Building a Hybrid Gross Anatomy Curriculum: Integration of Virtual & Cadaveric Models

Abstract

Cadaveric dissection is an important feature in a gross anatomy curriculum for medical practitioners. Currently, no other experience imparts a realistic, tactile understanding of tissues and organs necessary for actual surgical experience. Many students find cadaver dissection to be a beneficial experience. However, cadaveric dissection programs have three major drawbacks: (1) they require expensive logistical infrastructures to obtain, process, & utilize human gifts, (2) they provide limited exposure to the range of anatomical variation, and (3) they require students to study from textbook atlases as well as the physical dissection. This is a valuable experience, but can lead to confusion and loss of information when the cadaver does not match textbook anatomy or when structure is destroyed in the dissection process.To address these issues, many schools have looked at replacing physical cadavers with virtual models. Such “virtual cadavers” are relatively inexpensive and easier to work with. The best‐known example is the Visible Human Project[i], a publicly available dataset of a male and female cadaver in both annotated, Hi‐Res, cross‐sectional images & CT scans. Unfortunately, this is a limited dataset, which is not representative of the variation in population. Further, students lose the tactile experience of dissection, which is unique and has long‐lasting impacts throughout their medical education.To bridge this gap, the University at Buffalo (UB) is developing a hybrid gross anatomy program which integrates both formats. The program will leverage the Anatomical Gift program at UB, which provides 600–700 cadavers per year to schools across NY state, as well as state‐of‐the‐art imaging facilities at our Clinical and Translational Research Center, where cadavers are CT‐imaged at Hi‐Res. These scans are currently provided to students for dissection prep and review.To develop this program, several challenges must be addressed. Non‐contrast (NC) CT images must be processed to generate usable information for gross anatomy students. Registration must be performed to align samples for analysis (F1). Segmentation of structures to obtain virtual models is performed (F2). Finally, analytics must be performed to obtain anatomically relevant, quantitative information pertaining to structures such as probabilistic atlas creation (F3). These sample datasets will require novel automated deep learning methods to generate adequate models & analytics.In terms of education, the hybrid program must develop strategies to marry virtual models and dissection in a way that enhances learning without burdening students. Metrics must be implemented to define criteria for course improvement, success, & attrition. Students with special needs will need to be considered. The distribution format and access of the medical data will need to be assessed.The hybrid gross anatomy program will provide students with the benefits of dissection exposure, medical image utilization and a better understanding of human variation. The program offers exciting opportunities for technological and educational innovation.Support or Funding InformationIMSD R25 GM095459: Enabling Access to Cutting‐Edge Biomedical and Behavioral Science, Integration of Physical and Virtual Cadavers in a Hybrid Gross Anatomy Curriculum Center for Educational Innovation Grant.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.