Monte Carlo Computer Model Research Articles

Modelling Gd-diamond and Gd-SiC neutron detectors

A custom Monte Carlo (MC) computer model was developed to simulate thermal neutron absorption in, and subsequent photon and electron emission from, natural Gd with a view to using the material as a neutron conversion layer for neutron detectors. The MC code also modelled photon and electron detection with two dissimilar detectors: a thick (500 μm) single crystal diamond detector; and a thin (5.15 μm) commercial off the shelf (COTS) 4H–SiC photodiode detector. The detectors’ quantum detection efficiencies (QE) for hard X-rays and γ-rays were relatively low in comparison to their QE for electrons, thus making it possible to collect electron spectra from the Gd layer neutron conversion products which were not overwhelmed by photon emissions from the Gd. The MC code was utilised to determine the optimal thickness of Gd for the efficient detection of a thermal neutron flux. These radiation hard and spectroscopic detectors paired with natural Gd could find utility as robust and compact thermal neutron detectors for nuclear science and engineering, space science, and other applications.

Lagrangian perspective on the expansion dynamics and shielding effect of femtosecond laser-induced copper plasma plumes

Femtosecond laser ablation of metals generates a strongly ionized plasma plume near the irradiated surface. The resulting plasma shielding effect can reduce subsequent laser energy deposition and lower nanomachining efficiency, especially during multi-pulse irradiation. Understanding the spatiotemporal evolution of the laser-induced plasma and its associated shielding effect is, therefore, crucial. A hybrid two-temperature and direct simulation Monte Carlo (TTM-DSMC) computational model is developed in this study, which synergistically couples the ultrafast laser–metal interaction physics and the plasma collisional transport. The model simulates the plasma properties including electron density, temperature dynamics, reflectivity, and energy attenuation throughout the plume expansion process from femtosecond to nanosecond timescales. A complex “penguin-shaped” plasma plume with internal shockwaves is observed due to the effects of double-pulse irradiation. Significantly enhanced plasma reflectivity and reduced laser energy deposition demonstrate the accumulated shielding effect, which increases with higher plasma density accumulation when the pulse separation is insufficient. Our model provides valuable theoretical guidance for optimizing processing parameters to enhance efficiency and precision in femtosecond laser machining. The integrated TTM-DSMC approach could also facilitate the study of laser-induced plasmas in other contexts like material characterization and nanoparticle synthesis.

Pediatric Mini-Tablets: Predicting the Hidden Risk of Fill Errors

Compressed mini-tablets in sachets or capsules are an increasingly prevalent oral solid dosage form for pediatric products. While resembling adult tablets, additional care is required to control weight and potency (blend uniformity) variation due to their small size (≤2.5 mm average diameter). Additionally, sachet fill count errors complicate dose accuracy as they are difficult to resolve with weight-checking equipment. This study quantified the probability of failing content uniformity (CU) specifications (which results in the inability to release a batch) defined in USP <905> using a Monte Carlo computational model. Failure risk was modeled as a function of sachet fill count, mini-tablet weight, potency distribution, and fill error frequency. The model allows product developers to (1) determine appropriate fill counts based on anticipated product weight and potency relative standard deviation (RSD), (2) set fill error probability tolerances for sachet filling processes, (3) identify CU improvement opportunities, and (4) quantify the probability of CU failure informing risk management activities and risk disclosure for regulatory agencies. A representative product with weight and potency RSD no greater than 5%, fill count of 1-4 mini-tablets per sachet, and fill error probability per mini-tablet filled of 0.1% may experience CU batch failure probabilities as high as 8.23%, but only 0.283% if the fill count is increased to 5-10 mini-tablets per sachet. Generally, fill counts of less than five mini-tablets per sachet should be avoided where possible.

Direct pixel to pixel principal strain mapping from tagging MRI using end to end deep convolutional neural network (DeepStrain)

Regional soft tissue mechanical strain offers crucial insights into tissue's mechanical function and vital indicators for different related disorders. Tagging magnetic resonance imaging (tMRI) has been the standard method for assessing the mechanical characteristics of organs such as the heart, the liver, and the brain. However, constructing accurate artifact-free pixelwise strain maps at the native resolution of the tagged images has for decades been a challenging unsolved task. In this work, we developed an end-to-end deep-learning framework for pixel-to-pixel mapping of the two-dimensional Eulerian principal strains varvec{{varepsilon }}_{boldsymbol{p1}} and varvec{{varepsilon }}_{boldsymbol{p2}} directly from 1-1 spatial modulation of magnetization (SPAMM) tMRI at native image resolution using convolutional neural network (CNN). Four different deep learning conditional generative adversarial network (cGAN) approaches were examined. Validations were performed using Monte Carlo computational model simulations, and in-vivo datasets, and compared to the harmonic phase (HARP) method, a conventional and validated method for tMRI analysis, with six different filter settings. Principal strain maps of Monte Carlo tMRI simulations with various anatomical, functional, and imaging parameters demonstrate artifact-free solid agreements with the corresponding ground-truth maps. Correlations with the ground-truth strain maps were R = 0.90 and 0.92 for the best-proposed cGAN approach compared to R = 0.12 and 0.73 for the best HARP method for varvec{{varepsilon }}_{boldsymbol{p1}} and varvec{{varepsilon }}_{boldsymbol{p2}}, respectively. The proposed cGAN approach's error was substantially lower than the error in the best HARP method at all strain ranges. In-vivo results are presented for both healthy subjects and patients with cardiac conditions (Pulmonary Hypertension). Strain maps, obtained directly from their corresponding tagged MR images, depict for the first time anatomical, functional, and temporal details at pixelwise native high resolution with unprecedented clarity. This work demonstrates the feasibility of using the deep learning cGAN for direct myocardial and liver Eulerian strain mapping from tMRI at native image resolution with minimal artifacts.

Computational modeling suggests binding-induced expansion of Epsin disordered regions upon association with AP2.

Intrinsically disordered regions (IDRs) are prevalent in the eukaryotic proteome. Common functional roles of IDRs include forming flexible linkers or undergoing allosteric folding-upon-binding. Recent studies have suggested an additional functional role for IDRs: generating steric pressure on the plasma membrane during endocytosis, via molecular crowding. However, in order to accomplish useful functions, such crowding needs to be regulated in space (e.g., endocytic hotspots) and time (e.g., during vesicle formation). In this work, we explore binding-induced regulation of IDR steric volume. We simulate the IDRs of two proteins from Clathrin-mediated endocytosis (CME) to see if their conformational spaces are regulated via binding-induced expansion. Using Monte-Carlo computational modeling of excluded volumes, we generate large conformational ensembles (3 million) for the IDRs of Epsin and Eps15 and dock the conformers to the alpha subunit of Adaptor Protein 2 (AP2α), their CME binding partner. Our results show that as more molecules of AP2α are bound, the Epsin-derived ensemble shows a significant increase in global dimensions, measured as the radius of Gyration (RG) and the end-to-end distance (EED). Unlike Epsin, Eps15-derived conformers that permit AP2α binding at one motif were found to be more likely to accommodate binding of AP2α at other motifs, suggesting a tendency toward co-accessibility of binding motifs. Co-accessibility was not observed for any pair of binding motifs in Epsin. Thus, we speculate that the disordered regions of Epsin and Eps15 perform different roles during CME, with accessibility in Eps15 allowing it to act as a recruiter of AP2α molecules, while binding-induced expansion of the Epsin disordered region could impose steric pressure and remodel the plasma membrane during vesicle formation.

A Monte Carlo study of the impact of phosphor optical properties on EPID imaging performance

We have developed a Monte Carlo computational model of a clinically employed electronic portal imaging device (EPID), and demonstrated the impact of phosphor optical properties on the imaging performance. The EPID model was built with Geant4 application for tomographic emission. Both radiative and optical transport were included in the model. Modulation transfer function (MTF), normalized noise-power spectrum times the incident x-ray fluence (qNNPS), and detective quantum efficiency (DQE) were calculated for simulated and measured data, and their agreement was quantified by the normalized root-mean-square error (NRMSE). MTF was computed using a 100 µm wide slit tilted by 1.5° and qNNPS was estimated using the Fujita–Lubberts–Swank method. DQE was calculated from MTF and qNNPS data. The NRMSE value was 0.0467 for MTF, 0.0217 for qNNPS, and 0.0885 for DQE, showing good agreement between measurement and simulation. Five major optical properties, phosphor grain size, phosphor thickness, phosphor refractive index, binder refractive index, and packing ratio were tested for their influence on the qNNPS, MTF, and DQE(0) of the model. Generally, the effect on the qNNPS is greater than MTF, and no impact on DQE(0), except from phosphor thickness, was observed. Multiple applications, such as imager design optimization and investigations of the dosimetric performance, are expected to benefit from the validated model.

P 151 – Reliability of variables measured with an Android device during a modified timed up and go test in patients with Alzheimer’s disease

In this work we present a parallel Object kinetic Monte Carlo (OkMC) computational model implemented using GPUs (graphics processing units) computing to simulate the evolution of interacting random walkers in materials. Different test simulations were performed under different conditions and compared to analytical solutions and sequential OkMC codes. The simulation results obtained with our algorithm show to be in excellent agreement with sequential OkMC codes and analytical solutions. The speedups reached with the GPU programming with respect to sequential OkMC codes in the test cases used here were in the range [30–100]. This increased efficiency allows to follow the evolution of millions of interacting particles in a relatively short computational time in contrast to classical OkMC codes. We expect this parallel kMC algorithm based on GPU programming to allow for investigations on defect evolution in materials using simulation boxes of realistic dimensions and physical times close to those achieved experimentally.

Reaction Rate Benchmark Experiments with Miniature Fission Chambers at the Slovenian TRIGA Mark II Reactor

A series of fission rate profile measurements with miniature fission chambers, developed by the Commisariat á l’énergie atomique et auxénergies alternatives, were performed at the Jožef Stefan Institute’s TRIGA research reactor. Two types of fission chambers with different fissionable coating (235U and 238U) were used to perform axial fission rate profile measurements at various radial positions and several control rod configurations. The experimental campaign was supported by an extensive set of computations, based on a validated Monte Carlo computational model of the TRIGA reactor. The computing effort included neutron transport calculations to support the planning and design of the experiments as well as calculations to aid the evaluation of experimental and computational uncertainties and major biases. The evaluation of uncertainties was performed by employing various types of sensitivity analyses such as experimental parameter perturbation and core reaction rate gradient calculations. It has been found that the experimental uncertainty of the measurements is sufficiently low, i.e. the total relative fission rate uncertainty being approximately 5 %, in order for the experiments to serve as benchmark experiments for validation of fission rate profiles. The effect of the neutron flux redistribution due to the control rod movement was studied by performing measurements and calculations of fission rates and fission chamber responses in different axial and radial positions at different control rod configurations. It was confirmed that the control rod movement affects the position of the maximum in the axial fission rate distribution, as well as the height of the local maxima. The optimal detector position, in which the redistributions would have minimum effect on its signal, was determined.

Computational validation of the fission rate distribution experimental benchmark at the JSI TRIGA Mark II research reactor using the Monte Carlo method

A fission rate profile benchmark experiment has been performed at the Jožef Stefan Institute TRIGA Mark II reactor. The measurements were made using absolutely calibrated miniature fission chambers developed and manufactured by the Commissariat à l’Énergie Atomique et aux Énergies Alternatives. The aim of the paper is to describe the experimental set-up, fission rate measurements and to present the detailed Monte Carlo computational model of the TRIGA reactor, which was constructed with as used to compute absolute fission rate distributions in the core at a fixed control rod position, taking into account the detailed description of the experimental configuration. The paper focuses on the extensive evaluation of experimental and calculational uncertainties and biases following the International Reactor Physics Experiment Evaluation Project methodology. A comparison between the measured and computed absolute reaction rates concludes the paper, with the agreement being within one sigma standard uncertainty.

Optimum microstructural design of coated sphere filled viscoelastic composites for structural noise and vibration damping applications

An unstructured mesh Galerkin time domain finite element method is used to validate the effective viscoelastic stiffness predictions of the n-layered spherical inclusion model. We study composites consisting of a solid polymer matrix filled by core-shell inclusions made up of silica spheres coated with a viscoelastic polymer layer. Assuming temperature dependent properties of the coating layer, temperature runs are performed from below to above its glass transition region. The studied composites have a stiffness contrast from 30 to 3000 and coating layer thicknesses between 1 and 0.001 relative to the sphere radius. Periodic random Monte Carlo computer models with 27 non-overlapping identical core-shell spheres are employed in the finite element calculations. It is shown that the n-layered spherical inclusion model is remarkably accurate and suitable for quick and reliable microstructural design of viscoelastic composites with layered spherical inclusions. Damped natural vibrations of viscoelastic Bernoulli-Euler beams and Kirchhoff plates are considered and, using the viscoelastic corresponding principle, a refined figure of merit for selecting best performing materials for structural noise and vibration damping applications is derived. We perform optimum vibration damping time design and demonstrate that by optimizing the thickness and the properties of the coating layers, substantial improvements can be achieved in the vibration damping characteristics of viscoelastic beams and plates.

A GPU-based parallel Object kinetic Monte Carlo algorithm for the evolution of defects in irradiated materials

In this work we present a parallel Object kinetic Monte Carlo (OkMC) computational model implemented using GPUs (graphics processing units) computing to simulate the evolution of interacting random walkers in materials. Different test simulations were performed under different conditions and compared to analytical solutions and sequential OkMC codes. The simulation results obtained with our algorithm show to be in excellent agreement with sequential OkMC codes and analytical solutions. The speedups reached with the GPU programming with respect to sequential OkMC codes in the test cases used here were in the range [30–100]. This increased efficiency allows to follow the evolution of millions of interacting particles in a relatively short computational time in contrast to classical OkMC codes. We expect this parallel kMC algorithm based on GPU programming to allow for investigations on defect evolution in materials using simulation boxes of realistic dimensions and physical times close to those achieved experimentally.

Simulation of cellular changes on Optical Coherence Tomography of human retina.

We present a methodology to assess cell level alterations on the human retina responsible for functional changes observable in the Optical Coherence Tomography data in healthy ageing and in disease conditions, in the absence of structural alterations. The methodology is based in a 3D multilayer Monte Carlo computational model of the human retina. The optical properties of each layer are obtained by solving the Maxwell's equations for 3D domains representative of small regions of those layers, using a Discontinuous Galerkin Finite Element Method (DG-FEM). Here we present the DG-FEM Maxwell 3D model and its validation against Mie's theory for spherical scatterers. We also present an application of our methodology to the assessment of cell level alterations responsible for the OCT data in Diabetic Macular Edema. It was possible to identify which alterations are responsible for the changes observed in the OCT scans of the diseased groups.

Durability and shielding performance of borated Ceramicrete coatings in beta and gamma radiation fields

Ceramicrete™, a chemically bonded phosphate ceramic, was developed for nuclear waste immobilization and nuclear radiation shielding. Ceramicrete products are fabricated by an acid–base reaction between magnesium oxide and mono potassium phosphate. Fillers are used to impart desired properties to the product. Ceramicrete’s tailored compositions have resulted in several commercial structural products, including corrosion- and fire-protection coatings. Their borated version, called Borobond™, has been studied for its neutron shielding capabilities and is being used in structures built for storage of nuclear materials. This investigation assesses the durability and shielding performance of borated Ceramicrete coatings when exposed to gamma and beta radiations to predict the composition needed for optimal shielding performance in a realistic nuclear radiation field. Investigations were conducted using experimental data coupled with predictive Monte Carlo computer model. The results show that it is possible to produce products for simultaneous shielding of all three types of nuclear radiations, viz., neutrons, gamma-, and beta-rays. Additionally, because sprayable Ceramicrete coatings exhibit excellent corrosion- and fire-protection characteristics on steel, this research also establishes an opportunity to produce thick coatings to enhance the shielding performance of corrosion and fire protection coatings for use in high radiation environment in nuclear industry.

Resolving the surface details on Venus in the balloon- or lander-borne images with a computer modeling method

Due to the presence of opaque clouds at high altitudes, it is difficult to survey the surface of Venus in the optical spectral range. At the same time, in the under-cloud layer, there are transparency windows at the wavelengths λ = 1.08, 0.85, and 0.65 μm. At these wavelengths, the gaseous absorption (in the whole atmosphere rather than only in the under-cloud layer) is weaker, and the atmospheric transparency is mainly determined by the scattering on molecules. The paper presents the results of the Monte-Carlo computer modeling of the imaging of the surface from a balloon or a lander. It has been shown that the imaging from the lower boundary of the clouds is possible.

BrachyGuide: a brachytherapy-dedicated DICOM RT viewer and interface to Monte Carlo simulation software.

This work presents BrachyGuide, a brachytherapy‐dedicated software tool for the automatic preparation of input files for Monte Carlo simulation from treatment plans exported in DICOM RT format, and results of calculations performed for its benchmarking. Three plans were prepared using two computational models, the image series of a water sphere and a multicatheter breast brachytherapy patient, for each of two commercially available treatment planning systems: BrachyVision and Oncentra Brachy. One plan involved a single source dwell position of an 192Ir HDR source (VS2000 or mHDR‐v2) at the center of the water sphere using the TG43 algorithm, and the other two corresponded to the TG43 and advanced dose calculation algorithm for the multicatheter breast brachytherapy patient. Monte Carlo input files were prepared using BrachyGuide and simulations were performed with MCNP v.6.1. For the TG43 patient plans, the Monte Carlo computational model was manually edited in the prepared input files to resemble TG43 dosimetry assumptions. Hence all DICOM RT dose exports were equivalent to corresponding simulation results and their comparison was used for benchmarking the use of BrachyGuide. Monte Carlo simulation results and corresponding DICOM RT dose exports agree within type A uncertainties in the majority of points in the computational models. Treatment planning system, algorithm, and source specific differences greater than type A uncertainties were also observed, but these were explained by treatment planning system‐related issues and other sources of type B uncertainty. These differences have to be taken into account in commissioning procedures of brachytherapy dosimetry algorithms. BrachyGuide is accurate and effective for use in the preparation of commissioning tests for new brachytherapy dosimetry algorithms as a user‐oriented commissioning tool and the expedition of retrospective patient cohort studies of dosimetry planning.PACS numbers: 87.53.Bn, 87.53.Jw, 87.55.D‐, 87.55.Qr, 87.55.km, 87.55.K‐

MO‐G‐BRF‐05: Determining Response to Anti‐Angiogenic Therapies with Monte Carlo Tumor Modeling

Purpose:Patient response to anti‐angiogenic therapies with vascular endothelial growth factor receptor – tyrosine kinase inhibitors (VEGFR TKIs) is heterogeneous. This study investigates key biological characteristics that drive differences in patient response via Monte Carlo computational modeling capable of simulating tumor response to therapy with VEGFR TKI.Methods:VEGFR TKIs potently block receptors, responsible for promoting angiogenesis in tumors. The model incorporates drug pharmacokinetic and pharmacodynamic properties, as well as patientspecific data of cellular proliferation derived from [18F]FLT‐PET data. Sensitivity of tumor response was assessed for multiple parameters, including initial partial oxygen tension (pO2), cell cycle time, daily vascular growth fraction, and daily vascular regression fraction. Results were benchmarked to clinical data (patient 2 weeks on VEGFR TKI, followed by 1‐week drug holiday). The tumor pO2 was assumed to be uniform.Results:Among the investigated parameters, the simulated proliferation was most sensitive to the initial tumor pO2. Initial change of 5 mmHg can already Result in significantly different levels of proliferation. The model reveals that hypoxic tumors (pO2 ≥ 20 mmHg) show the highest decrease of proliferation, experiencing mean FLT standardized uptake value (SUVmean) decrease for at least 50% at the end of the clinical trial (day 21). Oxygenated tumors (pO2 20 mmHg) show a transient SUV decrease (30–50%) at the end of the treatment with VEGFR TKI (day 14) but experience a rapid SUV rebound close to the pre‐treatment SUV levels (70–110%) at the time of a drug holiday (day 14–21) – the phenomenon known as a proliferative flare.Conclusion:Model's high sensitivity to initial pO2 clearly emphasizes the need for experimental assessment of the pretreatment tumor hypoxia status, as it might be predictive of response to antiangiogenic therapies and the occurrence of proliferative flare. Experimental assessment of other model parameters would further improve understanding of patient response.

Компьютерное моделирование экспериментов по физическому моделированию многофазных систем в аппаратах радиохимического производства

Manuscript represents results of testing the code MCNP forMonte Carlosimulation of neutron measurements in physical model experiments with plutonium distribution through liquid multi-phase systems with radiochemical vessels. Satisfactory convergence of calculated and experimental data has been demonstrated. In order to assess applicability of the MCNP code for multivariate calculation modeling of nuclear-physical measurements at remote analytical monitoring of fissile materials its testing was performed for Monte-Carlo computer modeling of neutron measurements in the experiments aimed at physical modeling of plutonium distribution in liquid multiphase subcritical systems in the radiochemical plant tanks. The work studied calculation modeling of neutron radiation transfer through the use of Monte-Carlo method. The choice of MCNP code for modeling was justified. The work describes physical modeling facilities of plutonium distribution in solutions with concentration of up to several units g/l and the corresponding three-dimensional computer models. Physical modeling of the solution with plutonium concentration of up to 1 g/l was carried out at the facility consisting of the cylindrical tank filled with water, the plutonium-beryllium fast neutron source of IBN type and the measuring equipment. The computer model incorporated the cylindrical tank filled water, the helium counter tube and the ambient air. Physical modeling of plutonium distribution in the solutions with concentration of several units g/l was performed at the facility consisting of the cylindrical tank filled with water, special cuvettes filled with plutonium nitrate solution and the measuring equipment. The computer model included the cylindrical tank filled with water, the cuvettes with plutonium nitrate solutions, the helium counter tube and the ambient air. The results of comparison of "physical" and "computer" measurements of neutron field distributions are provided. The obtained satisfactory agreement of the calculated and the experimental results proves applicability of the MCNP code for modeling of neutron measurements in the multiphase systems with fissile materials. Key words :Monte Carlo method, simulation, plutonium, neutron count rate, slow neutron counter. (Russian) DOI: http://dx.doi.org/10.15826/analitika.2014.18.2.004 M.R. Khusainov, E.A. Parfentiev Federal State Unitary Enterprise MAYAK Production Association, Ozersk, Russian Federation

Origin of defects on targets used to make extreme ultraviolet mask blanks

Particle formation is a major problem in extreme ultraviolet masks, and one source of these particles has been identified to be the targets used to produce the mask surfaces. In particular, the silicon (Si) and ruthenium (Ru) target appear to produce more particles, especially silicon. The evidence of this is seen as a rough region on the edges of the silicon target. The features in the region were found to be triangular mesas pointing in the direction of the incident beam. The aim of this research is to prevent the mesa formation features on the target and thus reduce particle formation on the target. Both Si and Ru targets were sputtered using different ion beam conditions to understand the mesa formation mechanisms on the target and explore the ion beam conditions that can mitigate mesas. A simple 2D Monte-Carlo computer model (Illinois surface analysis model) was used to understand the formation of mesas with different incident angles of ion beam (0°, 35°, 54°, 75°) that agrees with the shapes of mesas seen in the experiments. Additionally, srim was used to calculate sputtering yields to better understand the different mechanisms between Si and Ru. It is concluded from both experiment and calculation results that an effective way to stop mesas formation is to have a sample oscillating between 0° and the desired angle during sputtering.

Thermal Rupture of Monatomic Metal Nanowires

The present study deals with the problem of thermal stability and rupture of metal nanowires, considered here as a monatomic chain located on an atomically smooth crystalline substrate. Based on a recently developed Monte Carlo computational model, the simulation results reveal a scenario of nanowire breaking via formation of atomic vacancies. Depending on temperature, the fluctuations in the positions of the nanowire atoms generate wave-shaped nanowire configurations with specific active sites for breaking. This process is followed by formation of one-atom vacancies in the nanowire. Their overgrowth into vacancies of two, three and more atoms leads to permanent nanowire rupture and, hence, to loss of the nanowire electronic and other physical properties. The time evolution of the atomic-scale nanowire morphology and breaking mechanism are discussed in detail. The proposed model of nanowire rupture sheds light on the general problem of thermal stability of artificial atomic structures on crystal surfaces and their application to electronic and other devices with exotic physical features.

Cost‐effectiveness of alternating magnetic resonance imaging and digital mammography screening in BRCA1 and BRCA2 gene mutation carriers

AbstractBACKGROUND:Current clinical guidelines recommend earlier, more intensive breast cancer screening with both magnetic resonance imaging (MRI) and mammography for women with breast cancer susceptibility gene (BRCA) mutations. Unspecified details of screening schedules are a challenge for implementing guidelines.METHODS:A Markov Monte Carlo computer model was used to simulate screening in asymptomatic women who were BRCA1 and BRCA2 mutation carriers. Three dual‐modality strategies were compared with digital mammography (DM) alone: 1) DM and MRI alternating at 6‐month intervals beginning at age 25 years (Alt25), 2) annual MRI beginning at age 25 years with alternating DM added at age 30 years (MRI25/Alt30), and 3) DM and MRI alternating at 6‐month intervals beginning at age 30 years (Alt30). Primary outcomes were quality‐adjusted life years (QALYs), lifetime costs (in 2010 US dollars), and incremental cost‐effectiveness (dollars per QALY gained). Additional outcomes included potential harms of screening, and lifetime costs stratified into component categories (screening and diagnosis, treatment, mortality, and patient time costs).RESULTS:All 3 dual‐modality screening strategies increased QALYs and costs. Alt30 screening had the lowest incremental costs per additional QALY gained (BRCA1, $74,200 per QALY; BRCA2, $215,700 per QALY). False‐positive test results increased substantially with dual‐modality screening and occurred more frequently in BRCA2 carriers. Downstream savings in both breast cancer treatment and mortality costs were outweighed by increases in up‐front screening and diagnosis costs. The results were influenced most by estimates of breast cancer risk and MRI costs.CONCLUSIONS:Alternating MRI and DM screening at 6‐month intervals beginning at age 30 years was identified as a clinically effective approach to applying current guidelines, and was more cost‐effective in BRCA1 gene mutation carriers compared with BRCA2 gene mutation carriers. Cancer 2013. © 2012 American Cancer Society.