The MDIC MXR Regulatory Science of Surgical Applications Project has involved key stakeholders from industry, healthcare, academia, and government to identify testing considerations and open evaluation challenges that impede the development, implementation, and novel applications of MXR devices across healthcare applications for surgical planning and procedures.
This framework document highlights safety and effectiveness considerations and testing approaches or evaluation gaps for MXR Human Factors and MXR Image Quality. The chapter on human factors includes a landscape analysis of human factors considerations for MXR devices for surgical planning and procedures, including healthcare provider safety and user experience, patient safety and user experience, and relevant testing approaches. The chapter on image quality includes a landscape analysis of image quality and visualization accuracy considerations and testing for these devices, including lessons learned and degree of overlap with 2D display evaluation methods.
The MDIC MXR Landscape Analysis of Surgical Applications Workgroup is comprised of leaders in MXR, its medical applications, and assessment, who have set for themselves the ambitious vision to advance the safe and effective implementation and evaluation of MXR devices. They aim to accelerate the development of MXR devices across application spaces, with an initial focus on surgical planning and procedures, to the ultimate benefit of patients.
The group is a learning community that has come together biweekly for over a year to answer questions about the cutting edge of AR/VR devices today, how they should be assessed, what drives innovation and adoption, and future impact the devices will have on patient care and the digital transformation of health. The result of these discussions and a survey of the landscape is this framework report, which focuses on human factors and image quality topics as areas in which MXR devices have faced hurdles. By reviewing the state of the art in these disciplines and considering how it can be applied specifically to MXR devices, the Workgroup hopes to support manufacturers developing novel devices in answering fundamental regulatory science questions about the assessment of their devices. The Workgroup has also identified assessment challenges and knowledge gaps, which require continued effort across the ecosystem to address and pave the way for consistent, clear standards and scientific consensus in MXR testing.
A landscape and gap analysis of approaches to demonstrate training effectiveness, identify training objectives and converting them into metrics, and identifying the most pressing gaps and/or challenges related to training and education.
Establish standard terminology and definitions for MXR applications relevant to the current framework
A landscape and gap analysis of image quality and visualization accuracy considerations and testing for MXR devices for surgical planning and procedures.
A landscape and gap analysis of human factors considerations for MXR devices for surgical planning and procedures.
Image Quality
Enosis
CEO
Image Quality
RealView Imaging Ltd.
Vice President of R&D
Human Factors
Inogen, Inc.
Human Factors Studies Senior Manger
Human Factors
Washington University in St. Louis
Director of Pediatric Electrophysiology / Professor of Pediatrics and Biomedical Engineering
Training & Education
Johnson & Johnson, MedTech
Sr. Director RA, Interventional Oncology
Training & Education
Brighter Research
Principal Scientist and Chief Consultant
Terminology
& Taxonomy
IVRHA
Executive Director
Digital Health & Technology
Senior Director
Digital Health & Technology
Project Manager