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 Concept Videos

Dose Size and Dosing Frequency: Determination Methods01:21

Dose Size and Dosing Frequency: Determination Methods

437
Determining the optimal dose size and dosing frequency in pharmacotherapy is crucial for achieving therapeutic effectiveness while minimizing adverse effects. This article explores the methodologies employed in determining these parameters, focusing on their significance and interplay to tailor dosing regimens.Dose Size: Dose size refers to the amount of a drug administered in a single dose. It is determined based on the drug's pharmacodynamics and pharmacokinetics properties and...
437
Determination of Multiple Dosing Parameters: Loading and Maintenance Doses01:25

Determination of Multiple Dosing Parameters: Loading and Maintenance Doses

301
A loading dose is an essential pharmacological strategy to rapidly achieve the target plasma drug concentration necessary for an immediate therapeutic effect. This approach is especially critical for drugs characterized by slow absorption or extended half-lives, where delaying therapeutic plasma levels could compromise treatment outcomes. By administering a loading dose, clinicians ensure a prompt onset of drug action, even for agents with complex pharmacokinetic profiles.Achieving steady-state...
301

You might also read

Related Articles

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

Sort by
Same author

TU-G-BRB-02: A New Mathematical Framework for IMRT Inverse Planning with Voxel-Dependent Optimization Parameters.

Medical physics·2017
Same author

WE-G-BRCD-01: A Procedure for Efficient Large-Scale Retrospective Clinical Studies for Online Adaptive Radiotherapy.

Medical physics·2017
Same author

WE-G-BRCD-07: IMRT Re-Planning by Adjusting Voxel-Based Weighting Factors for Adaptive Radiotherapy.

Medical physics·2017
Same author

Schwannomas of female genitalia from a gynaecologist's perspective: report of two cases and review of the literature.

European journal of gynaecological oncology·2016
Same author

MMP-9 genetic polymorphism may confer susceptibility to COPD.

Genetics and molecular research : GMR·2016
Same author

Functional porous composites by blending with solution-processable molecular pores.

Chemical communications (Cambridge, England)·2016

Related Experiment Video

Updated: Mar 2, 2026

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
08:34

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

Published on: February 6, 2019

21.2K

SU-E-T-503: IMRT Optimization Using Monte Carlo Dose Engine: The Effect of Statistical Uncertainty.

Z Tian1, X Jia1, Y Graves1

  • 1University of California, San Deigo, La Jolla, CA.

Medical Physics
|May 19, 2017
PubMed
Summary

Statistical errors in dose-deposition coefficients (DDC) from Monte Carlo (MC) simulations have minimal impact on intensity-modulated radiation therapy (IMRT) optimization. This allows for faster DDC computation with fewer MC histories, maintaining treatment plan accuracy.

Keywords:
Intensity modulated radiation therapyMatrix theoryMonte Carlo methodsOptimizationPerturbation theoryStatistical analysis

More Related Videos

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
07:57

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Published on: March 24, 2022

3.3K
PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator
10:48

PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator

Published on: December 28, 2017

10.1K

Related Experiment Videos

Last Updated: Mar 2, 2026

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
08:34

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

Published on: February 6, 2019

21.2K
Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
07:57

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Published on: March 24, 2022

3.3K
PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator
10:48

PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator

Published on: December 28, 2017

10.1K

Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Ultra-fast GPU-based Monte Carlo (MC) engines enable realistic computation of dose-deposition coefficients (DDC) for intensity-modulated radiation therapy (IMRT) optimization.
  • Calculating DDC with minimal statistical uncertainty using MC simulations is computationally intensive.

Purpose of the Study:

  • To investigate the impact of statistical errors in MC-computed DDC matrices on IMRT optimization outcomes.
  • To determine if reduced MC simulation time affects the accuracy of IMRT treatment plans.

Main Methods:

  • Simulated MC-computed DDC matrices with varying levels of statistical uncertainty.
  • Employed a penalty-based quadratic optimization model and gradient descent for fluence map optimization.
  • Recalculated dose distributions using noise-free DDC matrices and assessed deviations.
  • Utilized stochastic perturbation theory to estimate statistical errors in dose distributions.

Main Results:

  • Relative errors in final IMRT dose distributions were significantly smaller than errors in the DDC matrix.
  • Decreasing MC histories from 10^8 to 10^6 resulted in similar dose-volume histograms despite a 3.8% error in DDC.
  • Theoretical estimations aligned with simulation results regarding error propagation.

Conclusions:

  • Statistical errors in DDC matrices have a limited effect on the dose domain of IMRT optimization.
  • MC simulations can use a reduced number of histories for DDC computation, saving time without compromising treatment plan accuracy.