Reference dataset for benchmarking fetal doses derived from Monte Carlo simulations of CT exams.


Journal

Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746

Informations de publication

Date de publication:
Jan 2021
Historique:
received: 03 04 2020
revised: 26 07 2020
accepted: 06 10 2020
pubmed: 1 11 2020
medline: 15 5 2021
entrez: 31 10 2020
Statut: ppublish

Résumé

Task Group Report 195 of the American Association of Physicists in Medicine contains reference datasets for the direct comparison of results among different Monte Carlo (MC) simulation tools for various aspects of imaging research that employs ionizing radiation. While useful for comparing and validating MC codes, that effort did not provide the information needed to compare absolute dose estimates from CT exams. Therefore, the purpose of this work is to extend those efforts by providing a reference dataset for benchmarking fetal dose derived from MC simulations of clinical CT exams. The reference dataset contains the four necessary elements for validating MC engines for CT dosimetry: (a) physical characteristics of the CT scanner, (b) patient information, (c) exam specifications, and (d) fetal dose results from previously validated and published MC simulations methods in tabular form. Scanner characteristics include non-proprietary descriptions of equivalent source cumulative distribution function (CDF) spectra and bowtie filtration profiles, as well as scanner geometry information. Additionally, for the MCNPX MC engine, normalization factors are provided to convert raw simulation results to absolute dose in mGy. The patient information is based on a set of publicly available fetal dose models and includes de-identified image data; voxelized MC input files with fetus, uterus, and gestational sac identified; and patient size metrics in the form of water equivalent diameter (D Equivalent source CDFs and bowtie filtration profiles are available in text files. Image data are available in DICOM format. Voxelized models are represented by a header followed by a list of integers in a text file representing a three-dimensional model of the patient. Size distribution metrics are also given in text files. Results of absolute and normalized fetal dose with associated MC error estimates are presented in tabular form in an Excel spreadsheet. All data are stored on Zenodo and are publicly accessible using the following link: https://zenodo.org/record/3959512. Similar to the work of AAPM Report 195, this work provides a set of reference data for benchmarking fetal dose estimates from clinical CT exams. This provides researchers with an opportunity to compare MC simulation results to a set of published reference data as part of their efforts to validate absolute and normalized fetal dose estimates. This could also be used as a basis for comparison to other non-MC approaches, such as deterministic approaches, or to commercial packages that provide estimates of fetal doses from clinical CT exams.

Identifiants

pubmed: 33128259
doi: 10.1002/mp.14573
pmc: PMC7902432
mid: NIHMS1642630
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

523-532

Subventions

Organisme : NIBIB NIH HHS
ID : T32 EB002101
Pays : United States
Organisme : NIBIB NIH HHS
ID : T32-EB002101
Pays : United States

Informations de copyright

© 2020 American Association of Physicists in Medicine.

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Auteurs

Anthony J Hardy (AJ)

Livermore National Laboratory, Materials Engineering Division/Non-destructive Evaluation Group, Livermore, CA, 94550, USA.

Maryam Bostani (M)

Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, Livermore, CA, 90024, USA.
Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, CA, 90024, USA.

Erin Angel (E)

Canon Medical Systems USA, Inc, Tustin, CA, 92780, USA.

Chris Cagnon (C)

Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, Livermore, CA, 90024, USA.
Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, CA, 90024, USA.

Ioannis Sechopoulos (I)

Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein 10, Nijmegen, 6525 GA, The Netherlands.
Dutch Expert Center for Screening (LRCB), Wijchenseweg 101, Nijmegen, 6538 SW, The Netherlands.

Michael F McNitt-Gray (MF)

Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, Livermore, CA, 90024, USA.
Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, CA, 90024, USA.

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