Breast Magnetic Resonance Image Analysis for Surgeons Using Virtual Reality: A Comparative Study
The treatment of breast cancer, the leading cause of cancer and cancer mortality among women worldwide, is mainly on the basis of surgery. In this study, we describe the use of a medical image visualization tool on the basis of virtual reality (VR), entitled DIVA, in the context of breast cancer tumor localization among surgeons. The aim of this study was to evaluate the speed and accuracy of surgeons using DIVA for medical image analysis of breast magnetic resonance image (MRI) scans relative to standard image slice-based visualization tools.
Partial breast resection for multifocal lower quadrant breast tumour using virtual reality
Oncoplastic surgery allows an increase in the number of indications for conservative breast cancer treatments. However, uncertainty as to whether it can be performed still exists in certain situations such as with multicentric or multifocal lesions, even when the breast volume can accommodate it. With the aid of a virtual reality software, DIVA, allowing the precise visualisation of tumours and breast volumes based entirely on the patient’s MRI, we report the ability to rapidly confirm and secure an indication for partial surgery of multiple lesions in a 31-year-old patient. With the described approach, the patient did not have to suffer significant disfigurement from cancerous breast surgery without compromising safety.
Fast-track VR for Cardiac Imaging in Congenital Heart Disease
We sought to evaluate the appropriateness of cardiac anatomy renderings by a new virtual reality (VR) technology, entitled DIVA, directly applicable to raw MRI imaging data without intermediate segmentation steps in comparison to standard 3D rendering techniques (3D PDF and 3D printing). Differences in post processing times were also evaluated.
DIVA, a 3D virtual reality platform, improves undergraduate craniofacial trauma education
Craniofacial fracture management is challenging to teach due to the complex anatomy of the skull, even when using three-dimensional (3D) CT-scan images. DIVA is a software allowing the straightforward visualization of CT-scans in a user-friendly 3D virtual reality (VR) environment. Here, we assess DIVA as an educational tool for craniofacial trauma for undergraduate medical students.
Video Credit: AP-HP, Descartes University.
Management of ischiopagus twin separation with a focus on W–S incision design
Ischiopagus twins share parts of the spine, central nervous system, gastrointestinal and genitou-rinary tracts with various degrees of severity. Their separation is a surgical challenge. From the perspective of the plastic surgeon, one of the straightforward technical problems of conjoined twin separation is the coverage of the large residual parietal defects determined by the initial skin incisions.
This report provides a description of relevant incision design strategies for ischiopagus separation in order to minimize morbidity related to coverage issues, especially in the abdominal and perineal regions.
DIVA: natural navigation inside 3D images using virtual reality
As three-dimensional microscopy becomes commonplace in biological research, there is an increasing need for researchers to be able to view experimental image stacks in a natural three-dimensional viewing context. Through stereoscopy and motion tracking, commercial virtual reality headsets provide a solution to this important visualization challenge by allowing researchers to view volumetric objects in an entirely intuitive fashion. With this motivation, we present DIVA, a user-friendly software tool that automatically creates detailed three-dimensional reconstructions of raw experimental image stacks that are integrated in virtual reality. In DIVA’s immersive virtual environment, users can view, manipulate and perform volumetric measurements on their microscopy images as they would to real physical objects. In contrast to similar solutions, our software provides high-quality volume rendering with native TIFF file compatibility. We benchmark the software with diverse image types including those generated by confocal, light-sheet and electron microscopy. DIVA is available at https://diva.pasteur.fr/ and will be regularly updated.
Virtual reality: beyond visualization
Virtual reality (VR) has recently become an affordable technology. A wide range of options are available to access this unique visualization medium, from simple cardboard inserts for smartphones to truly advanced headsets tracked by external sensors. While it is now possible for any research team to gain access to VR, we can still question what it brings to scientific research. Visualization and the ability to navigate complex three-dimensional data are undoubtedly a gateway to many scientific applications; however, we are convinced that data treatment and numerical simulations, especially those mixing interactions with data, human cognition, and automated algorithms will be the future of VR in scientific research. Moreover, VR might soon merit the same level of attention to imaging data as machine learning currently has. In this short perspective, we discuss approaches that employ VR in scientific research based on some concrete examples.
Genuage: visualizing and analyzing multidimensional point cloud data in virtual reality
The quantity of experimentally recorded point cloud data, such generated in single-molecule experiments, is increasing continuously in both size and dimension. Gaining an intuitive understanding of the data and facilitating multi-dimensional data analysis remains a challenge. It is especially challenging when static distribution properties are not predictive of dynamical properties. Here, we report a new open-source software platform, Genuage, that enables the easy perception, interaction and analysis of complex multidimensional point cloud datasets by leveraging virtual reality. We illustrate the benefit of the Genuage with examples of three-dimensional static and dynamic localization microscopy datasets, as well as some synthetic datasets. Genuage has a large breadth of usage modes, due to its compatibility with arbitrary multidimensional data types extending beyond the single-molecule research community.
InferenceMAP: mapping of single- molecule dynamics with Bayesian inference
Cellular processes critically depend on the behavior of individual molecules. Through recent high-density single-particle tracking techniques, information about the dynamic environment experienced by molecules may be accessed through powerful statistical models. We present InferenceMAP, an interactive software tool that uses a powerful Bayesian technique to extract the parameters that describe the motion of individual molecules (diffusion, force, drift, and interaction energy) from single-molecule trajectories. Principle features include a versatile Bayesian analysis platform, extensive mapping functions which permit generation of dynamic landscapes of entire cells, and numerous user-friendliness considerations. InferenceMAP is controlled via a graphical user interface and is compatible with Mac OS X and Windows.
ViSP: representing single-particle localizations in three dimensions
ViSP is an interactive software tool for representing and quantifying localization data from photoactivation optical microscopy experiments. Tailored to efficiently handle datasets consisting of millions of individual localizations, ViSP accurately renders three-dimensional localization precisions, allows surface rendering of localization groupings, and is compatible with multi-channel datasets. Localizations are quantified through the measurement of arbitrary localization density profiles, cluster segmentation, and various filtering tools. ViSP is controlled through a graphical user interface and is compatible with Mac OS X and Windows.