Application of low-dose CT to the creation of 3D-printed kidney and perinephric tissue models for laparoscopic nephrectomy.

PURPOSE: The aim of this study was to explore the feasibility of 3D printing of kidney and perinephric fat based on low-dose CT technology. PATIENTS AND METHODS: A total of 184 patients with stage T1 complex renal tumors who underwent laparoscopic nephrectomy were prospectively enrolled and divided into three groups: group A (conventional dose kidney and perinephric fat 3D printing group, n = 62), group B (low-dose kidney and perinephric fat 3D printing, n = 64), and group C (conventional dose merely kidney 3D printing group, n = 58). The effective dose (ED), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were determined. The 3D printing quality was evaluated using a 4-point scale, and interobserver agreement was assessed using the intraclass correlation coefficient (ICC). RESULTS: The ED of group B was lower than that of group A, with a decrease of 55.1%. The subjective scores of 3D printing quality in all groups were 3 or 4 points. The interobserver agreement among the three observers in 3D printing quality was good (ICC = 0.84-0.92). The perioperative indexes showed that operation time (OT), warm ischemia time (WIT), estimated blood loss (EBL), and laparoscopic partial nephrectomy (LPN) conversion to laparoscopic radical nephrectomy (LRN) in groups A or B were significantly less than those in group C. LPN was more frequent in group A and group B than in group C (all p < 0.017). There were no significant differences in perioperative indexes between group A and group B (all p > 0.017). CONCLUSION: Low-dose CT technology can be effectively applied to 3D printing of kidney and perinephric fat and reduce the patient's radiation dose without compromising 3D printing quality. 3D printing of kidney and perinephric fat can significantly increase the success rate of LPN and decrease OT, WIT, and EBL.

The clinical application value of mixed-reality-assisted surgical navigation for laparoscopic nephrectomy.

PURPOSE: Laparoscopic nephrectomy (LN) has become the preferred method for renal cell carcinoma (RCC). Adequate preoperative assessment or intraoperative navigation is key to the successful implementation of LN. The aim of this study was to evaluate the clinical application value of mixed-reality-assisted surgical navigation (MRASN) in LN. PATIENTS AND METHODS: A total of 100 patients with stage T1N0M0 renal tumors who underwent laparoscopic partial nephrectomy (LPN) or laparoscopic radical nephrectomy (LRN) were prospectively enrolled and divided into a mixed-reality-assisted laparoscopic nephrectomy (MRALN) group (n = 50) and a non-mixed-reality-assisted laparoscopic nephrectomy (non-MRALN) group (n = 50). All patients underwent renal contrast-enhanced CT scans. The CT DICOM data of all patients in the MRALN group were imported into the mixed-reality (MR) postprocessing workstation and underwent holographic three-dimensional visualization (V3D) modeling and MR displayed, respectively. We adopted the Likert scale to evaluate the clinical application value of MRASN. The consistency of evaluators was assessed using the Cohen kappa coefficient (k). RESULTS: No significant differences in patient demographic indicators between the MRALN group and the non-MRALN group (P > .05). The subjective score of MRASN clinical application value in operative plan formulation, intraoperative navigation, remote consultation, teaching guidance, and doctor-patient communication were higher in the MRASN group than in the non-MRASN group (all P < .001). There were significantly more patients for whom LPN was successfully implemented in the MRALN group than in the non-MRALN group (82% vs 46%, P < .001). The MRALN group had a shorter operative time (OT) and warm ischemia time (WIT) and less estimated blood loss (EBL) than the non-MRALN group (all P < .001). CONCLUSION: MRASN is helpful for operative plan formulation, intraoperative navigation, remote consultation, teaching guidance, and doctor-patient communication. MRALN may effectively improve the successful implementation rate of LPN and reduce the OT, WIT, and EBL.