Evidence map›Paper›PMID 35960865›Full record

ArticleMedical physics2022

Virtual particle Monte Carlo: A new concept to avoid simulating secondary particles in proton therapy dose calculation.

Jie Shan, Hongying Feng, Danairis Hernandez Morales, Samir H Patel, William W Wong, Mirek Fatyga, Martin Bues, Steven E Schild, Robert L Foote, Wei Liu

Abstract read
In one paragraph

Article in Medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A Python package for fast GPU-based proton pencil beam dose calculation.Journal of applied clinical medical physics · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jie ShanDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Hongying FengDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Danairis Hernandez MoralesDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Samir H PatelDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
William W WongDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Mirek FatygaDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Martin BuesDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Steven E SchildDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Robert L FooteDepartment of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA.
Wei LiuDepartment of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.

Funding

4D Robust Optimization in Intensity-Modulated Proton TherapyK25CA168984 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIU, WEI · 2012 to 2015
$450k
Arizona Biomedical Research Commission Investigator AwardLawrence W. and Marilyn W. Matteson Fund for Cancer ResearchNational Cancer Institute (NCI) Career Developmental Award K25CA168984NCI NIH HHS K25 CA168984the Kemper Marley Foundation
6 · The paper itself

Abstract

backgroundIn proton therapy dose calculation, Monte Carlo (MC) simulations are superior in accuracy but more time consuming, compared to analytical calculations. Graphic processing units (GPUs) are effective in accelerating MC simulations but may suffer thread divergence and racing condition in GPU threads that degrades the computing performance due to the generation of secondary particles during nuclear reactions. PURPOSE: A novel concept of virtual particle (VP) MC (VPMC) is proposed to avoid simulating secondary particles in GPU-accelerated proton MC dose calculation and take full advantage of the computing power of GPU.

methodsNeutrons and gamma rays were ignored as escaping from the human body; doses of electrons, heavy ions, and nuclear fragments were locally deposited; the tracks of deuterons were converted into tracks of protons. These particles, together with primary and secondary protons, are considered to be the realistic particles. Histories of primary and secondary protons were replaced by histories of multiple VPs. Each VP corresponded to one proton (either primary or secondary). A continuous-slowing-down-approximation model, an ionization model, and a large angle scattering event model corresponding to nuclear interactions were developed for VPs by generating probability distribution functions (PDFs) based on simulation results of realistic particles using MCsquare. For efficient calculations, these PDFs were stored in the Compute Unified Device Architecture textures. VPMC was benchmarked with TOPAS and MCsquare in phantoms and with MCsquare in 13 representative patient geometries. Comparisons between the VPMC calculated dose and dose measured in water during patient-specific quality assurance (PSQA) of the selected 13 patients were also carried out. Gamma analysis was used to compare the doses derived from different methods and calculation efficiencies were also compared.

resultsIntegrated depth dose and lateral dose profiles in both homogeneous and inhomogeneous phantoms all matched well among VPMC, TOPAS, and MCsquare calculations. The 3D-3D gamma passing rates with a criterion of 2%/2 mm and a threshold of 10% was 98.49% between MCsquare and TOPAS and 98.31% between VPMC and TOPAS in homogeneous phantoms, and 99.18% between MCsquare and TOPAS and 98.49% between VPMC and TOPAS in inhomogeneous phantoms, respectively. In patient geometries, the 3D-3D gamma passing rates with 2%/2 mm/10% between dose distributions from VPMC and MCsquare were 98.56 ± 1.09% in patient geometries. The 2D-3D gamma analysis with 3%/2 mm/10% between the VPMC calculated dose distributions and the 2D measured planar dose distributions during PSQA was 98.91 ± 0.88%. VPMC calculation was highly efficient and took 2.84 ± 2.44 s to finish for the selected 13 patients running on four NVIDIA Ampere GPUs in patient geometries.

conclusionVPMC was found to achieve high accuracy and efficiency in proton therapy dose calculation.

Indexed as

Proton TherapyDeuteriumHumansMonte Carlo MethodProtonsWaterDeuteriumProtonsWaterGPU accelerationintensity-modulated proton therapyMonte Carloreal-time adaptive treatment planningsecondary particles

Identifiers

PMID35960865
PMCPMC9588716

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.