RESUMEN

Prostheses play a critical role in healthcare provision for many patients and encompass aesthetic facial prostheses, prosthetic limbs and prosthetic joints, bones, and other implantable medical devices in musculoskeletal surgery. An increasingly important component in cutting-edge healthcare treatments is the ability to accurately capture patient anatomy in order to guide the manufacture of personalized prostheses. This article examines methods for capturing patient anatomy and discusses the degrees of personalization in medical manufacturing alongside a summary of current trends in scanning technology with a focus on identifying workflows for incorporating personalization into patient-specific products. Over the next decade, with increased harmonization of both personalization and automated prosthetic manufacturing will be the realization of improved patient compliance, satisfaction, and clinical outcomes.

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RESUMEN

Three-dimensional (3D) scanning technologies, such as medical imaging and surface scanning, have important applications for capturing patient anatomy to create personalised prosthetics. Digital approaches for capturing anatomical detail as opposed to traditional, invasive impression techniques significantly reduces turnaround times and lower production costs while still maintaining the high aesthetic quality of the end product. While previous case studies utilise expensive 3D scanning and modelling frameworks, their clinical translation is limited due to high equipment costs. In this study, we develop and validate a low-cost framework for clinical 3D scanning of the external ear using photogrammetry and a smartphone camera. We recruited five novice operators who watched an instructional video before scanning 20 healthy adult participant ears who did not have microtia. Our results show that the smartphone-based photogrammetry methodology produces 3D scans of the external ear that were accurate to (1.5 ± 0.4) mm and were (71 ± 14) % complete compared with those from a gold standard reference scanner, with no significant difference observed between operators. A moderate to strong interrater reliability was determined for all novice operators, suggesting that all novice operators were able to capture repeatable scans. The development of this smartphone photogrammetry approach has the potential to provide a non-invasive, inexpensive and accessible means to capture patient morphology for use in clinical assessment and personalised device manufacture, specifically for ear prostheses. We also demonstrate that inexperienced operators can rapidly learn and apply smartphone photogrammetry for accurate and reliable scans of the external ear with important applications for future clinical translation.

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