Tuning spatially fractionated radiotherapy dose profiles using the moiré effect.

Spatially Fractionated Radiotherapy (SFRT) has demonstrated promising potential in cancer treatment, combining the advantages of reduced post-radiation effects and enhanced local control rates. Within this paradigm, proton minibeam radiotherapy (pMBRT) was suggested as a new treatment modality, possibly producing superior normal tissue sparing to conventional proton therapy, leading to improvements in patient outcomes. However, an effective and convenient beam generation method for pMBRT, capable of implementing various optimum dose profiles, is essential for its real-world application. Our study investigates the potential of utilizing the moiré effect in a dual collimator system (DCS) to generate pMBRT dose profiles with the flexibility to modify the center-to-center distance (CTC) of the dose distribution in a technically simple way.We employ the Geant4 Monte Carlo simulations tool to demonstrate that the angle between the two collimators of a DCS can significantly impact the dose profile. Varying the DCS angle from 10 ∘ to 50 ∘ we could cover CTC ranging from 11.8 mm to 2.4 mm, respectively. Further investigations reveal the substantial influence of the multi-slit collimator's (MSC) physical parameters on the spatially fractionated dose profile, such as period (CTC), throughput, and spacing between MSCs. These findings highlight opportunities for precision dose profile adjustments tailored to specific clinical scenarios.The DCS capacity for rapid angle adjustments during the energy transition stages of a spot scanning system can facilitate dynamic alterations in the irradiation profile, enhancing dose contrast in normal tissues. Furthermore, its unique attribute of spatially fractionated doses in both lateral directions could potentially improve normal tissue sparing by minimizing irradiated volume. Beyond the realm of pMBRT, the dual MSC system exhibits remarkable versatility, showing compatibility with different types of beams (X-rays and electrons) and applicability across various SFRT modalities.Our study illuminates the dual MSC system's potential as an efficient and adaptable tool in the refinement of pMBRT techniques. By enabling meticulous control over irradiation profiles, this system may expedite advancements in clinical and experimental applications, thereby contributing to the evolution of SFRT strategies.

[Research Photon Energy Spectrum of Medical Linear Accelerator by Monte Carlo Method].

Objective: The distribution of the photon energy spectrum in isocenter plane of the medical linear accelerator and the influence of secondary collimator on the photon energy spectrum are studied. Methods Use the BEAMnrc program to simulate the transmission of the 6 MeV electrons and photons in 5 cm×5 cm,10 cm×10 cm,15 cm×15 cm and 20 cm×20 cm fields in treatment head of the medical linear accelerator, where a phase space file was set up at the isocenter plane to record the particle information passing through this plane. The BEAMdp program is used to analyze the phase space file, in order to obtain the distribution of the photon energy spectrum in isocenter plane and the influence of secondary collimator on the photon energy spectrum. Results: By analyzing the photon energy spectrum of a medical linear accelerator with a nominal energy of 6 MV, it is found that the secondary collimator has little effect on the photon energy spectrum; different fields have different photon energy spectrum distributions; the photon energy spectrum in different central regions of the same field have the same normalized distribution. Conclusion: In the dose calculation of radiation therapy, the influence of photon energy spectrum should be carefully considered.

Monte Carlo simulation of the effect of melanin concentration on light-tissue interactions in transmittance and reflectance finger photoplethysmography.

Photoplethysmography (PPG) uses light to detect volumetric changes in blood, and is integrated into many healthcare devices to monitor various physiological measurements. However, an unresolved limitation of PPG is the effect of skin pigmentation on the signal and its impact on PPG based applications such as pulse oximetry. Hence, an in-silico model of the human finger was developed using the Monte Carlo (MC) technique to simulate light interactions with different melanin concentrations in a human finger, as it is the primary determinant of skin pigmentation. The AC/DC ratio in reflectance PPG mode was evaluated at source-detector separations of 1 mm and 3 mm as the convergence rate (Q), a parameter that quantifies the accuracy of the simulation, exceeded a threshold of 0.001. At a source-detector separation of 3 mm, the AC/DC ratio of light skin was 0.472 times more than moderate skin and 6.39 than dark skin at 660 nm, and 0.114 and 0.141 respectively at 940 nm. These findings are significant for the development of PPG-based sensors given the ongoing concerns regarding the impact of skin pigmentation on healthcare devices.

Dosimetric feasibility study ("proof of concept") of refractory ventricular tachycardia radioablation using proton minibeams.

PURPOSE: Preclinical data demonstrated that the use of proton minibeam radiotherapy reduces the risk of toxicity in healthy tissue. Ventricular tachycardia radioablation is an area under clinical investigation in proton beam therapy. We sought to simulate a ventricular tachycardia radioablation with proton minibeams and to demonstrate that it was possible to obtain a homogeneous coverage of an arrhythmogenic cardiac zone with this technique. MATERIAL AND METHODS: An arrhythmogenic target volume was defined on the simulation CT scan of a patient, localized in the lateral wall of the left ventricle. A dose of 25Gy was planned to be delivered by proton minibeam radiotherapy, simulated using a Monte Carlo code (TOPAS v.3.7) with a collimator of 19 0.4 mm-wide slits spaced 3mm apart. The main objective of the study was to obtain a plan ensuring at least 93% of the prescription dose in 93% of the planning target volume without exceeding 110% of the prescribed dose in the planning target volume. RESULTS: The average dose in the planning treatment volume in proton minibeam radiotherapy was 25.12Gy. The percentage of the planning target volume receiving 93% (V93%), 110% (V110%), and 95% (V95%) of the prescribed dose was 94.25%, 0%, and 92.6% respectively. The lateral penumbra was 6.6mm. The mean value of the peak-to-valley-dose ratio in the planning target volume was 1.06. The mean heart dose was 2.54Gy versus 5.95Gy with stereotactic photon beam irradiation. CONCLUSION: This proof-of-concept study shows that proton minibeam radiotherapy can achieve a homogeneous coverage of an arrhythmogenic cardiac zone, reducing the dose at the normal tissues. This technique, ensuring could theoretically reduce the risk of late pulmonary and breast fibrosis, as well as cardiac toxicity as seen in previous biological studies in proton minibeam radiotherapy.

A Bayesian model-based reduced major axis regression.

Reduced major axis (RMA) regression, widely used in the fields of zoology, botany, ecology, biology, spectroscopy, and among others, outweighs the ordinary least square regression by relaxing the assumption that the covariates are without measurement errors. A Bayesian implementation of the RMA regression is presented in this paper, and the equivalence of the estimates of the parameters under the Bayesian and the frequentist frameworks is proved. This model-based Bayesian RMA method is advantageous since the posterior estimates, the standard deviations, as well as the credible intervals of the estimates can be obtained through Markov chain Monte Carlo methods directly. In addition, it is straightforward to extend to the multivariate RMA case. The performance of the Bayesian RMA approach is evaluated in the simulation study, and, finally, the proposed method is applied to analyze a dataset in the plantation.

MR compatible detectors assessment for a 0.35 T MR-linac commissioning.

PURPOSE: To assess a large panel of MR compatible detectors on the full range of measurements required for a 0.35 T MR-linac commissioning by using a specific statistical method represented as a continuum of comparison with the Monte Carlo (MC) TPS calculations. This study also describes the commissioning tests and the secondary MC dose calculation validation. MATERIAL AND METHODS: Plans were created on the Viewray TPS to generate MC reference data. Absolute dose points, PDD, profiles and output factors were extracted and compared to measurements performed with ten different detectors: PTW 31010, 31021, 31022, Markus 34045 and Exradin A28 MR ionization chambers, SN Edge shielded diode, PTW 60019 microdiamond, PTW 60023 unshielded diode, EBT3 radiochromic films and LiF µcubes. Three commissioning steps consisted in comparison between calculated and measured dose: the beam model validation, the output calibration verification in four different phantoms and the commissioning tests recommended by the IAEA-TECDOC-1583. MAIN RESULTS: The symmetry for the high resolution detectors was higher than the TPS data of about 1%. The angular responses of the PTW 60023 and the SN Edge were - 6.6 and - 11.9% compared to the PTW 31010 at 60°. The X/Y-left and the Y-right penumbras measured by the high resolution detectors were in good agreement with the TPS values except for the PTW 60023 for large field sizes. For the 0.84 × 0.83 cm2 field size, the mean deviation to the TPS of the uncorrected OF was - 1.7 ± 1.6% against - 4.0 ± 0.6% for the corrected OF whereas we found - 4.8 ± 0.8% for passive dosimeters. The mean absolute dose deviations to the TPS in different phantoms were 0 ± 0.4%, - 1.2 ± 0.6% and 0.5 ± 1.1% for the PTW 31010, PTW 31021 and Exradin A28 MR respectively. CONCLUSIONS: The magnetic field effects on the measurements are considerably reduced at low magnetic field. The PTW 31010 ionization chamber can be used with confidence in different phantoms for commissioning and QA tests requiring absolute dose verifications. For relative measurements, the PTW 60019 presented the best agreement for the full range of field size. For the profile assessment, shielded diodes had a behaviour similar to the PTW 60019 and 60023 while the ionization chambers were the most suitable detectors for the symmetry. The output correction factors published by the IAEA TRS 483 seem to be applicable at low magnetic field pending the publication of new MR specific values.

The Effect of Dose Enhancement in Tumor With Silver Nanoparticles on Surrounding Healthy Tissues: A Monte Carlo Study.

Objectives: Cancer-related death rates account for approximately one-third of all deaths, and this rate is increasing remarkably every year. In this study, we examined the dose enhancement factor (DEF) in the tumor and surrounding tissues by adding different concentrations of silver nanoparticles (AgNPs) to the brain tumor using the Monte Carlo (MC) technique. Methods: This study used MCNP6.2 simulation software. A Planning Target Volume (PTV) of 1 × 1 × 1 cm3 was placed in the center of a cubic cranial model with dimensions of 5 × 5 × 5 cm3. Five different simulations were initially generated using the simple method. These simulations included pure PTV and PTV consisting of 4 different silver concentrations (5, 10, 20, and 30 mg/g). Additionally, a model was created using the nanolattice method, considering the size, position, and distribution of the AgNPs. Irradiation was performed using a source with a 6 MV linac photon spectrum. Measurements were performed using the *f8 tally, and DEF values were calculated. Results: In the simulation study using the simple method, the DEF value of PTV increased linearly with concentration, whereas the DEF values were lower than the simulation results with the nanolattice model (1.9 vs 1.4 for 30 mg/g NP concentration). Performing the simple method, we observed no remarkable dose increase in lateral OARs surrounding PTV. While a remarkable dose decrease was observed in distal OARs, a dose increase in the proximal OAR was observed, which was consistent with that of PTV. However, according to the results obtained by performing the nanolattice method, the dose increase was observed in both the proximal OAR and the distal OAR and was similar to that of PTV. Conclusion: While enhancing the dose in the tumor by adding NPs into the tumor, it is essential to consider whether it also increases the OAR dose. In addition, simulation studies on NPs showed that the dose increase varied significantly with particle size, position, and distribution. Hence, these factors should be considered carefully.

On the reliable estimation of sequential Monod kinetic parameters.

While dozens of studies have attempted to estimate the Monod kinetic parameters of microbial reductive dechlorination, published values in the literature vary by 2-6 orders of magnitude. This lack of consensus can be attributed in part to limitations of both experimental design and parameter estimation techniques. To address these issues, Hamiltonian Monte Carlo was used to produce more than one million sets of realistic simulated microcosm data under a variety of experimental conditions. These data were then employed in model fitting experiments using a number of parameter estimation algorithms for determining Monod kinetic parameters. Analysis of data from conventional triplicate microcosms yielded parameter estimates characterized by high collinearity, resulting in poor estimation accuracy and precision. Additionally, confidence intervals computed by commonly used classical regression analysis techniques contained true parameter values much less frequently than their nominal confidence levels. Use of an alternative experimental design, requiring the same number of analyses as conventional experiments but comprised of microcosms with varying initial chlorinated ethene concentrations, is shown to result in order-of-magnitude decreases in parameter uncertainty. A Metropolis algorithm which can be run on a typical personal computer is demonstrated to return more reliable parameter interval estimates.

A photon source model for alpha-emitter radionuclides.

Objective.A Monte Carlo virtual source model named PHID (photon from Ion decay) that generates photons emitted in the complex decay chain process of alpha-emitter radionuclides is proposed, typically for use during the simulation of SPECT image acquisition.Approach.Given an alpha-emitter radionuclide, the PHID model extracts from Geant4 databases the photon emission lines from all decaying daughters for both isometric transition and atomic relaxation processes. According to a given time range, abundances and activities in the decay chain are considered thanks to the Bateman equations, taking into account the decay rates and the initial abundances.Main results.PHID is evaluated by comparison with analog Monte Carlo simulation. It generates photons with the correct energy and temporal distribution, avoiding the costly simulation of the complete decay chain thus decreasing the computation time. The exact time gain depends on the simulation setup. As an example, it is 30× faster for simulating 1 MBq of225Ac in water for 1 section Moreover, for225Ac, PHID was also compared to a simplified source model with the two main photon emission lines (218 and 440 keV). PHID shows that 2 times more particles are simulated and 60% more counts are detected in the images.Significance.PHID can simulate any alpha-emitter radionuclide available in the Geant4 database. As a limitation, photons emitted from Bremsstrahlung are ignored, but they represent only 0.7% of the photons above 30 keV and are not significant for SPECT imaging. PHID is open-source, available in GATE 10, and eases the investigation of imaging photon emission from alpha emitters.

Fano cavity test and investigation of the response of the Roos chamber irradiated by proton beams in perpendicular magnetic fields up to 1 T.

Objective. The aim of this work is to investigate the response of the Roos chamber (type 34001) irradiated by clinical proton beams in magnetic fields.Approach. At first, a Fano test was implemented in Monte Carlo software package GATE version 9.2 (based on Geant4 version 11.0.2) using a cylindrical slab geometry in a magnetic field up to 1 T. In accordance to an experimental setup (Fuchset al2021), the magnetic field correction factorskQB⃗of the Roos chamber were determined at different energies up to 252 MeV and magnetic field strengths up to 1 T, by separately simulating the ratios of chamber signalsMQ/MQB⃗,without and with magnetic field, and the dose-conversion factorsDw,QB⃗/Dw,Qin a small cylinder of water, with and without magnetic field. Additionally, detailed simulations were carried out to understand the observed magnetic field dependence.Main results. The Fano test was passed with deviations smaller than 0.25% between 0 and 1 T. The ratios of the chamber signals show both energy and magnetic field dependence. The maximum deviation of the dose-conversion factors from unity of 0.22% was observed at the lowest investigated proton energy of 97.4 MeV andB⃗= 1 T. The resultingkQB⃗factors increase initially with the applied magnetic field and decrease again after reaching a maximum at around 0.5 T; except for the lowest 97.4 MeV beam that show no observable magnetic field dependence. The deviation from unity of the factors is also larger for higher proton energies, where the maximum lies at 1.0035(5), 1.0054(7) and 1.0069(7) for initial energies ofE0= 152, 223.4 and 252 MeV, respectively.Significance. Detailed Monte Carlo studies showed that the observed effect can be mainly attributed to the differences in the transport of electrons produced both outside and inside of the air cavity in the presence of a magnetic field.

Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models.

Birth-death models play a key role in phylodynamic analysis for their interpretation in terms of key epidemiological parameters. In particular, models with piecewise-constant rates varying at different epochs in time, to which we refer as episodic birth-death-sampling (EBDS) models, are valuable for their reflection of changing transmission dynamics over time. A challenge, however, that persists with current time-varying model inference procedures is their lack of computational efficiency. This limitation hinders the full utilization of these models in large-scale phylodynamic analyses, especially when dealing with high-dimensional parameter vectors that exhibit strong correlations. We present here a linear-time algorithm to compute the gradient of the birth-death model sampling density with respect to all time-varying parameters, and we implement this algorithm within a gradient-based Hamiltonian Monte Carlo (HMC) sampler to alleviate the computational burden of conducting inference under a wide variety of structures of, as well as priors for, EBDS processes. We assess this approach using three different real world data examples, including the HIV epidemic in Odesa, Ukraine, seasonal influenza A/H3N2 virus dynamics in New York state, America, and Ebola outbreak in West Africa. HMC sampling exhibits a substantial efficiency boost, delivering a 10- to 200-fold increase in minimum effective sample size per unit-time, in comparison to a Metropolis-Hastings-based approach. Additionally, we show the robustness of our implementation in both allowing for flexible prior choices and in modeling the transmission dynamics of various pathogens by accurately capturing the changing trend of viral effective reproductive number.

A pilot study of diabetes effects on radiation attenuation characteristics of tibia and femur of rats.

This study aimed to investigate the effect of diabetes on radiation attenuation parameters of the femur and tibia of rats using Monte Carlo Simulations. First, control and diabetic rats were identified and tibias and femurs were removed. Then, the elemental ratios of the bones obtained were calculated using EDS (Energy Dissipative X-ray Spectroscopy). Therefore, radiation permeability properties of control and diabetic bones were simulated by using the content ratios in the bones in MCNP6 (Monte Carlo N-Particle) and PHITS (Particle and Heavy Ion Transport code System) 3.22 and Stopping and Range of Ions in Matter (SRIM) simulation codes. Attenuation coefficient results were compared with the NIST database via XCOM. Although differences in absorption coefficients are observed at low energies, these differences disappear as the energy increases.

Study on induced radioactivity and individual dose evaluation in Gantry room for Varian ProBeam Proton Therapy System.

Proton therapy has emerged as an advantageous modality for tumor radiotherapy due to its favorable physical and biological properties. However, this therapy generates induced radioactivity through nuclear reactions between the primary beam, secondary particles, and surrounding materials. This study focuses on systematically investigating the induced radioactivity in the gantry room during pencil beam scanning, utilizing both experimental measurements and Monte Carlo simulations. Results indicate that patients are the primary source of induced radioactivity, predominantly producing radionuclides such as 11C, 13N, and 15O. Long-term irradiation primarily generates radionuclides like 22Na, 24Na, and 54Mn etc. Additionally, this study estimates the individual doses received by medical workers in the gantry room, the irradiation dose for patient escorts, and the additional dose to patients from residual radiation. Finally, the study offers recommendations to minimize unnecessary irradiation doses to medical workers, patient escorts, and patients.

A study on the treatment of brain tumors with BNCT using several moderators with different thicknesses.

Boron neutron capture therapy (BNCT) is an effective binary radiation therapy that depends on nuclear capture reactions. In recent years, BNCT can be performed without a reactor owing to the development of accelerator-based neutron sources. A new BNCT irradiation facility is proposed, which is based on a 15 mA 2.5 MeV proton accelerator with a 100 µm thickness natural lithium target as a neutron converter. A great quantity of studies has shown that neutron beams with different spectra have unique therapeutic effects on tumors. An appropriate neutron beam for BNCT is obtained by Beam Shaping Assembly (BSA) and the moderator plays a main role in determining the BSA outlet beam spectrum. To figure out the dose distribution in phantom with various kinds of neutron spectrum modes during BNCT, a series of cases are calculated by MCNPX code. The results give a database for treatment of brain tumors with BNCT by using different moderators.

Assessing the Negative Binomial-Lindley model for crash hotspot identification: Insights from Monte Carlo simulation analysis.

Identifying hazardous crash sites (or hotspots) is a crucial step in highway safety management. The Negative Binomial (NB) model is the most common model used in safety analyses and evaluations - including hotspot identification. The NB model, however, is not without limitations. In fact, this model does not perform well when data are highly dispersed, include excess zero observations, or have a long tail. Recently, the Negative Binomial-Lindley (NB-L) model has been proposed as an alternative to the NB. The NB-L model overcomes several limitations related to the NB, such as addressing the issue of excess zero observations in highly dispersed data. However, it is not clear how the NB-L model performs regarding the hotspot identification. In this paper, an innovative Monte Carlo simulation protocol was designed to generate a wide range of simulated data characterized by different means, dispersions, and percentage of zeros. Next, the NB-L model was written as a Full-Bayes hierarchical model and compared with the Full-Bayes NB model for hotspot identification using extensive simulation scenarios. Most previous studies focused on statistical fit, and showed that the NB-L model fits the data better than the NB. In this research, however, we investigated the performance of the NB-L model in identifying the hazardous sites. We showed that there is a trade-off between the NB-L and NB when it comes to hotspot identification. Multiple performance metrics were used for the assessment. Among those, the results show that the NB-L model provides a better specificity in identifying hotspots, while the NB model provides a better sensitivity, especially for highly dispersed data. In other words, while the NB model performs better in identifying hazardous sites, the NB-L model performs better, when budget is limited, by not selecting non-hazardous sites as hazardous.

[Health Risk Assessment for an Arsenic-contaminated Site Based on Monte Carlo Simulation and Parameters Optimization].

Risk assessment is a critical part of risk management for contaminated sites. However， in the specific management practice of As-contaminated sites， it is difficult to obtain realistic health risks for contaminated sites based on the total amount of pollutants and determined values of the model， thus preventing the control requirements of later remediation to be met. An increasing number of studies have recently been conducting risk assessments by considering bioavailability， modification parameters， and combined probabilistic models. To improve the accuracy of risk assessment results， taking a large As-contaminated site as a case， 432 sampling sites were set up and collected at different depths to analyze the level and distribution characteristics of As pollution， and probabilistic risk assessment was conducted with the modification of model parameters through literature research and Monte Carlo simulation. Then， the impact of traditional methods and probabilistic methods on health risk assessment was explored in comparison. The results indicated that ω（As） in the top soil of the study area ranged from 2.70-97.0 mg·kg-1， with a spatial variation coefficient of 0.61 and weaker spatial continuity. The carcinogenic risk and hazard index obtained by the traditional risk assessment method were 2.12E-4 and 8.36， respectively， which obviously overestimated the actual risk level and were not conductive to the refined management of As-contaminated sites. Combined with modification of model parameters and probabilistic risk assessment， the non-carcinogenic risk for adults and children was found to be at an acceptable level， and the carcinogenic risk was reduced by nearly an order of magnitude compared to that in the conventional method. Considering the relative biological effectiveness （RBA） of As， the 95% quantile of the total carcinogenic risk was 1.24E-5， a reduction of up to 36.41% compared to the uncorrected corresponding risk value of 1.95E-5. The carcinogenic risk of soil As for adults and children in the study area exceeded acceptable risk levels 1E-6， with oral ingestion of soil being the primary route of exposure. In addition， the results of the sensitivity analysis of the parameters showed that As concentration， daily oral ingestion rate of soils， and exposure duration of children had relatively larger effects for health risks. This work will provide a methodological and theoretical basis for achieving accurate risk assessment of As-contaminated sites and provide concepts for refined risk management.

Performance evaluation of a 71Ga(n,γ)72Ga reaction-based epithermal neutron flux detector at an AB-BNCT device.

The 71Ga(n,γ)72Ga reaction-based epithermal neutron flux detectors are novel instruments developed to measure the epithermal neutron flux of boron neutron capture therapy (BNCT) treatment beams. In this study, a spherical epithermal neutron flux detector using 71Ga(n,γ)72Ga reaction was prototyped. The performance of the detector was experimentally evaluated at an accelerator-based BNCT (AB-BNCT) device developed by Lanzhou University, China. Based on the experimental results and related analysis, we demonstrated that the detector is a reliable tool for the quality assurance of BNCT treatment beams.

Predicting the in vivo developmental toxicity of fenarimol from in vitro toxicity data using PBTK modelling-facilitated reverse dosimetry approach.

In vitro methods are widely used in modern toxicological testing; however, the data cannot be directly employed for risk assessment. In vivo toxicity of chemicals can be predicted from in vitro data using physiologically based toxicokinetic (PBTK) modelling-facilitated reverse dosimetry (PBTK-RD). In this study, a minimal-PBTK model was constructed to predict the in-vivo kinetic profile of fenarimol (FNL) in rats and humans. The model was verified by comparing the observed and predicted pharmacokinetics of FNL for rats (calibrator) and further applied to humans. Using the PBTK-RD approach, the reported in vitro developmental toxicity data for FNL was translated to in vivo dose-response data to predict the assay equivalent oral dose in rats and humans. The predicted assay equivalent rat oral dose (36.46 mg/kg) was comparable to the literature reported in vivo BMD10 value (22.8 mg/kg). The model was also employed to derive the chemical-specific adjustment factor (CSAF) for interspecies toxicokinetics variability of FNL. Further, Monte Carlo simulations were performed to predict the population variability in the plasma concentration of FNL and to derive CSAF for intersubject human kinetic differences. The comparison of CSAF values for interspecies and intersubject toxicokinetic variability with their respective default values revealed that the applied uncertainty factors were adequately protective.

Efficient computation of high-dimensional penalized generalized linear mixed models by latent factor modeling of the random effects.

Modern biomedical datasets are increasingly high-dimensional and exhibit complex correlation structures. Generalized linear mixed models (GLMMs) have long been employed to account for such dependencies. However, proper specification of the fixed and random effects in GLMMs is increasingly difficult in high dimensions, and computational complexity grows with increasing dimension of the random effects. We present a novel reformulation of the GLMM using a factor model decomposition of the random effects, enabling scalable computation of GLMMs in high dimensions by reducing the latent space from a large number of random effects to a smaller set of latent factors. We also extend our prior work to estimate model parameters using a modified Monte Carlo Expectation Conditional Minimization algorithm, allowing us to perform variable selection on both the fixed and random effects simultaneously. We show through simulation that through this factor model decomposition, our method can fit high-dimensional penalized GLMMs faster than comparable methods and more easily scale to larger dimensions not previously seen in existing approaches.

Characterizing imaging radiation risk in a population of 8918 patients with recurrent imaging for a better effective dose.

An updated extension of effective dose was recently introduced, namely relative effective dose ( E r ), incorporating age and sex factors. In this study we extended E r application to a population of about 9000 patients who underwent multiple CT imaging exams, and we compared it with other commonly used radiation protection metrics in terms of their correlation with radiation risk. Using Monte Carlo methods, E r , dose-length-product based effective dose ( E DLP ), organ-dose based effective dose ( E OD ), and organ-dose based risk index ( RI ) were calculated for each patient. Each metric's dependency to RI was assessed in terms of its sensitivity and specificity. E r showed the best sensitivity, specificity, and agreement with RI (R2 = 0.97); while E DLP yielded the lowest specificity and, along with E OD , the lowest sensitivity. Compared to other metrics, E r provided a closer representation of patient and group risk also incorporating age and sex factors within the established framework of effective dose.