We present a case of locally advanced pancreatic cancer with duodenal invasion treated with consolidative chemoradiation, where extensive unpredictable interfraction motion was observed. Initially, two attempts were made to treat with volumetric modulated arc therapy technique. However, due to substantial interfractional motion of the pancreatic head mass relative to the regional nodal areas, the patient was eventually replanned and treated with a four-field box technique. This case highlights the difficulty in delivering conformal radiation to the pancreas and quantifies the movement of the target, the adjacent biliary stent, and regional nodes.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6721882 | PMC |
| http://dx.doi.org/10.7759/cureus.5047 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
An Enigmatic Wild Passerine Mortality Event in the Eastern United States.
Vet Sci
January 2025
Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.
The ability to rapidly respond to wildlife health events is essential. However, such events are often unpredictable, especially with anthropogenic disturbances and climate-related environmental changes driving unforeseen threats. Many events also are short-lived and go undocumented, making it difficult to draw on lessons learned from past investigations.
View Article and Find Full Text PDFHuman-Inspired Gait and Jumping Motion Generation for Bipedal Robots Using Model Predictive Control.
Biomimetics (Basel)
January 2025
Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu 808-0135, Japan.
In recent years, humanoid robot technology has been developing rapidly due to the need for robots to collaborate with humans or replace them in various tasks, requiring them to operate in complex human environments and placing high demands on their mobility. Developing humanoid robots with human-like walking and hopping abilities has become a key research focus, as these capabilities enable robots to move and perform tasks more efficiently in diverse and unpredictable environments, with significant applications in daily life, industrial operations, and disaster rescue. Currently, methods based on hybrid zero dynamics and reinforcement learning have been employed to enhance the walking and hopping capabilities of humanoid robots; however, model predictive control (MPC) presents two significant advantages: it can adapt to more complex task requirements and environmental conditions, and it allows for various walking and hopping patterns without extensive training and redesign.
View Article and Find Full Text PDFAnalysis of Autonomous Penetration Testing Through Reinforcement Learning and Recommender Systems.
Sensors (Basel)
January 2025
Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor José García Santesmases, 9, Ciudad Universitaria, 28040 Madrid, Spain.
Conducting penetration testing (pentesting) in cybersecurity is a crucial turning point for identifying vulnerabilities within the framework of Information Technology (IT), where real malicious offensive behavior is simulated to identify potential weaknesses and strengthen preventive controls. Given the complexity of the tests, time constraints, and the specialized level of expertise required for pentesting, analysis and exploitation tools are commonly used. Although useful, these tools often introduce uncertainty in findings, resulting in high rates of false positives.
View Article and Find Full Text PDFQuantum machine learning for Lyapunov-stabilized computation offloading in next-generation MEC networks.
Sci Rep
January 2025
Purwanchal Campus Institute of Engineering, Tribhuvan University, Kirtipur, Nepal.
Quantum computing and machine learning convergence enable powerful new approaches for optimizing mobile edge computing (MEC) networks. This paper uses Lyapunov optimization theory to propose a novel quantum machine learning framework for stabilizing computation offloading in next-generation MEC systems. Our approach leverages hybrid quantum-classical neural networks to learn optimal offloading policies that maximize network performance while ensuring the stability of data queues, even under dynamic and unpredictable network conditions.
View Article and Find Full Text PDFEpithelioid hemangioendothelioma prognosis and outcome: report of two challenging cases.
J Cardiothorac Surg
December 2024
Thoracic and Vascular Surgery Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Background: Epithelioid hemangioendothelioma (EHE) is an uncommon vascular malignancy characterized by an unpredictable clinical course and a high potential for recurrence and metastasis. The lack of standard treatment guidelines, coupled with the tumor's inconsistent response to available treatments, complicates the management of EHE and leads to widely varying patient prognoses.
Case Presentation: We report two cases of EHE with distinct presentations reflecting the site of involvement.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!