Reference dataset for benchmarking fetal doses derived from Monte Carlo simulations of CT exams. Issue 1 (28th November 2020)
- Record Type:
- Journal Article
- Title:
- Reference dataset for benchmarking fetal doses derived from Monte Carlo simulations of CT exams. Issue 1 (28th November 2020)
- Main Title:
- Reference dataset for benchmarking fetal doses derived from Monte Carlo simulations of CT exams
- Authors:
- Hardy, Anthony J.
Bostani, Maryam
Angel, Erin
Cagnon, Chris
Sechopoulos, Ioannis
McNitt‐Gray, Michael F. - Abstract:
- Abstract : Purpose: 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. Acquisition and validation methods: 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 patientAbstract : Purpose: 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. Acquisition and validation methods: 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 ( Dw ) z‐axis distributions from a simulated topogram ( Dw, topo ) and from the image data ( Dw, image ). Exam characteristics include CT scan start and stop angles and table and patient locations, helical pitch, nominal collimation and measured beam width, and gantry rotation time for each simulation. For simulations involving estimating doses from exams using tube current modulation (TCM), a realistic TCM scheme is presented that is estimated based upon a validated method. (d) Absolute and CTDIvol ‐normalized fetal dose results for both TCM and FTC simulations are given for each patient model under each scan scenario. Data format and usage notes: 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 . Potential applications: 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. … (more)
- Is Part Of:
- Medical physics. Volume 48:Issue 1(2021)
- Journal:
- Medical physics
- Issue:
- Volume 48:Issue 1(2021)
- Issue Display:
- Volume 48, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 48
- Issue:
- 1
- Issue Sort Value:
- 2021-0048-0001-0000
- Page Start:
- 523
- Page End:
- 532
- Publication Date:
- 2020-11-28
- Subjects:
- benchmarking -- computed tomography -- fetal dose -- Monte Carlo simulations
Medical physics -- Periodicals
Medical physics
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610.153 - Journal URLs:
- http://scitation.aip.org/content/aapm/journal/medphys ↗
https://aapm.onlinelibrary.wiley.com/journal/24734209 ↗
http://www.aip.org/ ↗ - DOI:
- 10.1002/mp.14573 ↗
- Languages:
- English
- ISSNs:
- 0094-2405
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5531.130000
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- 21694.xml