Department of Plastic & Reconstructive Surgery, Johns Hopkins University School of Medicine.
Department of Biomedical Engineering, Johns Hopkins University Whiting School of Engineering.
J Craniofac Surg. 2022;33(1):151-155. doi: 10.1097/SCS.0000000000008134.
BACKGROUND: Recent advances in three-dimensional (3D) printing and augmented reality (AR) have expanded anatomical modeling possibilities for caregiver craniosynostosis education. The purpose of this study is to characterize caregiver preferences regarding these visual models and determine the impact of these models on caregiver understanding of craniosynostosis. METHODS: The authors constructed 3D-printed and AR craniosynostosis models, which were randomly presented in a cross-sectional survey. Caregivers rated each model's utility in learning about craniosynostosis, learning about skull anatomy, viewing an abnormal head shape, easing anxiety, and increasing trust in the surgeon in comparison to a two-dimensional (2D) diagram. Furthermore, caregivers were asked to identify the fused suture on each model and indicate their preference for generic versus patient-specific models. RESULTS: A total of 412 craniosynostosis caregivers completed the survey (mean age 33 years, 56% Caucasian, 51% male). Caregivers preferred interactive, patient-specific 3D-printed or AR models over 2D diagrams (mean score difference 3D-printed to 2D: 0.16, P < 0.05; mean score difference AR to 2D: 0.17, P < 0.01) for learning about craniosynostosis, with no significant difference in preference between 3D-printed and AR models. Caregiver detection accuracy of the fused suture on the sagittal model was 19% higher with the 3D-printed model than with the AR model (P < 0.05) and 17% higher with the 3D-printed model than with the 2D diagram (P < 0.05). CONCLUSIONS: Our findings indicate that craniosynostosis caregivers prefer 3D-printed or AR models over 2D diagrams in learning about craniosynostosis. Future craniosynostosis skull models with increased user interactivity and patient-specific components can better suit caregiver preferences.
背景: 三维 (3D) 打印和增强现实 (AR) 的最新进展扩大了 caregiver颅缝早闭教育的解剖模型可能性。本研究的目的是描述 caregiver 对这些视觉模型的偏好,并确定这些模型对 caregiver对颅缝早闭理解的影响。
方法:作者构建了 3D 打印和 AR 颅缝早闭模型,在横断面调查中随机呈现。 caregiver 对每种模型在学习颅缝早闭、学习颅骨解剖结构、观察异常头型、缓解焦虑以及增加对外科医生信任方面的效用进行评分,与二维 (2D) 图进行比较。此外, caregiver 被要求识别每个模型上融合的缝线,并表示他们对通用模型与患者特异性模型的偏好。
结果:共有 412 名颅缝早闭 caregiver完成了调查(平均年龄 33 岁,56%为白种人,51%为男性)。 caregiver 更喜欢交互式、患者特异性的 3D 打印或 AR 模型,而不是 2D 图(3D 打印与 2D 相比的平均评分差异:0.16,P<0.05;AR 与 2D 相比的平均评分差异:0.17,P<0.01),用于学习颅缝早闭,3D 打印和 AR 模型之间的偏好没有显著差异。与 AR 模型相比, caregiver 在矢状模型上检测融合缝线的准确性提高了 19%(P<0.05),与 2D 图相比提高了 17%(P<0.05)。
结论:我们的研究结果表明, caregiver 在学习颅缝早闭时更喜欢 3D 打印或 AR 模型,而不是 2D 图。未来具有更高用户交互性和患者特异性组件的颅缝早闭颅骨模型可以更好地满足 caregiver 的偏好。
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