globally optimised probabilistic tractography. RESULTS: When compared to healthy controls, ET patients exhibited higher structural connectivity in the cerebello-thalamo-cortical network. Interestingly, the comparison of tremor-dominant PD patients and PD patients without tremor yielded very similar results - higher structural connectivity in tremor-dominant PD sharing multiple nodes with the tremor network detected in ET, despite the generally lower structural connectivity between basal ganglia and frontal cortex in the whole PD group when compared to healthy controls. CONCLUSION: The higher structural connectivity of the cerebello-thalamo-cortical network seems to be the dominant tremor driver in both PD and ET. While it appears to be the only tremor-related network in ET, its combination with large scale hypoconnectivity in the frontal cortico-subcortical network in PD may explain different clinical features of tremor in these two disorders.
BACKGROUND: Diffusion kurtosis imaging has been applied to evaluate white matter and basal ganglia microstructure in mixed Parkinson's disease (PD) groups with inconclusive results. OBJECTIVES: To evaluate specific patterns of kurtosis changes in PD and to assess the utility of diffusion imaging in differentiating between healthy subjects and cognitively normal PD, and between PD with and without mild cognitive impairment. METHODS: Diffusion scans were obtained in 92 participants using 3T MRI. Differences in white matter were tested by tract-based spatial statistics. Gray matter was evaluated in basal ganglia, thalamus, hippocampus, and motor and premotor cortices. Brain atrophy was also assessed. Multivariate logistic regression was used to identify a combination of diffusion parameters with the highest discrimination power between groups. RESULTS: Diffusion kurtosis metrics showed a significant increase in substantia nigra (p = 0.037, Hedges' g = 0.89), premotor (p = 0.009, Hedges' g = 0.85) and motor (p = 0.033, Hedges' g = 0.87) cortices in PD with normal cognition compared to healthy participants. Combined diffusion markers in gray matter reached 81% accuracy in differentiating between both groups. Significant white matter microstructural changes, and kurtosis decreases in the cortex were present in cognitively impaired versus cognitively normal PD. Diffusion parameters from white and gray matter differentiated between both PD phenotypes with 78% accuracy. CONCLUSIONS: Increased kurtosis in gray matter structures in cognitively normal PD reflects increased hindrance to water diffusion caused probably by alpha-synuclein-related microstructural changes. In cognitively impaired PD, the changes are mostly driven by decreased white matter integrity. Our results support the utility of diffusion kurtosis imaging for PD diagnostics.
- MeSH
- Atrophy MeSH
- Basal Ganglia diagnostic imaging MeSH
- White Matter diagnostic imaging MeSH
- Diffusion Magnetic Resonance Imaging MeSH
- Hippocampus diagnostic imaging MeSH
- Cognitive Dysfunction diagnostic imaging physiopathology psychology MeSH
- Middle Aged MeSH
- Humans MeSH
- Logistic Models MeSH
- Motor Cortex diagnostic imaging MeSH
- Brain diagnostic imaging pathology MeSH
- Multivariate Analysis MeSH
- Parkinson Disease diagnostic imaging physiopathology psychology MeSH
- Gray Matter diagnostic imaging MeSH
- Aged MeSH
- Models, Statistical MeSH
- Thalamus diagnostic imaging MeSH
- Diffusion Tensor Imaging MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
In patients with pharmaco-resistant focal epilepsies investigated with intracranial electroencephalography (iEEG), direct electrical stimulations of a cortical region induce cortico-cortical evoked potentials (CCEP) in distant cerebral cortex, which properties can be used to infer large scale brain connectivity. In 2013, we proposed a new probabilistic functional tractography methodology to study human brain connectivity. We have now been revisiting this method in the F-TRACT project (f-tract.eu) by developing a large multicenter CCEP database of several thousand stimulation runs performed in several hundred patients, and associated processing tools to create a probabilistic atlas of human cortico-cortical connections. Here, we wish to present a snapshot of the methods and data of F-TRACT using a pool of 213 epilepsy patients, all studied by stereo-encephalography with intracerebral depth electrodes. The CCEPs were processed using an automated pipeline with the following consecutive steps: detection of each stimulation run from stimulation artifacts in raw intracranial EEG (iEEG) files, bad channels detection with a machine learning approach, model-based stimulation artifact correction, robust averaging over stimulation pulses. Effective connectivity between the stimulated and recording areas is then inferred from the properties of the first CCEP component, i.e. onset and peak latency, amplitude, duration and integral of the significant part. Finally, group statistics of CCEP features are implemented for each brain parcel explored by iEEG electrodes. The localization (coordinates, white/gray matter relative positioning) of electrode contacts were obtained from imaging data (anatomical MRI or CT scans before and after electrodes implantation). The iEEG contacts were repositioned in different brain parcellations from the segmentation of patients' anatomical MRI or from templates in the MNI coordinate system. The F-TRACT database using the first pool of 213 patients provided connectivity probability values for 95% of possible intrahemispheric and 56% of interhemispheric connections and CCEP features for 78% of intrahemisheric and 14% of interhemispheric connections. In this report, we show some examples of anatomo-functional connectivity matrices, and associated directional maps. We also indicate how CCEP features, especially latencies, are related to spatial distances, and allow estimating the velocity distribution of neuronal signals at a large scale. Finally, we describe the impact on the estimated connectivity of the stimulation charge and of the contact localization according to the white or gray matter. The most relevant maps for the scientific community are available for download on f-tract. eu (David et al., 2017) and will be regularly updated during the following months with the addition of more data in the F-TRACT database. This will provide an unprecedented knowledge on the dynamical properties of large fiber tracts in human.
- MeSH
- Atlases as Topic MeSH
- Databases, Factual MeSH
- Child MeSH
- Adult MeSH
- Electrocorticography methods MeSH
- Epilepsy diagnostic imaging physiopathology MeSH
- Evoked Potentials physiology MeSH
- Connectome methods MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Cerebral Cortex diagnostic imaging physiopathology MeSH
- Neural Pathways diagnostic imaging MeSH
- Child, Preschool MeSH
- Check Tag
- Child MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Male MeSH
- Child, Preschool MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Multicenter Study MeSH
- Research Support, Non-U.S. Gov't MeSH
One of the most widely investigated functions of the brain is vision. Whereas special attention is often paid to motion detection and its modulation by attention, comparatively still little is known about the structural background of this function. We therefore, examined the white matter microstructural background of coherent motion detection. A random-dot kinematogram paradigm was used to measure the sensitivity of healthy individuals׳ to movement coherence. The potential correlation was investigated between the motion detection threshold and the white matter microstructure as measured by high angular resolution diffusion MRI. The Track Based Spatial Statistics method was used to address this correlation and probabilistic tractography to reveal the connection between identified regions. A significant positive correlation was found between the behavioural data and the local fractional anisotropy in the posterior part of the right superior frontal gyrus, the right juxta-cortical superior parietal lobule, the left parietal white matter, the left superior temporal gyrus and the left optic radiation. Probabilistic tractography identified pathways that are highly similar to the segregated attention networks, which have a crucial role in the paradigm. This study draws attention to the structural determinant of a behavioural function.
- MeSH
- Anisotropy MeSH
- White Matter anatomy & histology physiology MeSH
- Differential Threshold physiology MeSH
- Diffusion Magnetic Resonance Imaging MeSH
- Adult MeSH
- Humans MeSH
- Young Adult MeSH
- Brain anatomy & histology physiology MeSH
- Neural Pathways anatomy & histology physiology MeSH
- Psychophysics MeSH
- Photic Stimulation MeSH
- Signal Detection, Psychological physiology MeSH
- Motion Perception physiology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
BACKGROUND: Thalamic gliomas represent a great challenge for neurosurgeons because of the high surgical risk of damaging the surrounding anatomy. Preoperative planning may considerably help the surgeon find the most ideal operative trajectory, avoiding thalamic nuclei and important white matter pathways adjacent to the tumor tissue. Thalamic segmentation is a promising imaging tool based on diffusion tensor magnetic resonance imaging. It provides the possibility to predict the relationship of the tumor to thalamic nuclei. OBJECTIVE: To propose a new tool in thalamic glioma surgery that may help to differentiate between normal thalamus and tumor tissue, making preoperative planning possible and facilitating the choice of the optimal surgical approach and trajectory for neuronavigation-assisted surgery. METHODS: Four patients with thalamic gliomas preoperatively underwent conventional and diffusion-weighted magnetic resonance imaging conducted on 1.5 T. Subsequently, probabilistic tractography and thalamic segmentation were performed with the FSL Software as preoperative planning. We also present a case when thalamic segmentation was applied retrospectively using preoperative images. All patients went through neuronavigation-assisted surgery (1 partial, 4 subtotal resections). RESULTS: Surgery performed based on the output of thalamic segmentation caused no deterioration in the neurological symptoms of our patients. Indeed, we noticed improvement in the neurological condition in 3 cases; furthermore, in 2 patients, a concern-free state was achieved. CONCLUSION: We suggest that thalamic segmentation may be applied successfully and routinely in the surgical treatment of thalamic gliomas.
- MeSH
- Diffusion Magnetic Resonance Imaging MeSH
- Adult MeSH
- Glioma pathology surgery MeSH
- Humans MeSH
- Young Adult MeSH
- Brain Neoplasms pathology surgery MeSH
- Nerve Fibers pathology MeSH
- Neurosurgical Procedures methods MeSH
- Neuronavigation MeSH
- Image Processing, Computer-Assisted MeSH
- Aged MeSH
- Thalamus pathology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
