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

Monte Carlo simulations for configuring and testing an analytical proton dose-calculation algorithm.

Wayne Newhauser1, Jonas Fontenot, Yuanshui Zheng

  • 1Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA. wnewhaus@mdanderson.org

Physics in Medicine and Biology
|July 20, 2007
PubMed
Summary
This summary is machine-generated.

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

DNA damage complexity as a predictor of cell survival: a microscopic Monte Carlo-based modeling framework for photon, proton and carbon ion irradiation.

Physics in medicine and biology·2026
Same author

Musculoskeletal and Marrow Sparing With Proton FLASH Radiation Therapy in Juvenile Mice.

International journal of radiation oncology, biology, physics·2026
Same author

Long-Term Outcomes After Proton Therapy Versus Intensity Modulated Photon Radiation Therapy With Concurrent Chemotherapy for Locally Advanced Non-Small Cell Lung Cancer: Post Hoc Analysis of a Prospective Randomized Trial.

International journal of radiation oncology, biology, physics·2026
Same author

FLASH Radiotherapy Mitigates Radiation-Induced Lymphopenia and Prevents Immunosuppression via Chk1-STAT3 Axis Modulation in a Preclinical Thoracic Irradiation Model.

International journal of radiation oncology, biology, physics·2026
Same author

Radiobiology of Particle Therapy: Revisiting the Preclinical Knowledge Base on Helium Ion Therapy.

Cancer journal (Sudbury, Mass.)·2026
Same author

Pretreatment Risk Model for Radiation-Induced Lymphopenia Is Associated With Adjuvant Durvalumab Efficacy in Patients With Unresectable Stage III NSCLC.

International journal of radiation oncology, biology, physics·2026
Same journal

Deep learning-based dose prediction to enhance planning efficiency in cervical brachytherapy with hybrid applicators.

Physics in medicine and biology·2026
Same journal

Corrigendum: Referenceless MR thermometry-a comparison of five methods (2017<i>Phys. Med. Biol</i>.<b>62</b>1-16).

Physics in medicine and biology·2026
Same journal

Corrigendum: Measured and Monte Carlo simulated electron backscatter to the monitor chamber for the varian TrueBeam linac (2016<i>Phys. Med. Biol</i>.<b>61</b>8779).

Physics in medicine and biology·2026
Same journal

Corrigendum: 3D range-modulator for scanned particle therapy: development, Monte Carlo simulations and experimental evaluation (2017<i>Phys. Med. Biol</i>.<b>62</b>7075).

Physics in medicine and biology·2026
Same journal

Recent progress in applications of computing to radiotherapy (ICCR 2016).

Physics in medicine and biology·2026
Same journal

Novel TMS coils designed using an inverse boundary element method.

Physics in medicine and biology·2026
See all related articles

This study demonstrates Monte Carlo simulations can configure proton radiotherapy planning systems before beam data is measured. This approach significantly reduces the time needed to prepare systems for patient treatment.

Area of Science:

  • Medical Physics
  • Radiotherapy
  • Computational Modeling

Background:

  • Proton radiotherapy treatment planning relies on analytical pencil-beam algorithms.
  • These algorithms require extensive beam data for accurate dose distribution prediction.
  • Preparing new systems is time-consuming due to the need for measured beam data.

Purpose of the Study:

  • To develop a Monte Carlo simulation model for a passively scattered proton therapy unit.
  • To simulate proton beam properties for configuring analytical treatment planning systems.
  • To validate simulated data against measured data for clinical readiness.

Main Methods:

  • Developed a Monte Carlo model of a passively scattered proton therapy unit.
  • Simulated proton field properties using the Monte Carlo technique.

Related Experiment Videos

  • Configured an analytical treatment planning system with simulated beam data.
  • Validated predictions against Monte Carlo simulations using realistic treatment beams.

    • Main Results:

    • Monte Carlo simulations successfully configured an analytical treatment planning system.
    • Dose distributions in a water phantom showed small differences and acceptable agreement.
    • Simulations took approximately 6 weeks using a parallel processing cluster for 768 beam profiles.

    Conclusions:

    • It is feasible to configure and test proton radiotherapy planning systems before measured beam data is available.
    • The Monte Carlo modeling approach can reduce system preparation time by several months.
    • This method accelerates the clinical implementation of proton therapy.