Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Methods of Medium Optimization

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...

Optimization Problems

Optimization Problems

Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...

Application of Nonlinear Inequalities

Application of Nonlinear Inequalities

A nonlinear inequality describes a comparison involving an expression that curves or behaves more complexly than a straight line. These inequalities often appear in forms that include squares, products, or variables in the denominator.To solve such an inequality, one starts by rewriting it so that zero appears on one side. For example, the inequality: can be factored as: This form makes it easier to identify the values that cause the expression to equal zero. In this case, the key values are 3...

Optimal Foraging

Optimal Foraging

How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.

Mathematical Modeling: Problem Solving

Mathematical Modeling: Problem Solving

Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Application of a model-based water-equivalent EPID image conversion algorithm for linac beam QA.

Journal of applied clinical medical physics·2025

Same author

Every Other Day or Once a Week: Long-term Oncological Outcomes in the Phase 2 PATRIOT Trial of Prostate Stereotactic Ablative Body Radiotherapy.

European urology oncology·2025

Same author

Predicting brain tumour growth patterns using a novel MRI-based tumour spread map: application to radiotherapy planning.

Medical physics·2025

Same author

Long-term performance monitoring of a-Si 1200 electronic portal imaging device for dosimetric applications.

Journal of applied clinical medical physics·2024

Same author

Endobronchially Implanted Real-Time Electromagnetic Transponder Beacon-Guided, Respiratory-Gated SABR for Moving Lung Tumors: A Prospective Phase 1/2 Cohort Study.

Advances in radiation oncology·2023

Same author

Pan-Canadian consensus recommendations for proton beam therapy access in Canada.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2022

Search research articles

Related Experiment Video

Updated: May 28, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

PARETO: A novel evolutionary optimization approach to multiobjective IMRT planning.

Jason Fiege¹, Boyd McCurdy, Peter Potrebko

¹Department of Physics and Astronomy, University of Manitoba, Winnipeg, Manitoba, Canada. fiege@physics.unimanitoba.ca

Medical Physics

|October 8, 2011

Summary

This summary is machine-generated.

This study introduces pareto, an evolutionary optimization tool for intensity-modulated radiation therapy (IMRT) treatment planning. It efficiently generates numerous treatment options, balancing target coverage and organ sparing for improved patient care.

More Related Videos

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Published on: February 6, 2019

Related Experiment Videos

Last Updated: May 28, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies

Published on: February 6, 2019

Area of Science:

Radiation Oncology
Medical Physics
Computational Biology

Background:

Radiation therapy treatment planning faces conflicting objectives: maximizing dose to the planning target volume (PTV) and minimizing dose to organs-at-risk (OARs).
Current methods often require compromises, potentially impacting treatment efficacy and patient safety.

Purpose of the Study:

Introduce Pareto-Aware Radiotherapy Evolutionary Treatment Optimization (pareto), a novel multiobjective optimization tool.
Optimize beam angles and fluence patterns for intensity-modulated radiation therapy (IMRT) treatment planning.

Main Methods:

Utilize a multiobjective genetic algorithm (GA) to treat IMRT plan optimization as a monolithic problem.
Employ parameterized beam fluence representation and realistic dose calculations, including scatter effects.
Validate the approach on cylindrical and patient-specific phantoms.

Main Results:

Generate a database of Pareto nondominated solutions, representing trade-offs between PTV and OAR objectives.
Achieve conformal PTV doses and reduced OAR doses using conformity, DVH, or EUD-based fitness functions.
Demonstrate effective hotspot elimination and potential for optimizing beam count.

Conclusions:

The pareto software tool shows feasibility for IMRT treatment planning.
Offers advantages over commercial systems, including automated optimization and a comprehensive set of Pareto-optimal solutions.
Facilitates efficient selection of optimal patient treatment plans through a graphical interface.