Multimodality Data Integration in Epilepsy

An important goal of software development in the medical field is the design of methods which are able to integrate information obtained from various imaging and nonimaging modalities into a cohesive framework in order to understand the results of qualitatively different measurements in a larger context. Moreover, it is essential to assess the various features of the data quantitatively so that relationships in anatomical and functional domains between complementing modalities can be expressed mathematically. This paper presents a clinically feasible software environment for the quantitative assessment of the relationship among biochemical functions as assessed by PET imaging and electrophysiological parameters derived from intracranial EEG. Based on the developed software tools, quantitative results obtained from individual modalities can be merged into a data structure allowing a consistent framework for advanced data mining techniques and 3D visualization. Moreover, an effort was made to derive quantitative variables (such as the spatial proximity index, SPI) characterizing the relationship between complementing modalities on a more generic level as a prerequisite for efficient data mining strategies. We describe the implementation of this software environment in twelve children (mean age 5.2 ± 4.3 years) with medically intractable partial epilepsy who underwent both high-resolution structural MR and functional PET imaging. Our experiments demonstrate that our approach will lead to a better understanding of the mechanisms of epileptogenesis and might ultimately have an impact on treatment. Moreover, our software environment holds promise to be useful in many other neurological disorders, where integration of multimodality data is crucial for a better understanding of the underlying disease mechanisms

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Epilepsy surgery is challenging and the use of 3D multimodality image integration (3DMMI) to aid presurgical planning is well-established. Multimodality image integration can be technically demanding, and is underutilised in clinical practice. We have developed a single software platform for image integration, 3D visualization and surgical planning. Here, our pipeline is described in step-by-step fashion, starting with image acquisition, proceeding through image co-registration, manual segmentation, brain and vessel extraction, 3D visualization and manual planning of stereoEEG (SEEG) implantations. With dissemination of the software this pipeline can be reproduced in other centres, allowing other groups to benefit from 3DMMI. We also describe the use of an automated, multi-trajectory planner to generate stereoEEG implantation plans. Preliminary studies suggest this is a rapid, safe and efficacious adjunct for planning SEEG implantations. Finally, a simple solution for the export of plans and models to commercial neuronavigation systems for implementation of plans in the operating theater is described. This software is a valuable tool that can support clinical decision making throughout the epilepsy surgery pathway

Resection planning in extratemporal epilepsy surgery using 3D multimodality imaging and intraoperative MRI

Surgical resection in non-lesional, extratemporal epilepsy, informed by stereoEEG recordings, is challenging. There are no clear borders of resection, and the surgeon is often operating in deep areas of the brain that are difficult to access. We present a technical note where 3D multimodality image integration in EpiNav(TM) is used to build a planned resection model, based on a previous intracranial EEG evaluation. Intraoperative MRI is then used to ensure a complete resection of the planned model. As stereoEEG becomes more common in the presurgical evaluation of epilepsy, these tools will become increasingly important to facilitate targeted cortical resections

Lightweight XML-based query, integration and visualization of distributed, multimodality brain imaging data

A need of many neuroimaging researchers is to integrate multimodality brain data that may be stored in separate databases. To address this need we have developed a framework that provides a uniform XML-based query interface across multiple online data sources. The development of this framework is driven by the need to integrate neurosurgical and neuroimaging data related to language. The data sources for the language studies are 1) a web-accessible relational database of neurosurgical cortical stimulation mapping data (CSM) that includes patient-specific 3-D coordinates of each stimulation site mapped to an MRI reconstruction of the patient brain surface; and 2) an XML database of fMRI and structural MRI data and analysis results, created automatically by a batch program we have embedded in SPM. To make these sources available for querying each is wrapped as an XML view embedded in a web service. A top level web application accepts distributed XQueries over the sources, which are dispatched to the underlying web services. Returned results can be displayed as XML, HTML, CSV (Excel format), a 2-D schematic of a parcellated brain, or a 3-D brain visualization. In the latter case the CSM patient-specific coordinates returned by the query are sent to a transformation web-service for conversion to normalized space, after which they are sent to our 3-D visualization program MindSeer, which is accessed via Java WebStart through a generated link. The anatomical distribution of pooled CSM sites can then be visualized using various surfaces derived from brain atlases. As this framework is further developed and generalized we believe it will have appeal for researchers who wish to query, integrate and visualize results across their own databases as well as those of collaborators

Feasibility of multimodal 3D neuroimaging to guide implantation of intracranial EEG electrodes

Since intracranial electrode implantation has limited spatial sampling and carries significant risk, placement has to be effective and efficient. Structural and functional imaging of several different modalities contributes to localising the seizure onset zone (SoZ) and eloquent cortex. There is a need to summarise and present this information throughout the pre/intra/post-surgical course

From Tones in Tinnitus to Sensed Social Interaction in Schizophrenia: How Understanding Cortical Organization Can Inform the Study of Hallucinations and Psychosis

The content, modality, and perceptual attributes of hallucinations and other psychotic symptoms may be related to neural representation at a single cell and population level in the cerebral cortex. A brief survey of some principles and examples of cortical representation and organization will be presented together with evidence for a correspondence between the neurobiology of brain areas activated at the time of a hallucination and the content of the corresponding hallucinatory and psychotic experiences. Contrasting the hallucinations of schizophrenia with other conditions, we highlight phenomenological aspects of hallucinations that are ignored in clinical practice but carry potentially important information about the brain regions and dysfunctions underlying them. Knowledge of cortical representation and organization are being used to develop animal models of hallucination and to test treatments that are now beginning to translate to the clinical domain

Multimodal, Multidimensional Models of Mouse Brain

Naturally occurring mutants and genetically manipulated strains of mice are widely used to model a variety of human diseases. Atlases are an invaluable aid in understanding the impact of such manipulations by providing a standard for comparison and to facilitate the integration of anatomic, genetic, and physiologic observations from multiple subjects and experiments. We have developed digital atlases of the C57BL/6J mouse brain (adult and neonate) as comprehensive frameworks for storing and accessing the myriad types of information about the mouse brain. Along with raw and annotated images, these contain database management systems and a set of tools for comparing information from different techniques and different animals. Each atlas establishes a canonical representation of the mouse brain and provides the tools for the manipulation and analysis of new data. We describe both these atlases and discuss how they may be put to use in organizing and analyzing data from mouse models of epilepsy

Distinct illusory own-body perceptions caused by damage to posterior insula and extrastriate cortex

Recent research in cognitive neuroscience using virtual reality, robotic technology and brain imaging has linked self-consciousness to the processing and integration of multisensory bodily signals. This work on bodily self-consciousness has implicated the temporo-parietal, premotor and extrastriate cortex and partly originated in work on neurological patients with different disorders of bodily self-consciousness. One class of such disorders is autoscopic phenomena, which are defined as illusory own-body perceptions, during which patients experience the visual illusory reduplication of their own body in extrapersonal space. Three main forms of autoscopic phenomena have been defined. During autoscopic hallucinations, a second own body is seen without any changes in bodily self-consciousness. During out-of-body experiences, the second own body is seen from an elevated perspective and location associated with disembodiment. During heautoscopy, subjects report strong self-identification with the second own body, often associated with the experience of existing at and perceiving the world from two places at the same time. Although it has been proposed that each autoscopic phenomenon is associated with different impairments of bodily self-consciousness, past research on neurological patients and the development of experimental paradigms for the study of bodily self-consciousness has focused on out-of-body experiences and the association with temporo-parietal cortex. Here, we performed quantitative lesion analysis in the—to date—largest group of patients with autoscopic hallucination and heautoscopy and compared the location of brain damage with those of control patients suffering from complex visual hallucinations. We found that heautoscopy was associated with lesions to the left posterior insula, and that autoscopic hallucinations were associated with damage to the right occipital cortex. Autoscopic hallucination and heautoscopy were further associated with distinct symptoms and deficits. The present data suggest that the autoscopic hallucination is a visuo-somatosensory deficit implicating extrastriate cortex and is, despite the visual hallucination of the own body, not associated with major deficits in bodily self-consciousness. Based on the symptoms and deficits in patients with heautoscopy and the implication of the left posterior insula, we suggest that abnormal bodily self-consciousness during heautoscopy is caused by a breakdown of self-other discrimination regarding affective somatosensory experience due to a disintegration of visuo-somatosensory signals with emotional (and/or interoceptive) bodily signals. These brain mechanisms are distinct from those described for out-of-body experiences. The present data extend previous models of autoscopic phenomena and provide clinical evidence for the importance of emotional and interoceptive signal processing in the posterior insula in relation to bodily self-consciousnes

Focal Spot, Winter 2009/2010

https://digitalcommons.wustl.edu/focal_spot_archives/1113/thumbnail.jp