I worked on numerous patient cases for cranioplasty implants, and refined the digital workflow alongside colleague Andrew Grosvenor. This process was eventually taught at recurring workshops to support both seasoned surgeons and surgical residents, and significantly improve patient outcomes.
A cranioplasty procedure is required when a portion of the skull is lost due to trauma or cancer, leaving the brain unprotected. Patients often wear a helmet while waiting for reconstruction, but delays increase the risk of complications.
Traditionally, treatment required a separate surgery to take a physical impression of the defect from the exposed skull, which was then sent to a lab to fabricate a custom implant. Resulting in both healing time required for the patient, and fabrication time for the implant.
This process introduced significant risk - prolonged exposure, potential infection, anatomical changes during healing, and, in some cases, poorly fitting implants that required intraoperative adjustments or additional surgeries.
The digital workflow involved acquiring patient CT data, 3D modeling a custom implant, and 3D printing the implant in a material suitable for casting. This eliminated the need for a separate impression surgery and reduced risk while accelerating time to treatment.
These patient specific cranioplasty wax 3D prints were rapidly processed into surgical-ready implants by our team's in-house osseointegration technologists. This resulted in reducing the potential for anatomical changes that required on the fly adjustments in surgery.
I designed workshop content to introduce these digital workflows to both young and seasoned surgeons. These '3D Modeling for Medical Applications' courses were built on a simple idea: complex tools become powerful when they’re made accessible. I translated technical workflows into clear, usable steps.
Rather than prescribing rigid methods, I designed the training to encourage exploration and non-linear problem solving, eventually helping clinicians adapt the tools to their own research and patient work.
This approach lowered the barrier to adopting advanced modeling technologies for both residents and experienced surgeons. It also highlighted a broader gap: the need for earlier, more practical integration of digital tools in medical training.
Ultimately, the courses provided a bridge between emerging technology and everyday clinical practice, and helped create new relationships and learning opportunities for both local and international surgeons to expand their capabilities