Fully Automated Versions of Clinically Validated Nephrometry Scores Demonstrate Superior Predictive Utility versus Human Scores.

OBJECTIVE: To automate the generation of three validated nephrometry scoring systems on preoperative computerised tomography (CT) scans by developing artificial intelligence (AI)-based image processing methods. Subsequently, we aimed to evaluate the ability of these scores to predict meaningful pathological and perioperative outcomes. PATIENTS AND METHODS: A total of 300 patients with preoperative CT with early arterial contrast phase were identified from a cohort of 544 consecutive patients undergoing surgical extirpation for suspected renal cancer. A deep neural network approach was used to automatically segment kidneys and tumours, and then geometric algorithms were used to measure the components of the concordance index (C-Index), Preoperative Aspects and Dimensions Used for an Anatomical classification of renal tumours (PADUA), and tumour contact surface area (CSA) nephrometry scores. Human scores were independently calculated by medical personnel blinded to the AI scores. AI and human score agreement was assessed using linear regression and predictive abilities for meaningful outcomes were assessed using logistic regression and receiver operating characteristic curve analyses. RESULTS: The median (interquartile range) age was 60 (51-68) years, and 40% were female. The median tumour size was 4.2 cm and 91.3% had malignant tumours. In all, 27% of the tumours were high stage, 37% high grade, and 63% of the patients underwent partial nephrectomy. There was significant agreement between human and AI scores on linear regression analyses (R ranged from 0.574 to 0.828, all P < 0.001). The AI-generated scores were equivalent or superior to human-generated scores for all examined outcomes including high-grade histology, high-stage tumour, indolent tumour, pathological tumour necrosis, and radical nephrectomy (vs partial nephrectomy) surgical approach. CONCLUSIONS: Fully automated AI-generated C-Index, PADUA, and tumour CSA nephrometry scores are similar to human-generated scores and predict a wide variety of meaningful outcomes. Once validated, our results suggest that AI-generated nephrometry scores could be delivered automatically from a preoperative CT scan to a clinician and patient at the point of care to aid in decision making.

Associations between R.E.N.A.L. nephrometry score and survival outcomes in renal tumours.

OBJECTIVE: The radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry score could be used to predict surgical outcomes and renal tumour aggressiveness. We aimed to analyse its associations with survival outcomes. METHODS: We included 1368 patients with sporadic, unilateral and non-metastatic renal tumours who received curative nephrectomy in Zhongshan Hospital from January 2009 to September 2019. Radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry scores were assigned by three urologists based on preoperative CT/MRI scans. Correlations between parameters or sum of radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry scores, overall survival and recurrence-free survival were analysed by Kaplan-Meier analyses and the multivariate Cox regression model. We further compared survival outcomes between patients who received partial nephrectomy and patients who received radical nephrectomy. RESULTS: We observed statistically significant associations between all components of radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry scores and oncologic outcomes, including R (radius) (overall survival, P < 0.001; recurrence-free survival , P < 0.001), E (exophytic/endophytic) (overall survival, P = 0.003; recurrence-free survival, P < 0.001), N (nearness) (overall survival, P = 0.063; recurrence-free survival, P < 0.001), A (anterior/posterior) (overall survival, P < 0.001; recurrence-free survival, P = 0.005), L (location) (overall survival, P = 0.008; recurrence-free survival, P < 0.001) and suffix 'h' (overall survival, P = 0.237; recurrence-free survival, P = 0.034). Kaplan-Meier curves of overall survival and recurrence-free survival rates were significantly different when stratified by radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry score complexity group (overall survival, P < 0.001; recurrence-free survival, P < 0.001). After adjusting for tumour stage and grade, radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry score as continuous variables was an adverse independent risk factor for survival outcomes [P = 0.027, hazard ratio (95% confidence interval) = 1.151 (1.016-1.303)] and recurrence-free survival [P < 0.001, hazard ratio (95% confidence interval) = 1.299 (1.125-1.501)]. For tumours with radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry scores of 4 and 5, partial nephrectomy showed a survival benefit than radical nephrectomy. CONCLUSION: Both components and complexity groups of the radius-exophytic/endophytic-nearness-anterior/posterior-location nephrometry score are associated with survival outcomes in renal tumour patients.

Best predictive single nephrometry score component to correlate with achievement of trifecta outcome in laparoscopic and robotic surgery.

BACKGROUND: To evaluate the predictive value of individual components of the R.E.N.A.L scoring system for Laparoscopic (LPN) and Robotic Partial Nephrectomy (RPN). METHODS: Patients that had undergone a Laparoscopic (LPN) or Robotic Partial Nephrectomy (RPN) between 2018 and 2023 were reviewed. Our data collection included Race, Ethnicity, Age, BMI, R.E.N.A.L nephrometry score, and complications. Cases that achieved trifecta outcomes were designated as "Group A" and cases that did not achieve trifecta were "Group B". All the data were collected using REDCap database. RESULTS: A total of 111 cases were included, Group A consisted of 82% of all cases, whereas Group B 18%. Radius score demonstrated significant distinction concerning trifecta attainment and was the most predictive component of the 5 scoring metrics of the nephrometry system. In a subgroup analysis, R-score of 3 or a renal mass measuring ≥ 7 cm, was a significant independent negative predictor for trifecta outcomes, as well as tumor size at presentation. CONCLUSION: Renal nephrometry score is predictive of trifecta outcomes for patients undergoing laparoscopic or robotic partial nephrectomy. Radius of mass was the most effective predictive component of the nephrometry score for trifecta prediction.

The DDD score outperforms the RENAL score in predicting high-grade renal cell carcinoma.

OBJECTIVES: To explore the relationship between Fuhrman grade of renal cell carcinoma (RCC) and the DDD score. METHODS: We reviewed the records of 527 nonmetastatic RCC patients. Demographic, clinical, and pathologic characteristics were reviewed. Binary logistic regression was used to explore the independent risk factors for high-grade RCC (HGRCC). RESULTS: Sex, BMI (Body Mass Index), RNS, and DDD score were significantly correlated with HGRCC. Based on these independent risk factors, we constructed two predictive models integrating the RNS and DDD scores with sex and BMI to predict tumor grade. The calibration curves of the predictive model showed good agreement between the observations and predictions. The concordance indexes (C-indexes) of the predictive models were 0.768 (95% CI, 0.713-0.824), and 0.809 (95% CI, 0.759-0.859). Receiver operating characteristic (ROC) curves were performed to compare the predictive power of the nomograms, and the prediction model including the DDD score had better prognostic ability (p = 0.01). CONCLUSIONS: This study found that RNS, DDD score, BMI, and sex were independent predictors of HGRCC. We developed effective nomograms integrating the above risk factors to predict HGRCC. Of note, the nomogram including the DDD score achieves better prediction ability for HGRCC.

Nephrometry scores to predict oncological outcomes following partial nephrectomy (UroCCR Study 70).

PURPOSE: Partial nephrectomy (PN) for large or complex renal tumors can be difficult and associated with a higher risk of recurrence than radical nephrectomy. We aim to evaluate the clinical useful of nephrometry scores for predicting oncological outcomes in a large cohort of patients who underwent PN for renal cell carcinomas. METHODS: Our analysis included patients who underwent PN for renal cell carcinoma in 21 French academic centers (2010-2020). RENAL, PADUA, and SPARE scores were calculated based on preoperative imaging. Uni- and multivariate cox models were performed to identify predictors of recurrence-free survival and overall survival. The area under the curve (AUC) was used to identify models with the highest discrimination. Decision curve analyses (DCAs) determined the net benefit associated with their use. RESULTS: A total of 1927 patients were analyzed with a median follow-up of 32 months (14-45). RENAL score (p = 0.01), age (p = 0.002), histological type (p = 0.001), high nuclear grade (p = 0.001), necrotic component (p < 0.001), and positive margins (p = 0.005) were significantly related to recurrence in multivariate analyses. The discriminative performance of the 3 radiological scores was modest (65, 63, and 63%, respectively). All 3 scores showed good calibration, which, however, deteriorated with time. Decision curve analysis of the three models for the prediction of overall and recurrence-free survival was similar for all three scores and of limited clinical relevance. CONCLUSION: The association between nephrometry scores and oncological outcomes after NP is very weak. The use of these scores for predicting oncological outcomes in routine practice is therefore of limited clinical value.

Impact of tumor contact surface area on collecting system entry in robot-assisted partial nephrectomy: a retrospective analysis.

BACKGROUND: Collecting system entry in robot-assisted partial nephrectomy may occur even in cases showing a low N factor in the R.E.N.A.L nephrometry score. Therefore, in this study, we focused on the tumor contact surface area with the adjacent renal parenchyma and attempted to construct a novel predictive model for collecting system entry. METHODS: Among 190 patients who underwent robot-assisted partial nephrectomy at our institution from 2015 to 2021, 94 patients with a low N factor (1-2) were analyzed. Contact surface was measured with three-dimensional imaging software and defined as the C factor, classified as C1, < 10 cm [2]; C2, ≥ 10 and < 15 cm [2]; and C3: ≥ 15 cm [2]. Additionally, a modified R factor (mR) was classified as mR1, < 20 mm; mR2, ≥ 20 and < 40 mm; and mR3, ≥ 40 mm. We discussed the factors influencing collecting system entry, including the C factor, and created a novel collecting system entry predictive model. RESULTS: Collecting system entry was observed in 32 patients with a low N factor (34%). The C factor was the only independent predictive factor for collecting system entry in multivariate regression analysis (odds ratio: 4.195, 95% CI: 2.160-8.146, p < 0.0001). Models including the C factor showed better discriminative power than the models without the C factor. CONCLUSIONS: The new predictive model, including the C factor in N1-2 cases, may be beneficial, considering its indication for preoperative ureteral catheter placement in patients undergoing robot-assisted partial nephrectomy.

RENAL nephrometry scoring system in bilateral Wilms tumor: predictive application.

AIM: This study aims to explore the application of RENAL nephrometry scoring system in bilateral Wilms tumor (BWT). METHODS: A retrospective review of patients with BWT from January 2010 to June 2022 was performed. Each kidney unit of the BWT was evaluated independently and scored according to RENAL nephrometry scoring system by 2 blinded reviewers, and reviewers were blinded to what surgery the patients ultimately had. Discrepancies were evaluated by a third reviewer to reach a consensus. Tumor anatomical characteristics were summarized and compared. RESULTS: 29 patients with 53 kidney units were included in the study. 53 kidney units included 12 (22.6%) low-complexity, 9 (17.0%) intermediate-complexity, and 32 (60.4%) high-complexity. 2 kidney units (3.8%) had tumor thrombus, and 14 (26.4%) had multiple lesions. A total of 42 kidney units (79.2%) underwent initial nephron-sparing surgery (NSS) and 11 (20.8%) underwent radical nephrectomy. Less complexity tumors were observed in the NSS group. Of the 42 kidney units undergoing initial NSS, 26 were performed in vivo and 16 ex vivo via autotransplantation. The latter group featured a higher complexity. During follow-up, 22 patients survived and 7 died, no statistically significant tumor complexity was observed between the two groups. CONCLUSIONS: The anatomical characteristics of BWT are complex. Despite this study did not indicate that the complexity correlates with prognosis, low-complexity tumors were candidates for NSS, and kidney autotransplantation provided a feasible procedure for high-complexity tumors. A refined system is required due to multiple lesions and tumor thrombus.

A pilot study investigating the feasibility of using a fully automatic software to assess the RENAL and PADUA score.

PURPOSE: Image-based morphometric scoring systems such as the RENAL and PADUA scores are useful to evaluate the complexity of partial nephrectomy for renal cell carcinoma (RCC). The main aim of this study was to develop a new imaging software to enable an automatic detection and a 3D visualization of RCC from CT angiography (CTA) and to address the feasibility to use it to evaluate the features of the RENAL and the PADUA scores. METHODS: A training dataset of 210 patients CTA-scans manually segmented was used to train a deep learning algorithm to develop the automatic detection and 3D-visualization of RCC. A trained operator blindly assessed the RENAL and PADUA scores on a testing dataset of 41 CTA from patients with RCC using a commercialized semi-automatic software (ground truth) and the new automatic software. Concordance between the two methods was evaluated. RESULTS: The median PADUA score was 9 (7-11) and the renal score was 8 (5.5-9). The automatic software enabled to automatically detect the tumoral kidney and provided a 3D-visualization in all cases, with a computational time less than 20 seconds. Concordances for staging the anatomical features of the RENAL scores were respectively: 87.8% for radius, 85.4% for exophytic rate, 82.9% for location to the polar lines and 92.7% for the antero-posterior location. For the PADUA scores, concordances were 90.2% for tumor size, 85.4% for exophytic rate, 87.8% for polar location and 100% for renal rim. CONCLUSION: By enabling an automatic 3D-visualization of tumoral kidney, this software could help to calculate morphometric scores, save time and improve reproducibility for clinicians.

Nephrometry scores: a validation of three systems for peri-operative outcomes in retroperitoneal robot-assisted partial nephrectomy.

OBJECTIVE: To externally validate the RENAL, PADUA and SPARE nephrometry scoring systems for use in retroperitoneal robot-assisted partial nephrectomy (RAPN). MATERIALS AND METHODS: Nephrometry scores were calculated for 322 consecutive patients receiving retroperitoneal RAPN at a tertiary referral centre from 2017. Patients with multiple tumours were excluded. Scores were correlated with peri-operative outcomes, including the trifecta (warm ischaemia time <25 min, no peri-operative complications and a negative surgical margin), both as continuous and categorical variables. Comparisons were performed using Spearman correlation and ability to predict the trifecta was assessed using binomial logistical regression. RESULTS: All three scoring systems correlated significantly with the main variables (operating time, warm ischaemia time and estimated blood loss), both as continuous and categorical variables. Only PADUA and SPARE were able to predict achievement of the trifecta (PADUA area under the curve [AUC] 0.623, 95% confidence interval [CI] 0.559-0.668; SPARE AUC 0.612, 95% CI 0.548-0.677). CONCLUSION: This study validates the RENAL, PADUA and SPARE scoring systems to predict key intra-operative outcomes in retroperitoneal RAPN. Only PADUA and SPARE were able to predict achievement of the trifecta. As a simplified version of the PADUA scoring system with comparable outcomes, we recommend using the SPARE system.

A low RENAL Nephrometry Score can avoid the need for the intraoperative insertion of a ureteral catheter in robot-assisted partial nephrectomy.

BACKGROUND: Intraoperative urinary collecting system entry (CSE) in robot-assisted partial nephrectomy (RAPN) may cause postoperative urinary leakage and extend the hospitalization. Therefore, identifying and firmly closing the entry sites are important for preventing postoperative urine leakage. In RAPN cases expected to require CSE, we insert a ureteral catheter and inject dye into the renal pelvis to identify the entry sites. We retrospectively analyzed the factors associated with intraoperative CSE in RAPN and explored the indications of intraoperative ureteral catheter indwelling in RAPN. METHODS: Of 104 Japanese patients who underwent RAPN at our institution from August 2016 to March 2020, 101 were analyzed. The patients were classified into CSE and non-CSE groups. The patients' background characteristics, RENAL Nephrometry Score (RNS), and surgical outcomes were analyzed. RESULTS: Intraoperative CSE was observed in 41 patients (41%). The CSE group had a significantly longer operative time, console time, ischemic time, and hospital stay than the non-CSE group. In a multivariable analysis, the N-score (odds ratio [OR] = 3.9, P < 0.05) and RNS total score excluding the L-score (OR = 3.1, P < 0.05) were associated with CSE. In a logistic regression analysis, CSE showed a moderate correlation with the RNS total score excluding the L-score (AUC 0.848, cut-off 5, sensitivity 0.83, specificity 0.73). CONCLUSION: A ureteral catheter should not be placed in patients with an RNS total score (excluding the L-score) of ≤ 4.

Nephrometry Scores: Can Preoperative Assessment of Sectional Imaging Really Mirror Intraoperative Renal Tumor Anatomy?

INTRODUCTION: To compare RENAL, preoperative aspects and dimensions used for an anatomical (PADUA) classification, and Mayo Adhesive Probability (MAP) scores with the respective intraoperative findings and surgeon's assessment in predicting surgical outcome of patients undergoing partial nephrectomy. METHODS: Data of 150 eligible patients treated at the University Medical Center Mannheim between 2016 and 2018 were analyzed. Tumors were radiologically and intraoperatively assessed by PADUA, RENAL, and MAP scores and surgeon's assessment. Correlations and regression models were created to predict ischemia time (IT), major complications, and Trifecta (negative surgical margin, IT < 25 min, and absence of major complications). RESULTS: There were strong correlations between radiological and intraoperative RENAL (r = 0.68; p < 0.001) and PADUA scores (r = 0.72; p < 0.001). Radiological RENAL, PADUA, and MAP scores and surgeon's assessment were independent predictors of Trifecta (OR = 0.71, p = 0.015; OR = 0.77, p = 0.035; OR = 0.65, p = 0.012; OR = 0.40, p = 0.005, respectively). IT showed significant associations with radiological RENAL, PADUA, and surgeon's assessment (OR = 1.41, p = 0.033; OR = 1.34, p = 0.044; OR = 3.04, p = 0.003, respectively). MAP score proved as only independent predictor of major complications (OR = 2.12, p = 0.002). CONCLUSION: Radiologically and intraoperatively assessed scores correlated well with each other. Intraoperative nephrometry did not outperform radiological scores in predicting outcome confirming the value of the existing systems. MAP score correlates well with surgeon's assessment of perirenal fat and major complications underlining the importance of perirenal fat characteristics.

[Comparative analysis of clinical features of robotic-assisted and laparoscopic partial nephrectomy].

INTRODUCTION: Kidney cancer (mostly renal cell carcinoma) is one of the ten most commonly diagnosed malignant tumors among men and women. Due to the widespread use of computer tomography and magnetic resonance imaging, the proportion of early-stage kidney cancers has increased. Currently, treatment options for stage 1 kidney cancer are radical nephrectomy, partial nephrectomy, and active surveillance. Among organ-preserving intervention, three main techniques can be distinguished: open surgery, minimally invasive surgery and ablation methods. To date, robotic-assisted procedures have occupied their place among minimally invasive interventions. AIM: To carry out a comparative analysis of two methods of organ-preserving treatment of kidney tumors, namely robot-assisted and laparoscopic partial nephrectomy. MATERIALS AND METHODS: A retrospective comparative analysis of two groups of patients with kidney tumors who underwent robotic-assisted or laparoscopic partial nephrectomy during the period from 2012 to 2019 was performed. RESULTS: There were no differences between two groups in age, mean score on the RENAL nephrometry scale, preoperative creatinine levels, tumor size, and duration of warm ischemia. However, duration of surgery, the volume of blood loss, serum creatinine after surgery, the length of stay, the use of the technique of early unclamping of the renal artery, the use of technique "off-clamp" and the proportion of exophytic tumors with growth were significantly different between patients of two groups. CONCLUSION: We believe that the robotic system is intuitively convenient for performing partial nephrectomy, allowing the treatment of potentially more complex cases and expanding the indications for organ-preserving procedures.

External validation of the Simplified PADUA REnal (SPARE) nephrometry system in predicting surgical outcomes after partial nephrectomy.

BACKGROUND: Pentafecta is a major goal in the era of partial nephrectomy (PN). Simplified PADUA REnal (SPARE) nephrometry system was developed to evaluate the complexity of tumor. However, the predictive ability in pentafecta of SPARE system is yet to be determined. The aim of this study was to externally validate the applicability of SPARE nephrometry system in predicting pentafecta achievement after partial nephrectomy, and to examine inter-observer concordance. METHODS: We retrospectively reviewed data of 207 consecutive patients who underwent PN between January 2012 and August 2018 at a tertiary referral center. We obtained SPARE, R.E.N.A.L., and PADUA scores and evaluated correlations among the nephrometries and surgical outcomes including pentafecta by Spearman test. Logistic regression analysis was used to identify independent predictors of pentafecta outcomes. We compared the nephrometries to determine the predictive ability of achieving pentafecta using receiver operating characteristic curve analysis. Fleiss' generalized kappa was used to assessed interobserver variation in the SPARE system. RESULTS: Based on the SPARE system, 120, 74, and 13 patients were stratified into low-risk, intermediate-risk, and high-risk groups, respectively. Regarding the individual components of pentafecta, there were significant differences in the complication rate (p = 0.03), ischemia time (p < 0.001), and percent change of eGFR (p < 0.001) among the three risk groups. In addition, higher tumor complexity was significantly associated with a lower achievement rate of pentafecta (p = 0.01). In Spearman correlation tests, SPARE nephrometry was correlated with ischemia time (ρ:0.37, p < 0.001), operative time (ρ:0.28, p < 0.001), complication rate (ρ:0.34, p < 0.001), percent change of eGFR (ρ:0.34, p < 0.001), and progression of chronic kidney disease stage (ρ:0.17, p = 0.02). Multivariate analysis revealed that SPARE significantly affected pentafecta (OR: 0.67, p < 0.001). In ROC curve analysis, SPARE showed fair predictive ability in the achievement pentafecta (AUC: 0.71). The predictive ability of pentafecta was similar between nephrometries (SPARE vs. R.E.N.A.L., p = 0.78; SPARE vs. PADUA, p = 0.66). The interobserver concordance of SPARE was excellent (Kappa: 0.82, p = 0.03). CONCLUSIONS: SPARE system was a predictive factor of surgical outcomes after PN. This refined nephrometry had similar predictive abilities for pentafecta achievement compared with R.E.N.A.L. and PADUA.

[Analysis of the learning curve in laparoscopic partial nephrectomy in patients with localized renal parenchymal lesions depending on the nephrometric score].

AIM: to analyze the learning curve of surgeons while performing laparoscopic partial nephrectomy in patients with localized renal parenchymal lesions by calculating the MIC (negative surgical margin, ischemia, and complications) index depending on tumor complexity according to the R.E.N.A.L. and PADUA nephrometric scores. MATERIALS AND METHODS: the retrospective study included the results of laparoscopic partial nephrectomies in 320 patients with localized renal parenchymal lesions. The procedures were carried out by four surgeons from the Institute of Urology and Human Reproductive Health of FGAOU VO I.M. Sechenov First Moscow State Medical University, Moscow, Russia (EC-1; ESH-4; EB-7; ME-13) from January 2014 to June 2019. At baseline, all operators had experience of performing at least 30 laparoscopic interventions. In addition to the standard preoperative examination, a 3D virtual planning was carried out using the Amira 3D modeling program. In all cases, the nephrometric assessment of complexity was performed according to the R.E.N.A.L. and PADUA scores. The learning curve was assessed based on the results of operations based on the MIC index. All surgical interventions were divided into eras. In the era, 40 consecutive procedures for each operator were evaluated. Acquired skills were assessed over two eras. RESULTS: The average age of patients, of which 191 (59.7%) were men, was 54.4+/-11.37 years. The average body mass index was 28.55+/-3.85 kg/m2, the absolute volume of kidney lesions was 26.72+/-43.72 cm3, the average Charlson comorbidity index was 1.46+/-1.29, the average R.E.N.A.L. and PADUA scores were 6.38+/-1.75 and 7.92+/-1.51, respectively, the average duration of procedure was 150.36+/-50.18 min, the average blood loss was 227.94+/-280.22 ml, the average time thermal ischemia was 13.28+/-7.82 min. Postoperative complications were seen in 36 (11.2%) cases, of which grade III and more according to Clavien-Dindo developed in 8 patients (2.5%). A positive surgical margin was found in 4 (1.2%) patients. The overall MIC index was achieved in 243 (75.9%) cases; in era 1 it was seen in 71.9% cases in comparison with 80% in era 2. With the 1st degree of complexity (152 (47.5%) patients), MIC was achieved in 80.9% of cases, compared to 76.6% and 56.8% in patients with 2nd degree of complexity (n=124, 38.8%) and 3rd degree of complexity (n=44, 13.8%), respectively. Rate of MIC achievement in eras 1 and 2 for different surgeons were as following: 65% and 72.5%, 75 and 80%, 87.5 and 85% and 60 and 82.5%, for operator 1, 4, 7 and 13, respectively. Age, tumor complexity, R.E.N.A.L. score and PADUA score were the most significant parameters for determining MIC, identified on the basis of the criterion of equality of group means of discrete analysis. CONCLUSION: In all surgeons, the MIC index increased with the accumulation of experience in performing laparoscopic partial nephrectomy, but was lower with an increased degree of complexity of procedures. The minimum number of laparoscopic partial nephrectomies required to achieve an MIC more or equal 70% should be at least 40.

The Simplified PADUA REnal (SPARE) nephrometry system: a novel classification of parenchymal renal tumours suitable for partial nephrectomy.

OBJECTIVE: To simplify the original Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) classification of renal tumours, generating a new system able to predict equally or better the risk of overall complications in patients undergoing partial nephrectomy (PN); and to test if the addition of the contact surface area (CSA) parameter improves the accuracy of the original PADUA and new Simplified PADUA REnal (SPARE) nephrometry classification systems. PATIENTS AND METHODS: We analysed the clinical records of 531 patients who underwent PN (open, laparoscopic and robot-assisted) for renal tumours at five tertiary academic referral centres from January 2014 to December 2016. The ability of each variable included in the PADUA classification to predict overall complications was tested using binary logistic regression analysis. The variables that were not statistically significant were excluded from the SPARE classification. In addition to the original PADUA and SPARE systems, another two models were generated adding tumour CSA. Receiver operating characteristic curve analysis was used to compare the ability of the four different models to predict overall complications. Binary logistic regression was used to perform both univariable and multivariable analyses looking for predictors of postoperative complications. Linear regression analysis was used to identify independent predictors of absolute change in estimated glomerular filtration rate (eGFR; ACE). RESULTS: The SPARE nephrometry score system including: (i) rim location, (ii) renal sinus involvement, (iii) exophytic rate, and (iv) tumour dimension; showed equal performance in comparison with the original PADUA score (area under the curve [AUC] 0.657 vs 0.664). Adding tumour CSA to the original PADUA (AUC 0.661) or to the SPARE (AUC 0.658) scores did not increase the accuracy of either system to predict overall complications. The SPARE system (odds ratio 1.2, 95% confidence interval 1.1-1.3) was an independent predictor of postoperative overall complications. Age (P < 0.001), body mass index (P < 0.001), Charlson Comorbidity Index (P = 0.02), preoperative eGFR (P < 0.001), and tumour CSA (P = 0.005) were independent predictors of ACE. Limitations include the retrospective design and the lack of central imaging review. CONCLUSIONS: The new SPARE score is comprised of only four variables instead of the original six and its accuracy to predict overall complications is similar to that of the original PADUA score. Addition of tumour CSA was not associated with an increase in prognostic accuracy. The SPARE system could replace the original PADUA score to evaluate the complexity of tumours suitable for PN.

Tumour contact surface area as a predictor of postoperative complications and renal function in patients undergoing partial nephrectomy for renal tumours.

OBJECTIVES: To evaluate the ability of original tumour contact surface area (CSA) to predict postoperative complications and renal function impairment in a series of patients who underwent elective partial nephrectomy (PN) for renal masses. MATERIALS AND METHODS: We analysed the clinical records of 531 consecutive patients who underwent elective PN because of a suspicion of kidney cancer at five academic, high-volume centres between January 2014 and December 2016. Each participating centre evaluated prospectively the radiological images to evaluate the CSA and to assign a PADUA score. Several expert surgeons performed the surgical procedures in each participating centre. Binary logistic regression was used to perform both univariable and multivariable analyses to identify predictors of postoperative complications. Linear regression analysis was used to identify independent predictors of absolute change in estimated glomerular filtration rate (eGFR; ACE). RESULTS: The median (interquartile range) CSA value was 14.2 (7.4-25.1) cm2 . A total of 349 tumours (65.7%) had a CSA ≤ 20 cm2 and the remaining 182 (34.3%) had a CSA > 20 cm2 . PNs were performed using an open approach in 237 (44.6%) cases, a pure laparoscopic approach in 152 cases (28.6%), and a robot-assisted approach in the remaining 142 cases (26.7%). Multivariable analyses found that only age (odds ratio [OR] 1.037, 95% confidence interval [CI] 1.018-1.057) and PADUA score (OR 1.289, 95%CI 1.132-1.469) were independent predictors of postoperative complications. Tumour CSA (OR 1.020, 95%CI 1.010-1.030) was found to be an independent predictor of postoperative complications only when PADUA score was removed from the model. Age (from -0.639 to -0.306; P < 0.001); body mass index (from 0.267 to 1.076; P = 0.001), age-adjusted Charlson score (from -3.193 to -0.259; P = 0.02), preoperative eGFR value (from -0.939 to -0.862; P < 0.001) and tumour CSA (from -0.260 to -0.048; P = 0.005) were found to be independent predictors of ACE. CONCLUSIONS: Tumour CSA is an independent predictor of postoperative renal function. Conversely, at multivariable analysis, PADUA score outperformed tumour CSA to predict postoperative complications after PN. The complexity of The Leslie et al. formula for calculating tumour CSA is a potential limitation with regard to its diffusion and application in clinical practice.

Three-dimensional virtual imaging of renal tumours: a new tool to improve the accuracy of nephrometry scores.

OBJECTIVES: To apply the standard PADUA and RENAL nephrometry score variables to three-dimensional (3D) virtual models (VMs) produced from standard bi-dimensional imaging, thereby creating three-dimensional (3D)-based (PADUA and RENAL) nephrometry scores/categories for the reclassification of the surgical complexity of renal masses, and to compare the new 3D nephrometry score/category with the standard 2D-based nephrometry score/category, in order to evaluate their predictive role for postoperative complications. MATERIALS AND METHODS: All patients with localized renal tumours scheduled for minimally invasive partial nephrectomy (PN) between September 2016 and September 2018 underwent 3D and 2D nephrometry score/category assessments preoperatively. After nephrometry score/category evaluation, all the patients underwent surgery. Chi-squared tests were used to evaluate the individual patients' grouping on the basis of the imaging tool (3D VMs and 2D imaging) used to assess the nephrometry score/category, while Cohen's κ coefficient was used to test the concordance between classifications. Receiver-operating characteristic curves were produced to evaluate the sensitivity and specificity of the 3D nephrometry score/category vs the 2D nephrometry score/category in predicting the occurrence of postoperative complications. A general linear model was used to perform multivariable analyses to identify predictors of overall and major postoperative complications. RESULTS: A total of 101 patients were included in the study. The evaluation of PADUA and RENAL nephrometry scores via 3D VMs showed a downgrading in comparison with the same scores evaluated with 2D imaging in 48.5% and 52.4% of the cases. Similar results were obtained for nephrometry categories (29.7% and 30.7% for PADUA risk and RENAL complexity categories, respectively). The 3D nephrometry score/category demonstrated better accuracy than the 2D nephrometry score/category in predicting overall and major postoperative complications (differences in areas under the curve for each nephrometry score/category were statistically significant comparing the 3D VMs with 2D imaging assessment). Multivariable analyses confirmed 3D PADUA/RENAL nephrometry category as the only independent predictors of overall (P = 0.007; P = 0.003) and major postoperative complications (P = 0.03; P = 0.003). CONCLUSIONS: In the present study, we showed that 3D VMs were more precise than 2D standard imaging in evaluating the surgical complexity of renal masses according to nephrometry score/category. This was attributable to a better perception of tumour depth and its relationships with intrarenal structures using the 3D VM, as confirmed by the higher accuracy of the 3D VM in predicting postoperative complications.

The role of RENAL, PADUA, C-index, CSA nephrometry systems in predicting ipsilateral renal function after partial nephrectomy.

BACKGROUND: Functional outcome is an important issue in nephron-sparing surgery. Various nephrometries have been developed to predict renal function preservation. The aim of this study was to examine the applicability of R.E.N.A.L., PADUA, C-index, and mathematical tumor contact surface area (CSA) in predicting ipsilateral renal function after partial nephrectomy using radio-isotope scans. METHODS: We performed this retrospective study in patients who underwent partial nephrectomy between May 2013 and April 2017, and used abdominopelvic computerized tomography or magnetic resonance imaging to obtain R.E.N.A.L., C-index, and CSA. Renal function was measured by 99mTc mercaptoacetyltriglycine (MAG3). We evaluated correlations between nephrometries and perioperative parameters, and comparatively analyzed different nephrometries to determine the predictive ability in the percent change of effective renal plasma flow of the affected kidney. RESULTS: Three, two, and 35 patients received partial nephrectomy in open, laparoscopic, and robotic approaches, respectively. The median (IQR) tumor size was 3.13 (2.4) cm. The median (IQR) R.E.N.A.L., PADUA, C-index, and CSA scores were 7 (3), 8 (2), 2.01 (1.87), and 14.14 (19.25) cm2, respectively. Spearman correlation analysis showed that four nephrometries were correlated with each other. The strongest correlations were between CSA and C-index (coefficient: - 0.885, p < 0.001), followed by R.E.N.A.L. and PADUA (coefficient: 0.778, p < 0.001). Ischemia time was significantly correlated with R.EN.A.L. (coefficient: 0.35, p = 0.025), PADUA (coefficient: 0.42, p = 0.007), C-index (coefficient: - 0.45, p = 0.004), and CSA (coefficient: 0.41, p = 0.009). In multivariate analysis, PADUA significantly affected ischemia time (p = 0.04). The percent change in effective renal plasma flow (PCE) of the operated kidney was correlated with PADUA (coefficient: 0.48 p = 0.002), C-index (coefficient: - 0.74, p < 0.001), and CSA (coefficient: 0.75, p < 0.001). Only CSA and C-index independently affected PCE (both p < 0.05) in multivariate analysis. In ROC curve analysis, both C-index and CSA could predict 20% change in effective renal plasma flow (AUC: 0.91 vs 0.86, p = 0.2) of the affected kidney. CONCLUSIONS: We suggest using PADUA to evaluate surgical complexity and ischemia time. Regarding the accuracy of the prediction of post-operative ipsilateral renal function, both CSA and C-index outperformed R.E.N.A.L. and PADUA nephrometries.

Predictors of renal function after open and robot-assisted partial nephrectomy: A propensity score-matched study.

OBJECTIVE: To investigate parameters predicting short- and long-term renal function after open partial nephrectomy and robot-assisted partial nephrectomy. METHODS: Medical records of 896 patients who underwent open partial nephrectomy or robot-assisted partial nephrectomy from 2004 to 2017 at a single large-volume institution were retrospectively reviewed. Propensity score matching of open partial nephrectomy and robot-assisted partial nephrectomy group was carried out with a ratio of 1:1. Postoperative outcomes were compared, and multivariate logistic regression was carried out to identify the parameters influencing acute kidney injury and chronic kidney disease progression. RESULTS: No significant differences in preoperative characteristics were observed between the two study groups after matching. Robot-assisted partial nephrectomy was significantly associated with a longer warm ischemic time (P < 0.001) yet, estimated blood loss, positive surgical margin, rates of major postoperative complications and chronic kidney disease progression were significantly lower in the robot-assisted partial nephrectomy group (P < 0.001, 0.033, <0.001, <0.001, and 0.005, respectively). Multivariate analysis showed robot-assisted partial nephrectomy was more favorable than open partial nephrectomy in terms of preserving renal function. Patients with a higher baseline estimated glomerular filtration rate were significantly associated with a greater risk of acute kidney injury (odds ratio 1.036; 95% confidence interval 1.021-1.052; P < 0.001), but a decreased risk of chronic kidney disease progression (odds ratio 0.975; 95% confidence interval 0.955-0.994; P = 0.011). Other independent predictors of chronic kidney disease progression were warm ischemic time (P = 0.025), age (P = 0.035), body mass index (P = 0.041) and diabetes mellitus (P = 0.035). CONCLUSIONS: Baseline estimated glomerular filtration rate, warm ischemic time and surgery type are independent predictors of both acute kidney injury and chronic kidney disease progression. Robot-assisted partial nephrectomy is more favorable than open partial nephrectomy for reducing estimated blood loss, positive surgical margin, major postoperative complications and renal function preservation.

The effectiveness of RENAL nephrometry score in ablated renal tumors via radiofrequency ablation or cryoablation

Background/aim: This study aimed to evaluate the clinical efficacy of radiofrequency ablation (RFA) and cryotherapy and to scrutinize the therapeutic success of the RENAL (radius, exophytic/endophytic, nearness to collecting system, anterior/posterior, and location) nephrometry score in terms of possible complications and the predictive status of oncological results. Materials and methods: Forty-five patients with biopsy-proven renal cell carcinomas (32 males, 13 females) treated with RFA and cryotherapy were included. Patients were 22­90 years old (average: 59.2 years). Statistical analyses were performed using SPSS for Windows. Results: A total of 79 lesions with dimensions varying between 0.9 and 4.5 cm (average: 2.2 cm) were ablated. Complete ablation was achieved for 72 (91.1%) lesions. Six repeat RFA sessions were applied for 4 (5%) lesions with residue/recurrence. The average RENAL nephrometry scores of lesions that underwent complete ablation and those that developed residue/recurrence were 6.3 and 7.7, respectively. The average recurrence-free survival time was 34.8 months (range: 3­55 months), while it was 44.6 months (range: 6­55 months) for cryotherapy and 28.6 months (range: 3­50 months) for RFA. Conclusion: Ablative therapies are minimally invasive and effective methods for treating small renal tumors. RENAL nephrometry scoring is a valuable system for standardizing renal tumors and evaluating the success of ablative therapies, possible complications, and oncological results.