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

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...

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...

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for k_a Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...

Multiple Comparison Tests

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...

You might also read

Related Articles

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

Sort by

Same author

Clinical Characteristics and Outcomes of Korean Patients with Lipoid Congenital Adrenal Hyperplasia: An Analysis of Data from the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) Cohort Study.

Endocrinology and metabolism (Seoul, Korea)·2026

Same author

Albiflorin attenuates dexamethasone-induced muscle atrophy by suppressing catabolic signaling and enhancing myogenic differentiation.

Journal of ethnopharmacology·2026

Same author

Stereotactic Body Radiation Therapy for Non-Spine Bone Metastases: A Case-Based Radiosurgery Society Review.

Practical radiation oncology·2026

Same author

Feasibility of autonomous medication delivery robots considering elevator utilization in high-traffic hospital environments.

Digital health·2026

Same author

Familial Occurrence of Type 1 Diabetes Mellitus in Korean Children and Adolescents: A Multicenter Study.

Diabetes & metabolism journal·2026

Same author

Design and implementation of an AAPM volunteer database for advancing global medical physics initiatives.

Journal of applied clinical medical physics·2026

Same journal

Correction to "On the shape of the radiation survival curve in tumor spheroids: The role of oxygen heterogeneity".

Medical physics·2026

Same journal

Multi-view constrained semi-supervised vertebra detection for 3D ultrasound spine volume.

Medical physics·2026

Same journal

Accuracy of quantitative <sup>177</sup>Lu SPECT/CT imaging: A systematic review.

Medical physics·2026

Same journal

Physics-constrained dual-domain network for CBCT reconstruction from orthogonal X-rays in gynecologic radiotherapy.

Medical physics·2026

Same journal

Decomposition-based harmonization for quantitative PET imaging across scanners and radiotracers.

Medical physics·2026

Same journal

Development and evaluation of an in vivo dose-based monitoring system for electron FLASH radiation therapy.

Medical physics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 7, 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

A hierarchical evolutionary algorithm for multiobjective optimization in IMRT.

Clay Holdsworth¹, Minsun Kim, Jay Liao

¹Department of Radiation Oncology, University of Washington Medical Center, Box 356043, Seattle, Washington 98195, USA. choldsw@u.washington.edu

Medical Physics

|October 23, 2010

Summary

This summary is machine-generated.

A new multiobjective evolutionary algorithm (MOEA) efficiently generates optimal intensity modulated radiation therapy (IMRT) plans. This method balances tumor coverage and normal tissue sparing, improving treatment outcomes.

Related Experiment Videos

Last Updated: Jun 7, 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

Area of Science:

Radiation Oncology
Medical Physics
Computational Biology

Background:

Current intensity modulated radiation therapy (IMRT) inverse planning struggles to balance competing objectives for tumor and normal tissues.
A need exists for flexible optimization algorithms that explore trade-offs in radiation therapy planning.

Purpose of the Study:

Develop an efficient multiobjective optimization algorithm for IMRT.
Create a flexible algorithm capable of handling diverse objective functions.
Generate a set of Pareto optimal plans reflecting optimal trade-offs.

Main Methods:

A hierarchical evolutionary multiobjective algorithm (MOEA) was developed.
The algorithm integrates a MOEA with an accelerated deterministic IMRT optimization.
Clinical criteria and Pareto optimality guide plan selection, using domination advantage for diversity.

Main Results:

The MOEA generated plan populations closer to the Pareto front compared to standard genetic algorithms.
Statistically significant improvement: MOEA plans dominated standard plans with 11.3% probability.
Clinically acceptable, diverse plans approximating the Pareto front were generated rapidly (under 1 hour).

Conclusions:

The MOEA effectively produces diverse Pareto optimal IMRT plans meeting dosimetric criteria.
The algorithm offers a feasible solution for complex treatment planning.
Future work includes integrating the algorithm with decision support tools for patient-specific plan selection.