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Published on: April 14, 2023
Patient-Specific Actual-Size Three-Dimensional Printed Models for Patient Education in Glioma Treatment: First
Tom H van de Belt1, Hugo Nijmeijer1, David Grim1
1Radboudumc REshape Innovation Center, Radboud University Medical Center, Nijmegen, The Netherlands.
Background:
Patients with cancer need high-quality information about disease stage, treatment options, and side effects. High-quality information can also improve health literacy, shared decision making, and satisfaction. We created patient-specific three-dimensional (3D) models of tumors including surrounding functional areas and assessed what patients with glioma value (or fear) about the models when they are used to educate them about the relationship between their tumor and specific brain parts, the surgical procedure, and risks.
Methods:
This exploratory study included adult patients with glioma who underwent functional magnetic resonance imaging and diffusion tensor imaging as part of preoperative work-up. All participants received an actual-size 3D model printed based on functional magnetic resonance imaging and diffusion tensor imaging. Semistructured interviews were conducted to identify facilitators and barriers for using the model and perceived effects.
Results:
Models were successfully created for all 11 participants. There were 18 facilitators and 8 barriers identified. The model improved patients' understanding about their situation; patients reported that it was easier to ask their neurosurgeon questions based on their model and that it supported their decision about preferred treatment. A perceived barrier for using the 3D model was that it could be emotionally confronting, particularly in an early phase of the disease. Positive effects were related to psychological domains, including coping, learning effects, and communication.
Conclusions:
Patient-specific 3D models are promising and simple tools that could help patients with glioma better understand their situation, treatment options, and risks. These models have the potential to improve shared decision making.
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