A newly developed 3D printing technique allows CT and MRI scans to be accurately represented in “exquisitely detailed” medical models, providing researchers and doctors with patient-specific reproductions for diagnosis.
Steven Keating, a graduate student in the MIT Media Lab’s Mediated Matter group, pioneered the research off the back of his own personal experience with a brain tumour.
After having a baseball-sized growth removed, he 3D printed his MRI and CT scans in an attempt to better understand his diagnosis and treatment options. He found existing methods time-consuming and clumsy, and they ultimately failed to reproduce details vital to diagnostic medicine.
The Wss Institute reports that he reached out to others in the Mediated Matter group to explore how 3D printing could be better applied to medical imagery. Wyss Institute researcher Ahmed Hosny, was instantly won over by the idea:
It never occurred to us to use this approach for human anatomy until Steve came to us and said, ‘Guys, here’s my data, what can we do?’
The resulting research paper, published by 3D Printing and Additive Manufacturing, reveals how the advances were made.
A slice above
Tomographical images produced by MRI and CT scans are generated as a series of slices. These cross-sections reveal the detailed internals of the human body, allowing medical professionals to identify any abnormalities or concerns and determine suitable treatment.
Yet these either have to be manually traced for objects of interest by a radiologist, or undergo an automatic thresholding process that converts grey pixels to either black or white based on the set threshold.
Even so, the resultant images aren’t optimised for 3D printing, meaning that much of the detail is lost in the process.
By printing with dithered bitmaps, which allocate black dots of varying sizes to convey gradients, the researchers were able to overcome these issues, going beyond the traditional image thresholding techniques used in medical imaging. By bypassing thresholding, the model-creation process is both faster and more accurate.
Furthermore, by feeding pre-processed binary bitmap slices into multi-material 3D printers, physical attributes, such as stiffness and opacity, can be represented in the final model.
A future for medical 3D printing?
The research paper does identify some limitations of the technique, caused by the resolution limitations of current imaging technology and the fact that image reconstruction methods are optimised for human image viewing, rather than 3D printing.
Nevertheless, these hurdles will be overcome as 3D printing advances and becomes more mainstream. Custom resin formulations may even eventually allow the mimicking of the elasticity of muscles and tendons and other biological properties such as density, conductivity, permeability, and biodegradability.
Internet of Business says
While this is far from the first instance of 3D printing being used to reproduce CT and MRI scans (one previous example includes tumour models to investigate how cancer cells spread), it is perhaps the most significant.
The research opens the door to bio-mechanically accurate models. The ability to quickly and accurately produce such models has huge implications in diagnostics, research, and teaching.
The idiosyncrasies of individual anatomy, and the minute effects and scarring caused by disease or trauma, can now be physically represented through 3D printing.
This includes the scar tissue in a damaged heart, which can cause fatal cardiac issues, potentially helping surgeons to prepare for surgery, or rehearse complex operations.
It’s also important to highlight that the bitmap files used for 3D printing were created using open-source software and existing image-processing algorithms, enabling easy, widespread adoption.
Since x-ray imagery was first used over a century ago, and modern high-resolution CT and MRI scanning was introduced, medical imaging has been propelled by the need for detailed, highly-accurate anatomical reproductions. This latest breakthrough is a significant milestone on that journey.
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