Deterministic linear Boltzmann transport equation solver for patient‐specific CT dose estimation: Comparison against a Monte Carlo benchmark for realistic scanner configurations and patient models

Principi, Sara; Wang, Adam; Maslowski, Alexander; Wareing, Todd A.; Jordan, Petr; Schmidt, Taly Gilat

doi:10.1002/mp.14494

Cited by 8 publications

(18 citation statements)

References 30 publications

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“…17 Acuros CTD was previously compared for realistic scanner configurations against the gold standard Monte Carlo method Geant4, 18 for different scanner acquisition parameters and anthropomorphic phantom models. 19 Good agreement was shown between the dose distributions generated by the two algorithms, with differences of the absorbed dose values of approximately 3.5%. Although the scanner model used in our previous comparison study enabled a good approximation of a real scanner, some features were generic and not scanner specific, such as the bowtie filter model and the spectral distribution of the X-ray source.…”

Section: Introductionmentioning

confidence: 70%

“…This effect is implemented in Acuros by discretizing the spectral fluence of the X‐ray beams across the cone angle and is affected by the discretization in view angle. The present study simulated 18 views per rotation, as our previous Acuros benchmarking studies demonstrated that 18 projection views per rotation provided sufficient accuracy even when modeling scanner effects such as TCM and overrange collimation 17,19 . The longitudinal + angular TCM (SmartmA; GE Healthcare) implemented on the GE Discovery 750 HD scanner was modeled by a previously validated custom MATLAB program developed in collaboration with the manufacturer 28 .…”

Section: Methodsmentioning

confidence: 99%

“…The alternative dose map generation method investigated in this study is Acuros CTD (Varian Medical Systems, Palo Alto, CA, USA), a deterministic linear Boltzmann transport equation (LBTE) solver aimed at generating rapid and reliable dose maps for CT applications 17 . Acuros CTD was previously compared for realistic scanner configurations against the gold standard Monte Carlo method Geant4, 18 for different scanner acquisition parameters and anthropomorphic phantom models 19 . Good agreement was shown between the dose distributions generated by the two algorithms, with differences of the absorbed dose values of approximately 3.5%.…”

Section: Introductionmentioning

confidence: 99%

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

Principi

Liu

et al. 2021

Medical Physics

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Purpose The 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. Methods The 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 CTDIvol displayed by the scanner, to account for the number of photons emitted by the X‐ray tube during the procedure. Results The 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. Conclusions An 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...

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Section: Introductionmentioning

confidence: 70%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Principi

Liu

et al. 2021

Medical Physics

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“…This scanner approximation is reasonable for this study, as the focus is on evaluating the error due to organ autosegmentation, while other studies have and are evaluating the error due to scanner modeling. 76 dividing by total mass of the contour. Partially irradiated organs were normalized by the partial organ mass contained in the CT image.…”

Section: 33mentioning

confidence: 99%

Technical note: Evaluation of a V‐Net autosegmentation algorithm for pediatric CT scans: Performance, generalizability, and application to patient‐specific CT dosimetry

et al. 2022

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This study developed and evaluated a fully convolutional network (FCN) for pediatric CT organ segmentation and investigated the generalizability of the FCN across image heterogeneities such as CT scanner model protocols and patient age. We also evaluated the autosegmentation models as part of a software tool for patient-specific CT dose estimation. Methods: A collection of 359 pediatric CT datasets with expert organ contours were used for model development and evaluation. Autosegmentation models were trained for each organ using a modified FCN 3D V-Net. An independent test set of 60 patients was withheld for testing. To evaluate the impact of CT scanner model protocol and patient age heterogeneities, separate models were trained using a subset of scanner model protocols and pediatric age groups. Train and test sets were split to answer questions about the generalizability of pediatric FCN autosegmentation models to unseen age groups and scanner model protocols, as well as the merit of scanner model protocol or age-groupspecific models. Finally, the organ contours resulting from the autosegmentation models were applied to patient-specific dose maps to evaluate the impact of segmentation errors on organ dose estimation. Results: Results demonstrate that the autosegmentation models generalize to CT scanner acquisition and reconstruction methods which were not present in the training dataset. While models are not equally generalizable across age groups, age-group-specific models do not hold any advantage over combining heterogeneous age groups into a single training set. Dice similarity coefficient (DSC) and mean surface distance results are presented for 19 organ structures, for example, median DSC of 0.52 (duodenum), 0.74 (pancreas), 0.92 (stomach), and 0.96 (heart). The FCN models achieve a mean dose error within 5% of expert segmentations for all 19 organs except for the spinal canal, where the mean error was 6.31%. Conclusions: Overall, these results are promising for the adoption of FCN autosegmentation models for pediatric CT, including applications for patientspecific CT dose estimation.

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“…From 2018 to 2020, some publications have been dedicated to developing new software tools for rapidly and accurately estimating scatter in x-ray projection images by solving the deterministic linear Boltzmann transport equation (LBTE) [92,96,100]. These methods use Linear Discontinuous Finite Elements, Multigroup, and Discrete Ordinates methods to maintain the accuracy of a continuous solution.…”

Section: Rq2: Which Are the Most Common Cbct Applications That Use Geant4 Simulations To Estimate The Dose And How Have They Changed Overmentioning

confidence: 99%

Dose Estimation by Geant4-Based Simulations for Cone-Beam CT Applications: A Systematic Review

et al. 2021

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The last two decades have witnessed increasing use of X-ray imaging and, hence, the exposure of humans to potentially harmful ionizing radiation. Computed tomography accounts for the largest portion of medically-related X-ray exposure. Accurate knowledge of ionizing radiation dose from Cone-Beam CT (CBCT) imaging is of great importance to estimate radiation risks and justification of imaging exposures. This work aimed to review the published evidence on CBCT dose estimation by focusing on studies that employ Geant4-based toolkits to estimate radiation dosage. A systematic review based on a scientometrics approach was conducted retrospectively, from January 2021, for a comprehensive overview of the trend, thematic focus, and scientific production in this topic. The search was conducted using WOS, PubMed, and Scopus databases, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In total, 93 unique papers were found, of which only 34 met the inclusion criteria. We opine that the findings of this study provides a basis to develop accurate simulations of CBCT equipment for optimizing the trade-off between clinical benefit and radiation risk.

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Deterministic linear Boltzmann transport equation solver for patient‐specific CT dose estimation: Comparison against a Monte Carlo benchmark for realistic scanner configurations and patient models

Cited by 8 publications

References 30 publications

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

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

Technical note: Evaluation of a V‐Net autosegmentation algorithm for pediatric CT scans: Performance, generalizability, and application to patient‐specific CT dosimetry

Dose Estimation by Geant4-Based Simulations for Cone-Beam CT Applications: A Systematic Review

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