Novel Virtual Reality App for Training Patients on MRI-guided Radiation Therapy.


Journal

Advances in radiation oncology
ISSN: 2452-1094
Titre abrégé: Adv Radiat Oncol
Pays: United States
ID NLM: 101677247

Informations de publication

Date de publication:
Jun 2024
Historique:
received: 12 09 2023
accepted: 09 02 2024
medline: 29 4 2024
pubmed: 29 4 2024
entrez: 29 4 2024
Statut: epublish

Résumé

Patients receiving respiratory gated magnetic resonance imaging-guided radiation therapy (MRIgRT) for abdominal targets must hold their breath for ≥25 seconds at a time. Virtual reality (VR) has shown promise for improving patient education and experience for diagnostic MRI scan acquisition. We aimed to develop and pilot-test the first VR app to educate, train, and reduce anxiety and discomfort in patients preparing to receive MRIgRT. A multidisciplinary team iteratively developed a new VR app with patient input. The app begins with minigames to help orient patients to using the VR device and to train patients on breath-holding. Next, app users are introduced to the MRI linear accelerator vault and practice breath-holding during MRIgRT. In this quality improvement project, clinic personnel and MRIgRT-eligible patients with pancreatic cancer tested the VR app for feasibility, acceptability, and potential efficacy for training patients on using breath-holding during MRIgRT. The new VR app experience was tested by 19 patients and 67 clinic personnel. The experience was completed on average in 18.6 minutes (SD = 5.4) by patients and in 14.9 (SD = 3.5) minutes by clinic personnel. Patients reported the app was "extremely helpful" (58%) or "very helpful" (32%) for learning breath-holding used in MRIgRT and "extremely helpful" (28%) or "very helpful (50%) for reducing anxiety. Patients and clinic personnel also provided qualitative feedback on improving future versions of the VR app. The VR app was feasible and acceptable for training patients on breath-holding for MRIgRT. Patients eligible for MRIgRT for pancreatic cancer and clinic personnel reported on future improvements to the app to enhance its usability and efficacy.

Identifiants

pubmed: 38681889
doi: 10.1016/j.adro.2024.101477
pii: S2452-1094(24)00040-X
pmc: PMC11043805
doi:

Types de publication

Journal Article

Langues

eng

Pagination

101477

Informations de copyright

© 2024 The Authors.

Déclaration de conflit d'intérêts

BDG reports fees unrelated to this project from Sure Med Compliance and Elly Health. KL reports fees unrelated to this project from ViewRay. HJ reports fees unrelated to this project from Kite Pharma and SBR Biosciences. JF reports fees unrelated to this project from ViewRay and Boston Scientific. SH reports fees unrelated to this project from VeiwRay.

Auteurs

Brian D Gonzalez (BD)

Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL.

Sylvia Choo (S)

Morsani College of Medicine, University of South Florida, Tampa, FL.

Joseph J Janssen (JJ)

Ringling College of Art and Design, Sarasota, FL.

Jeff Hazelton (J)

XdooR, Venice, FL.

Kujtim Latifi (K)

Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL.

Corinne R Leach (CR)

Center for Digital Health, Moffitt Cancer Center, Tampa, FL.

Shannon Bailey (S)

Morsani College of Medicine, University of South Florida, Tampa, FL.
Center for Advanced Medical Learning and Simulation, University of South Florida, Tampa, FL.

Heather S L Jim (HSL)

Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL.

Laura B Oswald (LB)

Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL.

Morgan Woolverton (M)

Ringling College of Art and Design, Sarasota, FL.

Martin Murphy (M)

Ringling College of Art and Design, Sarasota, FL.

Edward L Schilowitz (EL)

XdooR, Venice, FL.

Jessica M Frakes (JM)

Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL.

Edmondo J Robinson (EJ)

Center for Digital Health, Moffitt Cancer Center, Tampa, FL.

Sarah Hoffe (S)

Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL.

Classifications MeSH