Introduction Uptake of radiopharmaceuticals in normal organs is driven by physiology; that is, specific cell types drive the uptake and retention, which cannot be distinguished by conventional clinical imaging devices such as SPECT/CT and PET/CT. Consequently, particularly for alpha-emitters, with short ranges of energy deposition, localized activity uptake may result in localized absorbed dose (AD) distributions that highly non-uniform, with higher ADs in specific cell types that may drive overall organ toxicity, even if the whole organ mean AD is below traditional thresholds established in external beam radiation therapy (EBRT). This is true for salivary glands. Salivary gland toxicity is a quality of life concern in radioiodine treatment of thyroid cancer and more recently has become a concern for radiolabeled-PSMA therapy of prostate cancer, both Lu-177 and Ac-225. Small scale anatomical modeling and activity apportionment, the macro-to-micro methodology, has been proven to reconcile discrepancies between whole organ AD values and clinically or pre-clinically observed toxicities for alpha-particle renal and bone marrow toxicity. Objectives We present a parametrizable ‘Macro-to-Micro’ (M2μ) model that provides S-values for use in combination with time-integrated activity data for small-scale, localized, salivary gland RPT dosimetry to reconcile whole organ uptake and toxicity thresholds. Materials and Methods This model of the salivary gland has two components: a tree-branching structure composed of annular ductal cells, including excretory, lobar, interlobular cells and the acinar background voxels with dimensions set to reproduce ex-vivo murine histopathology measurements as well as human dimensions taken from cadavers . Simulations were performed by scoring and recording S-value histograms to the target ductal and acinar cells, for two beta emitters (177Lu, 131I) and one alpha emitter (225Ac). S-values were obtained for different source compartments (surface, contents, and volumes of the ductal cell annuli) using GEANT4 v11 for radiation transport calculations. Comparisons against whole gland uniform spherical self-dose S-value calculations were conducted to validate the radiation transport and to highlight differences between M2μ and conventional dosimetry approaches. Results Results from the different S-value scenarios for both the mouse and human model; both showed greater variability in comparison to the uniformly distributed activity S-value calculation with the human model showing more variation. In particular, the calculated S-values differed between different branches, depending on the geometric size of the annular ductal cells. For the surrounding acinar cells, S-values from ductal cells decreased as a function of distance from the branching structures. Conclusion This model quantifies the potential discrepancies between whole organ AD and small scale AD distributions, which are likely correlated to the observed clinical toxicity. Completion of the Macro2micro approach will require small scale activity measurements apportioned to the different compartments. This model is another example of the utility of such small scale dosimetric models. Funding Acknowledgements 2024 AAPM/ASTRO Physics Resident Seed Grant, NIH/NCI P01 CA272222, 3R01 CA116477. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Objective. In the present study, the pregnant-female mesh-type reference computational phantoms (MRCPs) of the International Commission on Radiological Protection (ICRP) were fully developed in the tetrahedral-mesh format by constructing the maternal phantoms for 8-, 10-, 15-, 20-, 25-, 30-, 35-, and 38 week fetal ages.Approach. The reference blood-inclusive organ dataset (masses, elemental compositions, and densities) and the anthropometric data (rib cage dimensions, spinal curvature and pelvic inclination angle, breast dimensions, and anthropometric parameters) were established, which were then used to develop the maternal phantoms. During the development process, the pregnant-female MRCPs were fully developed by installing the mesh-type fetal phantoms in the maternal uterus considering the shape and position of the fetus.Main results. The dosimetric impact of the phantoms, in terms of fetal dose from maternal radionuclide intake, was investigated by calculating the photon specific absorbed fractions (SAFs) for some selected maternal organs as source regions and the entire fetal phantom as a target region. The results showed that the SAFs for the older fetus were larger than those for the younger fetus when the source-target distance is long, and the opposite trend is observed when the distance is short. These results were observed due to the growth of the fetus.Significance. The pregnant-female MRCPs will serve as the only ICRP reference phantoms representing the pregnant women and fetuses. The comprehensive SAFs dataset will be computed to calculate the ICRP reference dose coefficients for fetal members of the public.

Objective. The skeleton is critical in radiation dosimetry. It is the tissue that houses both the red bone marrow (RBM) and the endosteum which are respectively linked to radiation-induced leukemia and bone cancer. The complex microstructure of these tissues provides challenges to dose assessment. Although detailed skeletal models have been developed, even the latest series of models remain voxel-based, thus limiting their anatomical and geometrical fidelity. The present study aims to develop the first mesh-based skeletal models aligned with the International Commission on Radiological Protection (ICRP) Reference Adult Male and Reference Adult Female to address these limitations. Approach. A target skeletal dataset was first established through an extensive literature review to align with the ICRP Reference Adults while achieving anatomical realism. Primitive trabecular bone models were then generated from micro-computed tomography images using Fiji/ImageJ and Blender. These models were subsequently processed through an in-house automated C++/Python program, which adjusted their trabecular bone volumes, defined their endosteal layers, and partitioned the marrow into RBM and yellow bone marrow (YBM) to generate a final series of mesh-based skeletal models consistent with the target mass dataset. Main Results. A total of 35 male and 38 female models of trabecular spongiosa were developed in a high-quality mesh format. Each model represents five distinct skeletal tissue regions: trabecular bone, and RBM and YBM within both the shallow (endosteal) and deep (non-endosteal) marrow. The models were designed to match the total skeletal tissue masses of the ICRP Reference Adults to within 0.5%. For selected cases, Monte Carlo simulations were performed by inputting them to the Particle and Heavy Ion Transport code System code together with the ICRP mesh-type reference phantoms, which showed that the improved model format enhanced specific absorbed fractions by up to 2.0-fold, while their anatomical refinement showed improvement by up to 1.6-fold. Significance. The automated modeling techniques established here show strong potential for improvements in radiological protection as well as optimization of patient-specific marrow dosimetry in radiopharmaceutical therapy.

BACKGROUND:Assessing the risk of radiation-induced hematologic cancer from medical imaging in children and adolescents might support informed decisions on the use of imaging. METHODS:We followed a retrospective cohort of 3,724,623 children born between 1996 and 2016 in six U.S. health care systems and Ontario, Canada, until the earliest of cancer or benign-tumor diagnosis, death, end of health care coverage, an age of 21 years, or December 31, 2017. Radiation doses to active bone marrow from medical imaging were quantified. Associations between hematologic cancers and cumulative radiation exposure (vs. no exposure), with a lag of 6 months, were estimated with the use of continuous-time hazards models. RESULTS:During 35,715,325 person-years of follow-up (mean, 10.1 years per person), 2961 hematologic cancers were diagnosed, primarily lymphoid cancers (2349 [79.3%]), myeloid cancers or acute leukemia (460 [15.5%]), and histiocytic- or dendritic-cell cancers (129 [4.4%]). The mean (±SD) exposure among children exposed to at least 1 mGy was 14.0±23.1 mGy overall (for comparison, 13.7 mGy was the exposure from one computed tomographic [CT] scan of the head) and 24.5±36.4 mGy among children with hematologic cancer. Cancer risk increased with cumulative dose, with a relative risk (vs. no exposure) of 1.41 (95% confidence interval [CI], 1.11 to 1.78) for 1 to less than 5 mGy, 1.82 (95% CI, 1.33 to 2.43) for 15 to less than 20 mGy, and 3.59 (95% CI, 2.22 to 5.44) for 50 to less than 100 mGy. The cumulative radiation dose to bone marrow was associated with an increased risk of all hematologic cancers (excess relative risk per 100 mGy, 2.54 [95% CI, 1.70 to 3.51; P<0.001]; relative risk for 30 vs. 0 mGy, 1.76 [95% CI, 1.51 to 2.05]) and most tumor subtypes. The excess cumulative incidence of hematologic cancers by 21 years of age among children exposed to at least 30 mGy (mean, 57 mGy) was 25.6 per 10,000. We estimated that, in our cohort, 10.1% (95% CI, 5.8 to 14.2) of hematologic cancers may have been attributable to radiation exposure from medical imaging, with higher risks from the higher-dose medical-imaging tests such as CT. CONCLUSIONS:Our study suggests an association between exposure to radiation from medical imaging and a small but significantly increased risk of hematologic cancer among children and adolescents. (Funded by the National Cancer Institute and others.).

Objective: To provide organ and effective radiation doses for common pediatric imaging examinations, which may help clinicians understand site-specific cancer risk, compare exposure across imaging modalities, and make informed care decisions. Study design: Within a large multicenter retrospective cohort, imaging utilization and associated radiation doses were estimated for children enrolled from birth into one of six US health care systems. Doses are described for examinations performed from 2012 to 2017. For computed tomography (CT), doses were estimated using examination-level technical parameters, patient height and weight, and Monte Carlo simulations. For fluoroscopy, angiography, nuclear medicine, and radiography, dose maps were developed by patient age, sex, size, and year through Monte Carlo simulations using technical parameters collected from patient examinations. The mean dose and standard deviation (SD) were calculated for each examination type, and each modality's contribution to the cohort's cumulative effective dose was calculated. Results: Eight hundred thirty-five thousand six hundred forty-three imaging examinations in 278 909 patients are included. Radiographs were the most commonly performed exam but made up 6% of radiation dose exposure. CT exams made up 4% of imaging exams but accounted for 80% of exposure. Head CT was the most common CT exam (44% of all CT). For head CT, the average radiation dose to the bone marrow (associated with hematologic cancer risk) was 9.8 mGy (SD = 6.7) and to the brain (associated with brain cancer risk) was 39 mGy (SD = 14.8). Conclusions: CT radiation doses to the bone marrow and brain fell within ranges associated with increased hematologic and brain cancer risk, and are highest in the youngest children.

Objective.To develop a computational framework coupling multiscale vascular models of the human liver for improved radiation dosimetry calculations that clearly distinguish the absorbed dose to tissue parenchyma and that to its blood content at all spatial scales. This framework thus addresses limitations of homogeneous blood/tissue organ models in present use in radiopharmaceutical therapy.Approach.High-fidelity tetrahedral mesh models of liver vasculature were constructed at two spatial scales. At the macroscale, detailed hepatic arterial, venous, and portal venous networks were generated within reference adult male and female computational phantoms. At the microscale, a classical hexagonal liver lobule model incorporating sinusoids, bile compartments, and cellular components was developed. A mathematical framework was further developed to couple Monte Carlo radiation transport results across these spatial scales, enabling comprehensive dosimetric calculations for radiation dose to both blood and parenchymal tissues.Main Results.The coupled model system successfully accounted for the entire blood content of the liver, with approximately 31% represented in macroscale vessels (⩾100μm diameter) and 69% within microscale structures. Specific absorbed fractions were computed for monoenergetic photons, electrons, and alpha particles, demonstrating reciprocity between blood-to-parenchyma and parenchyma-to-blood crossfire. ReferenceS-values were computed for 22 therapeutic and 11 diagnostic radionuclides, providing the first comprehensive dataset for blood-specific and parenchyma-specific internal dosimetry calculations in the liver.Significance.This work establishes a novel framework for multi-scale radiation transport calculations in vascularized organs, enabling separate tracking of blood and parenchymal tissue doses. The methodology has immediate applications in improving dose calculations for radiopharmaceutical therapies, Y-90 microsphere radioembolization treatment, and analysis of blood dose during external beam radiotherapy. The approach can be readily adapted for other vascularized organs, representing a significant advancement in radiation dosimetry accuracy for both therapeutic and diagnostic applications by fully and independently accounting for organ activity localized within two tissue compartments-organ blood and organ parenchyma.

PURPOSE:To develop a computational framework to investigate the implications of lymphocyte recirculation for understanding radiation-induced lymphopenia (RIL) and to compare model predictions with preclinical in vivo studies. METHODS AND MATERIALS:A whole-body compartmental model of lymphocyte migration in mice was developed, and unknown rate parameters were fitted to published experimental data. Using a stochastic representation of the model in combination with detailed mouse phantom meshes, implicit lymphocyte trajectories were computed. In parallel, a module was developed to reproduce small animal irradiation plans using either photon or proton beams. Combining these computational tools, we calculated the dose distribution of the recirculating lymphocyte pool in different irradiation scenarios and simulated the subsequent redistribution of viable lymphocytes. The relative importance of irradiation of secondary lymphoid organs (SLOs) versus the blood was investigated through in silico replications of 3 preclinical studies in which mice were locally irradiated. RESULTS:Lymphocyte recirculation between the blood and SLOs attenuates lymphocyte depletion in 1 compartment by distributing the loss throughout the system. Because only a relatively small fraction (∼17% for mice) of the recirculating lymphocyte pool is in the blood at any given time, with most lymphocytes in the SLOs, the effect of SLO irradiation is greater than that of the blood. Predicted depletion trends correlated with those observed in preclinical studies but underestimated the degree of lymphopenia. The finding that proton beams can avert lymphopenia after whole-brain irradiation by sparing head and neck lymph nodes was reproduced. CONCLUSIONS:The occurrence of RIL is associated with worse outcomes in patients with cancer but remains poorly understood. Therefore, a computational framework to replicate preclinical studies was developed to systematically investigate this phenomenon. Our simulations indicate that irradiation of SLOs contributes more to lymphocyte dose than blood irradiation. However, the expected cytotoxicity associated with the replicated preclinical studies could not fully account for the degree of lymphopenia observed.

In the present study, a comprehensive dataset of dose coefficients for idealized external electron exposures has been established using the newly released ICRP-156 pediatric mesh-type reference computational phantoms (MRCPs) in conjunction with the Geant4 Monte Carlo radiation transport code. The dataset comprises organ/ tissue-averaged absorbed dose coefficients for the 29 target organs and tissues which contribute to the effective dose, as well as effective dose coefficients, spanning three idealized, unidirectional, whole body irradiation geometries-antero-posterior (AP), postero-anterior (PA), and isotropic (ISO)-across 49 discrete electron energies from 10 keV to 10 GeV. Comparisons with the ICRP-145 adult MRCPs revealed significant age-dependent variations, with effective dose coefficients differing by up to similar to 38 times (5 years, PA, 50 keV), primarily due to variations in organ/tissue depths across different ages. Further comparisons with the ICRP-143 pediatric voxeltype reference computational phantoms (VRCPs) showed substantial differences below 10 MeV, with effective dose coefficients differing by up to four orders of magnitude, largely attributable to the inclusion of the thin skin target layer in the pediatric MRCPs. The findings of the present study are expected to serve as a valuable resource for optimizing radiological protection strategies for the pediatric population.

The International Commission on Radiological Protection (ICRP) recently released the pediatric mesh-type reference computational phantoms (MRCPs) through ICRP Publication 156 to overcome the limitations of the pediatric voxel-type reference computational phantoms (VRCPs) of ICRP Publication 143. In the present study, these pediatric MRCPs were implemented into the Geant4 Monte Carlo code to produce a comprehensive dataset of dose coefficients for idealized external photon exposure geometries. This dataset includes 29 individual organ/tissue dose coefficients and effective dose coefficients, covering six irradiation geometries (i.e., AP, PA, LLAT, RLAT, ROT, and ISO) and 55 monoenergetic photon energies ranging from 10 keV to 10 GeV. The dataset comparison with the adult MRCPs of ICRP Publication 145 revealed substantial differences in effective dose coefficients throughout most energy ranges, primarily due to the age-related variations in organ/tissue depths, the differences reaching up to a factor similar to 9. In addition, the comparisons with the pediatric VRCPs identified notable differences in effective dose coefficients, reaching up to a factor similar to 4, for photon energies below 50 keV, due to the differences in phantom geometries and updates in simulation setups. For photon energies above 50 keV, deviations in effective dose coefficients between the pediatric MRCPs and VRCPs remained within 10 %.

Estimates of organ-absorbed and committed doses to individuals exposed to radioactive materials via acute inhalation often rely on internal dose coefficients and detector responses from reference human computational models. To achieve more accurate dose assessments to United States Armed Forces service members exposed in-field, computational models with varying morphometric parameters representative of this population are necessary. The International Commission on Radiological Protection (ICRP) Publication 145 provides detailed mesh reference computational phantoms (MRCPs) for adult males and females, with morphometric parameters matched to the 50th percentile. Previously, these phantoms were 2D and 3D scaled to match desired height, mass, and secondary anthropomorphic parameters in the creation of the University of Florida / Memorial Sloan Kettering (UF/MSK) computational phantom library. To achieve body fat percentage targets required for accession into the US Armed Forces, muscle and fat volumes were adjusted accordingly, thus, creating the UF/Department of Defence computational phantom library presented in this study. A comprehensive library of mesh-type computational human phantoms was created, including 57 adult males and 49 adult females with morphometric parameters aligned with United States Armed Forces service members. Phantoms were restricted to a body mass index between 19 and 27.5, with body fat percentages below 26% for males and 36% for females. Specific absorbed fractions were computed for selected source and target combinations, demonstrating how variations in height and body mass influence energy absorption in target regions relative to the ICRP MRCPs. Radiation detector responses were also computed, revealing that higher body masses resulted in decreased registered counts in the detection volume. These findings highlight the importance of incorporating morphometric variability in computational phantoms to achieve more accurate dose assessments and radiation detection responses for United States Armed Forces service members who inhale radioactive materials in-field.

In radiopharmaceutical therapy (RPT) applications, the use of alpha-emitting radionuclides is growing in popularity for treatment of cancer due to their high energy deposition and potential for localized targeting. The design of intravenously administered therapies leveraging the short-range of alpha particles (50-100 µm) requires accurate dosimetry calculations. Current computational models used for these calculations, however, do not include tissue level details that incorporate the spatial patterns associated with blood microvessels, lymphatic vessels, or other anatomically relevant details. The objective of this study was to develop a 3D computational, tissue mimic model incorporating physiologically relevant microvascular network patterns for calculating local alpha particle dosimetry effects. It is hypothesized that to compute scale-accurate alpha particle doses, explicitly modeled blood and lymphatic microvasculature must be considered in radiation transport simulations. To obtain relevant microvascular network patterns, adult rat mesenteric tissues labeled for PECAM (blood vessel marker) and Lyve-1 (lymphatic marker) were imaged. Representative images of network regions were then imported into the Creo Parametric software and converted to a 3D surface polygon mesh model that incorporated vessel diameters, lengths and patterns. Post conversion of the structures into a tetrahedral mesh with delineated material properties was performed using POLY2TET. The model was then incorporated into the Particle and Heavy Ion Transport code System (PHITS), a Monte Carlo-based radiation transport code, and absorbed fractions were computed for the blood microvessel, lymphatic and interstitial regions. Simulations were performed for alpha particles of energies 0.5-12 MeV in increments of 0.5 MeV. The applicability of our model framework was supported by the computation of absorbed doses for alpha particles. In the low energy simulations closer to 0.5 MeV, absorbed fractions in non-source target regions were approximately zero due to minimal escape from the source regions. Absorbed fractions approached the volume fraction of the target region with increasing energy source particle. Our results provide the first estimates of alpha particle absorbed doses associated with experimentally derived blood and lymphatic microvascular structures and serve to guide whether such tissue level detail should be considered in pre-clinical treatment planning. Funding Provided by NCI Grant R01 CA248901 This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Purpose Brain radionecrosis (RN) is a significant late toxicity of radiation therapy, yet its progression remains challenging to predict because of patient-specific factors. This study develops a mechanistic model to simulate RN expansion focusing on vascular heterogeneity. Methods and Materials A 3-dimensional cellular automaton (CA) model was developed to simulate RN progression, based on the assumption that vascular heterogeneity drives its spatial dynamics. Patient-specific vasculature maps were generated by registering a synthetic brain phantom to magnetic resonance imaging-derived segmentations. Microvessel length density (Ld) was estimated to account for regional vascular heterogeneity. The model parameters—RN progression rate (k) and necrotic neighborhood threshold (ρt)—were inferred using sequential Monte Carlo approximate Bayesian computation. Probability risk maps were validated against follow-up (FU) imaging from 3 independent cases, with voxelwise agreement assessed using receiver operating characteristic analysis. Results The model successfully predicted RN expansion patterns, achieving area under the curve values of 0.87 to 0.95 in validation cases. Simulated necrotic regions exhibited anisotropic expansion influenced by local vascular density, supporting the vascular hypothesis. Patient-specific posterior distributions for progression rate reflected wide interpatient variability, whereas the necrotic neighboring effect had a narrower range. The model consistently identified high-risk voxels, with predicted necrotic regions overlapping observed RN in FU imaging. Conclusions This study presents a mechanistic model that integrates vascular heterogeneity to predict RN progression, providing interpretable, patient-specific risk maps. It extends RN evolution modeling beyond dose-based metrics, potentially aiding in refining treatment planning and adaptive FU strategies to minimize radiation-induced toxicity.

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating threedimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations - including turbulence and particle-wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

Estimation of absorbed organ doses used in computed tomography (CT) using time-intensive Monte Carlo simulations with virtual patient anatomic models is not widely reported in the literature. Using the library of computational phantoms developed by the University of Florida and the National Cancer Institute, we performed Monte Carlo simulations to calculate organ dose values for 9 CT categories representing the most common body regions and indications for imaging (reflecting low, routine, and high radiation dose examinations), stratified by patient age (in children) and effective diameter (in adults, using diameter as a measure of patient size). Our sample of 559,202 adult and 103,423 pediatric CT examinations was prospectively assembled between 2015-2020 from 156 imaging facilities from 27 healthcare organizations in 20 U.S. states and 7 countries in the University of California San Francisco International CT Dose Registry. Organ doses varied by body region and exam type. For example, the mean brain dose associated with head CT was 20 mGy [standard deviation (SD) 14] for head low dose, 46 mGy (SD 21) for head routine dose, and 64 mGy (SD 31) for head high dose scan protocols. The mean colon doses associated with abdomen and pelvis CT were 19 mGy (SD 12), 32 mGy (SD 28), and 69 mGy (SD 42) for low, routine, and high dose examinations, respectively. Organ doses in general varied modestly by patient diameter, and for many categories the organ doses among the largest quartile of patients were no more than 10% higher than doses in the smallest quartile. For example, for abdomen and pelvis high dose, the colon dose increased from 67 to 74 mGy from the smallest to the largest patients (10% increase). With few exceptions, pediatric organ doses also varied relatively little by patient age, except for the youngest children who, on average, had higher organ doses. Thyroid dose, however, tended to increase with age in neck or cervical spine and chest CT. Overall, the highest organ doses were to the skin, thyroid, brain, and eye lens. Mean organ doses differ substantially by site. The organ dose values included in this report are derived from empirical clinical exams and offer useful, representative values. Large inter-site variations demonstrate areas for radiation dose reduction. (c) 2025 by Radiation Research Society

In radiological and nuclear emergencies, military personnel and first responders are at elevated risk of internal contamination via inhalation of airborne radionuclides. Rapidin-vivoassessments are required for efficient triage, regulatory compliance, and medical intervention. This study investigates the impact of chest wall thickness (CWT) on lung counting efficiency using military-specific mesh-type human computational phantoms that represent the current standards and anthropomorphic parameters of U.S. members of the military. A 2″ × 2″ NaI(Tl) scintillation detector with digital base was modeled and benchmarked against experimental measurements using polymethyl methacrylate slab phantoms to assess attenuation effects. Monte Carlo simulations in Particle and Heavy Ion Transport code System were employed to characterize lung deposition of radionuclides, with variations in CWT examined across different anthropometric models. Results demonstrated an inverse exponential relationship between CWT and detector peak counting efficiency, with minor deviations in female phantoms due to geometric constraints. These results support improved calibration approaches forin-vivoradiation detection systems and enable more consistent internal contamination assessments across a range of body types during emergency response operations.

90Y-microsphere radioembolization has become a well-established treatment option for liver malignancies and is one of the first U.S. Food and Drug Administration-approved unsealed radionuclide brachytherapy devices to incorporate dosimetry-based treatment planning. Several different mathematical models are used to calculate the patient-specific prescribed activity of 90Y, namely, body surface area (SIR-Spheres only), MIRD single compartment, and MIRD dual compartment (partition). Under the auspices of the MIRDsoft initiative to develop community dosimetry software and tools, the body surface area, MIRD single-compartment, MIRD dual-compartment, and MIRD multicompartment models have been integrated into a MIRDy90 software worksheet. The worksheet was built in MS Excel to estimate and compare prescribed activities calculated via these respective models. The MIRDy90 software was validated against available tools for calculating 90Y prescribed activity. The results of MIRDy90 calculations were compared with those obtained from vendor and community-developed tools, and the calculations agreed well. The MIRDy90 worksheet was developed to provide a vetted tool to better evaluate patient-specific prescribed activities calculated via different models, as well as model influences with respect to varying input parameters. MIRDy90 allows users to interact and visualize the results of various parameter combinations. Variables, equations, and calculations are described in the MIRDy90 documentation and articulated in the MIRDy90 worksheet. The worksheet is distributed as a free tool to build expertise within the medical physics community and create a vetted standard for model and variable management.

Objective. The International Commission on Radiological Protection (ICRP) decided to develop pregnant-female reference computational phantoms, including the maternal and fetal phantoms, through its 2007 general recommendations. Acknowledging the advantages of the mesh geometry, the ICRP decided to develop the pregnant-female mesh-type reference computational phantoms (MRCPs) for 8, 10, 15, 20, 25, 30, 35, and 38 week fetal ages directly in the mesh format. As part of this process, the present study developed the mesh-type fetal phantoms. Approach. The reference blood-inclusive organ masses, elemental compositions, and densities were established based on various scientific literatures. Then, the phantoms were developed in accordance with the established reference dataset while reflecting the anatomical features of the developing fetus, such as fetal-age-specific anthropometric parameters, bone ossification, and contents formation time. Main results. The phantoms were developed in the tetrahedral-mesh format and can be implemented in the general-purpose Monte Carlo codes (i.e. Geant4, PHITS, MCNP6, and EGSnrc) without the necessity of the voxelization process. To explore the dosimetric impact of the developed phantoms, photon specific absorbed fractions (SAFs) were computed for energies between 10-2-101 MeV for the fetal liver and spleen as source regions and self-irradiation and cross-irradiation to the fetal brain, lungs, and urinary bladder wall as target regions. The SAFs showed the fetal-age-dependent dose trends (i.e. SAF decreases with increasing fetal age) due to organ masses increases via fetal growth. Significance. The mesh-type fetal phantoms, as part of the ICRP pregnant-female MRCPs, will be used to calculate reference dose coefficients for fetal members of the public for both the current and future ICRP general recommendations.

Advanced ovarian cancer with peritoneal metastasis is challenging to treat. Limited tumor delivery and penetration of the therapeutics to deep tumor regions are significant barriers to effective treatment. The rising radiopharmaceuticals offer hopes for patients through targeted delivery. However, site specific delivery avoiding off target effect remain critical and challenging. We have developed radioactive 166Holmium loaded mesoporous silica nanoparticles (166Ho-MSNs) that exhibited predominant accumulation to peritoneal metastases of ovarian cancer upon intraperitoneal administration. It was observed that fluorescence labeled radioactive 166Ho-MSNs distributed throughout the tumor tissues, while non-radioactive fluorescent 165Ho-MSNs showed mainly tumor surface deposition of MSNs. The deep penetration leads to uniform therapeutic radiation distribution and absorbed doses within tumors as demonstrated by the dosimetry analysis. The radiation dosing regimen consisting of two 100 µCi 166Ho-MSN doses separated by 7 days decreased tumor activity and increased the overall lifespan and ascites free survival in several models of IP tumor-bearing mice. These findings illustrate that 166Ho-MSN is promising for the treatment of ovarian peritoneal metastasis, with selective targeting advantage of the nanoparticles and limited off-target radiation exposure.