Article Text
Abstract
Introduction Modern patient portals are powerful tools that foster communication between providers and patients. While increasing patient access to their medical records, these portals often only provide written radiology reports and may not be user-friendly. At Michigan Medicine’s neurointerventional radiology (NIR) and neurosurgery clinics, we aim to enhance patient understanding of their head and neck anatomy and pathology during informed consent discussions utilizing interactive 3D models.
Materials and Methods Subjects from a single institution NIR and neurosurgery clinics were virtually consented for enrollment and randomly assigned to the 3D model arm, where 3D models served as visual aids, or the control arm, involving standard clinic discussions. All subjects received pre- and post-clinic surveys assessing general health literacy via a modified AHRQ health literacy survey. For subjects randomized into the 3D model arm, models were created from segmentations of their angiographic and cross-sectional imaging. The models were accessed through an online 3D visualization platform on their mobile devices (figure 1) and used as visual aids during the clinic visit.
Results To date, 47 subjects have been enrolled, 26 completing post-clinic surveys: 12 in the 3D model arm and 14 in the control. All subjects in the 3D arm had access to the 3D model during clinic, while only 7/14 (50%) subjects in the control arm were provided visual aids. Following clinic, 7/12 (58.3%) subjects in the 3D model arm could access the images at home, compared to 3/14 (21.4%) in the control arm. When evaluating the clarity of treatment explanations, 10/12 (83.3%) subjects in the 3D arm felt the explanations were ‘clear’ or ‘very clear,’ compared to 9/14 (64.2%) in the control arm.
Conclusion Interactive 3D models offer readily understandable and accessible imaging, helping patients better comprehend their medical conditions and proposed treatments. As traditional patient portals primarily offer text-based radiological records, patients often struggle to interpret the results. 3D models present images in an easily understandable format, and modern personal devices are already capable of rendering these models without specialized software. Our project aims to bridge the gap between radiological images and accessible 3D models on personal devices, empowering patients with deeper insights and facilitating informed decision-making.
Disclosures A. Park: None. M. Rhee: None. S. Panicker: None. B. Pinsky: None. A. Pandey: None. B. Thompson: None. D. Altshuler: None. Z. Wilseck: None. J. Gemmete: None. N. Chaudhary: None. L. Lin: 1; C; RSNA Education Project Award.