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Purpose: Transcranial magnetic stimulation (TMS) is a growing therapy for a variety of psychiatric and neurological disorders that arise from or are modulated by cortical regions of the brain represented by singular 3D target points. These target points are often determined manually with assistance from a pre-operative T1-weighted MRI, although there is growing interest in automatic target point localisation using an atlas. However, both approaches can be time-consuming which has an effect on the clinical workflow, and the latter does not take into account patient variability such as the varying number of cortical gyri where these targets are located., Methods: This paper proposes a multi-resolution convolutional neural network for point localisation in MR images for a priori defined points in increasingly finely resolved versions of the input image. This approach is both fast and highly memory efficient, allowing it to run in high-throughput centres, and has the capability of distinguishing between patients with high levels of anatomical variability., Results: Preliminary experiments have found the accuracy of this network to be [Formula: see text] mm, compared to [Formula: see text] mm for deformable registration and [Formula: see text] mm for a human expert. For most treatment points, the human expert and proposed CNN statistically significantly outperform registration, but neither statistically significantly outperforms the other, suggesting that the proposed network has human-level performance., Conclusions: The human-level performance of this network indicates that it can improve TMS planning by automatically localising target points in seconds, avoiding more time-consuming registration or manual point localisation processes. This is particularly beneficial for out-of-hospital centres with limited computational resources where TMS is increasingly being administered.

Subthalamic nucleus (STN) deep brain stimulation (DBS) is an effective surgical therapy to treat Parkinson's disease (PD). Conventional methods employ standard atlas coordinates to target the STN, which, along with the adjacent red nucleus (RN) and substantia nigra (SN), are not well visualized on conventional T1w MRIs. However, the positions and sizes of the nuclei may be more variable than the standard atlas, thus making the pre-surgical plans inaccurate. We investigated the morphometric variability of the STN, RN and SN by using label-fusion segmentation results from 3T high resolution T2w MRIs of 33 advanced PD patients. In addition to comparing the size and position measurements of the cohort to the Talairach atlas, principal component analysis (PCA) was performed to acquire more intuitive and detailed perspectives of the measured variability. Lastly, the potential correlation between the variability shown by PCA results and the clinical scores was explored., (Copyright © 2014 Wiley Periodicals, Inc.)

Purpose: Template-based segmentation techniques have been developed to facilitate the accurate targeting of deep brain structures in patients with movement disorders. Three template-based brain MRI segmentation techniques were compared to determine the best strategy for segmenting the deep brain structures of patients with Parkinson's disease., Methods: T1-weighted and T2-weighted magnetic resonance (MR) image templates were created by averaging MR images of 57 patients with Parkinson's disease. Twenty-four deep brain structures were manually segmented on the templates. To validate the template-based segmentation, 14 of the 24 deep brain structures from the templates were manually segmented on 10 MR scans of Parkinson's patients as a gold standard. We compared the manual segmentations with three methods of automated segmentation: two registration-based approaches, automatic nonlinear image matching and anatomical labeling (ANIMAL) and symmetric image normalization (SyN), and one patch-label fusion technique. The automated labels were then compared with the manual labels using a Dice-kappa metric and center of gravity. A Friedman test was used to compare the Dice-kappa values and paired t tests for the center of gravity., Results: The Friedman test showed a significant difference between the three methods for both thalami (p < 0.05) and not for the subthalamic nuclei. Registration with ANIMAL was better than with SyN for the left thalamus and was better than the patch-based method for the right thalamus., Conclusion: Although template-based approaches are the most used techniques to segment basal ganglia by warping onto MR images, we found that the patch-based method provided similar results and was less time-consuming. Patch-based method may be preferable for the subthalamic nucleus segmentation in patients with Parkinson's disease.

Purpose: The optimal electrode trajectory is needed to assist surgeons in planning Deep Brain Stimulation (DBS). A method for image-based trajectory planning was developed and tested., Methods: Rules governing the DBS surgical procedure were defined with geometric constraints. A formal geometric solver using multimodal brain images and a template built from 15 brain MRI scans were used to identify a space of possible solutions and select the optimal one. For validation, a retrospective study of 30 DBS electrode implantations from 18 patients was performed. A trajectory was computed in each case and compared with the trajectories of the electrodes that were actually implanted., Results: Computed trajectories had an average difference of 6.45° compared with reference trajectories and achieved a better overall score based on satisfaction of geometric constraints. Trajectories were computed in 2 min for each case., Conclusion: A rule-based solver using pre-operative MR brain images can automatically compute relevant and accurate patient-specific DBS electrode trajectories.

In the context of presurgical mapping or investigation of neurological and developmental disorders in children, language fMRI raises the issue of the design of a tasks panel achievable by young disordered children. Most language tasks shown to be efficient with healthy children require metalinguistic or reading abilities, therefore adding attentional, cognitive and academic constraints that may be problematic in this context. This study experimented a panel of four language tasks that did not require high attentional skills, reading, or metalinguistic abilities. Two reference tasks involving auditory stimulation (words generation from category, "category"; auditory responsive naming, "definition") were compared with two new tasks involving visual stimulation. These later were designed to tap spontaneous phonological production, in which the names of pictures to be named involve a phonological difference (e.g. in French poule/boule/moule; "phon-diff") or change of segmentation (e.g. in French car/car-te/car-t-on; "phon-seg"). Eighteen healthy children participated (mean age: 12.7+/-3 years). Data processing involved normalizing the data via a matched pairs pediatric template, and inter-task and region of interest analyses with laterality assessment. The reference tasks predominantly activated the left frontal and temporal core language regions, respectively. The new tasks activated these two regions simultaneously, more strongly for the phon-seg task. The union and intersection of all tasks provided more sensitive or specific maps. The study demonstrates that both reference and new tasks highlight core language regions in children, and that the latter are useful for the mapping of spontaneous phonological processing. The use of several different tasks may improve the sensitivity and specificity of fMRI., (Copyright 2010 Elsevier Inc. All rights reserved.)

New MR imaging protocols enable visualization of brain structures. However, for dedicated clinical applications such as targeting deep brain stimulation (DBS), a more accurate localization requires the use of atlases. We developed a three-dimensional digitized mono-subject anatomical template of the human brain based on 3-T magnetic resonance images (MRI). By averaging 15 registered T1 image acquisitions, we have shown that the final image corresponds to an optimal image, limited by the performance of the 3-T MR machine. We compared different preprocessing workflows for template construction. With the optimal strategy, along with validated existing processing methods, one T1 template and one T1-T2 mixing template were created in order to improve visualization of spatially complex deep structures. Reduction of voxel size to 0.25 mm(3) was also advantageous to observe fine structures and white matter/gray matter intensity crossings. Results demonstrated that such a template also improved inter-patient registration for population comparison in DBS. These MR templates are made freely available to our community (http://www.vmip.org/mritemplate) to serve as a reference for neuroimage processing methods.

Displaying anatomical and physiological information derived from preoperative medical images in the operating room is critical in image-guided neurosurgery. This paper presents a new approach referred to as augmented virtuality (AV) for displaying intraoperative views of the operative field over three-dimensional (3-D) multimodal preoperative images onto an external screen during surgery. A calibrated stereovision system was set up between the surgical microscope and the binocular tubes. Three-dimensional surface meshes of the operative field were then generated using stereopsis. These reconstructed 3-D surface meshes were directly displayed without any additional geometrical transform over preoperative images of the patient in the physical space. Performance evaluation was achieved using a physical skull phantom. Accuracy of the reconstruction method itself was shown to be within 1 mm (median: 0.76 mm +/- 0.27), whereas accuracy of the overall approach was shown to be within 3 mm (median: 2.29 mm +/- 0.59), including the image-to-physical space registration error. We report the results of six surgical cases where AV was used in conjunction with augmented reality. AV not only enabled vision beyond the cortical surface but also gave an overview of the surgical area. This approach facilitated understanding of the spatial relationship between the operative field and the preoperative multimodal 3-D images of the patient.

Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack of relevant ground truth. We propose a methodology to generate MRI and SPECT datasets dedicated to the evaluation of MRI/SPECT fusion methods and illustrate the method when dealing with ictal SPECT. The method consists in generating normal or pathological SPECT data perfectly aligned with a high-resolution 3D T1-weighted MRI using realistic Monte Carlo simulations that closely reproduce the response of a SPECT imaging system. Anatomical input data for the SPECT simulations are obtained from this 3D T1-weighted MRI, while functional input data result from an inter-individual analysis of anatomically standardized SPECT data. The method makes it possible to control the 'brain perfusion' function by proposing a theoretical model of brain perfusion from measurements performed on real SPECT images. Our method provides an absolute gold standard for assessing MRI/SPECT registration method accuracy since, by construction, the SPECT data are perfectly registered with the MRI data. The proposed methodology has been applied to create a theoretical model of normal brain perfusion and ictal brain perfusion characteristic of mesial temporal lobe epilepsy. To approach realistic and unbiased perfusion models, real SPECT data were corrected for uniform attenuation, scatter and partial volume effect. An anatomic standardization was used to account for anatomic variability between subjects. Realistic simulations of normal and ictal SPECT deduced from these perfusion models are presented. The comparison of real and simulated SPECT images showed relative differences in regional activity concentration of less than 20% in most anatomical structures, for both normal and ictal data, suggesting realistic models of perfusion distributions for evaluation purposes. Inter-hemispheric asymmetry coefficients measured on simulated data were found within the range of asymmetry coefficients measured on corresponding real data. The features of the proposed approach are compared with those of other methods previously described to obtain datasets appropriate for the assessment of fusion methods.

Two cases (a young male and a girl, suffering intractable epilepsy) of diffuse subcortical laminar heterotopia, or so-called double cortex (DC) have been investigated using magnetoencephalography (MEG). MEG confirmed involvement of both cortices (hetero- and normocortex) in the genesis of interictal spikes, and, according to the heterogeneity of DC syndrome, some differences were observed: spike initiation in the normocortex and latter involvement of the heterotopic cortex in the man, and rather a cancellation in both cortices in the girl. In addition, participation of heterotopic cortex in physiological activities could be demonstrated in the man.

Technetium-99m HMPAO and technetium-99m ECD single photon emission computed tomography (SPECT) imaging is commonly used to highlight brain regions with altered perfusion. It is particularly useful in the investigation of intractable partial epilepsy. However, SPECT suffers from poor spatial resolution that makes interpretation difficult. In this context, we propose an unsupervised voxel neighbourhood based method to assist the detection of significant functional inter-hemispheric asymmetries in brain SPECT, using anatomical information from MRI. For each MRI voxel, the anatomically homologous voxel in the contralateral hemisphere is identified. Both homologous voxel coordinates are then mapped into the SPECT volume using SPECT-MRI registration. Neighbourhoods are then defined around each SPECT voxel and compared to obtain a volume of inter-hemispheric differences. A volume including only the statistically significant inter-hemispheric differences is deduced from this volume using a non-parametric approach. The method was validated using realistic analytical simulated SPECT data including known asymmetries (in size and amplitude) as ground truth (gold standard). Detection performance was assessed using an ROC (receiver operating characteristic) approach based on the measures of the overlap between known and detected asymmetries. Validation with computer-simulated data demonstrates the ability to detect asymmetric zones with relatively small extension and amplitude. The registration of these detected functional asymmetries on the MRI enables good anatomical localization to be achieved.

Object: The authors present the use of cortical sulci, segmented from magnetic resonance (MR) imaging, and functional data from functional (f)MR imaging and magnetoencephalography (MEG) in the image-guided surgical management of lesions adjacent to the sensorimotor cortex., Methods: In an initial set of 11 patients, sulci near lesions were automatically segmented from MR imaging data sets, then MEG and fMR imaging examinations were performed. Relevant functional information was preoperatively interpreted and selected from MEG and fMR imaging and subsequently transferred to the navigation system for selected sulci. A neuronavigation system consisting of a surgical microscope with enhanced reality overlay display was used. Data were displayed as contours on the cut-plane images of a stereotactic workstation and as contours on the overlay screen of the head-up display within the optical path of the right eyepiece of the surgical microscope., Conclusions: This method, in which both sulcal and functional mapping are used for surgery planning and neuronavigation, provides helpful information. It is a promising procedure for the treatment of patients who harbor lesions in areas around the eloquent cortex.

We present the use of cortical sulci, segmented from magnetic resonance imaging, in image guided neurosurgery. Sulcal information was transferred to a surgical microscope with enhanced reality features. This assistance was used for the resection of supratentorial cavernomas (7 patients). Sulci were semi-automatically segmented from 3D MRI data sets. Sulci close to the cavernoma were selected and transferred to the neuronavigation system which allows the superimposition of graphics into the right ocular of the microscope. Selected sulci were displayed on the workstation and superimposed into the ocular of the microscope. Cortical sulci proved to be useful for the recognition of the anatomical environment. The superimposed sulci helped to optimize location and size of the skin incision as well as to guide the access to the cavernoma by using the course of a sulcus as indirect trajectory.

Object: The aim of this study was to evaluate different types of sensory stimulation used to distinguish between microvasculature and venous drainage on functional magnetic resonance (fMR) images with blood oxygen level-dependent (BOLD) contrast., Methods: Seven volunteers received three sensory stimulations. One consisted of small discontinuous automated pokes to the ventral aspect of the right thumbtip. The other two were delivered by the investigator, who vigorously brushed the ventral aspect of the right thumbtip either alone or in combination with the thenar region. Seven contiguous axial slices of the head were acquired using echoplanar fMR imaging during each mode of stimulation. Boxcar analysis and Student's t-test were performed. Cluster analysis was used to determine significant differences between rest and activation phases. The major findings were 1) that a discontinuous sensory stimulation involving a small skin area was able to evoke a limited activated area in the postcentral gyrus with a low activation index (AI [2%]); 2) that this limited activated area was included in the activated area elicited by the continuous sensory stimulations; and 3) that this also evoked multiple activated areas exhibiting AIs of either approximately 2% or greater than 5%. This indicated that the limited discontinuous tactile stimulation evoked a BOLD-contrast fMR image essentially of microvasculature, whereas the more extensive continuous stimulations evoked a BOLD-contrast fMR image in both microvasculature and venous drainage., Conclusions: Different sensory stimulations are necessary to differentiate primary sensory cortex from venous drainage for presurgical brain mapping.

Objective: Part of the planning and performance of neurosurgery consists of determining target areas, areas to be avoided, landmark areas, and trajectories, all of which are components of the surgical script. Nowadays, neurosurgeons have access to multimodal medical imaging to support the definition of the surgical script. The purpose of this paper is to present a software environment developed by the authors that allows full multimodal and multi-informational planning as well as neuronavigation for epilepsy and tumor surgery., Materials and Methods: We have developed a data fusion environment dedicated to neuronavigation around the Surgical Microscope Neuronavigator system (Carl Zeiss, Oberkochen, Germany). This environment includes registration, segmentation, 3D visualization, and interaction-applied tools. It provides the neuronavigation system with the multimodal information involved in the definition of the surgical script: lesional areas, sulci, ventricles segmented from magnetic resonance imaging (MRI), vessels segmented from magnetic resonance angiography (MRA), functional areas from magneto-encephalography (MEG), and functional magnetic resonance imaging (fMRI) for somatosensory, motor, or language activation. These data are considered to be relevant for the performance of the surgical procedure. The definition of each entity results from the same procedure: registration to the anatomical MRI data set (defined as the reference data set), segmentation, fused 3D display, selection of the relevant entities for the surgical step, encoding in 3D surface-based representation, and storage of the 3D surfaces in a file recognized by the neuronavigation software (STP 3.4, Leibinger; Freiburg, Germany)., Results: Multimodal neuronavigation is illustrated with two clinical cases for which multimodal information was introduced into the neuronavigation system. Lesional areas were used to define and follow the surgical path, sulci and vessels helped identify the anatomical environment of the surgical field, and, finally, MEG and fMRI functional information helped determine the position of functional high-risk areas., Conclusion: In this short evaluation, the ability to access preoperative multi-functional and anatomical data within the neuronavigation system was a valuable support for the surgical procedure., (Copyright 2000 Wiley-Liss, Inc.)