Rendering techniques for multimodal data

Many different direct volume rendering methods have been developed to visualize 3D scalar fields on uniform rectilinear grids. However, little work has been done on rendering simultaneously various properties of the same 3D region measured with different registration devices or at different instants of time. The demand for this type of visualization is rapidly increasing in scientific applications such as medicine in which the visual integration of multiple modalities allows a better comprehension of the anatomy and a perception of its relationships with activity. This paper presents different strategies of Direct Multimodal Volume Rendering (DMVR). It is restricted to voxel models with a known 3D rigid alignment transformation. The paper evaluates at which steps of the render-ing pipeline must the data fusion be realized in order to accomplish the desired visual integration and to provide fast re-renders when some fusion parameters are modified. In addition, it analyzes how existing monomodal visualization al-gorithms can be extended to multiple datasets and it compares their efficiency and their computational cost.Postprint (published version

Design of a multimodal rendering system

This paper addresses the rendering of aligned regular multimodal datasets. It presents a general framework of multimodal data fusion that includes several data merging methods. We also analyze the requirements of a rendering system able to provide these different fusion methods. On the basis of these requirements, we propose a novel design for a multimodal rendering system. The design has been implemented and proved showing to be efficient and flexible.Postprint (published version

Techniques and software tool for 3D multimodality medical image segmentation

The era of noninvasive diagnostic radiology and image-guided radiotherapy has witnessed burgeoning interest in applying different imaging modalities to stage and localize complex diseases such as atherosclerosis or cancer. It has been observed that using complementary information from multimodality images often significantly improves the robustness and accuracy of target volume definitions in radiotherapy treatment of cancer. In this work, we present techniques and an interactive software tool to support this new framework for 3D multimodality medical image segmentation. To demonstrate this methodology, we have designed and developed a dedicated open source software tool for multimodality image analysis MIASYS. The software tool aims to provide a needed solution for 3D image segmentation by integrating automatic algorithms, manual contouring methods, image preprocessing filters, post-processing procedures, user interactive features and evaluation metrics. The presented methods and the accompanying software tool have been successfully evaluated for different radiation therapy and diagnostic radiology applications

Adjuvant therapeutic potential of tonabersat in the standard treatment of glioblastoma : a preclinical F98 glioblastoma rat model study

Purpose Even with an optimal treatment protocol, the median survival of glioblastoma (GB) patients is only 12-15 months. Hence, there is need for novel effective therapies that improve survival outcomes. Recent evidence suggests an important role for connexin (Cx) proteins (especially Cx43) in the microenvironment of malignant glioma. Cx43-mediated gap junctional communication has been observed between tumor cells, between astrocytes and between tumor cells and astrocytes. Therefore, gap junction directed therapy using a pharmacological suppressor or modulator, such as tonabersat, could be a promising target in the treatment of GB. In this preclinical study, we evaluated the possible therapeutic potential of tonabersat in the F98 model. Procedures Female Fischer rats were inoculated with +/- 25.000 F98 tumor cells in the right frontal lobe. Eight days post-inoculation contrast-enhanced T1-weighted (CE-T1w) magnetic resonance (MR) images were acquired to confirm tumor growth in the brain. After tumor confirmation, rats were randomized into a Control Group, a Connexin Modulation Group (CM), a Standard Medical Treatment Group (ST), and a Standard Medical Treatment with adjuvant Connexin Modulation Group (STCM). To evaluate therapy response, T2-weighted (T2w) and CE-T1w sequences were acquired at several time points. Tumor volume analysis was performed on CE-T1w images and statistical analysis was performed using a linear mixed model. Results Significant differences in estimated geometric mean tumor volumes were found between the ST Group and the Control Group and also between the STCM Group and the Control Group. In addition, significant differences in estimated geometric mean tumor volumes between the ST Group and the STCM Group were demonstrated. No significant differences in estimated geometric mean tumor volumes were found between the Control Group and the CM Group. Conclusion Our results demonstrate a therapeutic potential of tonabersat for the treatment of GB when used in combination with radiotherapy and temozolomide chemotherapy

Polycation-siRNA nanoparticles can disassemble at the kidney glomerular basement membrane

Despite being engineered to avoid renal clearance, many cationic polymer (polycation)-based siRNA nanoparticles that are used for systemic delivery are rapidly eliminated from the circulation. Here, we show that a component of the renal filtration barrier—the glomerular basement membrane (GBM)—can disassemble cationic cyclodextrin-containing polymer (CDP)-based siRNA nanoparticles and, thereby, facilitate their rapid elimination from circulation. Using confocal and electron microscopies, positron emission tomography, and compartment modeling, we demonstrate that siRNA nanoparticles, but not free siRNA, accumulate and disassemble in the GBM. We also confirm that the siRNA nanoparticles do not disassemble in blood plasma in vitro and in vivo. This clearance mechanism may affect any nanoparticles that assemble primarily by electrostatic interactions between cationic delivery components and anionic nucleic acids (or other therapeutic entities)

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