Abstract
Purpose: 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. Materials and methods: 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 body mass index (BMIs) at 10th, 50th, and 90th percentiles of the US population. A graphics processing unit (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, USA) 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. Results: 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). Conclusions: 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 enables 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.
Original language | English |
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Pages (from-to) | 5439-5450 |
Number of pages | 12 |
Journal | Medical Physics |
Volume | 49 |
Issue number | 8 |
DOIs | |
State | Published - Aug 2022 |
Externally published | Yes |
Funding
The authors are grateful to Justin Brown, Elliott Stepusin, and Wesley Bolch at the Advanced Laboratory for Radiation Dosimetry Studies (ALRADS) at the University of Florida (UF), whose technical assistance and scientific critique were crucial for developing the simulation framework used for conducting the dose simulations for this study. The authors are also grateful to John Sabol at GE Healthcare for assisting the scanner-specific modeling of the VolumeRAD system used in this study. The research reported in this document was supported by the National Institutes of Health under award numbers R01EB001838 and 1P41EB028744. The authors also gratefully acknowledge the support of NVIDIA Corporation with the donation of the GeForce GTX Titan X GPU used for conducting simulations discussed in this study.
Keywords
- Monte Carlo
- Task Group 321
- XCAT
- patient specific
- radiation dosimetry and risk
- tomosynthesis