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The rapid advancement in the field of medical imaging presents a challenge in keeping up to date with the necessary objective evaluations and optimizations for safe and effective use in clinical settings. These evaluations are traditionally done using clinical imaging trials, which while effective, pose several limitations including high costs, ethical considerations for repetitive experiments, time constraints, and lack of ground truth. To tackle these issues, virtual trials (aka in silico trials) have emerged as a promising alternative, using computational models of human subjects and imaging devices, and observer models/analysis to carry out experiments. To facilitate the widespread use of virtual trials within the medical imaging research community, a major need is to establish a common consensus framework that all can use. Based on the ongoing efforts of an AAPM Task Group (TG387), this article provides a comprehensive overview of the requirements for establishing virtual imaging trial frameworks, paving the way toward their widespread use within the medical imaging research community. These requirements include credibility, reproducibility, and accessibility. Credibility assessment involves verification, validation, uncertainty quantification, and sensitivity analysis, ensuring the accuracy and realism of computational models. A proper credibility assessment requires a clear context of use and the questions that the study is intended to objectively answer. For reproducibility and accessibility, this article highlights the need for detailed documentation, user‐friendly software packages, and standard input/output formats. Challenges in data and software sharing, including proprietary data and inconsistent file formats, are discussed. Recommended solutions to enhance accessibility include containerized environments and data‐sharing hubs, along with following standards such as CDISC (Clinical Data Interchange Standards Consortium). By addressing challenges associated with credibility, reproducibility, and accessibility, virtual imaging trials can be positioned as a powerful and inclusive resource, advancing medical imaging innovation and regulatory science. [ABSTRACT FROM AUTHOR]

Preclinical dosimetry is essential for guiding the design of animal radiopharmaceutical biodistribution, imaging, and therapy experiments, evaluating efficacy and/or toxicities in such experiments, ensuring compliance with ethical standards for animal research, and, perhaps most importantly, providing reasonable initial estimates of normal-organ doses in humans, required for clinical translation of new radiopharmaceuticals. This MIB Guide provides a basic protocol for obtaining preclinical dosimetry estimates with organ-level dosimetry software. [ABSTRACT FROM AUTHOR]

Abstract Background Reliable estimates of radiation dose to bone marrow are critical to understanding the risk of radiation‐induced cancers. Although the medical internal radiation dose phantom is routinely used for dose estimation, bone marrow is not defined in the phantom. Consequently, methods of indirectly estimating bone marrow dose have been implemented based on dose to surrogate volumes or average dose to soft tissue. Methods In this study, new bone marrow structures were implemented and evaluated to the medical internal radiation dose phantom in Geant4, offering improved fidelity. The dose equivalent to the bone marrow was calculated across medical, occupational, and space radiation exposure scenarios, and compared with results using prior indirect estimation methods. Conclusion Our results show that bone marrow dose may be overestimated by up to a factor of three when using the traditional methods when compared with the improved fidelity medical internal radiation dose method, specifically at clinical x‐ray energies.

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 phantoms C R A M _ S / C R A F _ S have 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 ( < 2 M e V ) and high energies ( > 8 M e V ) 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. [ABSTRACT FROM AUTHOR]

Background: Reliable estimates of radiation dose to bone marrow are critical to understanding the risk of radiation‐induced cancers. Although the medical internal radiation dose phantom is routinely used for dose estimation, bone marrow is not defined in the phantom. Consequently, methods of indirectly estimating bone marrow dose have been implemented based on dose to surrogate volumes or average dose to soft tissue. Methods: In this study, new bone marrow structures were implemented and evaluated to the medical internal radiation dose phantom in Geant4, offering improved fidelity. The dose equivalent to the bone marrow was calculated across medical, occupational, and space radiation exposure scenarios, and compared with results using prior indirect estimation methods. Conclusion: Our results show that bone marrow dose may be overestimated by up to a factor of three when using the traditional methods when compared with the improved fidelity medical internal radiation dose method, specifically at clinical x‐ray energies. [ABSTRACT FROM AUTHOR]

Studies of radiobiological effects in murine rodents exposed to internal radiation in the wild or in laboratory experiments require dosimetric support. The main problem of bone marrow (BM) dosimetry for bone-seeking β-emitters is dosimetric modeling, because the bone is a heterogeneous structure with complex microarchitecture. To date, there are several approaches to calculating the absorbed dose in BM, which mostly use rough geometric approximations. Recently, in the framework of studies of people exposed to 90Sr in the Urals, a new approach (SPSD) has been developed. The aim of the current study was to test for the first time the possibility of extension of the SPSD approach elaborated for humans to mice. For this, computational phantoms of femur bones of laboratory animals (C57BL/6, C57BL/6 J, BALB/c, BALB/cJ) aged 5–8 weeks (growing) and > 8 weeks (adults) were created. The dose factors DFSr-90(BM ← TBV + CBV) to convert the Sr isotope activity concentration in a bone tissue into units of dose rate absorbed in the bone marrow were 1.75 ± 0.42 and 2.57 ± 0.93 μGy day−1 per Bq g−1 for growing and adult animals, respectively, while corresponding values for DFSr-89(BM ← TBV + CBV) were 1.08 ± 0.27 and 1.66 ± 0.67 μGy day−1 per Bq g−1, respectively. These results are about 2.5 times lower than skeleton-average DFs calculated assuming homogenous bone, where source and target coincide. The results of the present study demonstrate the possibility of application of the SPSD approach elaborated for humans to non-human mammals. It is concluded that the study demonstrates the feasibility and appropriateness of application of the SPSD approach elaborated for humans to non-human mammals. This approach opens up new prospects for studying the radiobiological consequences of red bone marrow exposure for both laboratory and wildlife mammals. [ABSTRACT FROM AUTHOR]

The estimation of radiation hazards to the human body before and after the use of shielding glass is the next level of research on its radiation shielding properties. In this work, the glass compositions of the x Bi 2 O 3 − 20AlF 3 − 20CaO − (60- x)B 2 O 3 (where 0 ≤ x ≤ 40 mol%) were prepared by the melt-quenching method. The adult male mesh-type reference computational phantoms (MRCP-AM) were used to represent the whole human body, including the shape, chemical composition, and densities of every organ. The absorbed dose and effective dose rate on the phantom before and after using the shielding glass (thickness 1.0 cm) were estimated by PHITS Monte Carlo simulation. The mono-energetic photon of 0.662 MeV was irradiated with an anterior-posterior (AP) direction. In addition, the physical properties and gamma-ray shielding properties of the glasses, including the density (ρ), molar volume (V m), mass attenuation coefficient (μ m), half-value layer (HVL), Z eff , and N eff , were investigated by PHITS and XCOM in an energy range of 0.015 MeV–15 MeV, as well as comparison with experimental methods at different energy (133Ba, 137Cs, and 60Co sources). The results found that the addition of the Bi 2 O 3 content into the glass structure affects the increase of the ρ, V m , μ m , Z eff , and N eff but the decrease of the HVL. In addition, the comparative study of radiation dose on the MRCP-AM phantom before and after using the shielding glass by PHITS Monte Carlo simulation demonstrated that the 40Bi 2 O 3 glass sample can reduce damage to the brain, liver, left lung, right lung, prostate, skin, and thyroid, which are equal to 30.34%, 28.93%, 29.33%, 29.70%, 21.15%, 25.72%, and 21.99%, respectively, when compared with no shielding materials. The effective dose rate in MRCP-AM with shielding glass revealed significantly less damage than without shielding glass. • New application of using MRCP-AM phantom by PHITS Monte Carlo simulation. • The radiation dose of human organs was estimated by the Monte Carlo method. • The high densities of the Bi 2 O 3 –AlF 3 –CaO–B 2 O 3 glass were prepared. • The gamma-ray shieling properties of the glass were investigated by PHITS, XCOM, and experimental methods. [ABSTRACT FROM AUTHOR]

Objective. CT-mesh hybrid phantoms (or ‘hybrid(s)’) made from integrated patient CT data and mesh-type reference computational phantoms (MRCPs) can be beneficial for patient-specific whole-body dose evaluation, but this benefit has yet to be evaluated for second cancer risk prediction. The purpose of this study is to compare the hybrid’s ability to predict risk throughout the body with a patient-scaled MRCP against ground truth whole-body CTs (WBCTs). Approach. Head and neck active scanning proton treatment plans were created for and simulated on seven hybrids and the corresponding scaled MRCPs and WBCTs. Equivalent dose throughout the body was calculated and input into five second cancer risk models for both excess absolute and excess relative risk (EAR and ERR). The hybrid phantom was evaluated by comparing equivalent dose and risk predictions against the WBCT. Main results. The hybrid most frequently provides whole-body second cancer risk predictions which are closer to the ground truth when compared to a scaled MRCP alone. The performance of the hybrid relative to the scaled MRCP was consistent across ERR, EAR, and all risk models. For all in-field organs, where the hybrid shares the WBCT anatomy, the hybrid was better than or equal to the scaled MRCP for both equivalent dose and risk prediction. For out-of-field organs across all patients, the hybrid’s equivalent dose prediction was superior than the scaled MRCP in 48% of all comparisons, equivalent for 34%, and inferior for 18%. For risk assessment in the same organs, the hybrid’s prediction was superior than the scaled MRCP in 51.8% of all comparisons, equivalent in 28.6%, and inferior in 19.6%. Significance. Whole-body risk predictions from the CT-mesh hybrid have shown to be more accurate than those from a reference phantom alone. These hybrids could aid in risk-optimized treatment planning and individual risk assessment to minimize second cancer incidence. [ABSTRACT FROM AUTHOR]

Objective . To allow the estimation of secondary cancer risks from radiation therapy treatment plans in a comprehensive and user-friendly Monte Carlo (MC) framework. Method . Patient planning computed tomography scans were extended superior-inferior using the International Commission on Radiological Protection's Publication 145 computational mesh phantoms and skeletal matching. Dose distributions were calculated with the TOPAS MC system using novel mesh capabilities and the digital imaging and communications in medicine radiotherapy extension interface. Finally, in-field and out-of-field cancer risk was calculated using both sarcoma and carcinoma risk models with two alternative parameter sets. Result . The TOPAS MC framework was extended to facilitate epidemiological studies on radiation-induced cancer risk. The framework is efficient and allows automated analysis of large datasets. Out-of-field organ dose was small compared to in-field dose, but the risk estimates indicate a non-negligible contribution to the total radiation induced cancer risk. Significance . This work equips the TOPAS MC system with anatomical extension, mesh geometry, and cancer risk model capabilities that make state-of-the-art out-of-field dose calculation and risk estimation accessible to a large pool of users. Furthermore, these capabilities will facilitate further refinement of risk models and sensitivity analysis of patient specific treatment options., (© 2024 Institute of Physics and Engineering in Medicine.)

Objective: This study aims to develop and validate a novel framework, iPhantom, for automated creation of patient-specific phantoms or “digital-twins (DT)” using patient medical images. The framework is applied to assess radiation dose to radiosensitive organs in CT imaging of individual patients. Method: Given a volume of patient CT images, iPhantom segments selected anchor organs and structures (e.g., liver, bones, pancreas) using a learning-based model developed for multi-organ CT segmentation. Organs which are challenging to segment (e.g., intestines) are incorporated from a matched phantom template, using a diffeomorphic registration model developed for multi-organ phantom-voxels. The resulting digital-twin phantoms are used to assess organ doses during routine CT exams. Result: iPhantom was validated on both with a set of XCAT digital phantoms (n = 50) and an independent clinical dataset (n = 10) with similar accuracy. iPhantom precisely predicted all organ locations yielding Dice Similarity Coefficients (DSC) 0.6 - 1 for anchor organs and DSC of 0.3-0.9 for all other organs. iPhantom showed <10% errors in estimated radiation dose for the majority of organs, which was notably superior to the state-of-the-art baseline method (20-35% dose errors). Conclusion: iPhantom enables automated and accurate creation of patient-specific phantoms and, for the first time, provides sufficient and automated patient-specific dose estimates for CT dosimetry. Significance: The new framework brings the creation and application of CHPs (computational human phantoms) to the level of individual CHPs through automation, achieving wide and precise organ localization, paving the way for clinical monitoring, personalized optimization, and large-scale research. [ABSTRACT FROM AUTHOR]

International Commission on Radiological Protection (ICRP) adult and pediatric reference computational phantoms are widely employed to evaluate calibration of in-vivo monitoring systems using Monte Carlo codes. Quick Scan Whole Body Monitor (QSWBM) is an in-vivo monitoring system capable of fast screening subjects in standing linear geometry. In the present study, our objectives include: (1) Monte Carlo estimation of QSWBM counting efficiencies using age and sex specific ICRP computational reference phantoms, (2) understand the effect of skeletal sampling in counting efficiency, (3) comparison of efficiencies for multiple sized voxel phantoms of same age group and sex, and (4) comparison of experimental and numerical calibration. With this study, we have numerically estimated QSWBM counting efficiencies for three important gamma energies, 662 keV from 137Cs and 1173 keV and 1332 keV from 60Co using FLUKA code and a total of fifteen computational phantoms. The results obtained from the present work rule out the necessity of computationally complex skeletal soft tissue sampling in numerical calibration of standing geometry whole body counters for in-vivo detection of uniformly distributed sources in human body. It was also found that the efficiencies were greatly influenced by the physical size of the subjects while the deviation due to sex is not very great. Experimental calibration using Indian Reference Bottle Mannequin ABsorber (BOMAB-I) phantom was compared with modified adult male computational phantom of equivalent physical dimensions to understand the deviations. With this study, QSWBM was numerically calibrated to detect 137Cs and 60Co in diverse subjects of a population. • Counting efficiencies of QSWBM were determined using computational phantoms. • Effect of skeletal sampling is negligible for uniform whole body source. • Significant deviation in efficiencies due to phantom size was observed. • Experimental and numerical efficiencies of QSWBM were compared. [ABSTRACT FROM AUTHOR]

• Computational anthropomorphic breast models based on mathematical formulations. • Computational breast models based on patient medical images. • Physical 3D anthropomorphic breast phantoms. • 3D printing technology for fabrication of anthropomorphic breast models. Anthropomorphic breast phantoms are both, computational and physical, anatomically and radiologically realistic models of the human female breast, and are considered an excellent tool for development, comparing, characterizing and optimizing of novel and existing breast screening and diagnostic modalities. Their role in the objective assessment of diagnostic task performance of breast imaging systems without conducting high cost and time-consuming clinical trials, as well as in developing and optimizing clinical protocols and image reconstruction algorithms is tangible increasing. The aim of this paper is to present a historical journey from the advent of the breast anthropomorphic models used with x-ray modalities, their further development and realistic improvement, to current achievements. Anthropomorphic breast models are both computational and physical. Computational phantoms are mainly based on mathematical formulations and patient medical images. The mathematical breast models consist of mathematical description of the breast structures, while the patient-based are created from segmented clinical datasets acquired by dedicated breast Computed Tomography. The later approach guarantees a very high degree of realism. Molding techniques, 3D printing and low cost paper-based approaches are the main methods for creation of physical breast anthropomorphic models. Among them, 3D printing technologies provide an excellent opportunity to create realistic models of the breast by using a number of printing materials with x-ray characteristics similar to these of breast tissues. The anatomical and radiological realism of the anthropomorphic breast phantoms together with the possibility for unlimited exposure during important diagnostic tasks is transforming them into a key instrument of every Radiology Department. [ABSTRACT FROM AUTHOR]

We have used the TOPAS Geant4-based package to create a parametric simulation of a new TOF-PET scanner design based on a low atomic number scintillator. TOPAS was extended to provide complete information on individual particle position, energy, and identity, allowing access to all particle interactions in the simulation. The data were then used as the 'truth' information of particle kinematics for the simulation of the TOF-PET scanner, as described in a separate paper. The Derenzo and XCAT phantoms were added to the simulation with in-patient scattering, positron emission placement, and positron diffusion. Running Geant4 simulations through TOPAS requires substantially smaller amounts of user training than would be needed in raw Geant4. This paper describes the methods used to simulate the low-Z whole-body scanner at reduced dose. Specifically, this paper covers the simulation of the FDG decay energy spectrum; the simulation of tissue densities, atomic compositions, and radiotracer doses within imaging phantoms with doses; the custom TOPAS extension used to record particle interaction data; computational performance; and required Geant4 libraries used in TOPAS. [ABSTRACT FROM AUTHOR]

Objective. Virtual imaging trials enable efficient assessment and optimization of medical image devices and techniques via simulation rather than physical studies. These studies require realistic, detailed ground-truth models or phantoms of the relevant anatomy or physiology. Anatomical structures within computational phantoms are typically based on medical imaging data; however, for small and intricate structures (e.g. trabecular bone), it is not reasonable to use existing clinical data as the spatial resolution of the scans is insufficient. In this study, we develop a mathematical method to generate arbitrary-resolution bone structures within virtual patient models (XCAT phantoms) to model the appearance of CT-imaged trabecular bone. Approach . Given surface definitions of a bone, an algorithm was implemented to generate stochastic bicontinuous microstructures to form a network to define the trabecular bone structure with geometric and topological properties indicative of the bone. For an example adult male XCAT phantom (50th percentile in height and weight), the method was used to generate the trabecular structure of 46 chest bones. The produced models were validated in comparison with published properties of bones. The utility of the method was demonstrated with pilot CT and photon-counting CT simulations performed using the accurate DukeSim CT simulator on the XCAT phantom containing the detailed bone models. Main results . The method successfully generated the inner trabecular structure for the different bones of the chest, having quantiative measures similar to published values. The pilot simulations showed the ability of photon-counting CT to better resolve the trabecular detail emphasizing the necessity for high-resolution bone models. Significance. As demonstrated, the developed tools have great potential to provide ground truth simulations to access the ability of existing and emerging CT imaging technology to provide quantitative information about bone structures., (© 2023 Institute of Physics and Engineering in Medicine.)

The calculation of doses to organs and tissues of interest due to internally emitting radionuclides requires knowledge of the time-dependent distribution of the radionuclide, its physical decay properties, and the fraction of emitted energy absorbed per mass of the target. The latter property is quantified as the specific absorbed fraction (SAF). This publication provides photon, electron, alpha particle, and neutron (for nuclides undergoing spontaneous fission) SAF values for the suite of reference individuals. The reference individuals are defined largely by information provided in ICRP Publication 89 . Some improvements and additional data are provided in this publication which define the reference individual's source and target region masses used in the Occupational Intake of Radionuclides (OIR) and Dose Coefficients for Intakes of Radionuclides by Members of the Public series of publications. The set of reference individuals includes males and females at 0 (newborn), 1, 5, 10, 15, and 20 (adult) years of age. The reference adult masses and SAFs provided in this publication are identical to those in ICRP Publication 133 and those used in the OIR series of publications. Computation of SAF values involves simulating radiation transport in computational models which represent the geometry of the reference individuals. The reference voxel phantoms of ICRP Publication 143 are used for photon and neutron transport, and most electron transport. Alpha particle transport is not necessary for large tissue regions as the short range allows for an assumption of full energy absorption (absorbed fraction of unity) for self-irradiation geometries. Additional computational models are needed for charged particles in small, overlapping, or interlaced geometries. Stylised models are described and used for electrons and alpha particles in the alimentary and respiratory tract regions. Image-based models are used to compute SAFs for charged particles within the skeleton. This publication is accompanied by an electronic supplement which includes files containing SAFs for each radiation type in each reference individual. The supplement also includes source and target region masses for each reference individual, as well as skeletal dose-response functions for photons incident upon the skeleton.© 2024 ICRP. Published by SAGE.

• The GATE MC toolkit was used to model and validate the multislice helical GE BrightSpeed Elite CT model. • An organ dose database for individuals (2.1–14 years age range), undergoing CT examinations was created. • Dependency of absorbed dose and the anatomical characteristics was researched for several organs. • Effective doses-normalized-to-DLP were estimated and correlated with the total body weight. The purpose of this study is to create an organ dose database for pediatric individuals undergoing chest, abdomen/pelvis, and head computed tomography (CT) examinations, and to report the differences in absorbed organ doses, when anatomical differences exist for pediatric patients. The GATE Monte Carlo (MC) toolkit was used to model the GE BrightSpeed Elite CT model. The simulated scanner model was validated with the standard Computed Tomography Dose Index (CTDI) head phantom. Twelve computational models (2.1–14 years old) were used. First, contributions to effective dose and absorbed doses per CTDI vol and per 100 mAs were estimated for all organs. Then, doses per CTDI vol were correlated with patient model weight for the organs inside the scan range for chest and abdomen/pelvis protocols. Finally, effective doses per dose-length product (DLP) were estimated and compared with the conventional conversion k-factors. The system was validated against experimental CTDI w measurements. The doses per CTDI vol and per 100 mAs for selected organs were estimated. The magnitude of the dependency between the dose and the anatomical characteristics was calculated with the coefficient of determination at 0.5–0.7 for the internal scan organs for chest and abdomen/pelvis protocols. Finally, effective doses per DLP were compared with already published data, showing discrepancies between 13 and 29% and were correlated strongly with the total weight (R2 > 0.8) for the chest and abdomen protocols. Big differences in absorbed doses are reported even for patients of similar age or same gender, when anatomical differences exist on internal organs of the body. [ABSTRACT FROM AUTHOR]

• A novel algorithm for generating computer-simulated soft tissue breast lesions. • Computer-simulated breast lesions generated by using fractal Perlin noise. • Includes simulated lesions inserted in computational breast phantoms. • Simulated lesions evaluated and classified by observers according to BI-RADS. • A simulation method that provides almost real-time lesion generation. Steadily increasing use of computational/virtual phantoms in medical physics has motivated expanding development of new simulation methods and data representations for modelling human anatomy. This has emphasized the need for increased realism, user control, and availability. In breast cancer research, virtual phantoms have gained an important role in evaluating and optimizing imaging systems. For this paper, we have developed an algorithm to model breast abnormalities based on fractal Perlin noise. We demonstrate and characterize the extension of this approach to simulate breast lesions of various sizes, shapes, and complexity. Recently, we developed an algorithm for simulating the 3D arrangement of breast anatomy based on Perlin noise. In this paper, we have expanded the method to also model soft tissue breast lesions. We simulated lesions within the size range of clinically representative breast lesions (masses, 5–20 mm in size). Simulated lesions were blended into simulated breast tissue backgrounds and visualized as virtual digital mammography images. The lesions were evaluated by observers following the BI-RADS assessment criteria. Observers categorized the lesions as round, oval or irregular, with circumscribed, microlobulated, indistinct or obscured margins. The majority of the simulated lesions were considered by the observers to have a realism score of moderate to well. The simulation method provides almost real-time lesion generation (average time and standard deviation: 1.4 ± 1.0 s). We presented a novel algorithm for computer simulation of breast lesions using Perlin noise. The algorithm enables efficient simulation of lesions, with different sizes and appearances. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: The purpose of this study was to experimentally validate UF‐RIPSA, a rapid in‐clinic peak skin dose mapping algorithm developed at the University of Florida using optically stimulated luminescent dosimeters (OSLDs) and tissue‐equivalent phantoms. Methods: The OSLDs used in this study were InLightTM Nanodot dosimeters by Landauer, Inc. The OSLDs were exposed to nine different beam qualities while either free‐in‐air or on the surface of a tissue equivalent phantom. The irradiation of the OSLDs was then modeled using Monte Carlo techniques to derive correction factors between free‐in‐air exposures and more complex irradiation geometries. A grid of OSLDs on the surface of a tissue equivalent phantom was irradiated with two fluoroscopic x ray fields generated by the Siemens Artis zee bi‐plane fluoroscopic unit. The location of each OSLD within the grid was noted and its dose reading compared with UF‐RIPSA results. Results: With the use of Monte Carlo correction factors, the OSLD's response under complex irradiation geometries can be predicted from its free‐in‐air response. The predicted values had a percent error of −8.7% to +3.2% with a predicted value that was on average 5% below the measured value. Agreement within 9% was observed between the values of the OSLDs and RIPSA when irradiated directly on the phantom and within 14% when the beam first traverses the tabletop and pad. Conclusions: The UF‐RIPSA only computes dose values to areas of irradiated skin determined to be directly within the x ray field since the algorithm is based upon ray tracing of the reported reference air kerma value, with subsequent corrections for air‐to‐tissue dose conversion, x ray backscatter, and table/pad attenuation. The UF‐RIPSA algorithm thus does not include the dose contribution of scatter radiation from adjacent fields. Despite this limitation, UF‐RIPSA is shown to be fairly robust when computing skin dose to patients undergoing fluoroscopically guided interventions. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to extend the extended cardiac-torso (XCAT) series of computational phantoms to include a detailed lung architecture including airways and pulmonary vasculature. Eleven XCAT phantoms of varying anatomy were used in this paper. The lung lobes and initial branches of the airways, pulmonary arteries, and veins were previously defined in each XCAT model. These models were extended from the initial branches of the airways and vessels to the level of terminal branches using an anatomically-based volume-filling branching algorithm. This algorithm grew the airway and vasculature branches separately and iteratively without intersecting each other using cylindrical models with diameters estimated by order-based anatomical measurements. Geometrical features of the extended branches were compared with the literature anatomy values to quantitatively evaluate the models. These features include branching angle, length to diameter ratio, daughter to parent diameter ratio, asymmetrical branching pattern, diameter, and length ratios. The XCAT phantoms were then used to simulate CT images to qualitatively compare them with the original phantom images. The proposed growth model produced 46369 ± 12521 airways, 44737 ± 11773 arteries, and 39819 ± 9988 veins to the XCAT phantoms. Furthermore, the growth model was shown to produce asymmetrical airway, artery, and vein networks with geometrical attributes close to morphometry and model based studies. The simulated CT images of the phantoms were judged to be more realistic, including more airways and pulmonary vessels compared with the original phantoms. Future work will seek to add a heterogeneous parenchymal background into the XCAT lungs to make the phantoms even more representative of human anatomy, paving the way towards the use of XCAT models as a tool to virtually evaluate the current and emerging medical imaging technologies. [ABSTRACT FROM PUBLISHER]

Purpose: To quantify differences in computationally estimated computed tomography (CT) organ doses for patient-specific voxel phantoms to estimated organ doses in matched computational phantoms using different matching criteria. Materials and methods: Fifty-two patient-specific computational voxel phantoms were created through CT image segmentation. In addition, each patient-specific phantom was matched to six computational phantoms of the same gender based, respectively, on age and gender (reference phantoms), height and weight, effective diameter (both central slice and exam range average), and water equivalent diameter (both central slice and exam range average). Each patient-specific phantom and matched computational phantom were then used to simulate six different torso examinations using a previously validated Monte Carlo CT dosimetry methodology that accounts for tube current modulation. Organ doses for each patient-specific phantom were then compared with the organ dose estimates of each of the matched phantoms. Results: Relative to the corresponding patient-specific phantoms, the root mean square of the difference in organ dose was 39.1%, 20.3%, 22.7%, 21.6%, 20.5%, and 17.6%, for reference, height and weight, effective diameter (central slice and scan average), and water equivalent diameter (central slice and scan average), respectively. The average magnitude of difference in organ dose was 24%, 14%, 16.9%, 16.2%, 14%, and 11.9%, respectively. Conclusion: Overall, these data suggest that matching a patient to a computational phantom in a library is superior to matching to a reference phantom. Water equivalent diameter is the superior matching metric, but it is less feasible to implement in a clinical and retrospective setting. For these reasons, height-and-weight matching is an acceptable and reliable method for matching a patient to a member of a computational phantom library with regard to CT dosimetry. [ABSTRACT FROM AUTHOR]

68Ga-PSMA (prostate specific membrane antigen) has increasingly used for diagnosis in metastasis prostate cancer patients. This study aimed to evaluate the patient doses and the biokinetic distribution of 68Ga-PSMA-11 PET/CT examination in Thai prostate cancer patients. The retrospective data were collected from sixteen metastasis prostate cancer patients age ranged between 54-83 years-old (mean±SD; 68.9±6.8), administered intravenously with 89–224 MBq of 68Ga-PSMA-11 (mean±SD, 153.87±36.98 MBq). Whole–body PET/CT static scan at 1 hour post injection was acquired by Siemens Biograph 16 PET/CT system. Thirteen source organs, i.e. brain, salivary glands, thyroid, lungs, heart wall, liver, gallbladder, spleen, adrenal glands, kidneys, red bone marrow, urinary bladder, and muscle were contoured on fused PET-CT images using the PMOD program. The region of interests (ROIs) were placed over the portion of the organ uptake with 68Ga-PSMA-11 to calculate the time-integrated activity coefficients (TIAC). The absorbed dose coefficients in target organs were calculated according to the Medical Internal Radiation Dose (MIRD) scheme using OLINDA/EXM version 2.0. Tissue weighting factors from ICRP 103 were used in effective dose calculations. The highest absorbed dose coefficient of 0.12±0.05 mGy/MBq was found in kidneys, followed by the adrenal glands, salivary glands, spleen and urinary bladder of 0.075±0.03, 0.057±0.02, 0.032±0.01 and 0.031±0.01 mGy/MBq, respectively. The average whole-body effective dose coefficient of 68Ga-PSMA-11 was 11±3.2 μSv/MBq. The highest activity uptake of 6.32% was seen in the muscle. Additional organs with high uptake were kidneys (4.60%), liver (4.54%) and urinary bladder (1.45%). The effective dose coefficient calculated by NURBS phantoms was lower than the old stylized computational phantoms by -17%. Kidneys were the critical organ for 68Ga-PSMA-11 radiopharmaceutical. The effective dose coefficient obtained in this study was slightly lower than previous literature as the single-time point data acquisition was used. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) is one of the top three causes of death worldwide, characterized by emphysema and bronchitis. Airway measurements reflect the severity of bronchitis and other airway-related diseases. Airway structures can be objectively evaluated with quantitative computed tomography (CT). The accuracy of such quantifications is limited by the spatial resolution and image noise characteristics of the imaging system and can be potentially improved with the emerging photon-counting CT (PCCT) technology. This study evaluated the quantitative performance of PCCT against energy-integrating CT (EICT) systems for airway measurements, and further identified optimum CT imaging parameters for such quantifications. The study was performed using a novel virtual imaging framework by developing the first library of virtual patients with bronchitis. These virtual patients were developed based on CT images of confirmed COPD patients with varied bronchitis severity. The human models were virtually imaged at 6.3 and 12.6 mGy dose levels using a scanner-specific simulator (DukeSim), synthesizing clinical PCCT and EICT scanners (NAEOTOM Alpha, FLASH, Siemens). The projections were reconstructed with two algorithms and kernels at different matrix sizes and slice thicknesses. The CT images were used to quantify clinically relevant airway measurements ("Pi10" and "WA%") and compared against their ground truth values. Compared to EICT, PCCT provided more accurate Pi10 and WA% measurements by 63.1% and 68.2%, respectively. For both technologies, sharper kernels and larger matrix sizes led to more reliable bronchitis quantifications. This study highlights the potential advantages of PCCT against EICT in characterizing bronchitis utilizing a virtual imaging platform.

Objective . As cancer survivorship increases, there is growing interest in minimizing the late effects of radiation therapy such as radiogenic second cancer, which may occur anywhere in the body. Assessing the risk of late effects requires knowledge of the dose distribution throughout the whole body, including regions far from the treatment field, beyond the typical anatomical extent of clinical computed tomography (CT) scans. Approach . A hybrid phantom was developed which consists of in-field patient CT images extracted from ground truth whole-body CT scans, out-of-field mesh phantoms scaled to basic patient measurements, and a blended transition region. Four of these hybrid phantoms were created, representing male and female patients receiving proton therapy treatment in pelvic and cranial sites. To assess the performance of the hybrid approach, we simulated treatments using the hybrid phantoms, the scaled and unscaled mesh phantoms, and the ground truth whole-body CTs. We calculated absorbed dose and equivalent dose in and outside of the treatment field, with a focus on neutrons induced in the patient by proton therapy. Proton and neutron dose was calculated using a general purpose Monte Carlo code. Main results . The hybrid phantom provided equal or superior accuracy in calculated organ dose and equivalent dose values relative to those obtained using the mesh phantoms in 78% in all selected organs and calculated dose quantities. Comparatively the default mesh and scaled mesh were equal or superior to the other phantoms in 21% and 28% of cases respectively. Significance . The proposed methodology for hybrid synthesis provides a tool for whole-body organ dose estimation for individual patients without requiring CT scans of their entire body. Such a capability would be useful for personalized assessment of late effects and risk-optimization of treatment plans., (Creative Commons Attribution license.)

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 (V 15 ) 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. V 15 , mean dose, and minimum dose received by 1% of the volume (D 1 ), and by 95% of the volume (D 95 ) 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 V 15 and mean dose, respectively. In the second dosimetric study, V 15 and mean dose were significantly different (p < 0.05) for all studied organs except the fully in-beam organs. D 1 and D 95 were 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., (Creative Commons Attribution license.)

Stylized and voxelized phantoms have been used to estimate S-values for positron-emitting radionuclides. However, there is a lack of computational phantoms that include head and brain structures of importance for neuroimaging studies, such as brain PET-CT. The aim of this work was to construct a multi-resolution whole-body phantom for Monte Carlo simulations in MCNP code that includes a complete set of head and brain structures. The International Commission on Radiological Protection (ICRP-110) male reference phantom and the Zubal head phantom were used to construct the ICRP-HEAD phantom. This multi-resolution phantom was used to calculate self-absorbed fractions (SAFs) and S-values for seven positron-emitting radionuclides used in PET neuroimaging (C-11, O-15, F-18, Cu-64, I-124, Ga-68, and Y-86). S-values calculated in this work were compared with two head/brain phantoms previously published: the stylized MIRD-15 phantom and the tomographic VIP-Man phantom. The voxel resolution of the phantom resulted well suited for Monte Carlo simulations in MCNP6.2 code. For the same target and source structure, the highest auto absorbed S-values were produced by O-15 and Ga-68, while for different target and source structures, Y-86 produced the highest S-values. The lowest S-values were produced by Cu-64. Comparison of S-values with those calculated from the MIRD-15 phantom showed significant differences, while a better agreement was found with those calculated from the VIP-Man phantom. The S-values obtained in this work could help to improve the accuracy of absorbed dose in brain and head structures for positron-emitting radionuclides used in PET neuroimaging. • A multi-resolution whole-body phantom was constructed in MCNP code that include a complete set of head and brain structures. • A voxel phantom was constructed based on the ICRP-110 adult male reference phantom and on the Zubal head phantom. • Self-absorbed fractions (self-AFs) and S-values were calculated for seven positron-emitting radionuclides. • The constructed ICRP-head phantom provides a more accurate representation of the head and brain structures. [ABSTRACT FROM AUTHOR]

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-131 S values derived from the reference computational phantoms of the International Commission on Radiological Protection (ICRP). However, the use of the S values 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-131 S values (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 the S values tend to decrease with increasing body height; for example, the S value (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 the S values tend to decrease with increasing body weight for some organs/tissues; for example, the S value (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, the S values tend to increase with increasing body weight; for example, the S value (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-dependent S values deviated to within 25% from those of the reference phantoms. We believe that the use of body-size-dependent S values in dose reconstructions should help quantify the dosimetric uncertainty in epidemiologic investigations of RAI-treated patients., (© 2020 Society for Radiological Protection. Published on behalf of SRP by IOP Publishing Limited. All rights reserved.)

Purpose: We previously developed an age-scalable 3D computational phantom that has been widely used for retrospective whole-body dose reconstructions of conventional two-dimensional historic radiation therapy (RT) treatments in late effects studies of childhood cancer survivors. This phantom is modeled in the FORTRAN programming language and is not readily applicable for dose reconstructions for survivors treated with contemporary RT whose treatment plans were designed using computed tomography images and complex treatment fields. The goal of this work was to adapt the current FORTRAN model of our age-scalable computational phantom into Digital Imaging and Communications in Medicine (DICOM) standard so that it can be used with any treatment planning system (TPS) to reconstruct contemporary RT. Additionally, we report a detailed description of the phantom's age-based scaling functions, information that was not previously published., Method: We developed a Python script that adapts our phantom model from FORTRAN to DICOM. To validate the conversion, we compared geometric parameters for the phantom modeled in FORTRAN and DICOM scaled to ages 1 month, 6 months, 1, 2, 3, 5, 8, 10, 15, and 18 years. Specifically, we calculated the percent differences between the corner points and volume of each body region and the normalized mean square distance (NMSD) between each of the organs. In addition, we also calculated the percent difference between the heights of our DICOM age-scaled phantom and the heights (50th percentile) reported by the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC) for male and female children of the same ages. Additionally, we calculated the difference between the organ masses for our DICOM phantom and the organ masses for two reference phantoms (from International Comission on Radiation Protection (ICRP) 89 and the University of Florida/National Cancer Institute reference hybrid voxel phantoms) for ages newborn, 1, 5, 10, 15 and adult. Lastly, we conducted a feasibility study using our DICOM phantom for organ dose calculations in a commercial TPS. Specifically, we simulated a 6 MV photon right-sided flank field RT plan for our DICOM phantom scaled to age 3.9 years; treatment field parameters and age were typical of a Wilms tumor RT treatment in the Childhood Cancer Survivor Study. For comparison, the same treatment was simulated using our in-house dose calculation system with our FORTRAN phantom. The percent differences (between FORTRAN and DICOM) in mean dose and percent of volume receiving dose ⩾5 Gy were calculated for two organs at risk, liver and pancreas., Results: The percent differences in corner points and the volumes of head, neck, and trunk body regions between our phantom modeled in FORTRAN and DICOM agreed within 3%. For all of the ages, the NMSDs were negliglible with a maximum NMSD of 7.80 × 10 -2 mm for occiptital lobe of 1 month. The heights of our age-scaled phantom agreed with WHO/CDC data within 7% from infant to adult, and within 2% agreement for ages 5 years and older. We observed that organ masses in our phantom are less than the organ masses for other reference phantoms. Dose calculations done with our in-house calculation system (with FORTRAN phantom) and commercial TPS (with DICOM phantom) agreed within 7%., Conclusion: We successfully adapted our phantom model from the FORTRAN language to DICOM standard and validated its geometric consistency. We also demonstrated that our phantom model is representative of population height data for infant to adult, but that the organ masses are smaller than in other reference phantoms and need further refinement. Our age-scalable computational phantom modeled in DICOM standard can be scaled to any age at RT and used within a commercial TPS to retrospectively reconstruct doses from contemporary RT in childhood cancer survivors.

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities., (© 2020 Society of Photo-Optical Instrumentation Engineers (SPIE).)

The aim of this study was to develop and validate a simulation platform that generates photon-counting CT images of voxelized phantoms with detailed modeling of manufacturer-specific components including the geometry and physics of the x-ray source, source filtrations, anti-scatter grids, and photon-counting detectors. The simulator generates projection images accounting for both primary and scattered photons using a computational phantom, scanner configuration, and imaging settings. Beam hardening artifacts are corrected using a spectrum and threshold dependent water correction algorithm. Physical and computational versions of a clinical phantom (ACR) were used for validation purposes. The physical phantom was imaged using a research prototype photon-counting CT (Siemens Healthcare) with standard (macro) mode, at four dose levels and with two energy thresholds. The computational phantom was imaged with the developed simulator with the same parameters and settings used in the actual acquisition. Images from both the real and simulated acquisitions were reconstructed using a reconstruction software (FreeCT). Primary image quality metrics such as noise magnitude, noise ratio, noise correlation coefficients, noise power spectrum, CT number, in-plane modulation transfer function, and slice sensitivity profiles were extracted from both real and simulated data and compared. The simulator was further evaluated for imaging contrast materials (bismuth, iodine, and gadolinium) at three concentration levels and six energy thresholds. Qualitatively, the simulated images showed similar appearance to the real ones. Quantitatively, the average relative error in image quality measurements were all less than 4% across all the measurements. The developed simulator will enable systematic optimization and evaluation of the emerging photon-counting computed tomography technology.