Three-dimensional visualization techniques improve surgical Decision Making of robotic-assisted partial nephrectomy
Yuchao Wang,
Qiliang Teng,
Zhihong Dai,
Chunyu Chen,
Liren Zhang,
Jiaxin Xie,
Hao Wang,
Zihan Xin,
Sishan Chen,
Yu Tai,
Liang Wang,
Bo Fan,
Zhiyu Liu
Affiliations
Yuchao Wang
Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China; Liaoning Provincial Key Laboratory of Urological Digital Precision Diagnosis and Treatment, Dalian, 116011, Liaoning Province, China; Liaoning Engineering Research Center of Integrated Precision Diagnosis and Treatment Technology for Urological Cancer, Dalian, 116011, Liaoning Province, China; Dalian Key Laboratory of Prostate Cancer Research, Dalian, 116011, Liaoning Province, China
Qiliang Teng
Department of Urology, Pelvic Floor Disorders Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518107, Guangdong Province, China
Zhihong Dai
Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China; Liaoning Provincial Key Laboratory of Urological Digital Precision Diagnosis and Treatment, Dalian, 116011, Liaoning Province, China; Liaoning Engineering Research Center of Integrated Precision Diagnosis and Treatment Technology for Urological Cancer, Dalian, 116011, Liaoning Province, China; Dalian Key Laboratory of Prostate Cancer Research, Dalian, 116011, Liaoning Province, China
Chunyu Chen
Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China; Liaoning Provincial Key Laboratory of Urological Digital Precision Diagnosis and Treatment, Dalian, 116011, Liaoning Province, China; Liaoning Engineering Research Center of Integrated Precision Diagnosis and Treatment Technology for Urological Cancer, Dalian, 116011, Liaoning Province, China; Dalian Key Laboratory of Prostate Cancer Research, Dalian, 116011, Liaoning Province, China
Liren Zhang
The Third People's Hospital of Dalian, Dalian, 116011, Liaoning Province, China
Jiaxin Xie
Institute of Urology, Peking University, Beijing, 100034, Beijing, China
Hao Wang
Department of Clinical Medicine, First Clinical School of Dalian Medical University, Dalian, 116044, Liaoning Province, China
Zihan Xin
Department of Clinical Medicine, First Clinical School of Dalian Medical University, Dalian, 116044, Liaoning Province, China
Sishan Chen
Department of Anesthesia, Dalian Medical University, Dalian, 116011, Liaoning Province, China
Yu Tai
Department of Anesthesia, Dalian Medical University, Dalian, 116011, Liaoning Province, China
Liang Wang
Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China; Liaoning Provincial Key Laboratory of Urological Digital Precision Diagnosis and Treatment, Dalian, 116011, Liaoning Province, China; Liaoning Engineering Research Center of Integrated Precision Diagnosis and Treatment Technology for Urological Cancer, Dalian, 116011, Liaoning Province, China; Dalian Key Laboratory of Prostate Cancer Research, Dalian, 116011, Liaoning Province, China; Corresponding author. Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Bo Fan
Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China; Liaoning Provincial Key Laboratory of Urological Digital Precision Diagnosis and Treatment, Dalian, 116011, Liaoning Province, China; Liaoning Engineering Research Center of Integrated Precision Diagnosis and Treatment Technology for Urological Cancer, Dalian, 116011, Liaoning Province, China; Dalian Key Laboratory of Prostate Cancer Research, Dalian, 116011, Liaoning Province, China; Corresponding author. Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Zhiyu Liu
Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China; Liaoning Provincial Key Laboratory of Urological Digital Precision Diagnosis and Treatment, Dalian, 116011, Liaoning Province, China; Liaoning Engineering Research Center of Integrated Precision Diagnosis and Treatment Technology for Urological Cancer, Dalian, 116011, Liaoning Province, China; Dalian Key Laboratory of Prostate Cancer Research, Dalian, 116011, Liaoning Province, China; Corresponding author. Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, 116011, Liaoning Province, China.
Background: Complete preoperative comprehension of the adjacent structures of the kidney and location of renal vessels is essential for robot-assisted partial nephrectomy (RAPN). The effectiveness of three-dimensional (3D) visualization techniques in improving perioperative outcomes of RAPN has been inconsistent and has not been reported in Northeastern China. Methods: In this cohort study, we reviewed patients with renal tumours who underwent RAPN between April 2019 and April 2024. Three-dimensional visualization models were reconstructed to evaluate resectability parameters, including vascular variations, collection system infiltration, and lymphatic involvement. Subsequently, a meta-analysis combining previous studies utilising 3D visualization techniques for partial nephrectomy was conducted. Results: Of the 324 patients in the cohort, 147 were preoperatively evaluated using the 3D technology. Group 3D had significantly less estimated blood loss (P < 0.001) and a shorter operative time (P = 0.016) than in group No 3D. We also found that the rates of intraoperative ultrasound use (P = 0.015), intraoperative complications (P = 0.007), intraoperative transfusions (P = 0.007), and postoperative Clavien complications (P < 0.001) in group 3D were significantly lower than in group No 3D. The above findings were consistent in the subgroup with R.E.N.A.L. ≥ 8 points partly. Furthermore, a meta-analysis identified 11 studies that included 1522 patients who underwent RAPN. Use of 3D visualization technology resulted in decreased 55 % risk of opening the collecting system (Risk Ratio [RR] = 0.45[0.22–0.92], P = 0.030) and 79 % incidence of conversion to radical nephrectomy (RR = 0.21[0.08–0.57], P = 0.002). The RAPN group assisted by 3D visualization techniques showed an 81 % reduction in the risk of blood transfusion than in the control group (RR = 0.19[0.08–0.44], P < 0.001). Conclusions: The application of 3D technology in RAPN appears to be superior for improving precise tumour removal and reducing adverse perioperative outcomes and should be considered for wide use in clinical practice.
