98%
921
2 minutes
20
Background: Percutaneous nephrolithotomy is the standard treatment for large or irregularly shaped kidney stones, especially staghorn calculus. However, establishing a precise and safe puncture is challenging and requires extensive training for the surgeon. Navigation surgery is a commonly employed technique that facilitates the puncture through generating a path before surgery. One critical challenge for navigation is skin-kidney path planning due to the complex anatomical deconstruction of the kidney as well as the irregular shape of kidney stones.
Method: In this paper, we propose a hybrid strategy puncture path planning algorithm, where we follow a 2-step flow path that considers the selection of puncture renal calyces and planning of a B-spine curve path. We imitate the decision-making process of the clinician in selecting the puncture calyx based on the projective area of the calculi to be cleared. We summarize subjective judgment and clinical experience during puncture, where parametric optimization indicators are proposed to realize the optimization of puncture path.
Results: An optimal frontier consisting of puncture pathways focused on different puncture factors can be generated from the proposed algorithm, where the physician can choose the path that works best under real circumstances. Results in 2D simulation show that the planned pathway is similar to that planned by a urologist.
Conclusions: The proposed 2-Step hybrid strategy reaches a balance on both optimal effect and efficiency. This automatic planning method based on the long axis section of the kidney can quickly and autonomously provide physicians with a series of optimized puncture paths, and provide auxiliary guidance for clinicians, especially young physicians. Nevertheless, the proposed method shows considerable potential in percutaneous nephrolithotomy surgical demonstration and teaching, and can integrated into robotic surgical navigation system.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.cmpb.2025.108763 | DOI Listing |
F1000Res
September 2025
School of Management, University of Khartoum, Khartoum, Khartoum, Sudan.
Background: At the 2020 UN General Assembly, China pledged to peak carbon emissions before 2030 and achieve carbon neutrality by 2060. However, the traditional social development model has led to increasing carbon emissions annually, highlighting the need to resolve the contradiction between development and carbon reduction. This study examines the relationship between carbon emissions, economy, population, and energy consumption in a specific region to support carbon peak and neutrality goals.
View Article and Find Full Text PDFISA Trans
September 2025
School of Mechatronic Engineering, Jiangsu Normal University, Xuzhou 221116, China. Electronic address:
Multi-arm rock drilling robots frequently encounter challenges in extreme environments, such as tunnels, where they are subjected to high-frequency impact loads, multi-degree-of-freedom motion coupling, and large-range motion control vibrations. First, we propose a collision-free path planning method that combines an improved genetic algorithm (IGA) and an improved artificial potential field method. This method is based on the kinematic model of the rock drilling robot.
View Article and Find Full Text PDFObjectives: Waterpipe smoking is increasingly becoming a public health threat due to its appealing features and misperceptions of its harmful effects. Tools assessing waterpipe addiction are essential for understanding waterpipe smokers' behaviors and designing effective smoking cessation plans. This study aimed to develop and validate the Waterpipe Addiction, Craving, and Anticipation Scale (WACAS) and describe the specific patterns and multidimensional aspects of waterpipe smoking behavior.
View Article and Find Full Text PDFFront Big Data
August 2025
MaiNLP, Center for Information and Language Processing, LMU Munich, Munich, Germany.
Predicting career trajectories is a complex yet impactful task, offering significant benefits for personalized career counseling, recruitment optimization, and workforce planning. However, effective career path prediction (CPP) modeling faces challenges including highly variable career trajectories, free-text resume data, and limited publicly available benchmark datasets. In this study, we present a comprehensive comparative evaluation of CPP models-linear projection, multilayer perceptron (MLP), LSTM, and large language models (LLMs)-across multiple input settings and two recently introduced public datasets.
View Article and Find Full Text PDFMed Phys
September 2025
Department of Radiation Oncology, Mayo Clinic in Florida, Jacksonville, Florida, USA.
Background: Dose-driven continuous scanning (DDCS) enhances the efficiency and precision of proton pencil beam delivery by reducing beam pauses inherent in discrete spot scanning (DSS). However, current DDCS optimization studies using traveling salesman problem (TSP) formulations often rely on fixed beam intensity and computationally expensive interpolation for move spot generation, limiting efficiency and methodological robustness.
Purpose: This study introduces a Break Spot-Guided (BSG) method, combined with two acceleration strategies-dose rate skipping and bounding-to optimize beam intensity while minimizing beam delivery time (BDT).