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Updated: Aug 20, 2026
A Training and Testing System for Performing Vascular Reconstruction In Vitro
Published on: October 26, 2019
Increasing face validity of a vascular interventional training system
John Winder1, Huiru Zheng, Simon Hughes
1School Of Applied Medical Sciences and Sports Studies, University of Ulster, Shore Road, Newtownabbey, BT37 0QB, Northern Ireland, UK.
Background:
Many aspects of medical training take place on real patients in a live environment thus incurring risk. Apart from the obvious risks to patients there is the issue of X-ray exposure to both staff and trainees. Image quality used during interventional procedures is low to ensure minimum X-ray radiation dose. A virtual interventional system may be used to simulate the interventional cardiology training environment therefore reducing overall risk. The purpose of this project was to determine the appropriate image quality settings on a virtual training system to accurately simulate interventional cardiology and increase the face validity of the overall system.
Methods:
Real image data was obtained from patients undergoing diagnostic interventional cardiology examinations in the Royal Victoria Hospital, Belfast. The images were obtained during catheter placement and contrast enhancement around the region of the heart. The diagnostic views were left anterior oblique, right anterior oblique, left lateral, caudal and the spider view. These five views were simulated on a virtual interventional training system (VIST, Mentice Medical Simulation AB, Sweden) by adjusting x-ray tube and table position at 20 different image quality settings. Signal to noise ratio and image contrast were measured for each of these views using soft tissue and vertebra. The results from the real image data and the VIST image data were compared. Calibration curves were compiled to determine the appropriate VIST image quality setting for each procedure.
Results:
Average SNR ranged from 2.94 to 74.0 and IC ranged from 0.009 to 0.61 on the real image data. This indicates the very wide range of image quality encountered in interventional cardiology. Calibration curves for each view with the corresponding range of real patient image quality were produced. These calibration curves enabled the appropriate VIST image quality setting to be determined and therefore simulate the real examination image quality as closely as possible.
Conclusions:
The VIST system has been calibrated in terms of image quality for interventional cardiology examinations. This has increased the face validity of the system.
