In this paper, we describe a first step towards a collaborative extension of the well-known 3D-Slicer; this platform is nowadays used as a standalone tool for both surgical planning and medical intervention. We show how this tool can be easily modified to make it collaborative so that it may constitute an integrated environment for expertise exchange as well as a useful tool for academic purposes.

We propose a new model to simulate the three-dimensional (3-D) growth of glioblastomas multiforma (GBMs), the most aggressive glial tumors. The GBM speed of growth depends on the invaded tissue: faster in white than in gray matter, it is stopped by the dura or the ventricles. These different structures are introduced into the model using an atlas matching technique. The atlas includes both the segmentations of anatomical structures and diffusion information in white matter fibers. We use the finite element method (FEM) to simulate the invasion of the GBM in the brain parenchyma and its mechanical interaction with the invaded structures (mass effect). Depending on the considered tissue, the former effect is modeled with a reaction-diffusion or a Gompertz equation, while the latter is based on a linear elastic brain constitutive equation. In addition, we propose a new coupling equation taking into account the mechanical influence of the tumor cells on the invaded tissues. The tumor growth simulation is assessed by comparing the in-silico GBM growth with the real growth observed on two magnetic resonance images (MRIs) of a patient acquired with 6 mo difference. Results show the feasibility of this new conceptual approach and justifies its further evaluation.

Magnetic resonance imaging (MRI) has become a central tool for patient management, as well as research, in multiple sclerosis (MS). Measurements of disease burden and activity derived from MRI through quantitative image analysis techniques are increasingly being used. There are many complexities and challenges in building computerized processing pipelines to ensure efficiency, reproducibility, and quality control for MRI scans from MS patients. Such paradigms require advanced image processing and analysis technologies, as well as integrated database management systems to ensure the most utility for clinical and research purposes. This article reviews pipelines available for quantitative clinical MRI research in MS, including image segmentation, registration, time-series analysis, performance validation, visualization techniques, and advanced medical imaging software packages. To address the complex demands of the sequential processes, the authors developed a workflow management system that uses a centralized database and distributed computing system for image processing and analysis. The implementation of their system includes a web-form-based Oracle database application for information management and event dispatching, and multiple modules for image processing and analysis. The seamless integration of processing pipelines with the database makes it more efficient for users to navigate complex, multistep analysis protocols, reduces the user’s learning curve, reduces the time needed for combining and activating different computing modules, and allows for close monitoring for quality-control purposes. The authors’ system can be extended to general applications in clinical trials and to routine processing for image-based clinical research.

BACKGROUND: The visual combination of different modalities is essential for many medical imaging applications in the field of Computer-Assisted medical Diagnosis (CAD) to enhance the clinical information content. Clinically, incontinence is a diagnosis with high clinical prevalence and morbidity rate. The search for a method to identify risk patients and to control the success of operations is still a challenging task. The conjunction of magnetic resonance (MR) and 3D ultrasound (US) image data sets could lead to a new clinical visual representation of the morphology as we show with corresponding data sets of the female anal canal with this paper. METHODS: We present a feasibility study for a non-rigid registration technique based on a biomechanical model for MR and US image data sets of the female anal canal as a base for a new innovative clinical visual representation. RESULTS: It is shown in this case study that the internal and external sphincter region could be registered elastically and the registration partially corrects the compression induced by the ultrasound transducer, so the MR data set showing the native anatomy is used as a frame for the US data set showing the same region with higher resolution but distorted by the transducer CONCLUSION: The morphology is of special interest in the assessment of anal incontinence and the non-rigid registration of normal clinical MR and US image data sets is a new field of the adaptation of this method incorporating the advantages of both technologies.

Multiple sclerosis (MS), a demyelinating disease, occurs principally in the white matter (WM) of the central nervous system. Conventional magnetic resonance imaging (MRI) is sensitive to some, but not all, brain changes associated with MS. Diffusion-weighted imaging (DWI) provides information about water diffusion in tissue and diffusion tensor MRI (DT-MRI) about fiber direction, allowing for the identification of WM abnormalities that are not apparent on conventional MRI images. These techniques can quantitatively characterize the local microstructure of tissues. MS-associated disease processes lead to regions characterized by an increased amount of water diffusion and a decrease in the anisotropy of diffusion direction. These changes have been found to produce different patterns in MS patients presenting different courses of the disease. Changes in water diffusion may allow examination of the type, appearance, enhancement, and location of lesions not readily visible by other means. Ongoing studies of MS are integrating conventional MRI and DT-MRI measures with connectivity-based regional assessment, aiming to provide a better understanding of the nature and the location of WM lesions. This integration and the development of novel image-processing and visualization techniques may improve the understanding of WM architecture and its disruption in MS. This article presents a brief history of DWI, its basic principles and applications in the study of MS, a review of the properties and applications of DT-MRI, and their use in the study of MS. In addition, this article illustrates the methodology for the analysis of DT-MRI in ongoing studies of MS.