TY - JOUR
T1 - Case-based radiological anatomy instruction using cadaveric MRI imaging and delivered with extended reality web technology
AU - Nakamatsu, Nicole A.
AU - Aytaç, Güneş
AU - Mikami, Brandi
AU - Thompson, Jesse D.
AU - Davis, McKay
AU - Rettenmeier, Christoph
AU - Maziero, Danilo
AU - Andrew Stenger, V.
AU - Labrash, Steven
AU - Lenze, Stacy
AU - Torigoe, Trevor
AU - Lozanoff, Beth K.
AU - Kaya, Brock
AU - Smith, Alice
AU - Douglas Miles, J.
AU - Lee, U. Young
AU - Lozanoff, Scott
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/1
Y1 - 2022/1
N2 - Purpose: Extended reality (XR) technology enhances learning in medical education. The purpose of this study was to develop and apply a case-based approach for teaching radiological anatomy utilizing XR technology for improved student exploration and engagement. Methods: The workflow consisted of MRI scanning cadavers followed by radiological, pathological, and anatomical assessment, and finally case presentation based on XR visualizations and student interaction. Case information (Subject, History, and Physical Exam) was presented to student groups who generated and recorded hypotheses using Google Forms. Results: Use of all components of the system was voluntary and a total of 74 students responded to the survey request (response rate = 95%). Assessment of the experience was conducted through a qualitative survey comprising four Likert scale questions (1–5, 1 lowest), three binary questions, and open-ended comments. Mean, standard deviation, and overall agreement (mean ± SD, OA) showed that students found MRI scans of cadavers to be helpful for dissections (4.14 ± 1.1, 74.3%) and provided an understanding of relevant anatomy (4.32 ± 0.9, 79.7%), while 78.4% of students used the DICOM viewer to visualize scans of cadavers. The difficulty of use was found to be average (2.90 ± 1.0, 23%). zSpace visualizations were used by 40.5% of students, generally agreeing that an understanding of spatial relationships improved as a result (3.60 ± 1.0, 43.2%). More case-based sessions were favored by 97.3% of students. Conclusions: Results suggest that cadaveric MRI radiological visualization and XR technology enhance understanding of case-based anatomical dissections and encourage student exploration and engagement.
AB - Purpose: Extended reality (XR) technology enhances learning in medical education. The purpose of this study was to develop and apply a case-based approach for teaching radiological anatomy utilizing XR technology for improved student exploration and engagement. Methods: The workflow consisted of MRI scanning cadavers followed by radiological, pathological, and anatomical assessment, and finally case presentation based on XR visualizations and student interaction. Case information (Subject, History, and Physical Exam) was presented to student groups who generated and recorded hypotheses using Google Forms. Results: Use of all components of the system was voluntary and a total of 74 students responded to the survey request (response rate = 95%). Assessment of the experience was conducted through a qualitative survey comprising four Likert scale questions (1–5, 1 lowest), three binary questions, and open-ended comments. Mean, standard deviation, and overall agreement (mean ± SD, OA) showed that students found MRI scans of cadavers to be helpful for dissections (4.14 ± 1.1, 74.3%) and provided an understanding of relevant anatomy (4.32 ± 0.9, 79.7%), while 78.4% of students used the DICOM viewer to visualize scans of cadavers. The difficulty of use was found to be average (2.90 ± 1.0, 23%). zSpace visualizations were used by 40.5% of students, generally agreeing that an understanding of spatial relationships improved as a result (3.60 ± 1.0, 43.2%). More case-based sessions were favored by 97.3% of students. Conclusions: Results suggest that cadaveric MRI radiological visualization and XR technology enhance understanding of case-based anatomical dissections and encourage student exploration and engagement.
KW - Case-Based Anatomy
KW - Radiological Anatomy Education
KW - XR Technology
UR - http://www.scopus.com/inward/record.url?scp=85119917646&partnerID=8YFLogxK
U2 - 10.1016/j.ejrad.2021.110043
DO - 10.1016/j.ejrad.2021.110043
M3 - Article
C2 - 34844172
AN - SCOPUS:85119917646
SN - 0720-048X
VL - 146
JO - European Journal of Radiology
JF - European Journal of Radiology
M1 - 110043
ER -