3D printed renal cancer models derived from MRI data: application in pre-surgical planning

Abstract

Objective: To determine whether patient-specific 3D printed renal tumor models change pre-operative planning decisions made by urological surgeons in preparation for complex renal mass surgical procedures.

Materials and methods: From our ongoing IRB approved study on renal neoplasms, ten renal mass cases were retrospectively selected based on Nephrometry Score greater than 5 (range 6-10). A 3D post-contrast fat-suppressed gradient-echo T1-weighted sequence was used to generate 3D printed models. The cases were evaluated by three experienced urologic oncology surgeons in a randomized fashion using (1) imaging data on PACS alone and (2) 3D printed model in addition to the imaging data. A questionnaire regarding surgical approach and planning was administered. The presumed pre-operative approaches with and without the model were compared. Any change between the presumed approaches and the actual surgical intervention was recorded.

Results: There was a change in planned approach with the 3D printed model for all ten cases with the largest impact seen regarding decisions on transperitoneal or retroperitoneal approach and clamping, with changes seen in 30%-50% of cases. Mean parenchymal volume loss for the operated kidney was 21.4%. Volume losses >20% were associated with increased ischemia times and surgeons tended to report a different approach with the use of the 3D model compared to that with imaging alone in these cases. The 3D printed models helped increase confidence regarding the chosen operative procedure in all cases.

Conclusions: Pre-operative physical 3D models created from MRI data may influence surgical planning for complex kidney cancer.

Keywords: 3D printing; Magnetic resonance imaging; Partial nephrectomy; Surgical planning; Urological oncology.

Conflict of interest statement

Conflict of Interest: All authors of this manuscript disclose no conflict of interest.

Figures

Fig. 1

(a) Axial, coronal, and sagittal views with segmentation masks for one representative case. Kidney = teal, tumor = pink, artery = red, vein = blue, collecting system = green (b) Anterior and Posterior 3D projections. Kidney = gray, tumor = pink, artery = red, vein = blue, ureter = green. (c) Photographs of 3D printed model. Kidney = transparent, tumor = purple, artery = pink, vein = light blue, ureter = dark blue.

Fig. 2

(a) CAD file of measurement phantom showing desired measurements in mm. Light blue = Heart print flex material, Dark blue = Vero Cyan material, Pink = Vero Magenta material, White = No material and (b) 3D printed phantom shown overlaid on graph paper in order to demonstrate accuracy of 3D printing. Each dark line on the graph paper represents 1cm and each light line represents 1mm. (c) Correlation plot showing agreement between CAD model measurements and caliper measurements made of 3D printed phantom model.

Fig. 3

3D models accurately depict tumor size. (a) Bland-Altman plot of diameter measurements made on 2D images versus 3D models. The fact that the points lie around the mean demonstrates that there is no inherent bias between the two methods. (b) Coronal MRI showing two diameter measurements (D1 = 39.1mm and D2 =37.5mm). (c) Diameter measurement D1 of 3D printed model by calipers. (d) Diameter measurement D2 measured on the same 3D printed model.

Fig. 4

Box plots demonstrating that operated kidney volume loss (a) correlates with ischemia time (b) correlates with changes in decision making regarding surgical approach with and without 3D model. *Whiskers extend to maximum and minimum values.