Evidence map›Paper›PMID 34669975›Full record

ArticleMedical physics2021

Validation of a deterministic linear Boltzmann transport equation solver for rapid CT dose computation using physical dose measurements in pediatric phantoms.

Sara Principi, Yonggang Lu, Yu Liu, Adam Wang, Alex Maslowski, Todd Wareing, John Van Heteren, Taly Gilat Schmidt

Open access · greenAbstract read
In one paragraph

Article in Medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Monte Carlo methods for medical imaging research.Biomedical engineering letters · 2024
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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

8 authors at 4 institutions in 1 country.

Sara PrincipiDepartment of Biomedical Engineering, Medical College of Wisconsin and Marquette University, Milwaukee, Wisconsin, USA.
Yonggang LuDepartment of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Yu LiuDepartment of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Adam WangDepartment of Radiology, Stanford University, Stanford, California, USA.
Alex MaslowskiVarian Medical Systems, Palo Alto, California, USA.
Todd WareingVarian Medical Systems, Palo Alto, California, USA.
John Van HeterenVarian Medical Systems, Palo Alto, California, USA.
Taly Gilat SchmidtDepartment of Biomedical Engineering, Medical College of Wisconsin and Marquette University, Milwaukee, Wisconsin, USA.
Medical College of Wisconsin · USVarian Medical Systems (United States) · USMarquette University · USStanford University · US

Funding

Software tool for routine, rapid, patient-specific CT organ dose estimationU01EB023822 · NIBIB · MARQUETTE UNIVERSITY · PI SCHMIDT, TALY GILAT, VAN HETEREN, JOHN · 2017 to 2020
$2.1M
NIBIB NIH HHS U01 EB023822
6 · The paper itself

Abstract

purposeThe risk of inducing cancer to patients undergoing CT examinations has motivated efforts for CT dose estimation, monitoring, and reduction, especially among pediatric population. The method investigated in this study is Acuros CTD (Varian Medical Systems, Palo Alto, CA), a deterministic linear Boltzmann transport equation (LBTE) solver aimed at generating rapid and reliable dose maps of CT exams. By applying organ contours, organ doses can also be obtained, thus patient-specific organ dose estimates can be provided. This study experimentally validated Acuros against measurements performed on a clinical CT system using a range of physical pediatric anthropomorphic phantoms and acquisition protocols.

methodsThe study consisted of (1) the acquisition of dose measurements on a clinical CT scanner through thermoluminescent dosimeters (TLDs), and (2) the modeling in the Acuros platform of the measurement set up, which includes the modeling of the CT scanner and of the anthropomorphic phantoms. For the measurements, 1-year-old, 5-year-old, and 10-year-old anthropomorphic phantoms of the CIRS ATOM family were used. TLDs were placed in selected organ locations such as stomach, liver, lungs, and heart. The pediatric phantoms were scanned helically with the GE Discovery 750 HD clinical scanner for several examination protocols. For the simulations in Acuros, scanner-specific input, such as bowtie filters, overrange collimation, and tube current modulation schemes, were modeled. These scanner complexities were implemented by defining discretized X-ray beams whose spectral distribution, defined in Acuros by only six energy bins, varied across fan angle, cone angle, and slice position. The images generated during the CT acquisitions were used to create the geometrical models, by applying thresholding algorithms and assigning materials to the HU values. The TLDs were contoured in the phantom models as sensitive cylindrical volumes at the locations selected for dosimeters placement, to provide dose estimates, in terms of dose per unit photon. To compare measured doses with dose estimates, a calibration factor was derived from the CTDI

resultsThe differences of the measured and estimated doses, in terms of absolute % errors, were within 13% for 153 TLD locations, with an error of 17% at the stomach for one study with the 10-year-old phantom. Root-mean-squared-errors (RMSE) across all TLD locations for all configurations were in the range of 3%-8%, with Acuros providing dose estimates in a time range of a few seconds up to 2 min.

conclusionsAn overall good agreement between measurements and simulations was achieved, with average RMSE of 6% across all cases. The results demonstrate that Acuros can model a specific clinical scanner despite the required discretization in spatial and energy domains. The proposed deterministic tool has the potential to be part of a near real-time individualized dosimetry monitoring system for CT applications, providing patient-specific organ dose estimates.

Indexed as

RadiometryTomography, X-Ray ComputedChildChild, PreschoolHumansInfantMonte Carlo MethodPhantoms, ImagingPhotonsRadiation DosageCT organ dosedeterministic solverthermoluminescent dosimetry

Identifiers

PMID34669975
PMCPMC8919397
OpenAlexW3207518415

What OpenQuestion holds

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Registered trials

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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.