Jacquemyn Xander, Bamps Kobe, Moermans Ruben, Dubois Christophe, Rega Filip, Verbrugghe Peter, Weyn Barbara, Dymarkowski Steven, Budts Werner, Van De Bruaene Alexander
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引用次数: 0
Abstract
Purpose: Virtual reality (VR) and augmented reality (AR) have led to significant advancements in cardiac preoperative planning, shaping the world in profound ways. A noticeable gap exists in the availability of a comprehensive multi-user, multi-device mixed reality application that can be used in a multidisciplinary team meeting.
Approach: A multi-user, multi-device mixed reality application was developed, supporting AR and VR implementations. Technical validation involved a standardized testing protocol and comparison of AR and VR measurements regarding absolute error and time. Preclinical validation engaged experts in interventional cardiology, evaluating the clinical applicability prior to clinical validation. Clinical validation included patient-specific measurements for five patients in VR compared with standard computed tomography (CT) for preoperative planning. Questionnaires were used at all stages for subjective evaluation.
Results: Technical validation, including 106 size measurements, demonstrated an absolute median error of 0.69 mm (0.25 to 1.18 mm) compared with ground truth. The time to complete the entire task was on average, with VR measurements being faster than AR ( versus , ). On clinical validation of five preoperative patients, there was no statistically significant difference between paired CT and VR measurements (0.58 [95% CI, to 2.74], ). Questionnaires showcased unanimous agreement on the user-friendly nature, effectiveness, and clinical value.
Conclusions: The mixed reality application, validated through technical, preclinical, and clinical assessments, demonstrates precision and user-friendliness. Further research of our application is needed to validate the generalizability and impact on patient outcomes.
期刊介绍:
JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.