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Dose coefficients for organ dosimetry in tomosynthesis imaging of adults and pediatrics across diverse protocols.
Abstract
<h4>Purpose</h4>The gold-standard method for estimation of patient-specific organ
doses in digital tomosynthesis (DT) requires protocol-specific Monte Carlo (MC) simulations
of radiation transport in anatomically accurate computational phantoms. Although accurate,
MC simulations are computationally expensive, leading to a turnaround time in the
order of core hours for simulating a single exam. This limits their clinical utility.
The purpose of this study is to overcome this limitation by utilizing patient- and
protocol-specific MC simulations to develop a comprehensive database of air-kerma-normalized
organ dose coefficients for a virtual population of adult and pediatric patient models
over an expanded set of exam protocols in DT for retrospective and prospective estimation
of radiation dose in clinical tomosynthesis.<h4>Materials and methods</h4>A clinically
representative virtual population of 14 patient models was used, with pediatric models
(M and F) at ages 1, 5, 10, and 15 and adult patient models (M and F) with BMIs at
10th , 50th , and 90th percentiles of the US population. A GPU-based MC simulation framework was used to
simulate organ doses in the patient models, incorporating the scanner-specific configuration
of a clinical DT system (VolumeRad, GE Healthcare, Waukesha, WI) and an expanded set
of exam protocols including 21 distinct acquisition techniques for imaging a variety
of anatomical regions (head and neck, thorax, spine, abdomen, and knee). Organ dose
coefficients (hn ) were estimated by normalizing organ dose estimates to air kerma at 70 cm (X70cm ) from the source in the scout view. The corresponding coefficients for projection
radiography were approximated using organ doses estimated for the scout view. The
organ dose coefficients were further used to compute air-kerma-normalized patient-specific
effective dose coefficients (Kn ) for all combinations of patients and protocols, and a comparative analysis examining
the variation of radiation burden across sex, age, and exam protocols in DT, and with
projection radiography was performed.<h4>Results</h4>The database of organ dose coefficients
(hn ) containing 294 distinct combinations of patients and exam protocols was developed
and made publicly available. The values of Kn were observed to produce estimates of effective dose in agreement with prior studies
and consistent with magnitudes expected for pediatric and adult patients across the
different exam protocols, with head and neck regions exhibiting relatively lower and
thorax and C-spine (apsc, apcs) regions relatively higher magnitudes. The ratios (r
= Kn /Kn,rad ) quantifying the differences air-kerma-normalized patient-specific effective doses
between DT and projection radiography were centered around 1.0 for all exam protocols,
with the exception of protocols covering the knee region (pawk, patk).<h4>Conclusions</h4>This
study developed a database of organ dose coefficients for a virtual population of
14 adult and pediatric XCAT patient models over a set of 21 exam protocols in DT.
Using empirical measurements of air kerma in the clinic, these organ dose coefficients
enable practical retrospective and prospective patient-specific radiation dosimetry.
The computation of air-kerma-normalized patient-specific effective doses further enable
the comparison of radiation burden to the patient populations between protocols and
between imaging modalities (e.g., DT and projection radiography), as presented in
this study. This article is protected by copyright. All rights reserved.
Type
Journal articlePermalink
https://hdl.handle.net/10161/25118Published Version (Please cite this version)
10.1002/mp.15798Publication Info
Sharma, Shobhit; Kapadia, Anuj; Ria, Francesco; Segars, W Paul; & Samei, Ehsan (2022). Dose coefficients for organ dosimetry in tomosynthesis imaging of adults and pediatrics
across diverse protocols. Medical physics. 10.1002/mp.15798. Retrieved from https://hdl.handle.net/10161/25118.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Anuj J Kapadia
Adjunct Associate Professor in the Department of Radiology
My research focuses on developing an innovative imaging modality - Neutron Stimulated
Emission Computed Tomography (NSECT), that uses inelastic scattering through fast
neutrons to generate tomographic images of the body's element composition. Such information
is vital in diagnosing a variety of disorders ranging from iron and copper overload
in the liver to several cancers. Specifically, there are two ongoing projects: 1)
Experimental Implementation of NSECT Neutron sp
Francesco Ria
Assistant Professor of Radiology
Dr. Francesco Ria is a medical physicist and he serves as an Assistant Professor in
the Department of Radiology. Francesco has an extensive expertise in the assessment
of procedure performances in radiology. In particular, his research activities focus
on the simultaneous evaluation of radiation dose and image quality in vivo in computed
tomography providing a comprehensive evaluation of radiological exams. Moreover, Francesco
is developing and investigating novel mathematical models t
Ehsan Samei
Reed and Martha Rice Distinguished Professor of Radiology
Dr. Ehsan Samei, PhD, DABR, FAAPM, FSPIE, FAIMBE, FIOMP, FACR is a Persian-American
medical physicist. He is a tenured Professor of Radiology, Medical Physics, Biomedical
Engineering, Physics, and Electrical and Computer Engineering at Duke University,
where he also serves as the Chief Imaging Physicist for Duke University Health System,
the director of the Carl E Ravin Advanced Imaging Laboratories, and the director of
Center for Virtual Imaging Trials. He is certi
William Paul Segars
Associate Professor in Radiology
Our current research involves the use of computer-generated phantoms and simulation
techniques to investigate and optimize medical imaging systems and methods. Medical
imaging simulation involves virtual experiments carried out entirely on the computer
using computational models for the patients as well as the imaging devices. Simulation
is a powerful tool for characterizing, evaluating, and optimizing medical imaging
systems. A vital aspect of simulation is to have realistic models of the subje
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