Synopsys Cloud
Cloud native EDA tools & pre-optimized hardware platforms
Request a Free Trial →
What is Point-of-Care Anatomical 3D Printing?
Three-dimensional (3D) printing technologies have been in existence for roughly four decades, and from the beginning, clinicians and researchers have been working to bring technology into the hospital to improve patient care. 3D printing technology is currently impacting medical practice in almost every way imaginable, from high-profile cases like the separation of conjoined twins, to more day-to-day applications like surgical planning, patient counselling, and student education. One of the most common hospital applications is the creation of patient-specific 3D printed models of human anatomy, commonly referred to as point-of-care (POC) anatomical 3D printing.
Anatomical 3D printing involves converting magnetic resonance imaging (MRI) or computed tomography (CT) scans of patients into 3D surface reconstructions (typically STL or 3MF) that are sent to a 3D printer to be printed by hospitals on-site, by third-parties, or embedded managed services companies at healthcare institutions. Read more about how point-of-care 3D printing works here. The main drivers expanding the use of POC anatomical 3D printing within hospitals are varied and complex, but essentially relate to improved medical outcomes and long-term time and money savings for the hospital. Other related drivers include increased anatomical comprehension, surgeon confidence, positive public relations, and improved procedural accuracy.
Surgeons can hold an accurate replica of a patient’s anatomy in their hands and use it for pre-surgical planning, communication, and training, reducing the need for expensive use of cadavers. 3D printed models have also been shown to reduce operating time by shortening procedures, which saves money for hospitals. When combined with increasing demands from patients and more adoption by doctors as they come to trust models, it is likely that POC 3D prints will be established enough to receive a Category 1 CPT code within the next few years for full reimbursement by insurers.
Synopsys and POC 3D Printing Software
Since the genesis of Synopsys Simpleware™ software over 20 years ago, there has always been a focus on making the process of converting DICOM image data into 3D print-ready models as easy and straightforward as possible. In recent years, aided by the acquisition of Simpleware by Synopsys, and clinician-based user groups and customer feedback, there has been even more focus and resources dedicated to improving the user interface/experience for manual workflows.
The industry-leading computational resources of Synopsys have been leveraged in AI-enabled technology for automation and scaling-up workflows, as well as for U.S. FDA 510(k) clearance and European CE-marking technology for Simpleware ScanIP Medical and a 3D printing toolkit feature. Simpleware software eliminates the need to jump between different software programs when preparing DICOM data for 3D printing, allowing users to:
- Work within the FDA-cleared and CE-marked software environment of Simpleware ScanIP Medical
- Cleared for 3D printing with Stratasys, Formlabs, HP, and Rize 3D printers
- Cleared for 3D printing with Stratasys, Formlabs, HP, and Rize 3D printers
- Segment anatomical scans into regions of interest, such as bone, muscle, and other tissues
- Use a range of tools to cut, hollow, emboss text, create connectors, build model platforms, and make pins and connectors
- Apply color maps to 3D models representing bone density using the greyscale values from CT image data or wall thickness
- Apply color proofing and check printability to help get the model right the first time
- Export all of the standard 3D printing formats such as STL, 3MF, OBJ, etc.
Example 3D models generated in Simpleware (left) and their equivalent 3D printed models used at the point-of-care (right). (Top) half of a pelvis automatically segmented with Simpleware AS Ortho and the bone mineral density mapped to the surface. (Middle) A lower skull and mandible with support structures used to hold the model together. (Bottom) A heart with all of the major chambers and blood vessels automatically segmented using Simpleware AS Cardio.
POC anatomical 3D printing has grown from being very rare, targeted at difficult clinical conditions and dependent on manual approaches, to a widely recognized technology requiring scaled-up workflows. However, manual and slow image segmentation remains the main bottleneck for growth, opening a space to apply the Simpleware group’s excellence in automation for 3D printing at different levels:
- Scripting at the software interface in Python and C#, where users can easily create scripts and customized tool sets and workflows for repeated tasks via API, macros, and log conversion
- Use of Simpleware AS Ortho and Simpleware AS Cardio add-on modules, which are off-the-shelf AI-enabled automatic segmentation and landmarking tools for the heart, shoulder, hip, knee, and ankle, with more to come
- Adoption of the Simpleware Custom Modeler add-on, a fully customized, AI-enabled auto segmentation solution that is developed hand-in-hand with the customer to provide an optimized solution for their needs
Watch the videos below to learn more about Simpleware software for 3D printing.
Case Study: 3D Printing with Nicklaus Children’s Hospital
Lateral View (A1) and Transverse View (B1) of the 3D print-ready model in Simpleware software, and resulting 3D printed anatomical model from Stratasys J750 Digital Anatomy printer (A2, B2) with the pathology encircled in orange.
One excellent example of POC 3D printing being applied clinically involves Simpleware users at Nicklaus Children’s Hospital in Miami, Florida. The Cardiovascular Surgery Advanced Projects Laboratory (APL) uses 3D anatomical models to help plan operations, teach colleagues, and counsel patients. APL has created more than 500 models of hearts, brains, spines, extremities, and other organs. In addition, the hospital has benefited from Simpleware AI-enabled tools to automate routine parts of their workflows.
In a recent case, the group created a model for a 16-year-old patient with an anomalous origin of the left coronary artery. The patient’s heart CT data was loaded into Simpleware ScanIP Medical, and the automated segmentation module, Simpleware AS Cardio, was used to segment and landmark the data in a click of a button, with additional 3D print prep carried out in the Simpleware 3D printing toolkit. With this method, the time-consuming work of processing the data was significantly reduced, going from approximately two hours biomedical engineering time to just 15 minutes.
The final model was 3D printed using a Stratasys J750 Digital Anatomy 3D printer, with different colors used to visualize individual regions of the heart and aid in the surgery. The work being carried out by the team at Nicklaus Children’s demonstrates the value of advanced POC solutions within the Simpleware platform, whereby scale models of patient hearts help plan surgeries and educate patients. Thomas Haglund, Biomedical Engineering at the Cardiovascular Surgery APL, had this to say about the heart project:
“Our new engineer segmented it. He hit the ‘go’ button on Simpleware AS Cardio and then added the base and supports. It is very quick.”
Future Growth of Medical 3D Printing
In medical 3D printing, anatomical models are becoming the norm rather than the exception, and continued growth is expected as more healthcare institutions adopt 3D printing. This shift will likely be driven by several factors, including recognition of the net positive effect of 3D printing on the hospital bottom line, despite upfront costs; hospitals using 3D printing as a means of differentiation for patients; increases in acceptance and adoption of anatomical 3D printing amongst clinical professionals; and reimbursement pathways for these models becoming increasingly established and deployed.
While it remains to be seen whether in-house, third-party, or managed services become the dominant business model for POC 3D printing, Synopsys Simpleware AI tools offer a flexible solution to the main bottleneck of manual segmentation and landmarking, helping propel 3D printing into more hospitals and to improve patient outcomes.