Immersive Radiation Experience for Interventional Radiology with Virtual Reality Radiation Dose Visualization Using Fast Monte Carlo Dose Estimation.
Interv Radiol (Higashimatsuyama)
; 5(2): 58-66, 2020 Jun 30.
Article
en En
| MEDLINE
| ID: mdl-36284664
For interventional radiology (IR), understanding the precise dose distribution is crucial to reduce the risks of radiation dermatitis to patients and staff. Visualization of dose distribution is expected to support radiation safety efforts immensely. This report presents techniques for perceiving the dose distribution using virtual reality (VR) technology and for estimating the air dose distribution accurately using Monte Carlo simulation for VR dose visualization. We adopted an earlier reported Monte-Carlo-based estimation system for IR and simulated the dose in a geometrical area resembling an IR room with fluoroscopic conditions. Users of our VR system experienced a simulated air dose distribution in the IR room while the irradiation angle, irradiation timing, and lead shielding were controlled. The estimated air dose was evaluated through comparison with measurements taken using a radiophotoluminescence glass dosimeter. Our dose estimation results were consistent with dosimeter readings, showing a 13.5% average mutual difference. The estimated air dose was visualized in VR: users could view a virtual IR room and walk around in it. Using our VR system, users experienced dose distribution changes dynamically with C-arm rotation. Qualitative tests were conducted to evaluate the workload and usability of our VR system. The perceived overall workload score (18.00) was lower than the scores reported in the literature for medical tasks (50.60) and computer activities (54.00). This VR visualization is expected to open new horizons for understanding dose distributions intuitively, thereby aiding the avoidance of radiation injury.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Qualitative_research
Idioma:
En
Revista:
Interv Radiol (Higashimatsuyama)
Año:
2020
Tipo del documento:
Article
País de afiliación:
Japón
Pais de publicación:
Japón