Abstract

PURPOSEMicrosoft HoloLens (HL) mixed reality technology offers students a novel modality to visualize clinically important anatomical structures, such as the breast, which are uniquely challenging to discern with the naked eye in traditional cadaveric dissection. In this study, we developed a 3‐D anatomical model of the breast and integrated it into a dynamic, educational module on the HoloLens. Here, we report the educational outcomes and overall impressions of medical students learning breast anatomy through our module, as compared with traditional dissections.METHODSA mixed reality breast anatomy module was created using AutoDesk 3DSMax and integrated into the HoloLens device. 38 first‐year medical students were then recruited and divided into two groups: one participated in the HL module prior to dissecting the cadaveric breast, and the second dissected the cadaveric breast prior to the HL module. Before and after each teaching modality, participants answered seven comprehension‐based breast anatomy questions and a survey about their experience.RESULTSOur results show that scores on the comprehension‐based questions significantly improved more after the HL module than after the dissection (p=0.0209). Additionally, students appear to react more positively to the HL module than the dissection, regardless of which they were presented with first (p = 0.0008).CONCLUSIONSThe present study demonstrates that students show better comprehension outcomes of breast structures using the HL. This is likely due to the ability to visualize structures that cannot be seen in the cadaver. Additionally, students appear to react more positively about learning breast anatomy through the HL module than through cadaveric dissection. Our results will be important in informing a future technology‐driven medical education, especially in using mixed reality to supplement what a traditional cadaveric dissection may lack.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.