MRI Atlas of the Human Deep Brain

Identification and characterization of the thalamic ventral posterior complex by 11.7T ex vivo diffusion tensor imaging

The thalamic ventral posterior (VP) nuclear complex includes several subnuclei, including the VPM, VPL, VPI, and VMb, each with distinct inputs, axonal trajectories, and staining properties. Understanding the three-dimensional organization of neuronal fiber structures of the VP complex is crucial for understanding intra-thalamic and thalamocortical connections related to somatosensory processing. In this study, an ex vivo block of the human brain was scanned using mesoscopic Diffusion Tensor Imaging (DTI), and the four VP subnuclei were identified using existing histological atlases as references. The VP subnuclei were characterized using a mean diffusivity (MeanD) map, orientation-coded fractional anisotropy (FA) map, and tractography obtained from DTI. The results demonstrated differential patterns in MeanD and orientation-coded FA maps among the four subnuclei, underscoring the potential of mesoscale imaging to identify and differentiate these subnuclei. The tractography identified patterns of afferent and efferent fibers unique to each nucleus, offering insights into their functional roles in sensory processing. The findings highlighted the advantages of DTI in visualizing the direction of fibrous structures and conducting three-dimensional tractography, offering a foundation for further investigations into in vivo imaging applications and the neural mechanisms of somatosensory disorders, including central pain syndrome.

Automated segmentation of deep brain structures from Inversion-Recovery MRI

Methods for the automated segmentation of brain structures are a major subject of medical research. The small structures of the deep brain have received scant attention, notably for lack of manual delineations by medical experts. In this study, we assessed an automated segmentation of a novel clinical dataset containing White Matter Attenuated Inversion-Recovery (WAIR) MRI images and five manually segmented structures (substantia nigra (SN), subthalamic nucleus (STN), red nucleus (RN), mammillary body (MB) and mammillothalamic fascicle (MT-fa)) in 53 patients with severe Parkinson's disease. T1 and DTI images were additionally used. We also assessed the reorientation of DTI diffusion vectors with reference to the ACPC line. A state-of-the-art nnU-Net method was trained and tested on subsets of 38 and 15 image datasets respectively. We used Dice similarity coefficient (DSC), 95% Hausdorff distance (95HD), and volumetric similarity (VS) as metrics to evaluate network efficiency in reproducing manual contouring. Random-effects models statistically compared values according to structures, accounting for between- and within-participant variability. Results show that WAIR significantly outperformed T1 for DSC (0.739 ± 0.073), 95HD (1.739 ± 0.398), and VS (0.892 ± 0.044). The DSC values for automated segmentation of MB, RN, SN, STN, and MT-fa decreased in that order, in line with the increasing complexity observed in manual segmentation. Based on training results, the reorientation of DTI vectors improved the automated segmentation.

An MRI Deep Brain Adult Template With An Advanced Atlas-Based Tool For Diffusion Tensor Imaging Analysis

Understanding the architecture of the human deep brain is especially challenging because of the complex organization of the nuclei and fascicles that support most sensorimotor and behaviour controls. There are scant dedicated tools to explore and analyse this region. Here we took a transdisciplinary approach to build a new deep-brain MRI architecture atlas drawing on advanced clinical experience of MRI-based deep brain mapping. This new tool comprises a young-male-adult MRI template spatially normalized to the ICBM152, containing T1, inversion-recovery, and diffusion MRI datasets (in vivo acquisition), and an MRI atlas of 118 labelled deep brain structures. It is open-source and gives users high resolution image datasets to describe nuclear-based and axonal architecture, combining pioneering and recent knowledge. It is a useful addition to current 3D atlases and clinical tools.

Probabilistic stimulation mapping from intra-operative thalamic deep brain stimulation data in essential tremor

Deep brain stimulation (DBS) is a therapy for Parkinson's disease (PD) and essential tremor (ET). The mechanism of action of DBS is still incompletely understood. Retrospective group analysis of intra-operative data recorded from ET patients implanted in the ventral intermediate nucleus of the thalamus (Vim) is rare. Intra-operative stimulation tests generate rich data and their use in group analysis has not yet been explored.Objective.To implement, evaluate, and apply a group analysis workflow to generate probabilistic stimulation maps (PSMs) using intra-operative stimulation data from ET patients implanted in Vim.Approach.A group-specific anatomical template was constructed based on the magnetic resonance imaging scans of 6 ET patients and 13 PD patients. Intra-operative test data (total:n= 1821) from the 6 ET patients was analyzed: patient-specific electric field simulations together with tremor assessments obtained by a wrist-based acceleration sensor were transferred to this template. Occurrence and weighted mean maps were generated. Voxels associated with symptomatic response were identified through a linear mixed model approach to form a PSM. Improvements predicted by the PSM were compared to those clinically assessed. Finally, the PSM clusters were compared to those obtained in a multicenter study using data from chronic stimulation effects in ET.Main results.Regions responsible for improvement identified on the PSM were in the posterior sub-thalamic area (PSA) and at the border between the Vim and ventro-oral nucleus of the thalamus (VO). The comparison with literature revealed a center-to-center distance of less than 5 mm and an overlap score (Dice) of 0.4 between the significant clusters. Our workflow and intra-operative test data from 6 ET-Vim patients identified effective stimulation areas in PSA and around Vim and VO, affirming existing medical literature.Significance.This study supports the potential of probabilistic analysis of intra-operative stimulation test data to reveal DBS's action mechanisms and to assist surgical planning.

Deep brain stimulation of the subthalamic nucleus in severe Parkinson's disease: relationships between dual-contact topographic setting and 1-year worsening of speech and gait

BACKGROUND

Subthalamic nucleus (STN) deep brain stimulation (DBS) alleviates severe motor fluctuations and dyskinesia in Parkinson's disease, but may result in speech and gait disorders. Among the suspected or demonstrated causes of these adverse effects, we focused on the topography of contact balance (CB; individual, right and left relative dual positions), a scantly studied topic, analyzing the relationships between symmetric or non-symmetric settings, and the worsening of these signs.

METHOD

An observational monocentric study was conducted on a series of 92 patients after ethical approval. CB was specified by longitudinal and transversal positions and relation to the STN (CB sub-aspects) and totalized at the patient level (patient CB). CB was deemed symmetric when the two contacts were at the same locations relative to the STN. CB was deemed asymmetric when at least one sub-aspect differed in the patient CB. Baseline and 1-year characteristics were routinely collected: (i) general, namely, Unified Parkinson's Disease Rating Scores (UPDRS), II, III motor and IV, daily levodopa equivalent doses, and Parkinson's Disease Questionnaire of Quality of Life (PDQ39) scores; (ii) specific, namely scores for speech (II-5 and III-18) and axial signs (II-14, III-28, III-29, and III-30). Only significant correlations were considered (p < 0.05).

RESULTS

Baseline characteristics were comparable (symmetric versus asymmetric). CB settings were related to deteriorations of speech and axial signs: communication PDQ39 and UPDRS speech and gait scores worsened exclusively with symmetric settings; the most influential CB sub-aspect was symmetric longitudinal position.

CONCLUSION

Our findings suggest that avoiding symmetric CB settings, whether by electrode positioning or shaping of electric fields, could reduce worsening of speech and gait.

Multiparametric MRI for Characterization of the Basal Ganglia and the Midbrain

Objectives To characterize subcortical nuclei by multi-parametric quantitative magnetic resonance imaging.

Materials and Methods: The following quantitative multiparametric MR data of five healthy volunteers were acquired on a 7T MRI system: 3D gradient echo (GRE) data for the calculation of quantitative susceptibility maps (QSM), GRE sequences with and without off-resonant magnetic transfer pulse for magnetization transfer ratio (MTR) calculation, a magnetization−prepared 2 rapid acquisition gradient echo sequence for T₁ mapping, and (after a coil change) a density-adapted 3D radial pulse sequence for ²³Na imaging. First, all data were co-registered to the GRE data, volumes of interest (VOIs) for 21 subcortical structures were drawn manually for each volunteer, and a combined voxel-wise analysis of the four MR contrasts (QSM, MTR, T₁, ²³Na) in each structure was conducted to assess the quantitative, MR value-based differentiability of structures. Second, a machine learning algorithm based on random forests was trained to automatically classify the groups of multi-parametric voxel values from each VOI according to their association to one of the 21 subcortical structures.

Results The analysis of the integrated multimodal visualization of quantitative MR values in each structure yielded a successful classification among nuclei of the ascending reticular activation system (ARAS), the limbic system and the extrapyramidal system, while classification among (epi-)thalamic nuclei was less successful. The machine learning-based approach facilitated quantitative MR value-based structure classification especially in the group of extrapyramidal nuclei and reached an overall accuracy of 85% regarding all selected nuclei.

Conclusion Multimodal quantitative MR enabled excellent differentiation of a wide spectrum of subcortical nuclei with reasonable accuracy and may thus enable sensitive detection of disease and nucleus-specific MR-based contrast alterations in the future.

Puberty, A Sensitive Window of Hypothalamic Development and Plasticity

Puberty is a developmental period characterized by a broad range of physiologic changes necessary for the acquisition of adult sexual and reproductive maturity. These changes mirror complex modifications within the central nervous system, including within the hypothalamus. These modifications result in the maturation of a fully active hypothalamic-pituitary-gonadal (HPG) axis, the neuroendocrine cascade ensuring gonadal activation, sex steroid secretion, and gametogenesis. A complex and finely regulated neural network overseeing the HPG axis, particularly the pubertal reactivation of gonadotropin-releasing hormone (GnRH) secretion, has been progressively unveiled in the last 3 decades. This network includes kisspeptin, neurokinin B, GABAergic, and glutamatergic neurons as well as glial cells. In addition to substantial modifications in the expression of key targets, several changes in neuronal morphology, neural connections, and synapse organization occur to establish mature and coordinated neurohormonal secretion, leading to puberty initiation. The aim of this review is to outline the current knowledge of the major changes that neurons secreting GnRH and their neuronal and glial partners undergo before and after puberty. Emerging mediators upstream of GnRH, uncovered in recent years, are also addressed herein. In addition, the effects of sex steroids, particularly estradiol, on changes in hypothalamic neurodevelopment and plasticity are discussed.

MRI maps, segregation, and white matter connectivity of the human hypothalamus in health

The human hypothalamus is composed of several gray matter territories, forming 10 different structures mainly referred to as nuclei: the preoptic, suprachiasmatic, supraoptic, infundibular, paraventricular, dorsomedial, ventromedial, posterior (dorsal; dorsal hypothalamic area), and tuberomamillary nuclei, and the lateral hypothalamic area. The macroconnectivity, described since the middle of the 19th century, is currently probed using MRI methods, notably those relying on diffusion techniques. The structural connections can be grouped as follows: connections with the olfactory system; stria terminalis connections; stria medullaris connections; ansa lenticularis connections; subthalamus connections; optic tract connections; intrahypothalamic connections; hypothalamo-hypophysis connections; hypothalamic commissures; cortex connections.

Evolution of Human Brain Atlases in Terms of Content, Applications, Functionality, and Availability

Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.

Anatomical brain structures normalization for deep brain stimulation in movement disorders

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Non-linear iterative structural normalization method focused on the deep brain.

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Multi-modality image data from deep brain stimulation patients.

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Comparison of ANTS, FNIRT and DRAMMS for the non-linear registrations using different settings for each.

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Evaluation of the registration tools based on the analysis of 58 structures of the deep brain segmented manually by a single expert.

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ANTS was identified as the best performing non-linear registration tool.

Deep brain stimulation (DBS) therapy requires extensive patient-specific planning prior to implantation to achieve optimal clinical outcomes. Collective analysis of patient’s brain images is promising in order to provide more systematic planning assistance. In this paper the design of a normalization pipeline using a group specific multi-modality iterative template creation process is presented. The focus was to compare the performance of a selection of freely available registration tools and select the best combination. The workflow was applied on 19 DBS patients with T1 and WAIR modality images available. Non-linear registrations were computed with ANTS, FNIRT and DRAMMS, using several settings from the literature. Registration accuracy was measured using single-expert labels of thalamic and subthalamic structures and their agreement across the group. The best performance was provided by ANTS using the High Variance settings published elsewhere. Neither FNIRT nor DRAMMS reached the level of performance of ANTS. The resulting normalized definition of anatomical structures were used to propose an atlas of the diencephalon region defining 58 structures using data from 19 patients.