How 3D surgical model printing can help improve insights from medical imaging data
As healthcare providers adopt 3D printing of surgical models, clinical team members can see value from different perspectives
Early studies demonstrate that 3D printing is well integrated in surgical practice and numerous early studies suggest advantages that include reduced surgical time, improved medical outcome and decreased radiation exposure.1
Clinical 3D printing of surgical models is an example of an innovation that has potential to enhance communication and collaboration for these teams. Much like the printed 3D models themselves, the benefits of this tool can be viewed from several different angles, depending on the person’s role in the care process:
Precise communication tool for the radiologist
A radiologist’s job is to produce and transmit information about a patient’s medical condition in a timely, accurate, usable way. Transitioning from text to 3D printed models has the potential to improve the precision and understanding of these communications.
Let’s use an example of a surgery to remove an aneurysm of the aorta in the abdomen. Within the last decade, surgeons have minimized risk with an approach that uses a stent delivered through the arteries of the leg. But this method requires a lot of detailed information about the vascular system, size and location of the aneurysm, which often generates a long, text-heavy radiologist report. Clinical 3D printing has the potential, for example, to enable surgeons to better understand the surgical site before starting the procedure, and in so doing, may decrease both operative time and complications.
Planning aid for the experienced surgeon
Surgeons who have conducted hundreds of surgeries on a specific organ or joint may not need a physical 3D printed model to visualize the body part itself. But even the most experienced surgeon may find an individual, true-to-life model of a complicated fracture, for example, to be helpful in planning an approach with precise measurements. And in another example, if a surgeon needs to repair a shattered femur, she may be able to picture the bone and injury well enough but may find a physical 3D printed model useful in preparing how to uniquely bend, position and affix a steel plate for each patient.
This aid in surgical planning may save surgeons time in the operating room. One study found that patient-specific 3D models may have helped reduce surgical time for a certain procedure by up to 45 minutes.2
Visualization aid for training and education purposes
Physicians can use 3D printed models to help explain procedures to people, including the patients themselves. It’s a tool that can help educate and explain the process in a more meaningful way than 2D images, 3D images on a screen, or generic models can offer.
With varying degrees of sub-specialization, surgeons may vary how often they provide a specific procedure. Especially when uncommon, it can take a long time for a physician to develop a high level of expertise with a procedure. 3D printed surgical models provide value so that surgeons can spend time outside the operating room planning in greater detail what they will do during the actual operation. And for those training residents in surgery, 3D printed surgical models can both optimize teaching and help standardize the assessment process.
Medicine is best practiced as a team sport, and technologies must support and augment these team efforts. As teams explore the potential of 3D printing of surgical models, we expect it will become another tool that draws new and helpful insights from data.
- Tack, et. al. 3D-printing techniques in a medical setting: a systematic literature review. BioMedical Engineering ONLine. 15, Article number 115 (2016) https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-016-0236-4
- L. Cherkasskiy, et.al. Patient-specific 3D models aid planning for triplane proximal femoral osteotomy in slipped capital femoral epiphysis Journal of Children’s Orthopaedics Vol. 11, No. 2 Published Online:6 Apr 2017 https://doi.org/10.1302/1863-2548-11-170277