V9-02: Patient-specific cast renal models for preoperative simulation of tumor resection during robotic partial nephrectomy

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INTRODUCTION

Pre-surgical models have been utilized to teach the general steps of various urological surgeries. These models are limited by their inability to capture the great variability in tumor morphology that exists between various patients. Our aim was to develop a reproducible patient specific pre-surgical model for robotic partial nephrectomy that allows preoperative rehearsal using a novel three dimensional (3d) printing and silicone casting technology._x000D_

METHODS

Using standard preoperative imaging, 3d reconstruction of renal parenchyma and tumor was performed to generate solid models suitable for rapid fabrication. Leveraging a novel prototyping process that utilizes 3d extrusion printing and subsequent polymer casting we generated pre-surgical models out of a silicone-based material. To determine how well these patient-specific models simulated actual operative experience, we compared enucleation times between model and actual tumor using the same robotic platform. For the final model, we performed 3d laser scans of both the enucleated model and tumor comparing their spatial characteristics. All surgical rehearsals were performed prior to the actual procedure.

RESULTS

We generated patient-specific pre-surgical models for 3 patients. R.E.N.A.L. nephrometry scoring for the pre-surgical models was 7a, 8p, 8a and tumor sizes were 3.5x3.4x3.5 cm, 4.1x3.8x3.5 cm, and 1.5x1.4x1.4 cm. Time of enucleation was similar between the patient-specific pre-surgical models and the actual surgery (6:24 vs. 5:58, 3:11 vs. 3:43, 4:55 vs. 6:09 mins). For case #3, the surgical model enucleation volume measured 6.4 mm3 and the actual excised specimen 12.8 mm3. A 3d-reconstructed visual overlay demonstrated a high level of coherence in the shape of the excised tumor and allowed measurement of the difference in the volume of excised normal renal parenchyma between the model and the actual patient specimen.

CONCLUSION

We have developed a patient-specific pre-surgical simulation for robotic partial nephrectomy. Our model provides accurate representation of enucleation time and volume of resected tissue. This highly reproducible simulation platform has the potential to alter surgical decision-making and allow for preoperative rehearsal in complex cases. Furthermore it may become a valuable tool for resident training.

Funding: none