4,614 research outputs found

    Addressing the challenges of ECMO simulation

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    This document is the Accepted Manuscript. The final, definitive version of this paper has been published in Perfusion, May 2018, published by SAGE Publishing, All rights reserved.Introduction/Aim: The patient’s condition and high-risk nature of extracorporeal membrane oxygenation (ECMO) therapy force clinical services to ensure clinicians are properly trained and always ready to deal effectively with critical situations. Simulation-based education (SBE), from the simplest approaches to the most immersive modalities, helps promote optimum individual and team performance. The risks of SBE are negative learning, inauthenticity in learning and over-reliance on the participants’ suspension of disbelief. This is especially relevant to ECMO SBE as circuit/patient interactions are difficult to fully simulate without confusing circuit alterations. Methods: Our efforts concentrate on making ECMO simulation easier and more realistic in order to reduce the current gap there is between SBE and real ECMO patient care. Issues to be overcome include controlling the circuit pressures, system failures, patient issues, blood colour and cost factors. Key to our developments are the hospital-university collaboration and research funding. Results: A prototype ECMO simulator has been developed that allows for realistic ECMO SBE. The system emulates the ECMO machine interface with remotely controllable pressure parameters, haemorrhaging, line chattering, air bubble noise and simulated blood colour change. Conclusion: The prototype simulator allows the simulation of common ECMO emergencies through innovative solutions that enhance the fidelity of ECMO SBE and reduce the requirement for suspension of disbelief from participants. Future developments will encompass the patient cannulation aspect.Peer reviewe

    Biopsym : a learning environment for transrectal ultrasound guided prostate biopsies

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    This paper describes a learning environment for image-guided prostate biopsies in cancer diagnosis; it is based on an ultrasound probe simulator virtually exploring real datasets obtained from patients. The aim is to make the training of young physicians easier and faster with a tool that combines lectures, biopsy simulations and recommended exercises to master this medical gesture. It will particularly help acquiring the three-dimensional representation of the prostate needed for practicing biopsy sequences. The simulator uses a haptic feedback to compute the position of the virtual probe from three-dimensional (3D) ultrasound recorded data. This paper presents the current version of this learning environment

    Focal Spot, Summer/Fall 2006

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    https://digitalcommons.wustl.edu/focal_spot_archives/1103/thumbnail.jp

    Medical image computing and computer-aided medical interventions applied to soft tissues. Work in progress in urology

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    Until recently, Computer-Aided Medical Interventions (CAMI) and Medical Robotics have focused on rigid and non deformable anatomical structures. Nowadays, special attention is paid to soft tissues, raising complex issues due to their mobility and deformation. Mini-invasive digestive surgery was probably one of the first fields where soft tissues were handled through the development of simulators, tracking of anatomical structures and specific assistance robots. However, other clinical domains, for instance urology, are concerned. Indeed, laparoscopic surgery, new tumour destruction techniques (e.g. HIFU, radiofrequency, or cryoablation), increasingly early detection of cancer, and use of interventional and diagnostic imaging modalities, recently opened new challenges to the urologist and scientists involved in CAMI. This resulted in the last five years in a very significant increase of research and developments of computer-aided urology systems. In this paper, we propose a description of the main problems related to computer-aided diagnostic and therapy of soft tissues and give a survey of the different types of assistance offered to the urologist: robotization, image fusion, surgical navigation. Both research projects and operational industrial systems are discussed

    Focal Spot, Spring 1978

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    https://digitalcommons.wustl.edu/focal_spot_archives/1020/thumbnail.jp

    Competence and training in interventional pulmonology

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