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Simulation of multi-photon emission isotopes using time-resolved SimSET multiple photon history generator

Abstract-Multiple-photon emitters, such as In-111 or Se-75, have enormous potential in the field of nuclear medicine imaging. For example, Se-75 can be used to investigate the bile acid malabsorption and measure the bile acid pool loss. The simulation system for emission tomography (SimSET) is a well-known Monte Carlo simulation (MCS) code in nuclear medicine for its high computational efficiency. However, current SimSET cannot simulate these isotopes due to the lack of modeling of complex decay scheme and the time-dependent decay process. To extend the versatility of SimSET for simulation of those multi-photon emission isotopes, a time-resolved multiple photon history generator based on SimSET codes is developed in present study. For developing the time-resolved SimSET (trSimSET) with radionuclide decay process, the new MCS model introduce new features, including decay time information and photon time-of-flight information, into this new code. The half-life of energy states were tabulated from the Evaluated Nuclear Structure Data File (ENSDF) database. The MCS results indicate that the overall percent difference is less than 8.5% for all simulation trials as compared to GATE. To sum up, we demonstrated that time-resolved SimSET multiple photon history generator can have comparable accuracy with GATE and keeping better computational efficiency. The new MCS code is very useful to study the multi-photon imaging of novel isotopes that needs the simulation of lifetime and the time-of-fight measurements. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

Subject-specific modeling framework for particle deposition using computational fluid dynamics

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 three-dimensional (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.

AI↗

Commissioning of a Varian Clinac iX 6 MV photon beam using Monte Carlo simulation

Monte Carlo modelling of a linear accelerator is the first and most important step in Monte Carlo dose calculations in radiotherapy. Monte Carlo is considered today to be the most accurate and detailed calculation method in different fields of medical physics. In this research, we developed a photon beam model for Varian Clinac iX 6 MV equipped with MilleniumMLC120 for dose calculation purposes using BEAMnrc/DOSXYZnrc Monte Carlo system based on the underlying EGSnrc particle transport code. Monte Carlo simulation for this commissioning head LINAC divided in two stages are design head Linac model using BEAMnrc, characterize this model using BEAMDP and analyze the difference between simulation and measurement data using DOSXYZnrc. In the first step, to reduce simulation time, a virtual treatment head LINAC was built in two parts (patient-dependent component and patient-independent component). The incident electron energy varied 6.1 MeV, 6.2 MeV and 6.3 MeV, 6.4 MeV, and 6.6 MeV and the FWHM (full width at half maximum) of source is 1 mm. Phase-space file from the virtual model characterized using BEAMDP. The results of MC calculations using DOSXYZnrc in water phantom are percent depth doses (PDDs) and beam profiles at depths 10 cm were compared with measurements. This process has been completed if the dose difference of measured and calculated relative depth-dose data along the central-axis and dose profile at depths 10 cm is ≤ 5%. The effect of beam width on percentage depth doses and beam profiles was studied. Results of the virtual model were in close agreement with measurements in incident energy electron 6.4 MeV. Our results showed that photon beam width could be tuned using large field beam profile at the depth of maximum dose. The Monte Carlo model developed in this study accurately represents the Varian Clinac iX with millennium MLC 120 leaf and can be used for reliable patient dose calculations. In this commissioning process, the good criteria of dose difference in PDD and dose profiles were achieve using incident electron energy 6.4 MeV.

61 RADIATION PROTECTION AND DOSIMETRY↗

SU-E-T-561: Monte Carlo-Based Organ Dose Reconstruction Using Pre-Contoured Human Model for Hodgkins Lymphoma Patients Treated by Cobalt-60 External Beam Therapy

Purpose: Organ doses for the Hodgkin’s lymphoma patients treated with cobalt-60 radiation were estimated using an anthropomorphic model and Monte Carlo modeling. Methods: A cobalt-60 treatment unit modeled in the BEAMnrc Monte Carlo code was used to produce phase space data. The Monte Carlo simulation was verified with percent depth dose measurement in water at various field sizes. Radiation transport through the lung blocks were modeled by adjusting the weights of phase space data. We imported a precontoured adult female hybrid model and generated a treatment plan. The adjusted phase space data and the human model were imported to the XVMC Monte Carlo code for dose calculation. The organ mean doses were estimated and dose volume histograms were plotted. Results: The percent depth dose agreement between measurement and calculation in water phantom was within 2% for all field sizes. The mean organ doses of heart, left breast, right breast, and spleen for the selected case were 44.3, 24.1, 14.6 and 3.4 Gy, respectively with the midline prescription dose of 40.0 Gy. Conclusion: Organ doses were estimated for the patient group whose threedimensional images are not available. This development may open the door to more accurate dose reconstruction and estimates of uncertainties in secondary cancer risk for Hodgkin’s lymphoma patients. This work was partially supported by the intramural research program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics.

61 RADIATION PROTECTION AND DOSIMETRY↗

Active interrogation of Special Nuclear Material containers using AmBe quasi-forward biased directional source and PGNAA

Special Nuclear Material (SNM) including 95% 235 U and 239 Pu is capable of being identified by utilizing a quasi-forward directional AmBe source from Patent No: US20190013109A1 using Prompt Gamma Neutron Activation Analysis (PGNAA) simulated with Monte-Carlo N-Particle transport 6.2 (MCNP). HPGe and LaBr 3 detector arrays were used to identify and quantify the peak-to-background and peak-to-total ratios of the associated photon spectra from the SNM encased in a polyethylene shield. The conducted simulations varied the volume of the SNM and neutron source strength in the MCNP data card to conduct an uncertainty analysis. Photopeaks identified include K-shell X-rays from 235 U and 239 Pu, 61 keV from fission, 2.223 MeV prompt gamma from hydrogen, 511 keV annihilation, and a single and double escape peak from the prompt gamma interaction from hydrogen. Relationships between peak-to-total and peak-to-background as a function of SNM and particle history were investigated to aid in the analysis. The capabilities of both detector systems to acquire well resolved photopeak with a 5% relative error or less, with a 1 Ci source activity, and a peak-to-background ratio of 1.15. Finally, this was determined to take 326 s for LaBr 3 and 163 s for HPGe which is comparable to current methods for material detection which take between 100 and 900 s to acquire.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The effect of voxel size on dose distribution in Varian Clinac iX 6 MV photon beam using Monte Carlo simulation

Recently, Monte Carlo (MC) calculation method has reported as the most accurate method of predicting dose distributions in radiotherapy. The MC code system (especially DOSXYZnrc) has been used to investigate the different voxel (volume elements) sizes effect on the accuracy of dose distributions. To investigate this effect on dosimetry parameters, calculations were made with three different voxel sizes. The effects were investigated with dose distribution calculations for seven voxel sizes: 1 × 1 × 0.1 cm{sup 3}, 1 × 1 × 0.5 cm{sup 3}, and 1 × 1 × 0.8 cm{sup 3}. The 1 × 10{sup 9} histories were simulated in order to get statistical uncertainties of 2%. This simulation takes about 9-10 hours to complete. Measurements are made with field sizes 10 × 10 cm2 for the 6 MV photon beams with Gaussian intensity distribution FWHM 0.1 cm and SSD 100.1 cm. MC simulated and measured dose distributions in a water phantom. The output of this simulation i.e. the percent depth dose and dose profile in d{sub max} from the three sets of calculations are presented and comparisons are made with the experiment data from TTSH (Tan Tock Seng Hospital, Singapore) in 0-5 cm depth. Dose that scored in voxels is a volume averaged estimate of the dose at the center of a voxel. The results in this study show that the difference between Monte Carlo simulation and experiment data depend on the voxel size both for percent depth dose (PDD) and profile dose. PDD scan on Z axis (depth) of water phantom, the big difference obtain in the voxel size 1 × 1 × 0.8 cm{sup 3} about 17%. In this study, the profile dose focused on high gradient dose area. Profile dose scan on Y axis and the big difference get in the voxel size 1 × 1 × 0.1 cm{sup 3} about 12%. This study demonstrated that the arrange voxel in Monte Carlo simulation becomes important.

61 RADIATION PROTECTION AND DOSIMETRY↗

SU-E-T-673: Recent Developments and Comprehensive Validations of a GPU-Based Proton Monte Carlo Simulation Package, GPMC

Purpose: A GPU-based Monte Carlo (MC) simulation package gPMC has been previously developed and high computational efficiency was achieved. This abstract reports our recent improvements on this package in terms of accuracy, functionality, and code portability. Methods: In the latest version of gPMC, nuclear interaction cross section database was updated to include data from TOPAS/Geant4. Inelastic interaction model, particularly the proton scattering angle distribution, was updated to improve overall simulation accuracy. Calculation of dose averaged LET (LETd) was implemented. gPMC was ported onto an OpenCL environment to enable portability across different computing devices (GPUs from different vendors and CPUs). We also performed comprehensive tests of the code accuracy. Dose from electro-magnetic (EM) interaction channel, primary and secondary proton doses and fluences were scored and compared with those computed by TOPAS. Results: In a homogeneous water phantom with 100 and 200 MeV beams, mean dose differences in EM channel computed by gPMC and by TOPAS were 0.28% and 0.65% of the corresponding maximum dose, respectively. With the Geant4 nuclear interaction cross section data, mean difference of primary proton dose was 0.84% for the 200 MeV case and 0.78% for the 100 MeV case. After updating inelastic interaction model, maximum difference of secondary proton fluence and dose were 0.08% and 0.5% for the 200 MeV beam, and 0.04% and 0.2% for the 100 MeV beam. In a test case with a 150MeV proton beam, the mean difference between LETd computed by gPMC and TOPAS was 0.96% within the proton range. With the OpenCL implementation, gPMC is executable on AMD and Nvidia GPUs, as well as on Intel CPU in single or multiple threads. Results on different platforms agreed within statistical uncertainty. Conclusion: Several improvements have been implemented in the latest version of gPMC, which enhanced its accuracy, functionality, and code portability.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Natural and Engineered Features Supporting Environmental Performance of Idaho National Laboratory's Remote-Handled Low-Level Waste Disposal Facility - 19436

The Idaho National Laboratory's (INL's) Remote-Handled Low-Level Waste (RH LLW) Disposal Facility has been designed and constructed to receive waste generated at the INL site in support of the US DOE Office of Nuclear Energy (NE) and Naval Reactors (NR) missions. The facility has been designed to receive legacy RH LLW currently in storage at INL facilities and new waste generated by nuclear research programs. RH LLW to be received at the facility is solid waste consisting of surface contaminated materials; ion exchange resins used to purify cooling and canal water; and activated metal components generated during reactor core change outs and Naval spent fuel management; and nuclear R and D. Disposal of INL's RH LLW poses unique disposal challenges due to high radiation levels (contact rates up to 600 Sv/hr [60,000 Rem/hr]) that require remote handling and adequate shielding for transportation and disposal. The facility has been designed to meet the requirements of DOE Order 435.1, Radioactive Waste Management, including the all-pathways dose, air pathway dose, inadvertent intruder doses, and radon emissions limits. This paper presents an overview of natural and engineered design features that support the safety case and enhance the environmental performance of the facility. These features include location selection, use of reinforced pre-cast concrete vaults; a robust hydraulic drainage system; use of steel waste canisters for waste disposal; the facility monitoring system; facility layout; and crediting waste forms. The facility performance assessment (PA) developed to meet the requirements of DOE Order 435.1, credits each of these protective features. Releases from waste forms disposed of at this facility are limited by corrosion of the steel waste canisters which will ultimately allow contact with infiltrating water followed by transport of radionuclides from the vault system. The steel waste canisters were credited for their ability to limit water contact with the waste based on the demonstrated ability of the reinforced pre-caste concrete vaults to provide long-term structural protection of the steel waste canisters. Verification of hydraulic and concrete performance was conducted through laboratory data, field infiltration tests supported by a robust monitoring system, and numerical modeling. Releases into the vault system from activated metals are based on site-specific corrosion data. Radionuclide transport from the vault system from all waste forms is based on site-specific climatological, hydrologic, and stratigraphic data. At INL, the groundwater pathway historically and appropriately has received the most attention. By crediting aspects of the natural system, the engineered vault system, and the waste, estimated radiologic doses via the groundwater pathway are minimal. Air pathway doses were reduced by differentially crediting corrosion of aluminum and stainless steel activated metals resulting in the pathway being screened out of the PA. Groundwater and inadvertent intruder doses were reduced through selective facility layout. This paper provides an overview of the system-wide protective features incorporated into the facility design along with an extensive reference list to supporting technical papers and analyses that provide data and interpretation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Toward Personalized Dosimetry with {sup 32}P Microparticle Therapy for Advanced Pancreatic Cancer

Purpose: To develop a Monte Carlo model for patient-specific dosimetry of {sup 32}P microparticle localized internal radionuclide therapy for advanced pancreatic cancer. Methods and Materials: Spherical tumor geometries and a pancreatic phantom were modeled, as well as different 3-dimensional non-uniform clinical pancreatic geometries based on patient-specific ultrasound images. The dosimetry simulations modeled the dose distribution due to the energy spectrum of emitted beta particles. Results: The average dose for small (3-cm diameter) and large (6-cm diameter) spherical tumors was 111 Gy (for 7.6 MBq administered activity) and 128 Gy (for 58 MBq), respectively. For the clinical 3-dimensional geometries, on the basis of patient data, the mean doses delivered to the tumor were calculated to be in the range 102 to 113 Gy, with negligible dose to the pancreas for the smallest tumor volumes. The calculated dose distributions are highly non-uniform. For the largest tumor studied, the pancreas received approximately 6% of the tumor dose (5.7 Gy). Importantly, we found that because the smallest tumor studied exhibited the most dynamic changes in volume in response to the treatment, the dose to tumor and pancreas is significantly underestimated if a static tumor volume is assumed. Conclusions: These results demonstrate the dosimetry of {sup 32}P microparticle localized internal radionuclide therapy for pancreatic cancer and the possibility of developing personalized treatment strategies. The results also highlight the importance of considering the effects of non-uniform dose distributions and dynamic change of tumor mass during treatment on the dosimetry of the tumor and critical organs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Dosimetric Comparison in Breast Radiotherapy of 4 MV and 6 MV on Physical Chest Simulator

According to the World Health Organization (2014) breast cancer is the main cause of death by cancer in women worldwide. The biggest challenge of radiotherapy in the treatment of cancer is to deposit the entire prescribed dose homogeneously in the breast, sparing the surrounding tissue. In this context, this paper aimed at evaluating and comparing internal dose distribution in the mammary gland based on experimental procedures submitted to two distinct energy spectra produced in breast cancer radiotherapy. The methodology consisted of reproducing opposite parallel fields used in the treatment of breast tumors in a chest phantom. This simulator with synthetic breast, composed of equivalent tissue material (TE), was previously developed by the NRI Research Group (UFMG). The computer tomography (CT) scan of the simulator was obtained antecedently. The radiotherapy planning systems (TPS) in the chest phantom were performed in the ECLIPSE system from Varian Medical Systems and CAT 3D system from MEVIS. The irradiations were reproduced in the Varian linear accelerator, model SL- 20 Precise, 6 MV energy and Varian linear accelerator, 4 MV Clinac 6x SN11 model. Calibrations of the absorbed dose versus optical density from radiochromic films were generated in order to obtain experimental dosimetric distribution at the films positioned within the glandular and skin equivalent tissues of the chest phantom. The spatial dose distribution showed equivalence with the TPS on measurement data performed in the 6 MV spectrum. The average dose found in radiochromic films placed on the skin ranged from 49 to 79%, and from 39 to 49% in the mammary areola, for the prescribed dose. Dosimetric comparisons between the spectra of 4 and 6 MV, keeping the constant geometry of the fields applied in the same phantom, will be presented showing their equivalence in breast radiotherapy, as well as the variations will be discussed. To sum up, the dose distribution has reached the value expected in the breast dose of the 180 cGy in a wide range of the film in the glandular TE in both spectra. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Real-Time, Adaptive Radiological Anomaly Detection and Isotope Identification Using Non-Negative Matrix Factorization

Spectroscopic anomaly detection and isotope identification algorithms are integral components in nuclear nonproliferation applications such as search operations. The task is especially challenging in the case of mobile detector systems because the observed gamma-ray background changes more than for a static detector system, and a pretrained background model can easily find itself out of domain. The result is that algorithms may exceed their intended false alarm rate or sacrifice detection sensitivity to maintain the desired false alarm rate. Non-negative matrix factorization (NMF) is a powerful tool for spectral anomaly detection and identification, but, like many similar algorithms that rely on data-driven background models, in its conventional implementation, it is unable to update in real time to account for environmental changes that affect the background spectroscopic signature. Here, we have developed a novel NMF-based algorithm that periodically updates its background model to accommodate changing environmental conditions. The adaptive NMF algorithm involves fewer assumptions about its environment, making it more generalizable than existing NMF-based methods while maintaining or exceeding detection performance on simulated and real-world datasets.

Anomaly detection↗

Correlation of Injury Simulation with Clinical Assessment of Traumatic Brain Injury

This report contains a summary of our efforts to correlate head injury simulations predicting intracranial fluid cavitation with clinical assessments of brain injury from blunt impact to the head. Magnetic resonance imaging (MRI) data, collected on traumatic brain injury (TBI) subjects by researchers at the MIND Institute of New Mexico, was acquired for the current work. Specific blunt impact TBI case histories were selected from the TBI data for further study and possible correlation with simulation. Both group and single-subject case histories were examined. We found one single-subject case that was particularly suited for correlation with simulation. Diffusion tensor image (DTI) analysis of the TBI subject identified white matter regions within the brain displaying reductions in fractional anisotropy (FA), an indicator of local damage to the white matter axonal structures. Analysis of functional magnetic resonance image (fMRI) data collected on this individual identified localized regions of the brain displaying hypoactivity, another indicator of brain injury. We conducted high fidelity simulations of head impact experienced by the TBI subject using the Sandia head-neck-torso model and the shock physics computer code CTH. Intracranial fluid cavitation predictions were compared with maps of DTI fractional anisotropy and fMRI hypoactivity to assess whether a possible correlation exists. The ultimate goal of this work is to assess whether one can correlate simulation predictions of intracranial fluid cavitation with the brain injured sites identified by the fMRI and DTI analyses. The outcome of this effort is described in this report.

59 BASIC BIOLOGICAL SCIENCES↗

SU-E-T-657: Quantitative Assessment of Plan Robustness for Helical Tomotherapy for Head and Neck Cancer Radiotherapy

Introduction: Geometric uncertainties in daily patient setup can lead to variations in the planned dose, especially when using highly conformal techniques such as helical Tomotherapy. To account for the potential effect of geometric uncertainty, our clinical practice is to expand critical structures by 3mm expansion into planning risk volumes (PRV). The PRV concept assumes the spatial dose cloud is insensitive to patient positioning. However, no tools currently exist to determine if a Tomotherapy plan is robust to the effects of daily setup variation. We objectively quantified the impact of geometric uncertainties on the 3D doses to critical normal tissues during helical Tomotherapy. Methods: Using a Matlab-based program created and validated by Accuray (Madison, WI), the planned Tomotherapy delivery sinogram recalculated dose on shifted CT datasets. Ten head and neck patients were selected for analysis. To simulate setup uncertainty, the patient anatomy was shifted ±3mm in the longitudinal, lateral and vertical axes. For each potential shift, the recalculated doses to various critical normal tissues were compared to the doses delivered to the PRV in the original plan Results: 18 shifted scenarios created from Tomotherapy plans for three patients with head and neck cancers were analyzed. For all simulated setup errors, the maximum doses to the brainstem, spinal cord, parotids and cochlea were no greater than 0.6Gy of the respective original PRV maximum. Despite 3mm setup shifts, the minimum dose delivered to 95% of the CTVs and PTVs were always within 0.4Gy of the original plan. Conclusions: For head and neck sites treated with Tomotherapy, the use of a 3mm PRV expansion provide a reasonable estimate of the dosimetric effects of 3mm setup uncertainties. Similarly, target coverage appears minimally effected by a 3mm setup uncertainty. Data from a larger number of patients will be presented. Future work will include other anatomical sites.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control

Abstract Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices as data drift may lead to unexpected performance. This work introduces a new framework for out of distribution (OOD) detection and data drift monitoring that combines ML and geometric methods with statistical process control (SPC). We investigated different design choices, including methods for extracting feature representations and drift quantification for OOD detection in individual images and as an approach for input data monitoring. We evaluated the framework for both identifying OOD images and demonstrating the ability to detect shifts in data streams over time. We demonstrated a proof-of-concept via the following tasks: 1) differentiating axial vs. non-axial CT images, 2) differentiating CXR vs. other radiographic imaging modalities, and 3) differentiating adult CXR vs. pediatric CXR. For the identification of individual OOD images, our framework achieved high sensitivity in detecting OOD inputs: 0.980 in CT, 0.984 in CXR, and 0.854 in pediatric CXR. Our framework is also adept at monitoring data streams and identifying the time a drift occurred. In our simulations tracking drift over time, it effectively detected a shift from CXR to non-CXR instantly, a transition from axial to non-axial CT within few days, and a drift from adult to pediatric CXRs within a day—all while maintaining a low false positive rate. Through additional experiments, we demonstrate the framework is modality-agnostic and independent from the underlying model structure, making it highly customizable for specific applications and broadly applicable across different imaging modalities and deployed ML models.

Zamzmi, Ghada↗

EM Program Expectations on Implementation of DOE O 458: Radiation Protection of Public/Environment - 19553

DOE Order 458.1, Radiation Protection of the Public and Environment, was issued in 2011. DOE sites were given 18 months to implement. The revised Order promulgates requirements for property clearance actions and independent verification. DOE Order 458.1 allows for preapproved authorized limits for the clearance of property. However, when property with the potential to contain residual radioactive material does not meet preapproved authorized limits, an authorized limits package must be developed. The Order contains a range of requirements for demonstrating with reasonable assurance that dose constraints are met for any actual or likely future use of the property to be released. EM has developed a draft guidance document that provides the elements of an authorized limits package. These elements are used to review all authorized limits packages that are submitted to EM. Expected elements include property description and process knowledge documentation, current and likely future use, the conceptual site model, dose modeling methodologies, specific authorized limits, dose- or concentration-based constraints, collective dose estimate to the potentially exposed population, stakeholder communications, description of the As Low As Reasonably Achievable (ALARA) analysis, implementation plan, evaluation of difficult to assess surfaces, and independent verification plan. The draft guidance document also provides further explanation of the desired elements of an independent verification (IV) plan. An IV plan should describe the planning phase, implementation phase, assessment phase, and decision phase of an activity. The planning phase includes scope and cost, concurrent with cleanup contractor procurement, and review and approval of site radiological survey clearance program and IV program plans. The implementation phase assures sufficient collection of data and adjustment can be made as necessary. During the assessment phase, data and reports are reviewed, and coordination between the clean-up contractor and IV personnel occurs. A decision of whether or not the clearance actions need to be altered occurs during the decision phase. IV certification that the clearance action is complete also occurs during the decision phase. Issuance of the final guidance document is meant to improve the consultation process and minimize iterative interactions with EM. Standardizing and formalizing property clearance and IV actions also helps assure that cleanup actions are transparent and sustainable for future scrutiny. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Using 3D Measurements from MRI to Improve VVUQ

Magnetic resonance velocimetry (MRV) is a diagnostic that can measure 3D, three-component turbulent velocity fields in arbitrarily complex flow configurations. The approach uses magnetic resonance imaging (MRI), which is a system commonly available in radiology departments or medical research centers. MRV acquires signal from hydrogen protons in water channel flows. Despite the obvious utility of the measurements for investigating a variety of flows, comparisons with computational fluid dynamic (CFD) simulations largely retain traditional metrics, comparing velocity profiles and planes at discrete regions within the flow rather than using the 3D nature of the measured field. In this effort, MRV was conducted in a simple water channel with six spanwise-centered periodic obstacles roughly shaped as cubes. At a fully turbulent Reynolds number of 15,000, the channel includes two flows: a main streamwise flow and, in the wake of the second obstacle, an injected flow oriented perpendicular to the streamwise flow. The flow geometry includes partial obstacles on the side walls and is inherently 3D because of the interaction of the two streams and the wake features, making the flow challenging to completely measure with traditional optical techniques. Aside from line profiles and planar comparisons, two 3D metrics are used to compare the data with a steady Reynolds-averaged Navier–Stokes (RANS) simulation result. A brief discussion about the comparison is provided, including comments about uncertainty.

Benson, Mike [ORNL] (ORCID:000000023210116X)↗

NaroNet: Discovery of tumor microenvironment elements from highly multiplexed images

Understanding the spatial interactions between the elements of the tumor microenvironment -i.e. tumor cells. fibroblasts, immune cells- and how these interactions relate to the diagnosis or prognosis of a tumor is one of the goals of computational pathology. We present NaroNet, a deep learning framework that models the multi-scale tumor microenvironment from multiplex-stained cancer tissue images and provides patient-level interpretable predictions using a seamless end-to-end learning pipeline. Trained only with multiplex-stained tissue images and their corresponding patient-level clinical labels, NaroNet unsupervisedly learns which cell phenotypes, cell neighborhoods, and neighborhood interactions have the highest influence to predict the correct label. To this end, NaroNet incorporates several novel and state-of-the-art deep learning techniques, such as patch-level contrastive learning, multi-level graph embeddings, a novel max-sum pooling operation, or a metric that quantifies the relevance that each microenvironment element has in the individual predictions. We validate NaroNet using synthetic data simulating multiplex-immunostained images where a patient label is artificially associated to the -adjustable- probabilistic incidence of different microenvironment elements. We then apply our model to two sets of images of human cancer tissues: 336 seven-color multiplex-immunostained images from 12 high-grade endometrial cancer patients; and 382 35-plex mass cytometry images from 215 breast cancer patients. In both synthetic and real datasets, NaroNet provides outstanding predictions of relevant clinical information while associating those predictions to the presence of specific microenvironment elements.

60 APPLIED LIFE SCIENCES↗

Role of belly board device in the age of intensity modulated radiotherapy for pelvic irradiation

Small bowel dose often represents a limiting factor for radiation treatment of pelvic malignancies. To reduce small bowel toxicity, a belly board device (BBD) with a prone position is often recommended. Intensity modulated radiotherapy (IMRT) could reduce dose to small bowel based on the desired dose-volume constraints. We investigated the efficacy of BBD in conjunction with IMRT. A total of 11 consecutive patients with the diagnosis of rectal cancer, who were candidates for definitive therapy, were selected. Patients were immobilized with BBD in prone position for simulation and treatment. Supine position computed tomography (CT) data were either acquired at the same time or during a diagnostic scan, and if existed was used. Target volumes (TV) as well as organs at risk (OAR) were delineated in both studies. Three-dimensional conformal treatment (3DCRT) and IMRT plans were made for both scans. Thus for each patient, 4 plans were generated. Statistical analysis was conducted for maximum, minimum, and mean dose to each structure. When comparing the normalized mean Gross TV dose for the different plans, there was no statistical difference found between the planning types. There was a significant difference in small bowel sparing when using prone position on BBD comparing 3DCRT and IMRT plans, favoring IMRT with a 29.6% reduction in dose (p = 0.007). There was also a statistically significant difference in small bowel sparing when comparing supine position IMRT to prone-BBD IMRT favoring prone-BBD IMRT with a reduction of 30.3% (p = 0.002). For rectal cancer when small bowel could be a limiting factor, prone position using BBD along with IMRT provides the best sparing. We conclude that whenever a dose escalation in rectal cancer is desired where small bowel could be limiting factor, IMRT in conjunction with BBD should be selected.

61 RADIATION PROTECTION AND DOSIMETRY↗