The UF/NCI family of hybrid computational phantoms representing the current US population of male and female children, adolescents, and adults--application to CT dosimetry

Digital phantom versus patient-specific radiation dosimetry in adult routine thorax CT examinations

PURPOSE

The aim of this study was to compare the organ doses assessed through a digital phantom-based and a patient specific-based dosimetric tool in adult routine thorax computed tomography (CT) examinations with reference to physical dose measurements performed in anthropomorphic phantoms.

METHODS

Two Monte Carlo based dose calculation tools were used to assess organ doses in routine adult thorax CT examinations. These were a digital phantom-based dosimetry tool (NCICT, National Cancer Institute, USA) and a patient-specific individualized dosimetry tool (ImpactMC, CT Imaging GmbH, Germany). Digital phantoms and patients were classified in four groups according to their water equivalent diameter (Dw). Normalized to volume computed tomography dose index (CTDIvol), organ dose was assessed for lungs, esophagus, heart, breast, active bone marrow, and skin. Organ doses were compared to measurements performed using thermoluminescent detectors (TLDs) in two physical anthropomorphic phantoms that simulate the average adult individual as a male (Alderson Research Labs, USA) and as a female (ATOM Phantoms, USA).

RESULTS

The average percent difference of NCICT to TLD and ImpactMC to TLD dose measurements across all organs in both sexes was 13% and 6%, respectively. The average ± 1 standard deviation in dose values across all organs with NCICT, ImpactMC, and TLDs was ± 0.06 (mGy/mGy), ± 0.19 (mGy/mGy), and ± 0.13 (mGy/mGy), respectively. Organ doses decreased with increasing Dw in both NCICT and ImpactMC.

CONCLUSION

Organ doses estimated with ImpactMC were in closer agreement to TLDs compared to NCICT. This may be attributed to the inherent property of ImpactMC methodology to generate phantoms that resemble the realistic anatomy of the examined patient as opposed to NCICT methodology that incorporates an anatomical discrepancy between phantoms and patients.

Dose length product to effective dose coefficients in adults

OBJECTIVES

The most accurate method for estimating patient effective dose (a principal metric for tracking patient radiation exposure) from computed tomography (CT) requires time-intensive Monte Carlo simulation. A simpler method multiplies a scalar coefficient by the widely available scanner-reported dose length product (DLP) to estimate effective dose. We developed new adult effective dose coefficients using actual patient scans and assessed their agreement with Monte Carlo simulation.

METHODS

A multicenter sample of 216,906 adult CT scans was prospectively assembled in 2015-2020 from the University of California San Francisco International CT Dose Registry and the University of Florida library of computational phantoms. We generated effective dose coefficients for eight body regions, stratified by patient sex, diameter, and scanner manufacturer. We applied the new coefficients to DLPs to calculate effective doses and assess their correlations with Monte Carlo radiation transport-generated effective dose.

RESULTS

Effective dose coefficients varied by body region and decreased in magnitude with increasing patient diameter. Coefficients were approximately twofold higher for torso scans in smallest compared with largest diameter categories. For example, abdomen and pelvis coefficients decreased from 0.027 to 0.013 mSv/mGy-cm between the 16-20 cm and 41+ cm categories. There were modest but consistent differences by sex and manufacturer. Diameter-based coefficients used to estimate effective dose produced strong correlations with the reference standard (Pearson correlations 0.77-0.86). The reported conversion coefficients differ from previous studies, particularly in neck CT.

CONCLUSIONS

New effective dose coefficients derived from empirical clinical scans can be used to easily estimate effective dose using scanner-reported DLP.

CLINICAL RELEVANCE STATEMENT

Scalar coefficients multiplied by DLP offer a simple approximation to effective dose, a key radiation dose metric. New effective dose coefficients from this study strongly correlate with gold standard, Monte Carlo-generated effective dose, and differ somewhat from previous studies.

KEY POINTS

• Previous effective dose coefficients were derived from theoretical models rather than real patient data. • The new coefficients (from a large registry/phantom library) differ from previous studies. • The new coefficients offer reasonably reliable values for estimating effective dose.

131I dose coefficients for a reference population using age-specific models

Age-specific dose coefficients are required to assess internal exposure to the general public. This study utilizes reference age-specific biokinetic models of iodine to estimate the total number of nuclear disintegrations ã(rS,τ) occurring in source regions (rS) during the commitment time (τ). Age-specific S values are estimated for 35 target regions due to131I present in 22rSusing data from 10 paediatric reference computational phantoms (representing five ages for both sexes) published recently by the International Commission of Radiation Protection (ICRP). Monte Carlo transport simulations are performed in FLUKA code. The estimated ã(rS,τ) and S values are then used to compute the committed tissue equivalent dose HT(τ) for 27 radiosensitive tissues and dose coefficients e(τ) for all five ages due to inhalation and ingestion of131I. The derived ã(rS,τ) values in the thyroid source are observed to increase with age due to the increased retention of iodine in the thyroid. S values are found to decrease with age, mainly due to an increase in target masses. Generally, HT(τ) values are observed to decrease with age, indicating the predominant behaviour of S values over ã(rS,τ). On average, ingestion dose coefficients are 63% higher than for inhalation in all ages. The maximum contribution to dose coefficients is from the thyroid, accounting for 96% in the case of newborns and 98%-99% for all other ages. Furthermore, the estimated e(τ) values for the reference population are observed to be lower than previously published reference values from the ICRP. The estimated S, HT(τ) and e(τ) values can be used to improve estimations of internal doses to organs/whole body for members of the public in cases of131I exposure. The estimated dose coefficients can also be interpolated for other ages to accurately evaluate the doses received by the general public during131I therapy or during a radiological emergency.

The Pediatric Proton and Photon Therapy Comparison Cohort: Study Design for a Multicenter Retrospective Cohort to Investigate Subsequent Cancers After Pediatric Radiation Therapy

Purpose

The physical properties of protons lower doses to surrounding normal tissues compared with photons, potentially reducing acute and long-term adverse effects, including subsequent cancers. The magnitude of benefit is uncertain, however, and currently based largely on modeling studies. Despite the paucity of directly comparative data, the number of proton centers and patients are expanding exponentially. Direct studies of the potential risks and benefits are needed in children, who have the highest risk of radiation-related subsequent cancers. The Pediatric Proton and Photon Therapy Comparison Cohort aims to meet this need.

Methods and Materials

We are developing a record-linkage cohort of 10,000 proton and 10,000 photon therapy patients treated from 2007 to 2022 in the United States and Canada for pediatric central nervous system tumors, sarcomas, Hodgkin lymphoma, or neuroblastoma, the pediatric tumors most frequently treated with protons. Exposure assessment will be based on state-of-the-art dosimetry facilitated by collection of electronic radiation records for all eligible patients. Subsequent cancers and mortality will be ascertained by linkage to state and provincial cancer registries in the United States and Canada, respectively. The primary analysis will examine subsequent cancer risk after proton therapy compared with photon therapy, adjusting for potential confounders and accounting for competing risks.

Results

For the primary aim comparing overall subsequent cancer rates between proton and photon therapy, we estimated that with 10,000 patients in each treatment group there would be 80% power to detect a relative risk of 0.8 assuming a cumulative incidence of subsequent cancers of 2.5% by 15 years after diagnosis. To date, 9 institutions have joined the cohort and initiated data collection; additional centers will be added in the coming year(s).

Conclusions

Our findings will affect clinical practice for pediatric patients with cancer by providing the first large-scale systematic comparison of the risk of subsequent cancers from proton compared with photon therapy.

Cardiac Substructure Radiation Dose and Risk of Late Cardiac Disease in Survivors of Childhood Cancer: A Report From the Childhood Cancer Survivor Study

PURPOSE

Radiation-associated cardiac disease is a major cause of morbidity/mortality among childhood cancer survivors. Radiation dose-response relationships for cardiac substructures and cardiac diseases remain unestablished.

METHODS

Using the 25,481 5-year survivors of childhood cancer treated from 1970 to 1999 in the Childhood Cancer Survivor Study, we evaluated coronary artery disease (CAD), heart failure (HF), valvular disease (VD), and arrhythmia. We reconstructed radiation doses for each survivor to the coronary arteries, chambers, valves, and whole heart. Excess relative rate (ERR) models and piecewise exponential models evaluated dose-response relationships.

RESULTS

The cumulative incidence 35 years from diagnosis was 3.9% (95% CI, 3.4 to 4.3) for CAD, 3.8% (95% CI, 3.4 to 4.2) for HF, 1.2% (95% CI, 1.0 to 1.5) for VD, and 1.4% (95% CI, 1.1 to 1.6) for arrhythmia. A total of 12,288 survivors (48.2%) were exposed to radiotherapy. Quadratic ERR models improved fit compared with linear ERR models for the dose-response relationship between mean whole heart and CAD, HF, and arrhythmia, suggesting a potential threshold dose; however, such departure from linearity was not observed for most cardiac substructure end point dose-response relationships. Mean doses of 5-9.9 Gy to the whole heart did not increase the risk of any cardiac diseases. Mean doses of 5-9.9 Gy to the right coronary artery (rate ratio [RR], 2.6 [95% CI, 1.6 to 4.1]) and left ventricle (RR, 2.2 [95% CI, 1.3 to 3.7]) increased risk of CAD, and to the tricuspid valve (RR, 5.5 [95% CI, 2.0 to 15.1]) and right ventricle (RR, 8.4 [95% CI, 3.7 to 19.0]) increased risk of VD.

CONCLUSION

Among children with cancer, there may be no threshold dose below which radiation to the cardiac substructures does not increase the risk of cardiac diseases. This emphasizes their importance in modern treatment planning.

Associated radiation exposure from medical imaging and excess lifetime risk of developing cancer in pediatric patients with pulmonary hypertension

Pediatric patients with pulmonary hypertension (PH) receive imaging studies that use ionizing radiation (radiation) such as computed tomography (CT) and cardiac catheterization to guide clinical care. Radiation exposure is associated with increased cancer risk. It is unknown how much radiation pediatric PH patients receive. The objective of this study is to quantify radiation received from imaging and compute associated lifetime cancer risks for pediatric patients with PH. Electronic health records between 2012 and 2022 were reviewed and radiation dose data were extracted. Organ doses were estimated using Monte Carlo modeling. Cancer risks for each patient were calculated from accumulated exposures using National Cancer Institute tools. Two hundred and forty-nine patients with PH comprised the study cohort; 97% of patients had pulmonary arterial hypertension, PH due to left heart disease, or PH due to chronic lung disease. Mean age at the time of the first imaging study was 2.5 years (standard deviation [SD] = 4.9 years). Patients underwent a mean of 12 studies per patient per year, SD = 32. Most (90%) exams were done in children <5 years of age. Radiation from CT and cardiac catheterization accounted for 88% of the total radiation dose received. Cumulative mean effective dose was 19 mSv per patient (SD = 30). Radiation dose exposure resulted in a mean increased estimated lifetime cancer risk of 7.6% (90% uncertainty interval 3.0%-14.2%) in females and 2.8% (1.2%-5.3%) in males. Careful consideration for the need of radiation-based imaging studies is warranted, especially in the youngest of children.

Dose length product to effective dose coefficients in children

BACKGROUND

The most accurate method for estimating effective dose (the most widely understood metric for tracking patient radiation exposure) from computed tomography (CT) requires time-intensive Monte Carlo simulation. A simpler method multiplies a scalar coefficient by the widely available scanner-reported dose length product (DLP) to estimate effective dose.

OBJECTIVE

Develop pediatric effective dose coefficients and assess their agreement with Monte Carlo simulation.

MATERIALS AND METHODS

Multicenter, population-based sample of 128,397 pediatric diagnostic CT scans prospectively assembled in 2015-2020 from the University of California San Francisco International CT Dose Registry and the University of Florida library of highly realistic hybrid computational phantoms. We generated effective dose coefficients for seven body regions, stratified by patient age, diameter, and scanner manufacturer. We applied the new coefficients to DLPs to calculate effective doses and assessed their correlations with Monte Carlo radiation transport-generated effective doses.

RESULTS

The reported effective dose coefficients, generally higher than previous studies, varied by body region and decreased in magnitude with increasing age. Coefficients were approximately 4 to 13-fold higher (across body regions) for patients  <1 year old compared with patients 15-21 years old. For example, head CT (54% of scans) dose coefficients decreased from 0.039 to 0.003 mSv/mGy-cm in patients  <1 year old vs. 15-21 years old. There were minimal differences by manufacturer. Using age-based conversion coefficients to estimate effective dose produced moderate to strong correlations with Monte Carlo results (Pearson correlations 0.52-0.80 across body regions).

CONCLUSIONS

New pediatric effective dose coefficients update existing literature and can be used to easily estimate effective dose using scanner-reported DLP.

NCIRF: an organ dose calculator for patients undergoing radiography and fluoroscopy

Background. It is critical to monitor the radiation dose delivered to patients undergoing radiography and fluoroscopy to prevent both acute and potential long-term adverse health effects. Accurate estimation of organ doses is essential to ensuring that radiation dose is maintained As Low As Reasonably Achievable. We developed a graphical user interface-based organ dose calculation tool for pediatric and adult patients undergoing radiography and fluoroscopy examinations.Methods. Our dose calculator follows the four sequential steps. First, the calculator obtains input parameters related to patient age and gender, and x-ray source data. Second, the program creates an input file describing the anatomy and material composition of a phantom, x-ray source, and organ dose scorers for Monte Carlo radiation transport using the user input parameters. Third, a built-in Geant4 module was developed to import the input file and to calculate organ absorbed doses and skeletal fluences through Monte Carlo radiation transport. Lastly, active marrow and endosteum doses are derived from the skeletal fluences and effective dose is calculated from the organ and tissue doses. Following benchmarking with MCNP6, we conducted some benchmarking calculations calculated organ doses for an illustrative cardeiac interventional fluoroscopy and compared the results with those from an existing dose calculator, PCXMC.Results. The graphical user interface-based program was entitled National Cancer Institute dosimetry system for Radiography and Fluoroscopy (NCIRF). Organ doses calculated from NCIRF showed an excellent agreement with those from MCNP6 in the simulation of an illustrative fluoroscopy exam. In the cardiac interventional fluoroscopy exam of the adult male and female phantoms, the lungs received relatively greater doses than any other organs. PCXMC based on stylistic phantoms overall overestimated major organ doses calculated from NCIRF by up to 3.7-fold (active bone marrow).Conclusion. We developed an organ dose calculation tool for pediatric and adult patients undergoing radiography and fluoroscopy examinations. NCIRF could substantially increase the accuracy and efficiency of organ dose estimation in radiography and fluoroscopy exams.

Diagnostic reference level quantities for adult chest and abdomen-pelvis CT examinations: correlation with organ doses

OBJECTIVES

To evaluate correlations between DRL quantities (DRLq) stratified into patient size groups for non-contrast chest and abdomen-pelvis CT examinations in adult patients and the corresponding organ doses.

METHODS

This study presents correlations between DRLq  (CTDI_vol, DLP and SSDE) stratified into patient size ranges and corresponding organ doses shared in four groups: inside, peripheral, distributed and outside. The demographic, technical and dosimetric parameters were used to identify the influence of these quantities in organ doses. A robust statistical method was implemented in order to establish these correlations and its statistical significance.

RESULTS

Median values of the grouped organ doses are presented according to the effective diameter ranges. Organ doses in the regions inside the imaged area are higher than the organ doses in peripheral, distributed and outside regions, excepted to the peripheral doses associated with chest examinations. Different levels of statistical significance between organ doses and the DRLq were presented.

CONCLUSIONS

Correlations between DRLq and target-organ doses associated with clinical practice can support guidance's to the establishment of optimization criteria. SSDE demonstrated to be significant in the evaluation of organ doses is also highlighted. The proposed model allows the design of optimization actions with specific risk-reduction results.

A body-size-dependent series of Chinese adult standing phantoms for radiation dosimetry

Phantoms of different sizes, as indicated by several studies, have a significant impact on the accuracy of dose calculations. Therefore, it is necessary to establish a body-size-dependent series of Chinese standing adult phantoms to improve the accuracy of radiation dosimetry. In this study, the Chinese reference polygon-mesh phantomsCRAM_S/CRAF_Shave been refined and a method for automatically constructing lymph nodes in a mesh phantom has been proposed. Then, based on the refined phantoms, this study has developed 42 anthropometric standing adult computational phantoms, 21 models for each gender, with a height range of 145-185 cm and weight as a function of body mass index corresponding to healthy, overweight and obese. The parameters were extracted from the National Occupational Health Standards (GBZ) document of the People's Republic of China, which covers more than 90% of the Chinese population. For a given body height and mass, phantoms are scaled in proportion to a factor reflecting the change of adipose tissue and the internal organs. The remainder is adjusted manually to match the target parameters. In addition, the constructed body-size-specific phantoms have been implemented in the in-house THUDose Monte Carlo code to calculate the dose coefficients (DCs) for external photon exposures in the antero-posterior, postero-anterior and right lateral geometries. The results showed that organ DCs varied significantly with body size at low energies (<2MeV) and high energies (>8MeV) due to the differences in anatomy. Organ DC differences between a phantom of a given size and a reference phantom vary by up to 40% for the same height and up to 400% for the whole phantom. The influence of body size differences on the DCs demonstrates that the body-size-dependent Chinese adult phantoms hold great promise for a wide range of applications in radiation dosimetry.

Development and validation of a population-based anatomical colorectal model for radiation dosimetry in late effects studies of survivors of childhood cancer

PURPOSE

The purposes of this study were to develop and integrate a colorectal model that incorporates anatomical variations of pediatric patients into the age-scalable MD Anderson Late Effects (MDA-LE) computational phantom, and validate the model for pediatric radiation therapy (RT) dose reconstructions.

METHODS

Colorectal contours were manually derived from whole-body non-contrast computed tomography (CT) scans of 114 pediatric patients (age range: 2.1-21.6 years, 74 males, 40 females). One contour was used for an anatomical template, 103 for training and 10 for testing. Training contours were used to create a colorectal principal component analysis (PCA)-based statistical shape model (SSM) to extract the population's dominant deformations. The SSM was integrated into the MDA-LE phantom. Geometric accuracy was assessed between patient-specific and SSM contours using several overlap metrics. Two alternative colorectal shapes were generated using the first 17 dominant modes of the PCA-based SSM. Dosimetric accuracy was assessed by comparing colorectal doses from test patients' CT-based RT plans (ground truth) with reconstructed doses for the mean and two alternative models in age-matched MDA-LE phantoms.

RESULTS

When using all 103 PCA modes, the mean (min-max) Dice similarity coefficient, distance-to-agreement and Hausdorff distance between the patient-specific and reconstructed contours for the test patients were 0.89 (0.85-0.91), 2.1 mm (1.7-3.0), and 8.6 mm (5.7-14.3), respectively. The average percent difference between reconstructed and ground truth mean and maximum colorectal doses for the mean (alternative 1, 2) model were 6.3% (8.1%, 6.1%) and 4.4% (4.3%, 4.7%), respectively.

CONCLUSIONS

We developed, validated and integrated a colorectal PCA-based SSM into the MDA-LE phantom and demonstrated its dosimetric performance for accurate pediatric RT dose reconstruction.

Variations in size-specific effective dose with patient stature and beam width for kV cone beam CT imaging in radiotherapy

The facilities now available on linear accelerators for external beam radiotherapy enable radiation fields to be conformed to the shapes of tumours with a high level of precision. However, in order for the treatment delivered to take advantage of this, the patient must be positioned on the couch with the same degree of accuracy. Kilovoltage cone beam computed tomography systems are now incorporated into radiotherapy linear accelerators to allow imaging to be performed at the time of treatment, and image-guided radiation therapy is now standard in most radiotherapy departments throughout the world. However, because doses from imaging are much lower than therapy doses, less effort has been put into optimising radiological protection of imaging protocols. Standard imaging protocols supplied by the equipment vendor are often used with little adaptation to the stature of individual patients, and exposure factors and field sizes are frequently larger than necessary. In this study, the impact of using standard protocols for imaging anatomical phantoms of varying size from a library of 193 adult phantoms has been evaluated. Monte Carlo simulations were used to calculate doses for organs and tissues for each phantom, and results combined in terms of size-specific effective dose (SED). Values of SED from pelvic scans ranged from 11 mSv to 22 mSv for male phantoms and 8 mSv to 18 mSv for female phantoms, and for chest scans from 3.8 mSv to 7.6 mSv for male phantoms and 4.6 mSv to 9.5 mSv for female phantoms. Analysis of the results showed that if the same exposure parameters and field sizes are used, a person who is 5 cm shorter will receive a size SED that is 3%-10% greater, while a person who is 10 kg lighter will receive a dose that is 10%-14% greater compared with the average size.

Quantifying cancer risk from exposures to medical imaging in the Risk of Pediatric and Adolescent Cancer Associated with Medical Imaging (RIC) Study: research methods and cohort profile

PURPOSE

The Risk of Pediatric and Adolescent Cancer Associated with Medical Imaging (RIC) Study is quantifying the association between cumulative radiation exposure from fetal and/or childhood medical imaging and subsequent cancer risk. This manuscript describes the study cohorts and research methods.

METHODS

The RIC Study is a longitudinal study of children in two retrospective cohorts from 6 U.S. healthcare systems and from Ontario, Canada over the period 1995-2017. The fetal-exposure cohort includes children whose mothers were enrolled in the healthcare system during their entire pregnancy and followed to age 20. The childhood-exposure cohort includes children born into the system and followed while continuously enrolled. Imaging utilization was determined using administrative data. Computed tomography (CT) parameters were collected to estimate individualized patient organ dosimetry. Organ dose libraries for average exposures were constructed for radiography, fluoroscopy, and angiography, while diagnostic radiopharmaceutical biokinetic models were applied to estimate organ doses received in nuclear medicine procedures. Cancers were ascertained from local and state/provincial cancer registry linkages.

RESULTS

The fetal-exposure cohort includes 3,474,000 children among whom 6,606 cancers (2394 leukemias) were diagnosed over 37,659,582 person-years; 0.5% had in utero exposure to CT, 4.0% radiography, 0.5% fluoroscopy, 0.04% angiography, 0.2% nuclear medicine. The childhood-exposure cohort includes 3,724,632 children in whom 6,358 cancers (2,372 leukemias) were diagnosed over 36,190,027 person-years; 5.9% were exposed to CT, 61.1% radiography, 6.0% fluoroscopy, 0.4% angiography, 1.5% nuclear medicine.

CONCLUSION

The RIC Study is poised to be the largest study addressing risk of childhood and adolescent cancer associated with ionizing radiation from medical imaging, estimated with individualized patient organ dosimetry.

Body region-specific 3D age-scaling functions for scaling whole-body computed tomography anatomy for pediatric late effects studies

Purpose.Radiation epidemiology studies of childhood cancer survivors treated in the pre-computed tomography (CT) era reconstruct the patients' treatment fields on computational phantoms. For such studies, the phantoms are commonly scaled to age at the time of radiotherapy treatment because age is the generally available anthropometric parameter. Several reference size phantoms are used in such studies, but reference size phantoms are only available at discrete ages (e.g.: newborn, 1, 5, 10, 15, and Adult). When such phantoms are used for RT dose reconstructions, the nearest discrete-aged phantom is selected to represent a survivor of a specific age. In this work, we (1) conducted a feasibility study to scale reference size phantoms at discrete ages to various other ages, and (2) evaluated the dosimetric impact of using exact age-scaled phantoms as opposed to nearest age-matched phantoms at discrete ages.Methods.We have adopted the University of Florida/National Cancer Institute (UF/NCI) computational phantom library for our studies. For the feasibility study, eight male and female reference size UF/NCI phantoms (5, 10, 15, and 35 years) were downscaled to fourteen different ages which included next nearest available lower discrete ages (1, 5, 10 and 15 years) and the median ages at the time of RT for Wilms' tumor (3.9 years), craniospinal (8.0 years), and all survivors (9.1 years old) in the Childhood Cancer Survivor Study (CCSS) expansion cohort treated with RT. The downscaling was performed using our in-house age scaling functions (ASFs). To geometrically validate the scaling, Dice similarity coefficient (DSC), mean distance to agreement (MDA), and Euclidean distance (ED) were calculated between the scaled and ground-truth discrete-aged phantom (unscaled UF/NCI) for whole-body, brain, heart, liver, pancreas, and kidneys. Additionally, heights of the scaled phantoms were compared with ground-truth phantoms' height, and the Centers for Disease Control and Prevention (CDC) reported 50th percentile height. Scaled organ masses were compared with ground-truth organ masses. For the dosimetric assessment, one reference size phantom and seventeen body-size dependent 5-year-old phantoms (9 male and 8 female) of varying body mass indices (BMI) were downscaled to 3.9-year-old dimensions for two different radiation dose studies. For the first study, we simulated a 6 MV photon right-sided flank field RT plan on a reference size 5-year-old and 3.9-year-old (both of healthy BMI), keeping the field size the same in both cases. Percent of volume receiving dose ≥15 Gy (V₁₅) and the mean dose were calculated for the pancreas, liver, and stomach. For the second study, the same treatment plan, but with patient anatomy-dependent field sizes, was simulated on seventeen body-size dependent 5- and 3.9-year-old phantoms with varying BMIs. V₁₅, mean dose, and minimum dose received by 1% of the volume (D₁), and by 95% of the volume (D₉₅) were calculated for pancreas, liver, stomach, left kidney (contralateral), right kidney, right and left colons, gallbladder, thoracic vertebrae, and lumbar vertebrae. A non-parametric Wilcoxon rank-sum test was performed to determine if the dose to organs of exact age-scaled and nearest age-matched phantoms were significantly different (p < 0.05).Results.In the feasibility study, the best DSCs were obtained for the brain (median: 0.86) and whole-body (median: 0.91) while kidneys (median: 0.58) and pancreas (median: 0.32) showed poorer agreement. In the case of MDA and ED, whole-body, brain, and kidneys showed tighter distribution and lower median values as compared to other organs. For height comparison, the overall agreement was within 2.8% (3.9 cm) and 3.0% (3.2 cm) of ground-truth UF/NCI and CDC reported 50th percentile heights, respectively. For mass comparison, the maximum percent and absolute differences between the scaled and ground-truth organ masses were within 31.3% (29.8 g) and 211.8 g (16.4%), respectively (across all ages). In the first dosimetric study, absolute difference up to 6% and 1.3 Gy was found for V₁₅and mean dose, respectively. In the second dosimetric study, V₁₅and mean dose were significantly different (p < 0.05) for all studied organs except the fully in-beam organs. D₁and D₉₅were not significantly different for most organs (p > 0.05).Conclusion.We have successfully evaluated our ASFs by scaling UF/NCI computational phantoms from one age to another age, which demonstrates the feasibility of scaling any CT-based anatomy. We have found that dose to organs of exact age-scaled and nearest aged-matched phantoms are significantly different (p < 0.05) which indicates that using the exact age-scaled phantoms for retrospective dosimetric studies is a better approach.

A GPU-accelerated framework for individualized estimation of organ doses in digital tomosynthesis

PURPOSE

Estimation of organ doses in digital tomosynthesis (DT) is challenging due to the lack of existing tools that accurately and flexibly model protocol- and view-specific collimations and motion trajectories of the source and detector for a variety of exam protocols, and the computational inefficiencies of conducting MC simulations. The purpose of this study was to overcome these limitations by developing and benchmarking a GPU-accelerated MC simulation framework compatible with patient-specific computational phantoms for individualized estimation of organ doses in DT.

MATERIALS AND METHODS

The framework for individualized estimation of dose in DT was developed as a two-step workflow: (1) a custom MATLAB code that accepts a patient-specific computational phantom and exam description (organ markers for defining the extremities of the anatomical region of interest, tube voltage, source-to-image distance, angular sweep range, number of projection views, and the pivot point to image distance - PPID) to compute the field of views (FOVs) for a clinical DT system, and (2) a MC tool (developed using MC-GPU) modeling the configuration of a clinical DT system to estimate organ doses based on the computed FOVs. Using this framework, we estimated organ doses for 28 radiosensitive organs in an adult reference patient model (M; 30 years) imaged using a commercial DT system (VolumeRad, GE Healthcare, Waukesha, WI). The estimates were benchmarked against values from a comparable organ dose estimation framework (reference dataset developed by the Advanced Laboratory for Radiation Dosimetry Studies at University of Florida) for a posterior-anterior chest exam. The resulting differences were quantified as percent relative errors and analyzed to identify any potential sources of bias and uncertainties. The timing performance (run duration in seconds) of the framework was also quantified for the same simulation to gauge the feasibility of the workflow for time-constrained clinical applications.

RESULTS

The organ dose estimates from the developed framework showed a close agreement with the reference dataset, with percent relative errors ranging from -6.9% to 5.0% and a mean absolute percent difference of 1.7% over all radiosensitive organs, with the exception of testes and eye lens, for which the percent relative errors were higher at -18.9% and -27.6%, respectively, due to their relative positioning outside the primary irradiation field, leading to fewer photons depositing energy and consequently higher errors in estimated organ doses. The run duration for the same simulation was 916.3 s, representing a substantial improvement in performance over existing nonparallelized MC tools.

CONCLUSIONS

This study successfully developed and benchmarked a GPU-accelerated framework compatible with patient-specific anthropomorphic computational phantoms for accurate individualized estimation of organ doses in DT. By enabling patient-specific estimation of organ doses, this framework can aid clinicians and researchers by providing them with tools essential for tracking the radiation burden to patients for dose monitoring purposes and identifying the trends and relationships in organ doses for a patient population to optimize existing and develop new exam protocols.

An update on computational anthropomorphic anatomical models

The prevalent availability of high-performance computing coupled with validated computerized simulation platforms as open-source packages have motivated progress in the development of realistic anthropomorphic computational models of the human anatomy. The main application of these advanced tools focused on imaging physics and computational internal/external radiation dosimetry research. This paper provides an updated review of state-of-the-art developments and recent advances in the design of sophisticated computational models of the human anatomy with a particular focus on their use in radiation dosimetry calculations. The consolidation of flexible and realistic computational models with biological data and accurate radiation transport modeling tools enables the capability to produce dosimetric data reflecting actual setup in clinical setting. These simulation methodologies and results are helpful resources for the medical physics and medical imaging communities and are expected to impact the fields of medical imaging and dosimetry calculations profoundly.

Secondary neutron dose contribution from pencil beam scanning, scattered and spatially fractionated proton therapy

The Orsay Proton therapy Center (ICPO) has a long history of intracranial radiotherapy using both double scattering (DS) and pencil beam scanning (PBS) techniques, and is actively investigating a promising modality of spatially fractionated radiotherapy using proton minibeams (pMBRT). This work provides a comprehensive comparison of the organ-specific secondary neutron dose due to each of these treatment modalities, assessed using Monte Carlo (MC) algorithms and measurements. A MC model of a universal nozzle was benchmarked by comparing the neutron ambient dose equivalent,H*(10), in the gantry room with measurements obtained using a WENDI-II counter. The secondary neutron dose was evaluated for clinically relevant intracranial treatments of patients of different ages, in which secondary neutron doses were scored in anthropomorphic phantoms merged with the patients' images. The MC calculatedH*(10) values showed a reasonable agreement with the measurements and followed the expected tendency, in which PBS yields the lowest dose, followed by pMBRT and DS. Our results for intracranial treatments show that pMBRT yielded a higher secondary neutron dose for organs closer to the target volume, while organs situated furthest from the target volume received a greater quantity of neutrons from the passive scattering beam line. To the best of our knowledge, this is the first study to compare MC secondary neutron dose estimates in clinical treatments between these various proton therapy modalities and to realistically quantify the secondary neutron dose contribution of clinical pMBRT treatments. The method established in this study will enable epidemiological studies of the long-term effects of intracranial treatments at ICPO, notably radiation-induced second malignancies.

Dose quantities for measurement and comparison of doses to individual patients in computed tomography (CT)

The dose quantities displayed routinely on CT scanners, the volume averaged CT dose index (CTDI_vol) and dose length product, provide measures of doses calculated for standard phantoms. The American Association of Medical Physics has published conversion factors for the adjustment of CTDI_volto take account of variations in patient size, the results being termed size-specific dose estimate (SSDE). However, CTDI_voland SSDE, while useful in comparing and optimising doses from a set procedure, do not provide risk-related information that takes account of the organs and tissues irradiated and associated cancer risks. A derivative of effective dose that takes account of differences in body and organ sizes and masses, referred to here as size-specific effective dose (SED), can provide such information. Data on organ doses from NCICT software that is based on Monte Carlo simulations of CT scans for 193 adult phantoms have been used to compute values of SED for CT examinations of the trunk and results compared with corresponding values of SSDE. Relationships within ±8% were observed between SED and SSDE for scans extending over similar regions for phantoms with a wide range of sizes. Coefficients have been derived from fits of the data to estimate SED values from SSDEs for different regions of the body for scans of standard lengths based on patient height. A method developed to take account of differences in scan length gave SED results within ±5% of values calculated using the NCI phantom library. This approach could potentially be used to estimate SED from SSDE values, allowing their display at the time a CT scan is performed.

Radiation therapy related cardiac disease risk in childhood cancer survivors: Updated dosimetry analysis from the Childhood Cancer Survivor Study

BACKGROUND AND PURPOSE

We previously evaluated late cardiac disease in long-term survivors in the Childhood Cancer Survivor Study (CCSS) based on heart radiation therapy (RT) doses estimated from an age-scaled phantom with a simple atlas-based heart model (H_Atlas). We enhanced our phantom with a high-resolution CT-based anatomically realistic and validated age-scalable cardiac model (H_Hybrid). We aimed to evaluate how this update would impact our prior estimates of RT-related late cardiac disease risk in the CCSS cohort.

METHODS

We evaluated 24,214 survivors from the CCSS diagnosed from 1970 to 1999. RT fields were reconstructed on an age-scaled phantom with H_Hybrid and mean heart dose (D_m), percent volume receiving ≥ 20 Gy (V₂₀) and ≥ 5 Gy with V₂₀ = 0 ( [Formula: see text] ) were calculated. We reevaluated cumulative incidences and adjusted relative rates of grade 3-5 Common Terminology Criteria for Adverse Events outcomes for any cardiac disease, coronary artery disease (CAD), and heart failure (HF) in association with D_m, V₂₀, and [Formula: see text] (as categorical variables). Dose-response relationships were evaluated using piecewise-exponential models, adjusting for attained age, sex, cancer diagnosis age, race/ethnicity, time-dependent smoking history, diagnosis year, and chemotherapy exposure and doses. For relative rates, D_m was also considered as a continuous variable.

RESULTS

Consistent with previous findings with H_Atlas, reevaluation using H_Hybrid dosimetry found that, D_m ≥ 10 Gy, V₂₀ ≥ 0.1%, and [Formula: see text]  ≥ 50% were all associated with increased cumulative incidences and relative rates for any cardiac disease, CAD, and HF. While updated risk estimates were consistent with previous estimates overall without statistically significant changes, there were some important and significant (P < 0.05) increases in risk with updated dosimetry for D_m in the category of 20 to 29.9 Gy and V₂₀ in the category of 30% to 79.9%. When changes in the linear dose-response relationship for D_m were assessed, the slopes of the dose response were steeper (P < 0.001) with updated dosimetry. Changes were primarily observed among individuals with chest-directed RT with prescribed doses ≥ 20 Gy.

CONCLUSION

These findings present a methodological advancement in heart RT dosimetry with improved estimates of RT-related late cardiac disease risk. While results are broadly consistent with our prior study, we report that, with updated cardiac dosimetry, risks of cardiac disease are significantly higher in two dose and volume categories and slopes of the Dm-specific RT-response relationships are steeper. These data support the use of contemporary RT to achieve lower heart doses for pediatric patients, particularly those requiring chest-directed RT.

Development of whole-body representation and dose calculation in a commercial treatment planning system

For the epidemiological evaluation of long-term side effects of radiotherapy patients, it is important to know the doses to organs and tissues everywhere in the patient. Computed tomography (CT) images of the patients which contain the anatomical information are sometimes available for each treated patient. However, the available CT scans usually cover only the treated volume of the patient including the target and surrounding anatomy. To overcome this limitation, in this work we describe the development of a software tool using the Varian Eclipse Scripting API for extending a partial-body CT to a whole-body representation in the treatment planning system for dose calculation. The whole-body representation is created by fusing the partial-body CT with a similarly sized whole-body computational phantom selected from a library containing 64 phantoms of different heights, weights, and genders. The out-of-field dose is calculated with analytical models from the literature and merged with the treatment planning system-calculated dose. To test the method, the out-of-field dose distributions on the computational phantoms were compared to dose calculations on whole-body patient CTs. The mean doses, D2% and D98% were compared in 26 organs and tissues for 14 different treatment plans in 5 patients using 3D-CRT, IMRT, VMAT, coplanar and non-coplanar techniques. From these comparisons we found that mean relative differences between organ doses ranged from -10% and +20% with standard deviations of up to 40%. The developed method will help epidemiologists and researchers estimate organ doses outside the treated volume when only limited treatment planning CT information is available.

Patient Size-Dependent Dosimetry Methodology Applied to 18F-FDG Using New ICRP Mesh Phantoms

Despite the known influence of anatomic variability on internal dosimetry, dosimetry for 18F-FDG and other diagnostic radiopharmaceuticals is routinely derived using reference phantoms, which embody population-averaged morphometry for a given age and sex. Moreover, phantom format affects dosimetry estimates to varying extent. Here, we applied newly developed mesh format reference phantoms and a patient-dependent phantom library to assess the impact of height, weight, and body contour variation on dosimetry of 18F-FDG. We compared the mesh reference phantom dosimetry estimates with corresponding estimates from common software to identify differences related to phantom format or software implementation. Our study serves as an example of how more precise patient size-dependent dosimetry methodology could be performed. Methods: Absorbed dose coefficients were computed for the adult mesh reference phantoms and derivative patient-dependent phantom series by Monte Carlo simulation using the PHITS radiation transport code within PARaDIM software. The dose coefficients were compared with reference absorbed dose coefficients obtained from ICRP Publication 128, or generated using software including OLINDA 2.1, OLINDA 1.1, and IDAC-dose 2.1. Results: Differences in dosimetry arising from anatomical variations were shown to be significant, with detriment-weighted dose coefficients for the percentile-specific phantoms varying by up to ±40% relative to the corresponding reference phantom effective dose coefficients, irrespective of phantom format. Similar variations were seen in the individual organ absorbed dose coefficients for the percentile-specific phantoms relative to the reference phantoms. The effective dose coefficient for the mesh reference adult was 0.017 mSv/MBq, which was 5% higher than estimated by a corresponding voxel phantom, and 10% lower than estimated by the stylized phantom format. Conclusion: We observed notable variability in 18F-FDG dosimetry across morphometrically different patients, supporting the use of patient-dependent phantoms for more accurate dosimetric estimations relative to standard reference dosimetry. These data may help in optimizing imaging protocols and research studies, in particular when longer-lived isotopes are employed.

Monte Carlo-based patient internal dosimetry in fluoroscopy-guided interventional procedures: A review

PURPOSE

This systematic review aims to understand the dose estimation approaches and their major challenges. Specifically, we focused on state-of-the-art Monte Carlo (MC) methods in fluoroscopy-guided interventional procedures.

METHODS

All relevant studies were identified through keyword searches in electronic databases from inception until September 2020. The searched publications were reviewed, categorised and analysed based on their respective methodology.

RESULTS

Hundred and one publications were identified which utilised existing MC-based applications/programs or customised MC simulations. Two outstanding challenges were identified that contribute to uncertainties in the virtual simulation reconstruction. The first challenge involves the use of anatomical models to represent individuals. Currently, phantom libraries best balance the needs of clinical practicality with those of specificity. However, mismatches of anatomical variations including body size and organ shape can create significant discrepancies in dose estimations. The second challenge is that the exact positioning of the patient relative to the beam is generally unknown. Most dose prediction models assume the patient is located centrally on the examination couch, which can lead to significant errors.

CONCLUSION

The continuing rise of computing power suggests a near future where MC methods become practical for routine clinical dosimetry. Dynamic, deformable phantoms help to improve patient specificity, but at present are only limited to adjustment of gross body volume. Dynamic internal organ displacement or reshaping is likely the next logical frontier. Image-based alignment is probably the most promising solution to enable this, but it must be automated to be clinically practical.

Fluoroscopy X-Ray Organ-Specific Dosimetry System (FLUXOR) for Estimation of Organ Doses and Their Uncertainties in the Canadian Fluoroscopy Cohort Study

As part of ongoing efforts to assess lifespan disease mortality and incidence in 63,715 patients from the Canadian Fluoroscopy Cohort Study (CFCS) who were treated for tuberculosis between 1930 and 1969, we developed a new FLUoroscopy X-ray ORgan-specific dosimetry system (FLUXOR) to estimate radiation doses to various organs and tissues. Approximately 45% of patients received medical procedures accompanied by fluoroscopy, including artificial pneumothorax (air in pleural cavity to collapse of lungs), pneumoperitoneum (air in peritoneal cavity), aspiration of fluid from pleural cavity and gastrointestinal series. In addition, patients received chest radiographs for purposes of diagnosis and monitoring of disease status. FLUXOR utilizes age-, sex- and body size-dependent dose coefficients for fluoroscopy and radiography exams, estimated using radiation transport simulations in up-to-date computational hybrid anthropomorphic phantoms. The phantoms include an updated heart model, and were adjusted to match the estimated mean height and body mass of tuberculosis patients in Canada during the relevant time period. Patient-specific data (machine settings, exposure duration, patient orientation) used during individual fluoroscopy or radiography exams were not recorded. Doses to patients were based on parameter values inferred from interviews with 91 physicians practicing at the time, historical literature, and estimated number of procedures from patient records. FLUXOR uses probability distributions to represent the uncertainty in the unknown true, average value of each dosimetry parameter. Uncertainties were shared across all patients within specific subgroups of the cohort, defined by age at treatment, sex, type of procedure, time period of exams and region (Nova Scotia or other provinces). Monte Carlo techniques were used to propagate uncertainties, by sampling alternative average values for each parameter. Alternative average doses per exam were estimated for patients in each subgroup, with the total average dose per individual determined by the number of exams received. This process was repeated to produce alternative cohort vectors of average organ doses per patient. This article presents estimates of doses to lungs, female breast, active bone marrow and heart wall. Means and 95% confidence intervals (CI) of average organ doses across all 63,715 patients were 320 (160, 560) mGy to lungs, 250 (120, 450) mGy to female breast, 190 (100, 340) mGy to heart wall and 92 (47, 160) mGy to active bone marrow. Approximately 60% of all patients had average doses to the four studied organs of less than 10 mGy, 10% received between 10 and 100 mGy, 25% between 100 and 1,000 mGy, and 5% above 1,000 mGy. Pneumothorax was the medical procedure that accounted for the largest contribution to cohort average doses. The major contributors to uncertainty in estimated doses per procedure for the four organs of interest are the uncertainties in exposure duration, tube voltage, tube output, and patient orientation relative to the X-ray tube, with the uncertainty in exposure duration being most often the dominant source. Uncertainty in patient orientation was important for doses to female breast, and, to a lesser degree, for doses to heart wall. The uncertainty in number of exams was an important contributor to uncertainty for ∼30% of patients. The estimated organ doses and their uncertainties will be used for analyses of incidence and mortality of cancer and non-cancer diseases. The CFCS cohort is an important addition to existing radio-epidemiological cohorts, given the moderate-to-high doses received fractionated over several years, the type of irradiation (external irradiation only), radiation type (X rays only), a balanced combination of both genders and inclusion of people of all ages.

Technical Note: Patient-morphed mesh-type phantoms to support personalized nuclear medicine dosimetry - a proof of concept study

PURPOSE

Current standard practice for clinical radionuclide dosimetry utilizes reference phantoms, where defined organ dimensions represent population averages for a given sex and age. Greater phantom personalization would support more accurate dose estimations and personalized dosimetry. Tailoring phantoms is traditionally accomplished using operator-intensive organ-level segmentation of anatomic images. Modern mesh phantoms provide enhanced anatomical realism, which has motivated their integration within Monte Carlo codes. Here, we present an automatable strategy for generating patient-specific phantoms/dosimetry using intensity-based deformable image registration between mesh reference phantoms and patient CT images. This work demonstrates a proof-of-concept personalized dosimetry workflow, presented in comparison to the manual segmentation approach.

METHODS

A linear attenuation coefficient phantom was generated by resampling the PSRK-Man reference phantom onto a voxel grid and defining organ regions with corresponding Hounsfield unit (HU) reference values. The HU phantom was co-registered with a patient CT scan using Plastimatch B-spline deformable registration. In parallel, major organs were manually contoured to generate a "ground truth" patient-specific phantom for comparisons. Monte Carlo derived S-values, which support nuclear medicine dosimetry, were calculated using both approaches and compared.

RESULTS

Application of the derived B-spline transform to the polygon vertices comprising the PSRK-Man yielded a deformed variant more closely matching the patient's body contour and most organ volumes as-evaluated by Hausdorff distance and Dice metrics. S-values computed for fluorine-18 for the deformed phantom using the Particle and Heavy Ion Transport code System showed improved agreement with those derived from the patient-specific analog.

CONCLUSIONS

Deformable registration techniques can be used to create a personalized phantom and better support patient-specific dosimetry. This method is shown to be easier and faster than manual segmentation. Our study is limited to a proof-of-concept scope, but demonstrates that integration of personalized phantoms into clinical dosimetry workflows can reasonably be achieved when anatomical images (CT) are available.

Estimation of Heights and Body Masses of Tuberculosis Patients in the Canadian Fluoroscopy Cohort Study for Use in Individual Dosimetry

ABSTRACT

This paper documents the estimation of mean heights and body masses, by age and sex, used in development of organ-specific dose conversion coefficients for external radiation for a historical cohort of about 64,000 patients from the Canadian Fluoroscopy Cohort Study. Patients were exposed to repeated fluoroscopy and chest radiography examinations in the course of treatment for tuberculosis in residential medical facilities throughout Canada between 1930 and 1969. Using Canadian national survey data and extensive literature review, mean heights and masses were obtained for the White population of Canada during the time period of interest, and the differences in mean body mass between tuberculosis patients and the general population were estimated. Results in terms of mean height and body mass of Canadian tuberculosis patients, with uncertainties, are reported for selected age groups (children of ages 1, 5, 10, and 15 y and adults age 20+) and for both sexes. Use of estimated average heights and body masses by age and sex permits the adjustment of computerized phantoms for body mass for a given age, thereby increasing the relevance of the organ-specific dose conversion coefficients for the cohort and improving the accuracy of the resulting estimated organ doses.

Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy

To study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, thus 3D dose distributions must be reconstructed from limited information. State-of-the-art methods achieve this by using 3D surrogate anatomies. These can however lack personalization and lead to coarse reconstructions. We present and validate a surrogate-free dose reconstruction method based on Machine Learning (ML). Abdominal planning CTs (n = 142) of recently-treated childhood cancer patients were gathered, their organs at risk were segmented, and 300 artificial Wilms' tumor plans were sampled automatically. Each artificial plan was automatically emulated on the 142 CTs, resulting in 42,600 3D dose distributions from which dose-volume metrics were derived. Anatomical features were extracted from digitally reconstructed radiographs simulated from the CTs to resemble historical radiographs. Further, patient and radiotherapy plan features typically available from historical treatment records were collected. An evolutionary ML algorithm was then used to link features to dose-volume metrics. Besides 5-fold cross validation, a further evaluation was done on an independent dataset of five CTs each associated with two clinical plans. Cross-validation resulted in mean absolute errors ≤ 0.6 Gy for organs completely inside or outside the field. For organs positioned at the edge of the field, mean absolute errors ≤ 1.7 Gy for [Formula: see text], ≤ 2.9 Gy for [Formula: see text], and ≤ 13% for [Formula: see text] and [Formula: see text], were obtained, without systematic bias. Similar results were found for the independent dataset. To conclude, we proposed a novel organ dose reconstruction method that uses ML models to predict dose-volume metric values given patient and plan features. Our approach is not only accurate, but also efficient, as the setup of a surrogate is no longer needed.

Development and validation of an age-scalable cardiac model with substructures for dosimetry in late-effects studies of childhood cancer survivors

BACKGROUND AND PURPOSE

Radiation therapy is a risk factor for late cardiac disease in childhood cancer survivors. Several pediatric cohort studies have established whole heart dose and dose-volume response models. Emerging data suggest that dose to cardiac substructures may be more predictive than whole heart metrics. In order to develop substructure dose-response models, the heart model previously used for pediatric cohort dosimetry needed enhancement and substructure delineation.

METHODS

To enhance our heart model, we combined the age-scalable capability of our computational phantom with the anatomically-delineated (with substructures) heart models from an international humanoid phantom series. We examined cardiac volume similarity/overlap between registered age-scaled phantoms (1, 5, 10, and 15 years) with the enhanced heart model and the reference phantoms of the same age; dice similarity coefficient (DSC) and overlap coefficient (OC) were calculated for each matched pair. To assess the accuracy of our enhanced heart model, we compared doses from computed tomography-based planning (ground truth) with reconstructed heart doses. We also compared doses calculated with the prior and enhanced heart models for a cohort of nearly 5000 childhood cancer survivors.

RESULTS

We developed a realistic cardiac model with 14-substructures, scalable across a broad age range (1-15 years); average DSC and OC were 0.84 ± 0.05 and 0.90 ± 0.05, respectively. The average percent difference between reconstructed and ground truth mean heart doses was 4.2%. In the cohort dosimetry analysis, dose and dose-volume metrics were approximately 10% lower on average when the enhanced heart model was used for dose reconstructions.

CONCLUSION

We successfully developed and validated an anatomically realistic age-scalable cardiac model that can be used to establish substructure dose-response models for late cardiac disease in childhood cancer survivor cohorts.

Improving Image Quality and Reducing Radiation Dose for Pediatric CT by Using Deep Learning Reconstruction

Background CT deep learning reconstruction (DLR) algorithms have been developed to remove image noise. How the DLR affects image quality and radiation dose reduction has yet to be fully investigated. Purpose To investigate a DLR algorithm's dose reduction and image quality improvement for pediatric CT. Materials and Methods DLR was compared with filtered back projection (FBP), statistical-based iterative reconstruction (SBIR), and model-based iterative reconstruction (MBIR) in a retrospective study by using data from CT examinations of pediatric patients (February to December 2018). A comparison of object detectability for 15 objects (diameter, 0.5-10 mm) at four contrast difference levels (50, 150, 250, and 350 HU) was performed by using a non-prewhitening-matched mathematical observer model with eye filter (d'_NPWE), task transfer function, and noise power spectrum analysis. Object detectability was assessed by using area under the curve analysis. Three pediatric radiologists performed an observer study to assess anatomic structures with low object-to-background signal and contrast to noise in the azygos vein, right hepatic vein, common bile duct, and superior mesenteric artery. Observers rated from 1 to 10 (worst to best) for edge definition, quantum noise level, and object conspicuity. Analysis of variance and Tukey honest significant difference post hoc tests were used to analyze differences between reconstruction algorithms. Results Images from 19 patients (mean age, 11 years ± 5 [standard deviation]; 10 female patients) were evaluated. Compared with FBP, SBIR, and MBIR, DLR demonstrated improved object detectability by 51% (16.5 of 10.9), 18% (16.5 of 13.9), and 11% (16.5 of 14.8), respectively. DLR reduced image noise without noise texture effects seen with MBIR. Radiologist ratings were 7 ± 1 (DLR), 6.2 ± 1 (MBIR), 6.2 ± 1 (SBIR), and 4.6 ± 1 (FBP); two-way analysis of variance showed a difference on the basis of reconstruction type (P < .001). Radiologists consistently preferred DLR images (intraclass correlation coefficient, 0.89; 95% CI: 0.83, 0.93). DLR demonstrated 52% (1 of 2.1) greater dose reduction than SBIR. Conclusion The DLR algorithm improved image quality and dose reduction without sacrificing noise texture and spatial resolution. © RSNA, 2020 Online supplemental material is available for this article.

Body-size-dependent Iodine-131Svalues

In a recent epidemiologic risk assessment on late health effects of patients treated with radioactive iodine (RAI), organ/tissue doses of the patients were estimated based on iodine-131Svalues derived from the reference computational phantoms of the International Commission on Radiological Protection (ICRP). However, the use of theSvalues based on the reference phantoms may lead to significant biases in the estimated doses of patients whose body sizes (height and weight) are significantly different from the reference body sizes. To fill this critical gap, we established a comprehensive dataset of body-size-dependent iodine-131Svalues (r_T← thyroid) for 30 radiosensitive target organs/tissues by performing Monte Carlo dose calculations coupled with a total of 212 adult male and female computational phantoms in different heights and weights. We observed that theSvalues tend to decrease with increasing body height; for example, theSvalue (gonads ← thyroid) of the 160 cm male phantom is about 3 times higher than that of the 190 cm male phantom at the 70 kg weight. We also observed that theSvalues tend to decrease with increasing body weight for some organs/tissues; for example, theSvalue (skin ← thyroid) of the 45 kg female phantom is about two times higher than that of the 130 kg female phantom at the 160 cm height. For other organs/tissues, which are relatively far from the thyroid, in contrast, theSvalues tend to increase with increasing body weight; for example, theSvalue (bladder ← thyroid) of the 45 kg female phantom is about 2 times lower than that of the 130 kg female phantom. Overall, the majority of the body-size-dependentSvalues deviated to within 25% from those of the reference phantoms. We believe that the use of body-size-dependentSvalues in dose reconstructions should help quantify the dosimetric uncertainty in epidemiologic investigations of RAI-treated patients.

Fabrication of a pediatric torso phantom with multiple tissues represented using a dual nozzle thermoplastic 3D printer

Purpose

To demonstrate an on‐demand and nearly automatic method for fabricating tissue‐equivalent physical anthropomorphic phantoms for imaging and dosimetry applications using a dual nozzle thermoplastic three‐dimensional (3D) printer and two types of plastic.

Methods

Two 3D printing plastics were investigated: (a) Normal polylactic acid (PLA) as a soft tissue simulant and (b) Iron PLA (PLA‐Fe), a composite of PLA and iron powder, as a bone simulant. The plastics and geometry of a 1‐yr‐old computational phantom were combined with a dual extrusion 3D printer to fabricate an anthropomorphic imaging phantom. The volumetric fill density of the 3D‐printed parts was varied to approximate tissues of different radiographic density using a calibration curve relating the printer infill density setting to measured CT number. As a demonstration of our method we printed a 10 cm axial cross‐section of the computational phantom’s torso at full scale. We imaged the phantom on a CT scanner and compared HU values to those of a 1‐yr‐old patient and a commercial 5‐yr‐old physical phantom.

Results

The phantom was printed in six parts over the course of a week. The printed phantom included 30 separate anatomical regions including soft tissue remainder, lungs (left and right), heart, esophagus, rib cage (left and right ribs 1 to 10), clavicles (left and right), scapulae (left and right), thoracic vertebrae (one solid object defining thoracic vertebrae T1 to T9). CT scanning of the phantom showed five distinct radiographic regions (heart, lung, soft tissue remainder, bone, and air cavity) despite using only two types of plastic. The 3D‐printed phantom demonstrated excellent similarity to commercially available phantoms, although key limitations in the printer and printing materials leave opportunity for improvement.

Conclusion

Patient‐specific anthropomorphic phantoms can be 3D printed and assembled in sections for imaging and dosimetry applications. Such phantoms will be useful for dose verification purposes when commercial phantoms are unavailable for purchase in the specific anatomies of interest.

Organ Doses from Chest Radiographs in Tuberculosis Patients in Canada and Their Uncertainties in Periods from 1930 to 1969

This paper describes a study to estimate absorbed doses to various organs from film-based chest radiographs and their uncertainties in the periods 1930 to 1948, 1949 to 1955, and 1956 to 1969. Estimated organ doses will be used in new analyses of risks of cancer and other diseases in tuberculosis patients in Canada who had chest fluoroscopic and radiographic examinations in those periods. In this paper, doses to lungs, female breast, active bone marrow, and heart from a single chest radiograph in adults and children of ages 1, 5, 10, and 15 y in the Canadian cohort and their uncertainties are estimated using (1) data on the tube voltage (kV), total filtration (mm Al), tube-current exposure-time product (mA s), and tube output (mR [mA s]) in each period; (2) assumptions about patient orientation, distance from the source to the skin of a patient, and film size; and (3) new calculations of sex- and age-specific organ dose conversion coefficients (organ doses per dose in air at skin entrance). Variations in estimated doses to each organ across the three periods are less than 20% in adults and up to about 30% at younger ages. Uncertainties in estimated organ doses are about a factor of 2 to 3 in adults and up to a factor of 4 at younger ages and are due mainly to uncertainties in the tube voltage and tube-current exposure-time product.

A database of 40 patient-based computational models for benchmarking organ dose estimates in CT

PURPOSE

Patient radiation burden in computed tomography (CT) can best be characterized through risk estimates derived from organ doses. Organ doses can be estimated by Monte Carlo simulations of the CT procedures on computational phantoms assumed to emulate the patients. However, the results are subject to uncertainties related to how accurately the patient and CT procedure are modeled. Different methods can lead to different results. This paper, based on decades of organ dosimetry research, offers a database of CT scans, scan specifics, and organ doses computed using a validated Monte Carlo simulation of each patient and acquisition. It is aimed that the database can serve as means to benchmark different organ dose estimation methods against a benchmark dataset.

ACQUISITION AND VALIDATION METHODS

Organ doses were estimated for 40 adult patients (22 male, 18 female) who underwent chest and abdominopelvic CT examinations. Patient-based computational models were created for each patient including 26 organs for female and 25 organs for male cases. A Monte Carlo code, previously validated experimentally, was applied to calculate organ doses under constant and two modulated tube current conditions.

DATA FORMAT AND USAGE NOTES

The generated database reports organ dose values for chest and abdominopelvic examinations per patient and imaging condition. Patient information and images and scan specifications (energy spectrum, bowtie filter specification, and tube current profiles) are provided. The database is available at publicly accessible digital repositories.

POTENTIAL APPLICATIONS

Consistency in patient risk estimation, and associated justification and optimization requires accuracy and consistency in organ dose estimation. The database provided in this paper is a helpful tool to benchmark different organ dose estimation methodologies to facilitate comparisons, assess uncertainties, and improve risk assessment of CT scans based on organ dose.

Machine learning for the prediction of pseudorealistic pediatric abdominal phantoms for radiation dose reconstruction

Purpose: Current phantoms used for the dose reconstruction of long-term childhood cancer survivors lack individualization. We design a method to predict highly individualized abdominal three-dimensional (3-D) phantoms automatically. Approach: We train machine learning (ML) models to map (2-D) patient features to 3-D organ-at-risk (OAR) metrics upon a database of 60 pediatric abdominal computed tomographies with liver and spleen segmentations. Next, we use the models in an automatic pipeline that outputs a personalized phantom given the patient's features, by assembling 3-D imaging from the database. A step to improve phantom realism (i.e., avoid OAR overlap) is included. We compare five ML algorithms, in terms of predicting OAR left-right (LR), anterior-posterior (AP), inferior-superior (IS) positions, and surface Dice-Sørensen coefficient (sDSC). Furthermore, two existing human-designed phantom construction criteria and two additional control methods are investigated for comparison. Results: Different ML algorithms result in similar test mean absolute errors: ∼ 8    mm for liver LR, IS, and spleen AP, IS; ∼ 5    mm for liver AP and spleen LR; ∼ 80 % for abdomen sDSC; and ∼ 60 % to 65% for liver and spleen sDSC. One ML algorithm (GP-GOMEA) significantly performs the best for 6/9 metrics. The control methods and the human-designed criteria in particular perform generally worse, sometimes substantially ( + 5 - mm error for spleen IS, - 10 % sDSC for liver). The automatic step to improve realism generally results in limited metric accuracy loss, but fails in one case (out of 60). Conclusion: Our ML-based pipeline leads to phantoms that are significantly and substantially more individualized than currently used human-designed criteria.

Body-size-dependent phantom library constructed from ICRP mesh-type reference computational phantoms

Recently, ICRP Task Group 103 developed new mesh-type reference computational phantoms (MRCPs) for the adult male and female by converting the current voxel-type reference computational phantoms (VRCPs) of ICRP Publication 110 into a high-quality/fidelity mesh format. Utilizing the great deformability/flexibility of the MRCPs compared with the VRCPs, in the present study, we established a body-size-dependent phantom library by modifying the MRCPs. The established library includes 108 adult male and 104 adult female phantoms in different standing heights and body weights, covering most body sizes representative of Caucasian and Asian populations. Ten secondary anthropometric parameters with respect to standing height and body weight were derived from various anthropometric databases and applied in the construction of the phantom library. An in-house program for automatic phantom adjustment was developed and applied for practical construction of such a large number of phantoms in the library with minimized human intervention. Organ/tissue doses calculated with three male phantoms in different standing heights (165, 175, and 190 cm) with a fixed body weight of 80 kg for external exposures to broad parallel photon beams from 0.01 to 10⁴ MeV were compared, observing there are significant dose differences particularly for the photon energies <0.1 MeV in which the organ/tissue doses tended to increase with increasing standing height. In addition, the organ/tissue doses of three female phantoms in different body weights (45, 65, and 140 kg) with a fixed standing height of 165 cm were compared, showing a significant decreasing tendency with increasing body weight for the photon energies <10 MeV. For the higher energies, the opposite trend, interestingly, was observed; that is, the organ/tissue doses tended to increase with increasing body weight. The results, despite the limited number of exposure cases, suggest that the use of the body-size-dependent phantom library can improve the accuracy of individual dose estimates for many retrospective dosimetry studies by taking the body size of individuals into account.

Automatic Mapping of CT Scan Locations on Computational Human Phantoms for Organ Dose Estimation

To develop an algorithm to automatically map CT scan locations of patients onto computational human phantoms to provide with patient-specific organ doses. We developed an algorithm that compares a two-dimensional skeletal mask generated from patient CTs with that of a whole body computational human phantom. The algorithm selected the scan locations showing the highest Dice Similarity Coefficient (DSC) calculated between the skeletal masks of a patient and a phantom. To test the performance of the algorithm, we randomly selected five sets of neck, chest, and abdominal CT images from the National Institutes of Health Clinical Center. We first automatically mapped scan locations of the CT images on a computational human phantom using our algorithm. We had several radiologists to manually map the same CT images on the phantom and compared the results with the automated mapping. Finally, organ doses for automated and manual mapping locations were calculated by an in-house CT dose calculator and compared to each other. The visual comparison showed excellent agreement between manual and automatic mapping locations for neck, chest, and abdomen-pelvis CTs. The difference in mapping locations averaged over the start and end in the five patients was less than 1 cm for all neck, chest, and AP scans: 0.9, 0.7, and 0.9 cm for neck, chest, and AP scans, respectively. Five cases out of ten in the neck scans show zero difference between the average manual and automatic mappings. Average of absolute dose differences between manual and automatic mappings was 2.3, 2.7, and 4.0% for neck, chest, and AP scans, respectively. The automatic mapping algorithm provided accurate scan locations and organ doses compared to manual mapping. The algorithm will be useful in cases requiring patient-specific organ dose for a large number of patients such as patient dose monitoring, clinical trials, and epidemiologic studies.

Stylized versus voxel phantoms: a juxtaposition of organ depth distributions

For external irradiation, the variability in organ dose estimation found between computational phantom generations arises particularly from the differences in organ positioning. This work represents the first effort to quantify the differences in organ depth below the body surface between a stylized and voxel phantom series. Herein, the revised Oak Ridge National Laboratory stylized phantom series and the University of Florida/National Cancer Institute voxel phantom series were compared. Both series include whole-body models of the newborn; the 1-, 5-, 10-, and 15-year-old; and the adult human. Organ depths from eight different directions applicable to external irradiation geometries were computed: antero-posterior, postero-anterior, left and right lateral, rotational, isotropic, cranial and caudal directions. Organ depths in the stylized phantoms were computed using a ray-tracing technique available through Monte Carlo radiation transport simulations in MCNP6. Organ depths in the voxel phantom were found using phantom matrix manipulation. Resultant organ depths for both series were plotted as distributions; available are twenty-four organs and two bone tissue distributions for each of six phantom ages and in each of the eight directional geometries. Quantitative data descriptors (e.g. mean and median depths) were also tabulated. For demonstration purposes, a literature review of relevant stylized versus voxel comparison works was performed to explore where the quantification of organ depth differences can provide further insight or evidence to study conclusions. The entire dataset of organ depth distributions and their data descriptors can be found in online supplementary files.

Dose coefficients of percentile-specific computational phantoms for photon external exposures

The use of dose coefficients (DCs) based on the reference phantoms recommended by the International Commission on Radiological Protection (ICRP) with a fixed body size may produce errors to the estimated organ/tissue doses to be used, for example, for epidemiologic studies depending on the body size of cohort members. A set of percentile-specific computational phantoms that represent 10th, 50th, and 90th percentile standing heights and body masses in adult male and female Caucasian populations were recently developed by modifying the mesh-type ICRP reference computational phantoms (MRCPs). In the present study, these percentile-specific phantoms were used to calculate a comprehensive dataset of body-size-dependent DCs for photon external exposures by performing Monte Carlo dose calculations with the Geant4 code. The dataset includes the DCs of absorbed doses for 29 individual organs/tissues from 0.01 to 104 MeV photon energy, in the antero-posterior, postero-anterior, right lateral, left lateral, rotational, and isotropic geometries. The body-size-dependent DCs were compared with the DCs of the MRCPs in the reference body size, showing that the DCs of the MRCPs are generally similar to those of the 50th percentile standing height and body mass phantoms over the entire photon energy region except for low energies (≤ 0.03 MeV); the differences are mostly less than 10%. In contrast, there are significant differences in the DCs between the MRCPs and the 10th and 90th percentile standing height and body mass phantoms (i.e., H10M10 and H90M90). At energies of less than about 10 MeV, the MRCPs tended to under- and over-estimate the organ/tissue doses of the H10M10 and H90M90 phantoms, respectively. This tendency was revised at higher energies. The DCs of the percentile-specific phantoms were also compared with the previously published values of another phantom sets with similar body sizes, showing significant differences particularly at energies below about 0.1 MeV, which is mainly due to the different locations and depths of organs/tissues between the different phantom libraries. The DCs established in the present study should be useful to improve the dosimetric accuracy in the reconstructions of organ/tissue doses for individuals in risk assessment for epidemiologic investigations taking body sizes into account.

Patient organ and effective dose estimation in CT: comparison of four software applications

Background

Radiation dose in computed tomography (CT) has become a topic of high interest due to the increasing numbers of CT examinations performed worldwide. Hence, dose tracking and organ dose calculation software are increasingly used. We evaluated the organ dose variability associated with the use of different software applications or calculation methods.

Methods

We tested four commercial software applications on CT protocols actually in use in our hospital: CT-Expo, NCICT, NCICTX, and Virtual Dose. We compared dose coefficients, estimated organ doses and effective doses obtained by the four software applications by varying exposure parameters. Our results were also compared with estimates reported by the software authors.

Results

All four software applications showed dependence on tube voltage and volume CT dose index, while only CT-Expo was also dependent on other exposure parameters, in particular scanner model and pitch caused a variability till 50%. We found a disagreement between our results and those reported by the software authors (up to 600%), mainly due to a different extent of examined body regions. The relative range of the comparison of the four software applications was within 35% for most organs inside the scan region, but increased over the 100% for organs partially irradiated and outside the scan region. For effective doses, this variability was less evident (ranging from 9 to 36%).

Conclusions

The two main sources of organ dose variability were the software application used and the scan region set. Dose estimate must be related to the process used for its calculation.

Automatic generation of three-dimensional dose reconstruction data for two-dimensional radiotherapy plans for historically treated patients

Performing large-scale three-dimensional radiation dose reconstruction for patients requires a large amount of manual work. We present an image processing-based pipeline to automatically reconstruct radiation dose. The pipeline was designed for childhood cancer survivors that received abdominal radiotherapy with anterior-to-posterior and posterior-to-anterior field set-up. First, anatomical landmarks are automatically identified on two-dimensional radiographs. Second, these landmarks are used to derive parameters to emulate the geometry of the plan on a surrogate computed tomography. Finally, the plan is emulated and used as input for dose calculation. For qualitative evaluation, 100 cases of automatic and manual plan emulations were assessed by two experienced radiation dosimetrists in a blinded comparison. The two radiation dosimetrists approved 100%/100% and 92%/91% of the automatic/manual plan emulations, respectively. Similar approval rates of 100% and 94% hold when the automatic pipeline is applied on another 50 cases. Further, quantitative comparisons resulted in on average < 5    mm difference in plan isocenter/borders, and < 0.9    Gy in organ mean dose (prescribed dose: 14.4 Gy) calculated from the automatic and manual plan emulations. No statistically significant difference in terms of dose reconstruction accuracy was found for most organs at risk. Ultimately, our automatic pipeline results are of sufficient quality to enable effortless scaling of dose reconstruction data generation.

A Scalable Database of Organ Doses for Common Diagnostic Fluoroscopy Procedures of Children: Procedures of Historical Practice for Use in Radiation Epidemiology Studies

Assessment of health effects from low-dose radiation exposures in patients undergoing diagnostic imaging is an active area of research. High-quality dosimetry information pertaining to these medical exposures is generally not readily available to clinicians or epidemiologists studying radiation-related health risks. The purpose of this study was to provide methods for organ dose estimation in pediatric patients undergoing four common diagnostic fluoroscopy procedures: the upper gastrointestinal (UGI) series, the lower gastrointestinal (LGI) series, the voiding cystourethrogram (VCUG) and the modified barium swallow (MBS). Abstracted X-ray film data and physician interviews were combined to generate procedure outlines detailing X-ray beam projections, imaged anatomy, length of X-ray exposure, and presence and amount of contrast within imaged anatomy. Monte Carlo radiation transport simulations were completed for each of the four diagnostic fluoroscopy procedures across the 162-member (87 males and 75 females) University of Florida/National Cancer Institute pediatric phantom library, which covers variations in both subject height and weight. Absorbed doses to 28 organs, including the active marrow and bone endosteum, were assigned for all 162 phantoms by procedure. Additionally, we provide dose coefficients (DCs) in a series of supplementary tables. The DCs give organ doses normalized to procedure-specific dose metrics, including: air kerma-area product (µGy/mGy · cm2), air kerma at the reference point (µGy/µGy), number of spot films (SF) (µGy/number of SFs) and total fluoroscopy time (µGy/s). Organs accumulating the highest absorbed doses per procedure were as follows: kidneys between 0.9-25.4 mGy, 1.1-16.6 mGy and 1.1-9.7 mGy for the UGI, LGI and VCUG procedures, respectively, and salivary glands between 0.2-3.7 mGy for the MBS procedure. Average values of detriment-weighted dose, a phantom-specific surrogate for the effective dose based on ICRP Publication 103 tissue-weighting factors, were 0.98 mSv, 1.16 mSv, 0.83 mSv and 0.15 mSv for the UGI, LGI, VCUG and MBS procedures, respectively. Scalable database of organ dose coefficients by patient sex, height and weight, and by procedure exposure time, reference point air kerma, kerma-area product or number of spot films, allows clinicians and researchers to compute organ absorbed doses based on their institution-specific and patient-specific dose metrics. In addition to informing on patient dosimetry, this work has the potential to facilitate exposure assessments in epidemiological studies designed to investigate radiation-related risks.

Organ and detriment-weighted dose rate coefficients for exposure to radionuclide-contaminated soil considering body morphometries that differ from reference conditions: adults and children

The system of protection established by the International Commission on Radiological Protection (ICRP) provides a robust framework for ionizing radiation exposure justification, optimization, and dose limitation. The system is built upon fundamental concepts of a reference person, defined in ICRP Publication 89, and the radiation protection quantity effective dose, defined in ICRP Publication 103. For external exposures to radionuclide-contaminated soil, values of the organ dose rate coefficient (Gy/s per Bq/m²) and effective dose rate coefficient (Sv/s per Bq/m²) have been computed by several authors and national laboratories using ICRP-compliant reference phantoms-both stylized and voxelized. These coefficients are of great value in post-accident exposure assessments as seen in Japan following the 2011 Fukushima Daiichi nuclear power station disaster. Questions arise, however, among the general public regarding the accuracy of organ and effective dose estimates based upon reference phantom methodologies, especially for those individuals with height and/or total body mass that differ modestly or even substantially from the nearest age-matched reference person. In this pilot study, this issue is explored through use of the extended 351-member UF/NCI hybrid phantom library in which values of organ and detriment-weighted dose rate coefficients are computed for sex/height/mass-specific phantoms, and systematically compared to their values of the effective dose rate coefficient computed using corresponding reference phantoms. Results are given for monoenergetic photons, and then for some 33 different radionuclides, with all dose rate coefficient data provided in a series of electronic annexes. For environmentally relevant radionuclides such as ⁸⁹Sr, ⁹⁰Sr, ¹³⁷Cs, and ¹³¹I, percent differences between the detriment-weighted dose rate coefficient computed using non-reference and the effective dose rate coefficient computed using reference phantoms vary only ± 5% for young children approximated by the reference 1-year-old phantom. With increased body size and age, the range of percent differences in these two quantities increases to + 7% to - 14% for the reference 5-year-old, to + 10% to - 27% for the reference 10-year-old, to + 33% to - 31% for the reference 15-year-old, and to + 15% to - 40% for male and female adults.

Dosimetric impact of voxel resolutions of computational human phantoms for external photon exposure

Several research teams have developed computational phantoms in polygonal-mesh (PM) and/or Non-Uniform Rational B-Spline format, but it has not been systematically evaluated if the existing voxel phantoms are still dosimetrically valid. We created three voxel phantoms with the resolutions of 1,000, 125, and 1 mm3 and simulated the irradiation in antero-posterior geometry with photons of 0.1, 1, and 10 MeV using voxel Monte Carlo codes, and compared the energy deposition to their organs/tissues with the values from the original PM phantom using mesh Monte Carlo codes. The coefficient of variation in energy deposition overall showed about five-fold decrease as the voxel resolution increased but differences were mostly less than 5% for any voxel resolution. We conclude that PM phantoms and mesh Monte Carlo techniques may not be necessary for external photon exposure (0.1 - 10 MeV) and the existing voxel phantoms can provide enough dosimetric accuracy in those exposure conditions.

Organ-specific dose coefficients derived from Monte Carlo simulations for historical (1930s to 1960s) fluoroscopic and radiographic examinations of tuberculosis patients

This work provides dose coefficients necessary to reconstruct doses used in epidemiological studies of tuberculosis patients treated from the 1930s through the 1960s, who were exposed to diagnostic imaging while undergoing treatment. We made use of averaged imaging parameters from measurement data, physician interviews, and available literature of the Canadian Fluoroscopy Cohort Study and, on occasion, from a similar study of tuberculosis patients from Massachusetts, United States, treated between 1925 and 1954. We used computational phantoms of the human anatomy and Monte Carlo radiation transport methods to compute dose coefficients that relate dose in air, at a point 20 cm away from the source, to absorbed dose in 58 organs. We selected five male and five female phantoms, based on the mean height and weight of Canadian tuberculosis patients in that era, for the 1-, 5-, 10-, 15-year old and adult ages. Using high-performance computers at the National Institutes of Health, we simulated 2,400 unique fluoroscopic and radiographic exposures by varying x-ray beam quality, field size, field shuttering, imaged anatomy, phantom orientation, and computational phantom. Compared with previous dose coefficients reported for this population, our dosimetry system uses improved anatomical phantoms constructed from computed tomography imaging datasets. The new set of dose coefficients includes tissues that were not previously assessed, in particular, for tissues outside the x-ray field or for pediatric patients. In addition, we provide dose coefficients for radiography and for fluoroscopic procedures not previously assessed in the dosimetry of this cohort (i.e. pneumoperitoneum and chest aspirations). These new dose coefficients would allow a comprehensive assessment of exposures in the cohort. In addition to providing newly derived dose coefficients, we believe the automation and methods developed to complete these dosimetry calculations are generalizable and can be applied to other epidemiological studies interested in an exposure assessment from medical x-ray imaging. These epidemiological studies provide important data for assessing health risks of radiation exposure to help inform the current system of radiological protection and efforts to optimize the use of radiation in medical studies.

Conversion of computational human phantoms into DICOM-RT for normal tissue dose assessment in radiotherapy patients

Radiotherapy (RT) treatment planning systems (TPS) are designed for the fast calculation of dose to the tumor bed and nearby organs at risk using x-ray computed tomography (CT) images. However, CT images for a patient are typically available for only a small portion of the body, and in some cases, such as for retrospective epidemiological studies, no images may be available at all. When dose to organs that lie out-of-scan must be estimated, a convenient alternative for the unknown patient anatomy is to use a matching whole-body computational phantom as a surrogate. The purpose of the current work is to connect such computational phantoms to commercial RT TPS for retrospective organ dose estimation. A custom software with graphical user interface (GUI), called the DICOM-RT Generator, was developed in MATLAB to convert voxel computational phantoms into the digital imaging and communications in medicine radiotherapy (DICOM-RT) format, compatible with commercial TPS. DICOM CT image sets for the phantoms are created via a density-to-Hounsfield unit (HU) conversion curve. Accompanying structure sets containing the organ contours are automatically generated by tracing binary masks of user-specified organs on each phantom CT slice. The software was tested on a library of body size-dependent phantoms, the International Commission on Radiological Protection reference phantoms, and a canine voxel phantom, taking only a few minutes per conversion. The resulting DICOM-RT files were tested on several commercial TPS. As an example application, a library of converted phantoms was used to estimate organ doses for members of the National Wilms Tumor Study (NWTS) cohort. The converted phantom library, in DICOM format, and a standalone MATLAB-compiled executable of the DICOM-RT Generator are available for others to use for research purposes (http://ncidose.cancer.gov).

A scalable database of organ doses for common diagnostic fluoroscopy examinations of children: procedures of current practice at the University of Florida

Of all the medical imaging modalities that utilize ionizing radiation, fluoroscopy proves to be the most difficult to assess values of patient organ dose owing to the dynamic and patient-specific nature of the irradiation geometry and its associated x-ray beam characteristics. With the introduction of the radiation dose structured report (RDSR) in the mid-2000s, however, computational tools have been developed to extract patient and procedure-specific data for each irradiation event of the study, and when coupled to a computational phantom of the patient, values of skin and internal organ dose may be assessed. Unfortunately, many legacy and even current diagnostic fluoroscopy units do not have RDSR reporting capabilities, thus limiting these dosimetry reporting advances. Nevertheless, knowledge of patient organ doses for patient care, as well as for radiation epidemiology studies, remains a research and regulatory priority. In this study, we created procedural outlines which document all radiation exposure information required for organ dose assessment, akin to a reference RDSR, for six common diagnostic fluoroscopy procedures performed at the University of Florida (UF) Shands Pediatric Hospital. These procedures include the voiding cystourethrogram, the gastrostomy-tube placement, the lower gastrointestinal study, the rehabilitation swallow, the upper gastrointestinal study, and the upper gastrointestinal study with follow through. These procedural outlines were used to develop an extensive database of organ doses for the 162-member UF/NCI (National Cancer Institute) library of pediatric hybrid phantoms, with each member varying combinations of sex, height, and weight. The organ dose assessment accounts for the varying x-ray fields, fluoroscopy time, relative concentration of x-ray contrast in the organs, and changes in the fluoroscope output due to patient size. Furthermore, we are also reporting organ doses normalized to total fluoroscopy time, reference point air kerma, and kerma-area product, effectively providing procedure dose coefficients. The extensive organ dose library produced in this study may be used prospectively for patient organ dose reporting or retrospectively in epidemiological studies of radiation-associated health risks.

ORGAN DOSE ESTIMATION ACCOUNTING FOR UNCERTAINTY FOR PEDIATRIC AND YOUNG ADULT CT SCANS IN THE UNITED KINGDOM

Since our previous publication of organ dose for the pediatric CT cohort in the UK, there have been questions about the magnitude of uncertainty in our dose estimates. We therefore quantified shared and unshared uncertainties in empirical CT parameters extracted from 1073 CT films (1978-2008) from 36 hospitals in the study and propagated these uncertainties into organ doses using Monte Carlo random sampling and NCICT organ dose calculator. The average of 500 median brain and marrow doses for the full cohort was 35 (95% confidence interval: 30-40) mGy and 6 (5-7) mGy, respectively. We estimated that shared uncertainty contributed ~99% of coefficient of variation of median brain doses in brain scans compared to unshared uncertainty (1% contribution). We found that the previous brain doses were slightly underestimated for <1990 and overestimated for >1990 compared to the results in the current study due to the revised CTDI models based on CT films.