Presentation Authors: Clement Michiels*, Eva Jambon, Joffrey Sarrazin, Chrystelle Latxague, Astrid Boulenger de Hauteclocque, Gregoire Capon, Henri Bensadoun, Gregoire Robert, Jean-Marie Ferriere, Frederic Bos, Nicolas Grenier, Jean-Christophe Bernhard, Bordeaux, France
Introduction: 3D printing is being used for surgical assistance during Robot-assisted Partial Nephrectomy (RAPN). We have also been using patient-specific 3D printed kidney models for patient education as well as a radiology education tool for medical students. The objective of this study was to assess objectively the anatomical accuracy of our 3D printed models used for RAPN and assess the quality of our workflow protocol behind the making of a 3D printed kidney model, from segmentation to postprocessing of the fabricated model.
Methods: We prospectively included patients who underwent 3D printing-assisted RAPN and anonymized computed tomography (CT). Patient consent for prospective collection of clinical data including imaging data inside UroCCR database was obtained (NCT03293563â€“CNIL DR 2013-206). The preoperative CT was segmented with Synapse 3DÂ® (FujifilmÂ®). 3D files were processed before printing on the StratasysÂ®-J750 3D printer, with vascular, urinary, parenchymal and tumor elements. The 3D printed model was then scanned. Six quantitative judgement criteria (major axis of the kidney and tumor, volume of the tumor, 3 measurements between arterial branches were used to blindly compare the initial patient CT and the 3D printed model CT (fig.1). The correlation of the arterial distribution between the scanner and the 3D model was also evaluated on a Likert scale.
Results: The first 16 patients of our 3D printing RAPN series were included between December 2017 and March 2018. The median tumor size was 5.1 cm. Between the initial CT scan and the 3D kidney, the major renal axis varied on average by 2.3% (Â±1.8), the major tumor axis varied by 4.1%(Â±4.2), mean tumor volume variation was 17.9% (Â±10.4). Arterial inter-branch measurements, with 3 measurements performed on each kidney, ranged from 2.2%(Â±1.5). The Likert scale evaluation of the correlation of the vasculature resulted in a median of 5[4;5]/5.
Conclusions: Our 3D-models are accurate to the anatomical reality. We need quality assurance protocols like this, with radiologists, to enable appropriate medical practice regarding 3D printing. Evaluation of security of surgical assistance with 3D printed models comes next.