Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Optimizer convergence and local minima errors and their clinical importance.

Robert Jeraj1, Chuan Wu, Thomas R Mackie

  • 1Department of Medical Physics, University of Wisconsin-Madison, 1530 MSC, 1300 University Ave., Madison, WI 53706, USA. rjeraj@wisc.edu

Physics in Medicine and Biology
|October 1, 2003
PubMed
Summary

Optimizer convergence errors are small in inverse treatment planning, suggesting relaxed stopping criteria for faster optimization. However, local minima errors significantly impact tumor control and complication probabilities, highlighting their clinical importance.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

DeepER-Med: Advancing Deep Evidence-Based Research in Medicine Through Agentic AI.

ArXiv·2026
Same author

Toward Practical Solid-State Lithium Batteries With High-Nickel Cathodes: An Interface-Centered Perspective.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Illustration of transfer learning from breast cancer detection to risk prediction: adaptation to local data and local objectives.

Journal of medical imaging (Bellingham, Wash.)·2026
Same author

Generative Artificial Intelligence and Large Language Models in Clinical Oncology.

MedComm·2026
Same author

Investigation on the unsteady aerodynamic coefficients of iced conductors and the applicability of quasi-static assumptions.

Scientific reports·2026
Same author

GPR15-guided CD8<sup>+</sup> T regulatory cells control intestinal inflammation.

Nature·2026

Area of Science:

  • Medical Physics
  • Computational Biology
  • Radiotherapy Optimization

Background:

  • Inverse treatment planning optimization is crucial for radiotherapy.
  • Common errors include optimizer convergence and local minima.
  • These errors can affect treatment efficacy and patient safety.

Purpose of the Study:

  • To investigate the magnitude and clinical significance of optimizer convergence and local minima errors in inverse treatment planning.
  • To compare the impact of these errors on tumor control probability (TCP) and normal tissue complication probability (NTCP).

Main Methods:

  • Evaluated optimizer convergence and local minima errors in inverse treatment planning.
  • Compared two distinct optimizers: simulated annealing (stochastic) and gradient method (deterministic).

Related Experiment Videos

  • Assessed clinical significance using TCP and NTCP metrics on a clinical example.

    • Main Results:

    • Optimizer convergence errors were found to be small, especially compared to dose calculation errors.
    • Local minima errors were also relatively small, comparable to dose calculation convergence errors.
    • Local minima errors significantly altered TCP/NTCP values (up to a factor of 2), indicating clinical relevance.

    Conclusions:

    • Optimizer convergence errors are generally minor in typical inverse treatment planning, allowing for potentially relaxed stopping criteria to improve speed.
    • Local minima errors, while often small in magnitude, can have substantial clinical implications on treatment outcomes (TCP/NTCP).
    • Further research into mitigating local minima errors is warranted for robust and clinically reliable radiotherapy optimization.