“Can you make my model clinically accurate?” It’s the one question that we hear more than any other. As simple as the question seems, the answer is the same annoying answer as many others you find in science and medicine: it depends.
Getting the story straight
The reason the answer is not as straightforward as one may assume is that, although the intent of the customer asking the question is never to be ambiguous, the question itself is indeed ambiguous.
“Clinically accurate” refers to the degree of precision of the model. A clinically accurate model would be created to look, feel, and act as close to real human tissue as possible, down to the cellular level.
Depending on what you’re using as your sample, clinical accuracy can be achieved with a high degree of time and resources, but even with these variables in place, it is still nearly impossible to define in the context of anatomy. As you all know, there are infinite variations in human anatomy, and within any anatomical structure, there are numerous layers of tissue, all with their own individual composition.
What is a clinically accurate depiction of one person may be largely inaccurate for another. There is beauty in the endless uniqueness of our species, but it solidifies the fact that there truly can’t be a decidedly clinically accurate model that encompasses humans as a whole.
Rephrasing the question
In almost all instances, the intent of the question is actually, “Can you make my model clinically relevant?” The answer to that is a resounding yes!
Clinically relevant refers to the degree of usefulness of the model. And the degree of that relevance can be as intricate as necessary for the model to tell the story that the customer needs it to tell.
As was discussed in our March issue, our models are made to tell a story. The story they tell comes down to what message needs to be conveyed by the customer. Will their model be used for patient demonstration of anatomy or a physiologic process? Will it be used to train surgeons on a new procedure? Will it be used for testing surgical equipment or technology? The answer to these questions will lead us to the answer of what “clinically relevant” means on a case-by-case basis.
To give a more specific example: if a customer needs a model for skin tissue, we will work with them to specify what the model needs to do and what it does not need to do. If all the customer needs is a model that provides a visual representation of the different layers and colors of skin tissue without the feel or function of the skin, relevance will be achieved in a much different way than for a customer who needs the tissue to accept an adhesive bandage, surgical staples and includes simulated blood flow.
Additionally, we wouldn’t want to create the same models for these two hypothetical customers because the cost of the first model will be significantly lower than that of the second model. We maximize the model for the function it needs to serve without adding unnecessary costly features that won’t be part of the story the customer wishes to portray with their model.
To bring this discussion all together, the way a model is created is totally dependent on the goal of the customer. The point of what we do is to allow the customer to convey what they need to convey as clearly as possible, not to make a model accurate down to a microscopic level.
We can make a model as “accurate” as necessary for the specific purpose for which it will be used. But through this process, what we’re truly doing is making the model relevant. But isn’t that what you really wanted to know all along?