Evidence map›Paper›PMID 32244240›Full record

ArticlePhysics in medicine and biology2020

A rapid, accurate image simulation strategy for mega-voltage cone-beam computed tomography.

Mengying Shi, Marios Myronakis, Matthew Jacobson, Mathias Lehmann, Dianne Ferguson, Paul Baturin, Pascal Huber, Rony Fueglistaller, Thomas Harris, Ingrid Valencia Lozano and 3 more

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Monte Carlo methods for medical imaging research.Biomedical engineering letters · 2024
    Review
  2. Article
  3. Article
  4. GPU-accelerated Monte Carlo simulation of MV-CBCT.Physics in medicine and biology · 2020
    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

13 authors.

Mengying ShiMedical Physics Program, Department of Physics and Applied Physics, University of Massachusetts Lowell, Lowell, MA, United States of America.
Marios MyronakisBrigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.
Matthew JacobsonBrigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.
Mathias LehmannVarian Medical Systems, Baden, Switzerland.
Dianne FergusonBrigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.
Paul BaturinVarian Medical Systems, Palo Alto, CA, United States of America.
Pascal HuberVarian Medical Systems, Baden, Switzerland.
Rony FueglistallerVarian Medical Systems, Baden, Switzerland.
Thomas HarrisBrigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.
Ingrid Valencia LozanoBrigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.
Christopher WilliamsBrigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.
Daniel MorfVarian Medical Systems, Baden, Switzerland.
Ross I BerbecoBrigham and Women's Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, United States of America.

Funding

A novel flat-panel detector for advanced on-board radiation therapy imagingR01CA188446 · NCI · DANA-FARBER CANCER INST · PI BERBECO, ROSS I., FUEGLISTALLER, RONY · 2014 to 2024
$7.2M
NCI NIH HHS R01 CA188446
6 · The paper itself

Abstract

Intensive computation time is required to simulate images of electronic portal imaging device (EPID) using Monte Carlo (MC) technique, limiting the development of applications associated with EPID, such as mega-voltage cone-beam computed tomography (MV-CBCT). In this study, a fast, accurate simulation strategy for MV-CBCT utilizing the FastEPID technique has been developed and validated. During FastEPID simulation, photon detection was determined by pre-calculated photon energy deposition efficiency (η) and particle transport within the EPID was replaced with a pre-calculated optical photon spread function. This method is capable of reducing the time required for EPID image simulation by a factor of 90-140, without compromising image quality. MV-CBCT images reconstructed from the FastEPID simulated projections have been validated against measurement in terms of mean Hounsfield unit (HU), noise, and cupping artifact. These images were obtained with both a Catphan 604 phantom and an anthropomorphic pelvis phantom, under treatment beam energies of 2.5 MV, 6 MV, and 6 MV flattening filter free. The agreement between measurement and simulation was excellent in all cases. This novel strategy was capable of reducing the run time of a full scan simulation of MV-CBCT performed on a CPU cluster to a matter of hours, rather than weeks or months required by a conventional approach. Multiple applications associated with MV-CBCT (e.g. imager design optimization) are anticipated to gain from the implementation of this novel simulation strategy.

Indexed as

Cone-Beam Computed TomographyAlgorithmsArtifactsHumansImage Processing, Computer-AssistedMonte Carlo MethodPelvisPhantoms, ImagingTime Factors

Identifiers

PMID32244240
PMCPMC9142213

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.