Objective
To describe novel 3-dimensional (3D) printing and augmented reality (AR) methods of
image data visualization to facilitate anatomic understanding and to assist with surgical
planning and decision-making during robotic partial nephrectomy.
Materials and Methods
We created a video of the workflow for creating 3D printed and AR kidney models along
with their application to robotic partial nephrectomy. Key steps in their development
are (1) radiology examination (magnetic resonance imaging and computed tomography),
(2) image segmentation, (3) preparing for 3D printing or AR, and (4) printing the
model or deploying the model to the AR device.
Results
We demonstrate the workflow and utility of 3D printing and AR kidney models applied
to a case of a 70-year-old woman with a 3.4 cm renal mass on her left pelvic kidney.
A 3D printed kidney model was created using multicolor PolyJet technology (Stratasys
J750), allowing a transparent kidney with coloring of the renal tumor, artery, vein,
and ureter. An AR kidney model was created using Unity 3D software and deployed to
a Microsoft HoloLens. The 3D printed and AR models were used preoperatively and intraoperatively
to assist in robotic partial nephrectomy. To date, we have created 15 3D printed and
AR kidney models to use for robotic partial nephrectomy planning and intraoperative
guidance. The application of 3D printed and AR models is safe and feasible and can
influence surgical decisions.
Conclusion
Our video highlights the workflow and novel application of 3D printed and AR kidney
models to provide preoperative guidance for robotic partial nephrectomy. The insights
gained from advanced visualization can influence surgical planning decisions.
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Article info
Publication history
Published online: May 22, 2018
Accepted:
December 15,
2017
Received:
September 15,
2017
Footnotes
Financial Disclosure: The authors declare that they have no relevant financial interests.
Funding Support: This work was funded by the NIH P41 EB017183 Industry Support: Stratasys Ltd.
Identification
Copyright
© 2018 Elsevier Inc. All rights reserved.
