CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images.

In the last decade, a large number of clinical trials have been deployed using Cardiac Magnetic Resonance (CMR) to evaluate cardioprotective strategies aiming at reducing the irreversible myocardial damage at the time of reperfusion. In these studies, segmentation and quantification of myocardial infarct lesion are often performed with a commercial software or an in-house closed-source code development thus creating a barrier for reproducible research. This paper introduces CMRSegTools: an open-source application software designed for the segmentation and quantification of myocardial infarct lesion enabling full access to state-of-the-art segmentation methods and parameters, easy integration of new algorithms and standardised results sharing. This post-processing tool has been implemented as a plug-in for the OsiriX/Horos DICOM viewer leveraging its database management functionalities and user interaction features to provide a bespoke tool for the analysis of cardiac MR images on large clinical cohorts. CMRSegTools includes, among others, user-assisted segmentation of the left-ventricle, semi- and automatic lesion segmentation methods, advanced statistical analysis and visualisation based on the American Heart Association 17-segment model. New segmentation methods can be integrated into the plug-in by developing components based on image processing and visualisation libraries such as ITK and VTK in C++ programming language. CMRSegTools allows the creation of training and testing data sets (labeled features such as lesion, microvascular obstruction and remote ROI) for supervised Machine Learning methods, and enables the comparative assessment of lesion segmentation methods via a single and integrated platform. The plug-in has been successfully used by several CMR imaging studies.

International registry of congenital porto-systemic shunts: a multi-centre, retrospective and prospective registry of neonates, children and adults with congenital porto-systemic shunts.

BACKGROUND: Congenital portosystemic shunts (CPSS) are rare vascular malformations associated with the risk of life-threatening systemic conditions, which remain underdiagnosed and often are identified after considerable diagnostic delay. CPSS are characterized by multiple signs and symptoms, often masquerading as other conditions, progressing over time if the shunt remains patent. Which patients will benefit from shunt closure remains to be clarified, as does the timing and method of closure. In addition, the etiology and pathophysiology of CPSS are both unknowns. This rare disorder needs the strength of numbers to answer these questions, which is the purpose of the international registry of CPSS (IRCPSS). METHOD: A retrospective and prospective registry was designed using secuTrial® by the ISO certified Clinical Research Unit. Given that a significant number of cases entered in the registry are retrospective, participants have the opportunity to use a semi-structured minimal or complete data set to facilitate data entry. In addition, the design allows subjects to be entered into the IRCPSS according to clinically relevant events. Emphasis is on longitudinal follow-up of signs and symptoms, which is paramount to garner clinically relevant information to eventually orient patient management. The IRCPSS includes also three specific forms to capture essential radiological, surgical, and cardiopulmonary data as many times as relevant, which are completed by the specialists themselves. Finally, connecting the clinical data registry with a safe image repository, using state-of-the-art pseudonymization software, was another major focus of development. Data quality and stewardship is ensured by a steering committee. All centers participating in the IRCPSS have signed a memorandum of understanding and obtained their own ethical approval. CONCLUSION: Through state-of-the-art management of data and imaging, we have developed a practical, user-friendly, international registry to study CPSS in neonates, children, and adults. Via this multicenter and international effort, we will be ready to answer meaningful and urgent questions regarding the management of patients with CPSS, a condition often ridden with significant diagnostic delay contributing to a severe clinical course.

A multicentric IT platform for storage and sharing of imaging-based radiation dosimetric data.

PURPOSE: The MEDIRAD project is about the effects of low radiation dose in the context of medical procedures. The goal of the work is to develop an informatics service that will provide the researchers of the MEDIRAD project with a platform to share acquired images, along with the associated dosimetric data pertaining to the radiation resulting from the procedure. METHODS: The authors designed a system architecture to manage image data and dosimetric data in an integrated way. DICOM and non-DICOM data are stored in separated repositories, and the link between the two is provided through a semantic database, i.e., a database whose information schema in aligned with an ontology. RESULTS: The system currently supports CT, PET, SPECT, and NM images as well as dose reports. Currently, two workflows for non-DICOM data generated from dosimetric calculations have been taken into account, one concerning Monte Carlo-based calculation of organ doses in Chest CT, and the other estimation of doses in nontarget organs in 131I targeted radionuclide therapy of the thyroid. CONCLUSION: The system is currently deployed, thus providing access to image and related dosimetric data to all MEDIRAD users. The software was designed in such a way that it can be reused to support similar needs in other projects.

A semantic database for integrated management of image and dosimetric data in low radiation dose research in medical imaging.

Medical ionizing radiation procedures and especially medical imaging are a non negligible source of exposure to patients. Whereas the biological effects of high absorbed doses are relatively well known, the effects of low absorbed doses are still debated. This work presents the development of a computer platform called Image and Radiation Dose BioBank (IRDBB) to manage research data produced in the context of the MEDIRAD project, a European project focusing on research on low doses in the context of medical procedures. More precisely, the paper describes a semantic database linking dosimetric data (such as absorbed doses to organs) to the images corresponding to X-rays exposure (such as CT images) or scintigraphic images (such as SPECT or PET images) that allow measuring the distribution of a radiopharmaceutical. The main contributions of this work are: 1) the implementation of the semantic database of the IRDBB system and 2) an ontology called OntoMEDIRAD covering the domain of discourse involved in MEDIRAD research data, especially many concepts from the DICOM standard modelled according to a realist approach.

Stereoscopic augmented reality for da Vincii™ robotic biliary surgery.

INTRODUCTION: New laparoscopic techniques put distance between the surgeon and his patient. PRESENTATION OF CASE: 3D volume rendered images directly displayed in the da Vinci surgeon's console fill this gap by allowing the surgeon to fully immerse in its intervention. DISCUSSION: During the robotic operation the surgeon has a greater control on the procedure because he can stay more focused not being obliged to turn is sight out of his operative field. Moreover, thanks to depth perception of the rendered images he had a precise view of important anatomical structures. CONCLUSION: We describe our preliminary experience in the quest of computer-assisted robotic surgery.

Augmented reality to the rescue of the minimally invasive surgeon. The usefulness of the interposition of stereoscopic images in the Da Vinci™ robotic console.

BACKGROUND: Computerized management of medical information and 3D imaging has become the norm in everyday medical practice. Surgeons exploit these emerging technologies and bring information previously confined to the radiology rooms into the operating theatre. The paper reports the authors' experience with integrated stereoscopic 3D-rendered images in the da Vinci surgeon console. METHODS: Volume-rendered images were obtained from a standard computed tomography dataset using the OsiriX DICOM workstation. A custom OsiriX plugin was created that permitted the 3D-rendered images to be displayed in the da Vinci surgeon console and to appear stereoscopic. These rendered images were displayed in the robotic console using the TilePro multi-input display. The upper part of the screen shows the real endoscopic surgical field and the bottom shows the stereoscopic 3D-rendered images. These are controlled by a 3D joystick installed on the console, and are updated in real time. RESULTS: Five patients underwent a robotic augmented reality-enhanced procedure. The surgeon was able to switch between the classical endoscopic view and a combined virtual view during the procedure. Subjectively, the addition of the rendered images was considered to be an undeniable help during the dissection phase. CONCLUSION: With the rapid evolution of robotics, computer-aided surgery is receiving increasing interest. This paper details the authors' experience with 3D-rendered images projected inside the surgical console. The use of this intra-operative mixed reality technology is considered very useful by the surgeon. It has been shown that the usefulness of this technique is a step toward computer-aided surgery that will progress very quickly over the next few years.

Console-integrated stereoscopic OsiriX 3D volume-rendered images for da Vinci colorectal robotic surgery.

The increased distance between surgeon and surgical field is a significant problem in laparoscopic surgery. Robotic surgery, although providing advantages for the operator, increases this gap by completely removing force feedback. Enhancement with visual tools can therefore be beneficial. The goal of this preliminary work was to create a custom plugin for OsiriX to display volume-rendered images in the da Vinci surgeon's console. The TilePro multi-input display made the generated stereoscopic pairs appear to have depth. Tumor position, vascular supply, spatial location, and relationship between organs appear directly within the surgeon's field of view. This study presents a case of totally robotic right colectomy for cancer using this new technology. Sight diversion was no longer necessary. Depth perception was subjectively perceived as profitable. Total immersion in the operative field helped compensate for the lack of tactile feedback specific to robotic intervention. This innovative tool is a step forward toward augmented-reality robot-assisted surgery.

A computational framework for ultrastructural mapping of neural circuitry.

Circuitry mapping of metazoan neural systems is difficult because canonical neural regions (regions containing one or more copies of all components) are large, regional borders are uncertain, neuronal diversity is high, and potential network topologies so numerous that only anatomical ground truth can resolve them. Complete mapping of a specific network requires synaptic resolution, canonical region coverage, and robust neuronal classification. Though transmission electron microscopy (TEM) remains the optimal tool for network mapping, the process of building large serial section TEM (ssTEM) image volumes is rendered difficult by the need to precisely mosaic distorted image tiles and register distorted mosaics. Moreover, most molecular neuronal class markers are poorly compatible with optimal TEM imaging. Our objective was to build a complete framework for ultrastructural circuitry mapping. This framework combines strong TEM-compliant small molecule profiling with automated image tile mosaicking, automated slice-to-slice image registration, and gigabyte-scale image browsing for volume annotation. Specifically we show how ultrathin molecular profiling datasets and their resultant classification maps can be embedded into ssTEM datasets and how scripted acquisition tools (SerialEM), mosaicking and registration (ir-tools), and large slice viewers (MosaicBuilder, Viking) can be used to manage terabyte-scale volumes. These methods enable large-scale connectivity analyses of new and legacy data. In well-posed tasks (e.g., complete network mapping in retina), terabyte-scale image volumes that previously would require decades of assembly can now be completed in months. Perhaps more importantly, the fusion of molecular profiling, image acquisition by SerialEM, ir-tools volume assembly, and data viewers/annotators also allow ssTEM to be used as a prospective tool for discovery in nonneural systems and a practical screening methodology for neurogenetics. Finally, this framework provides a mechanism for parallelization of ssTEM imaging, volume assembly, and data analysis across an international user base, enhancing the productivity of a large cohort of electron microscopists.