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Personalised three‐dimensional printed transparent kidney model for robot‐assisted partial nephrectomy in patients with complex renal tumours (R.E.N.A.L. nephrometry score ≥7): a prospective case‐matched study
Author(s) -
Kwon Kim Jung,
Ryu Hoyoung,
Kim Myong,
Kwon EunKyung,
Lee Hakmin,
Joon Park Sang,
Byun SeokSoo
Publication year - 2021
Publication title -
bju international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.773
H-Index - 148
eISSN - 1464-410X
pISSN - 1464-4096
DOI - 10.1111/bju.15275
Subject(s) - medicine , nephrectomy , surgery , kidney , 3d printed , logistic regression , urology , prospective cohort study , dissection (medical) , kidney cancer , cancer , biomedical engineering
Objectives To evaluate the effectiveness of a three‐dimensional (3D) printed transparent kidney model as a surgical navigator for robot‐assisted partial nephrectomy (RPN) in patients with complex renal tumours, defined by a R.E.N.A.L. (Radius, Exophytic/Endophytic, Nearness, Anterior/Posterior, Location) nephrometry score of ≥7. Patients and Methods A total of 80 patients who underwent RPN were included in the present prospective case‐matched study (case group [ n = 40, application of 3D‐printed transparent kidney model during RPN] vs matching group [ n = 40, routine protocol]). The RPNs were performed by a single experienced surgeon. The RPN procedure consisted of six steps: (i) preparation of the renal hilar vessel for clamping, (ii) tumour detection and dissection, (iii) robotic ultrasonography, (iv) tumour resection, (v) calyx repair and haemostasis, and (vi) renorrhaphy. The time for each step, console time, and warm ischaemia time were compared between the two groups as a surrogate marker for surgical effectiveness. Results Both groups were well‐balanced for all baseline characteristics. The use of the model reduced the console time by ~20% compared to the matched group (64.6 vs 78.5 min, P = 0.001). On multivariate logistic regression analysis, tumour radius ( P < 0.001) and application of the model ( P = 0.009) were identified as significant predictors of a console time of ≤70 min. Conclusion We established the usefulness of a personalised 3D‐printed transparent kidney model for more effective RPNs. Use of the 3D‐printed transparent kidney model reduced the operative time even for complex renal tumours and would be expected to broaden the indications for PN.