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Virtual Imaging for Patient Information on Radiotherapy Planning and Delivery for Prostate Cancer

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Medical Image Understanding and Analysis (MIUA 2021)

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Abstract

The provision of information on radiotherapy (RT) planning and delivery for patient with cancer is a vital issue in improving not only patients’ satisfaction but also patients’ compliance to treatment. In the present study, patients with prostate cancer receiving RT were randomised to have the provision of information on RT planning and delivery using Virtual Reality (VR) prior to RT or on the last day of RT. Bladder and rectal volumes and separations were measured prior to starting RT, weekly during RT and on the last day of RT. A quality of life questionnaire was completed prior to RT, halfway through RT, at the end of RT and at 3 and 6 months after RT in order to assess side effects. Bladder volumes decreased towards the end of RT but no differences were seen between patients in either cohort. The scores of the quality of life questionnaire showed only a statistical difference at 3 months after RT with lower scores (less intense side effects) for patients in Cohort 1. Although this study failed to show that provision of information to patients receiving RT using VR improves compliance, VT tools were very welcomed by patients as a means of providing information on RT planning and delivery. In the future, this study may provide cancer centres with an useful tool to audit local protocols regarding patient preparations and training for prostate RT.

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This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

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Correspondence to Miguel Martínez-Albaladejo .

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Martínez-Albaladejo, M., Sulé-Suso, J., Lines, D., Bisson, J., Jassal, S., Edwards, C. (2021). Virtual Imaging for Patient Information on Radiotherapy Planning and Delivery for Prostate Cancer. In: Papież, B.W., Yaqub, M., Jiao, J., Namburete, A.I.L., Noble, J.A. (eds) Medical Image Understanding and Analysis. MIUA 2021. Lecture Notes in Computer Science(), vol 12722. Springer, Cham. https://doi.org/10.1007/978-3-030-80432-9_10

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  • DOI: https://doi.org/10.1007/978-3-030-80432-9_10

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  • Online ISBN: 978-3-030-80432-9

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