Background/Objectives: This study evaluates and compares the surgical outcomes of open pyelolithotomy, laparoscopic pyelolithotomy, and retrograde intrarenal surgery (RIRS) in the management of pelvic ectopic kidney stones. Methods: A retrospective analysis was conducted on 47 adult patients with pelvic ectopic kidney stones who underwent surgery between January 2009 and January 2024. Patients were categorized as open pyelolithotomy (n = 15), laparoscopic pyelolithotomy (n = 14), or RIRS (n = 18). Stone-free (SF) rates were assessed in the early postoperative period (1st or 2nd day), in the 1st month, and in the 3rd month. Demographic data, stone characteristics, operative data, and complications were recorded. Results: RIRS had significantly shorter operative and hospitalization times but a lower SF rate in the 3rd month (44.4%) compared to laparoscopy (92.9%) and open pyelolithotomy (86.7%). Additional procedures were required in 50% of RIRS cases to achieve SF status, while none were needed in the other groups. Complications included three Grade 2 cases (two bleeding; transient creatinine elevation) in open pyelolithotomy, two Grade 2 (urinary leakage; infection) and two Grade 3 cases (conversion to open surgery; trapped stent removal) in laparoscopic pyelolithotomy, and one Grade 2 case (febrile infection) in RIRS. Conclusions: Laparoscopic pyelolithotomy demonstrated the highest efficacy and comparable complication rates; making it the preferred approach for pelvic ectopic kidney stones. Open pyelolithotomy remains a valuable alternative where laparoscopic expertise or resources are limited. Although less invasive, RIRS showed lower efficacy due to the challenging anatomy of pelvic ectopic kidneys.

Background/Objectives: Urinary system stone disease is an important health problem both clinically and economically due to its high recurrence rates. In this study, an innovative hybrid approach based on deep learning is proposed to predict the recurrence risk of stone disease. Methods: Patient data were divided into three subsets: anthropometric measurements (Part A), derived body composition indices (Part B), and other clinical and demographic information (Part C). Each data subset was processed with autoencoder models, and low-dimensional, meaningful features were extracted. The obtained features were combined, and the classification process was performed using four different machine learning algorithms: Extreme Gradient Boosting (XGBoost), Cubic Support Vector Machines (Cubic SVM), k-Nearest Neighbor algorithm (KNN), and Decision Tree (DT). Results: According to the experimental results, the highest classification performance was obtained with the XGBoost algorithm. The suggested approach adds to the literature by offering a novel solution that makes early risk calculation for stone disease recurrence easier. It also shows how well structural feature engineering and deep representation can be integrated in clinical prediction issues. Conclusions: Prediction of the stone recurrence risk in advance is of great importance both in terms of improving the quality of life of patients and reducing the unnecessary diagnostic evaluations along with lowering treatment costs.

Purpose: To evaluate the role of certain radiological parameters and patient characteristics in predicting the success of endoscopic treatment in ureteral stricture disease. Methods: Fifty one adult patients with ureteral stricture disease (< 1 cm) after developing due to upper ureteral stones with ureteroscopic laser disintegration were included and in addition to stone and patient parameters, radiological parameters including ureteral wall thickness (UWT) at the impacted stone site were also measured on computed tomography (CT) images. Patients were divided into two groups: Group 1: Patients with endoscopic treatment success and Group 2: Patients with endoscopic treatment failure. The possible relationship between the UWT values and other radiological parameter was comparatively evaluated. Results: Mean UWT value assessed at the treated stone site was significantly higher in cases unresponsive to endoscopic treatment with values of 2.77 ± 1.03 mm and 4.25 ± 1.32 mm in Group 1 and 2 respectively. A cut off value 3.55 mm for UWT was found to be highly predictive for endoscopic treatment failure. Conclusions: Our current results indicated that assessment of UWT value at the obstructing stone could be helpful enough to predict the likelihood of failure following endoscopic management of strictures with high sensitivity and specificity. Evaluation of this particular parameter could let the endourologists to look for more rational treatment alternatives with necessary measures taken on time.