Cadavers have been a "cornerstone" of medical education for centuries, but cost concerns and clinical limitations are leading some medical schools to stop using cadavers and instead uses virtual reality (VR), Bahar Gholipour reports for Scientific American.

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Training with cadavers has been regarded as essential to western medical education for nearly a millennium, Gholipour reports. Frederick II, the Holy Roman Emperor who ruled over much of Europe, in the 13th century issued a decree that schools that trained doctors must hold a dissection with a cadaver every five years.

But while the practice has endured for centuries, it's not without its limitations, one of which is the cost. Cadavers can be expensive to keep at a medical school, Gholipour reports. They require a cadaver laboratory, which can cost millions of dollars.

And while cadavers are donated, medical schools bear the cost of preparing the bodies and maintaining them and later burying them, Gholipour reports.

The cadavers can also be difficult to obtain, according to a 2018 study, as many countries face a shortage of cadaver donations and often must rely on unclaimed bodies for dissection, Gholipour reports.

Along with potentially prohibitive costs, cadavers come with clinical limitations, Gholipour writes. For instance, a dissection is time consuming, and in some instances, body parts can be so hard to reach that they're destroyed during dissection.

The insides of cadavers also don't look exactly like the insides of live human beings, Gholipour reports.

James Young, chief academic officer of the Cleveland Clinic Lerner College of Medicine noted that he experienced a "massive disconnect" between his anatomy education in the 1970s and what he saw during his clinical training in cardiology. "They're totally different," Young said. "The embalmed cadaver has a very flat, compressed organ presentation. The colors are not the vibrant colors of a living human." That difference can distract from learning, Young said.

That's why some schools, like Young's Lerner College, are going "cadaverless," and instead, are relying on virtual anatomy tools, Gholipour reports.

These tools, like VR headsets or augmented-reality goggles, provide students with a more realistic view of living organs, and students are able to examine the organs from every angle, Gholipour reports. They can even select views that add different organs to the circulatory and nervous systems to see how structures are related.

Mark Schuster, dean of Kaiser Permanente School of Medicine, said he "was amazed" by the tools. "I wished I had that when I'd been learning anatomy," he said. "It really helped make it all come together." Kaiser, which will host its first class in 2020, will have a cadaverless curriculum for its first-year students.

However, virtual anatomy tools are not without their drawbacks, Gholipour reports. For example, it can be difficult to develop a depth perception of a virtual body, and students won't be able to see the natural anatomical variations that occur in bodies, according to Darren Hoffman, an assistant professor of anatomy and cell biology at the University of Iowa Carver College of Medicine.

Students also won't have the emotional and potentially philosophical impact of working with an actual body, Gholipour reports. "There's a sort of awe and respect that comes from that," Hoffman said. "You recognize how amazingly cool and intricate the human body is, and you start to realize that everybody on the planet is this amazingand so am I."

There's also the question of how well students learn with digital tools, Gholipour reports. Educators are currently studying whether replacing older techniques with new technology actually improves education rather than harms it.

Still, educators like Young see a significant shift happening. "We're at the beginning of a paradigm shift, no question about that," Young said. "That shift is going to take several years. But if you asked me how is anatomy education going to be done in a decade? It's not going to be done with cadavers. That's my prediction" (Gholipour, Scientific American, October 2019).

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