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DOE OSTI2016

Prediction of binary nanoparticle superlattices from soft potentials

Driven by the hypothesis that a sufficiently continuous short-ranged potential is able to account for shell flexibility and phonon modes and therefore provides a more realistic description of nanoparticle interactions than a hard sphere model, we compute the solid phase diagram of particles of different radii interacting with an inverse power law potential. From a pool of 24 candidate lattices, the free energy is optimized with respect to additional internal parameters and the p-exponent, determining the short-range properties of the potential, is varied between p = 12 and p = 6. The phase diagrams contain the phases found in ongoing self-assembly experiments, including DNA programmable self-assembly and nanoparticles with capping ligands assembled by evaporation from an organic solvent. Thus, the resulting phase diagrams can be mapped quantitatively to existing experiments as a function of only two parameters: Nanoparticle radius ratio (γ) and softness asymmetry.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2015

Characterizing energy dependence and count rate performance of a dual scintillator fiber-optic detector for computed tomography

Purpose: Kilovoltage (kV) x-rays pose a significant challenge for radiation dosimetry. In the kV energy range, even small differences in material composition can result in significant variations in the absorbed energy between soft tissue and the detector. In addition, the use of electronic systems in light detection has demonstrated measurement losses at high photon fluence rates incident to the detector. This study investigated the feasibility of using a novel dual scintillator detector and whether its response to changes in beam energy from scatter and hardening is readily quantified. The detector incorporates a tissue-equivalent plastic scintillator and a gadolinium oxysulfide scintillator, which has a higher sensitivity to scatter x-rays. Methods: The detector was constructed by coupling two scintillators: (1) small cylindrical plastic scintillator, 500 μm in diameter and 2 mm in length, and (2) 100 micron sheet of gadolinium oxysulfide 500 μm in diameter, each to a 2 m long optical fiber, which acts as a light guide to transmit scintillation photons from the sensitive element to a photomultiplier tube. Count rate linearity data were obtained from a wide range of exposure rates delivered from a radiological x-ray tube by adjusting the tube current. The data were fitted to a nonparalyzable dead time model to characterize the time response. The true counting rate was related to the reference free air dose air rate measured with a 0.6 cm{sup 3} Radcal{sup ®} thimble chamber as described in AAPM Report No. 111. Secondary electron and photon spectra were evaluated using Monte Carlo techniques to analyze ionization quenching and photon energy-absorption characteristics from free-in-air and in phantom measurements. The depth/energy dependence of the detector was characterized using a computed tomography dose index QA phantom consisting of nested adult head and body segments. The phantom provided up to 32 cm of acrylic with a compatible 0.6 cm{sup 3} calibrated ionization chamber to measure the reference air kerma. Results: Each detector exhibited counting losses of 5% when irradiated at a dose rate of 26.3 mGy/s (Gadolinium) and 324.3 mGy/s (plastic). The dead time of the gadolinium oxysulfide detector was determined to be 48 ns, while the dead time of the plastic scintillating detector was unable to accurately be calculated due to poor counting statistics from low detected count rates. Noticeable depth/energy dependence was observed for the plastic scintillator for depths greater than 16 cm of acrylic that was not present for measurements using the gadolinium oxysulfide scintillator, leading us to believe that quenching may play a larger role in the depth dependence of the plastic scintillator than the incident x-ray energy spectrum. When properly corrected for dead time effects, the energy response of the gadolinium oxysulfide scintillator is consistent with the plastic scintillator. Using the integrated dual detector method was superior to each detector individually as the depth-dependent measure of dose was correctable to less than 8% between 100 and 135 kV. Conclusions: The dual scintillator fiber-optic detector accommodates a methodology for energy dependent corrections of the plastic scintillator, improving the overall accuracy of the dosimeter across the range of diagnostic energies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Back-to-back inclusive dijets in DIS at small x : Sudakov suppression and gluon saturation at NLO

Back-to-back dijet cross-sections in deeply inelastic scattering (DIS) at small xBj are suppressed by many-body multiple scattering and screening effects arising from gluon saturation at high parton densities. They are similarly sensitive in these kinematics to large Sudakov logarithms from soft gluon radiation. Uncovering novel physics in this DIS channel therefore requires understanding the interplay of the two phenomena. In this work, we compute the small $x_\text{Bj}$ inclusive dijet DIS cross-section in back-to-back kinematics at next-to-leading order (NLO) in the Color Glass Condensate effective field theory (CGC EFT). Our result includes, for the first time, all real and virtual NLO contributions to the impact factor. These include all Sudakov double and single logarithm contributions, as well as all other finite $\mathcal{O}(α_s)$ terms that contribute at this order. We demonstrate explicitly that resummations of small x and Sudakov logarithms can be performed simultaneously in the CGC EFT. This requires that the JIMWLK kernel for small x evolution of the Weizsäcker-Williams (WW) gluon distribution satisfies a kinematic constraint imposed by lifetime ordering of successive gluon emissions; the corresponding modifications to the kernel, corresponding to resummations of large double transverse logarithms, are precisely of the type required to stabilize JIMWLK evolution beyond leading logarithmicaccuracy. We compute the azimuthal harmonics of the NLO back-to-back distributions and show their sensitivity to both the unpolarized and linearly polarized WW gluon distributions. Finally, we discuss how TMD factorization is broken by an emergent saturation scale at small $x$.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

Practical thermodynamics of Yukawa systems at strong coupling

Simple practical approach to estimate thermodynamic properties of strongly coupled Yukawa systems, in both fluid and solid phases, is presented. The accuracy of the approach is tested by extensive comparison with direct computer simulation results (for fluids and solids) and the recently proposed shortest-graph method (for solids). Possible applications to other systems of softly repulsive particles are briefly discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

2022 American Conference on Neutron Scattering (ACNS 2022)

The 11th American Conference on Neutron Scattering (ACNS 2022) will be held on June 5-9, 2022, in Boulder, CO. The Conference will provide essential information on the breadth and depth of current neutron-related research worldwide. Hosted by the Neutron Scattering Society of America, this year’s Conference will feature a combination of invited and contributed talks, poster sessions, and tutorials. Topics of the conference are: Advances in Neutron Facilities, Instrumentation and Software: Developments in sources, instrumentation, sample environments and control software. Hard Condensed Matter: Magnetism, correlated metals, quantum/topological materials, superconductors, ferroelectrics, multiferroics, glasses, and disorder phenomena. Submissions outlining examples of neutron scattering in industrial and engineering applications involving hard condensed matter systems are also encouraged. Soft Matter: Neutron studies of soft materials and related fields including in situ and in operando studies. Polymers, surfactants, emulsions, gels, nanoparticles, colloidal suspensions and more. Submissions of computational studies or applications of machine learning beneficial to neutron scattering experiments, as well as examples of neutron scattering in industrial and engineering applications are strongly encouraged. Biology, Biophysics and Biotechnology: Neutron studies of biological and biologically relevant systems. Proteins, bio membranes, biological assemblies, natural materials, nucleic acids, drug-delivery platforms and biomedical systems. Submissions of computational studies or applications of machine learning beneficial to biological neutron scattering experiments, as well as examples of neutron scattering in applied research involving biological systems, are strongly encouraged. Materials Chemistry and Energy: Neutron-based studies of functional materials and materials for energy applications. Examples include porous materials such as metal organic frameworks (MOFs), zeolites; phosphors; novel pigments; electrolytes; catalysts; ionic conductors/cathode materials; photovoltaic materials (hybrid perovskites); thermoelectrics; magnetocalorics/electrocalorics. Structural Materials and Engineering: Neutron scattering studies of materials and engineering processes including structural materials, concrete and metals, as well as engineering processes including combustion, corrosion, additive manufacturing, and others. Neutron Physics: Fundamental physical studies of the neutron and related areas. Emerging Applications in Neutron Scattering: Machine Learning and Data Science: Advances in computing power have contributed to rapidly evolving machine learning and data science fields that can be leveraged to the benefit of the neutron scattering community. The purpose of this session is to highlight recent advances in machine learning and data science and to serve as the foundation of a parallel data and computation track highlighting computation advances and applications in neutron scattering throughout the conference.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Stochasticity in the Switching of Nanodisks for Probabilistic Computing

Stochasticity in magnetic nanodevices is an essential characteristic for harnessing these devices to computing based on population coding or the building blocks of probabilistic computing, p-bits. A magnetic tunneling junction (MTJ) consisting of a patterned magnetic element is considered a promising computing unit in the concept of artificial neurons and p-bits. A comprehensive understanding of the stochasticity in the switching of patterned magnetic elements is crucial for realizing MTJ-based probabilistic computing technology. In the present work, the stochastic behavior in the switching process of a perpendicularly magnetized Co/Pt disk within an array was directly observed utilizing full-field soft X-ray microscopy. Within 50 repeated hysteretic cycles, the stochastic magnetization switching of individual Co/Pt disks within disk arrays is identified. We found that the stochasticity in the magnetization switching of disks considerably depends on the disk size. The stochasticity initially decreases as the disk radius gets bigger from 125 to 375 nm (region I), then increases with further enlarging the disk size to 625 nm (region II). The variance of thermal fluctuation relevant to the disk size and the multilevel switching within a disk are severely involved in the observed size-dependent stochasticity. Furthermore, this work provides the way for controlling the stochasticity in the switching of nanopatterned elements, which is a key aspect of MTJ-based probabilistic computing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A cohesive zone treatment for the material point method involving problems of large deformation and damage

A new algorithm is described that permits the use of cohesive zones in the material point method for problems involving large deformation and fracture. In contrast to previous cohesive zone implementations, this method does not utilize massless surface-element particles. Instead, cohesive tractions are computed using the shape function mappings from a reference grid configuration in combination with explicitly defined particle surface normals and surface positions. These normals and relative surface positions are updated each time step according to particle deformation. The tractions are converted to cohesive forces using the nodal areas and mapped back to particles using the same reference shape function mappings. These forces are then remapped by conventional particle-to-grid interpolation as external forces using the current-configuration shape-function mappings. This allows highly compliant cohesive zones to function over jump displacements larger than a grid cell. Upon damage, these interfaces can revert to conventional multi-field contact surfaces. This approach is general and readily applies to two and three dimensions as well as being compatible with damage-field gradient partitioning offering exceptional computational flexibility. The framework for this method enables other capabilities, such as improved contact precision using explicitly defined surface normals and positions, and a method to mitigate spurious material damage at weak discontinuities between stiff brittle materials and soft or compliant materials.

Cohesive zone↗

DOE OSTI2012

Characterization of tissue magnetic susceptibility-induced distortions for MRIgRT

Purpose: MR image geometric integrity is one of the building blocks of MRI-guided radiotherapy. In particular, tissue magnetic susceptibility-induced effects are patient-dependent and their behavior is difficult to assess and predict. In this study, the authors investigated in detail the characteristics of susceptibility ({chi}) distortions in the context of MRIgRT, including the case of two common MR-linac system configurations. Methods: The magnetic field distortions were numerically simulated for several imaging parameters and anatomical sites, i.e., brain, lung, pelvis (with air pockets), and prostate. The simulation process consisted of (a) segmentation of patient CT data into susceptibility relevant anatomical volumes (i.e., soft-tissue, bone and air/lung), (b) conversion of CT data into susceptibility masks by assigning bulk {chi} values to the structures defined at (a), (c) numerical computations of the local magnetic fields by using a finite difference algorithm, and (d) generation of the geometric distortion maps from the magnetic field distributions. For each patient anatomy, the distortions were quantified at the interfaces of anatomical structures with significantly different {chi} values. The analysis was performed for two specific orientations of the external main magnetic field (B{sub 0}) characteristic to the MR-linac systems, specifically along the z-axis for a bore MR scanner and in the (x,y)-plane for a biplanner magnet. The magnetic field local perturbations were reported in ppm. The metrics used to quantify the geometric distortions were the maximum, mean, and range of distortions. The numerical simulation algorithm was validated using phantom data measurements. Results: Susceptibility-induced distortions were determined for both quadratic and patient specific geometries. The numerical simulations showed a good agreement with the experimental data. The measurements were acquired at 1.5 and 3 T and with an encoding gradient varying between 3 and 20 mT/m by using an annular phantom mimicking the water-air and water-oil {chi} interfaces. For quadratic geometries, the magnitude of field distortion increased rapidly with the size of the inhomogeneity up to about 10 mm and then tended to plateau. This trend became more evident for materials with a larger {Delta}{chi} relative to water. The simulations showed only a slight increase in the maximum distortion values when the B{sub 0} orientation was varied with regard to the shape of the {chi} inhomogeneity. In the case of patient anatomy, the largest distortion values arose at the air-soft-tissue interface. Considering the two MR-linac system configurations and comparing the field distortion values corresponding to all organ structures, the distortions tended to be larger for the biplanar magnet. The authors provide a reference table with ppm values which can be used to easily evaluate the geometric distortions for patient data as a function of B{sub 0} and the strength of the encoding gradient. Conclusions: The susceptibility distortions were quantified as a function of multiple parameters such as the {chi} inhomogeneity size and shape, the magnitude of B{sub 0} and the readout gradient, and the orientation of B{sub 0} with respect to the sample geometry. The analysis was performed for several anatomical sites and corresponding to two B{sub 0} orientations as featured by MR-linac systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

An optimization-based approach to tailor the mechanical response of soft metamaterials undergoing rate-dependent instabilities

An optimization-based design framework is proposed to tune the response of soft metamaterials involving both geometric instabilities and nonlinear viscoelastic material behavior. Designing the response of soft metamaterials to harness instabilities and undergo large, tailored configuration changes will enable advancements in soft robotics, shock and vibration mitigation, and flexible electronics. In line with the metamaterial concept, the response of these materials is governed to a large extent by the geometric and topological makeup of their small-scale features. However, the link between structure and response is less intuitive for soft metamaterials due to their reliance upon highly nonlinear responses triggered by geometric instabilities. This is further complicated by the effects of viscoelastic relaxation, which recent studies have shown to alter the emergence of instabilities in non-intuitive ways. Here, these effects are accounted for in our framework to achieve various design objectives, including tailored force–displacement response and maximized energy absorption from both geometric and material effects. To fully automate this process, it is essential to have a completely robust equation solver for forward problems involving instabilities and viscoelastic relaxation. We achieve this by casting the search for stable mechanical equilibrium — i.e. the forward problem — as a minimization problem and utilize a trust region algorithm to robustly handle instabilities and follow energetically-favorable equilibrium paths through critical points.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Accretion of matter and spectra of binary X-ray sources in massive gravity

We study low-mass binary X-ray sources involving stellar mass black holes within massive gravity. Regarding the accretion disk, we adopt the standard model for an optically thick, cool, and geometrically thin disk by Shakura–Sunyaev. For the gravitational field generated by the black hole, we consider the analogue of the Schwarzschild–de Sitter space–time of Einstein’s theory in massive gravity, for which we found an additional term linear in the radial coordinate. Then, we compute the radial velocity, the energy density and the pressure as a function of the radial coordinate, and the X-ray emission’s soft spectral component expected from the disk. We also investigated in detail the impact of this new geometry. Our result indicates that by using observed spectra from confirmed X-ray binaries involving astrophysical black holes, we can put strong constraints on alternative theories of gravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

FLAMES─Fast, Low-Storage, Accurate, and Memory-Efficient Adaptive Sampling─Approach to Resolve Spatially Dependent Dynamics of Molecular Liquids

Many critical phenomena in soft matter occur at large length scales, necessitating the resolution of their structure and dynamics at low wavenumbers. However, resolving wavenumber-dependent dynamics computationally via molecular dynamics simulations presents significant challenges, as these phenomena span several orders of magnitude in both time and length scales, resulting in high computational costs and memory demands. Here, this work highlights the computational and memory challenges associated with analyzing molecular trajectories in reciprocal space and demonstrates a method to address them. We introduce FLAMESFast, Low-storage, Accurate, and Memory-Efficient adaptive Sampling, which is a direct method for calculation of structure factors, allowing us to select only the required number of wavevectors for binning. We also use wavenumber-dependent time steps to extract dynamics. Our FLAMES approach effectively mitigates computational and memory/storage bottlenecks. We demonstrate the method using simulations of a model system, liquid octane, at various temperatures. Comparisons with experimental data and real space computation show that the FLAMES technique achieves high accuracy in resolving temperature- and spatially dependent dynamics while being significantly more computationally efficient and requiring less memory and storage than methods based on a uniform wavevector grid and fixed temporal spacing.

Chen, Guang [Argonne National Laboratory (ANL), Ar↗

DOE OSTI2016

Nuclear magnetic relaxation by the dipolar EMOR mechanism: Three-spin systems

In aqueous systems with immobilized macromolecules, including biological tissue, the longitudinal spin relaxation of water protons is primarily induced by exchange-mediated orientational randomization (EMOR) of intra- and intermolecular magnetic dipole-dipole couplings. Starting from the stochastic Liouville equation, we have developed a non-perturbative theory that can describe relaxation by the dipolar EMOR mechanism over the full range of exchange rates, dipole couplings, and Larmor frequencies. Here, we implement the general dipolar EMOR theory for a macromolecule-bound three-spin system, where one, two, or all three spins exchange with the bulk solution phase. In contrast to the previously studied two-spin system with a single dipole coupling, there are now three dipole couplings, so relaxation is affected by distinct correlations as well as by self-correlations. Moreover, relaxation can now couple the magnetizations with three-spin modes and, in the presence of a static dipole coupling, with two-spin modes. As a result of this complexity, three secondary dispersion steps with different physical origins can appear in the longitudinal relaxation dispersion profile, in addition to the primary dispersion step at the Larmor frequency matching the exchange rate. Furthermore, and in contrast to the two-spin system, longitudinal relaxation can be significantly affected by chemical shifts and by the odd-valued (“imaginary”) part of the spectral density function. We anticipate that the detailed studies of two-spin and three-spin systems that have now been completed will provide the foundation for developing an approximate multi-spin dipolar EMOR theory sufficiently accurate and computationally efficient to allow quantitative molecular-level interpretation of frequency-dependent water-proton longitudinal relaxation data from biophysical model systems and soft biological tissue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

MO-A-BRD-10: A Fast and Accurate GPU-Based Proton Transport Monte Carlo Simulation for Validating Proton Therapy Treatment Plans

Purpose: To build a GPU-based Monte Carlo (MC) simulation of proton transport with detailed modeling of elastic and non-elastic (NE) protonnucleus interactions, for use in a very fast and cost-effective proton therapy treatment plan verification system. Methods: Using the CUDA framework, we implemented kernels for the following tasks: (1) Simulation of beam spots from our possible scanning nozzle configurations, (2) Proton propagation through CT geometry, taking into account nuclear elastic and multiple scattering, as well as energy straggling, (3) Bertini-style modeling of the intranuclear cascade stage of NE interactions, and (4) Simulation of nuclear evaporation. To validate our MC, we performed: (1) Secondary particle yield calculations in NE collisions with therapeutically-relevant nuclei, (2) Pencil-beam dose calculations in homogeneous phantoms, (3) A large number of treatment plan dose recalculations, and compared with Geant4.9.6p2/TOPAS. A workflow was devised for calculating plans from a commercially available treatment planning system, with scripts for reading DICOM files and generating inputs for our MC. Results: Yields, energy and angular distributions of secondaries from NE collisions on various nuclei are in good agreement with the Geant4.9.6p2 Bertini and Binary cascade models. The 3D-gamma pass rate at 2%–2mm for 70–230 MeV pencil-beam dose distributions in water, soft tissue, bone and Ti phantoms is 100%. The pass rate at 2%–2mm for treatment plan calculations is typically above 98%. The net computational time on a NVIDIA GTX680 card, including all CPU-GPU data transfers, is around 20s for 1×10{sup 7} proton histories. Conclusion: Our GPU-based proton transport MC is the first of its kind to include a detailed nuclear model to handle NE interactions on any nucleus. Dosimetric calculations demonstrate very good agreement with Geant4.9.6p2/TOPAS. Our MC is being integrated into a framework to perform fast routine clinical QA of pencil-beam treatment plans. Hardware for such a system will cost under $5000. This work was funded in part by a grant from Varian Medical Systems, Inc.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2024

Gas-Phase Coordination of Phosphine-Chalcogenides to the Uranyl Cation

It is generally believed that actinides exhibit an increased covalency in bonding to soft-donor atoms such as nitrogen and sulfur compared to the lanthanides. The explanation is that the greater spatial extent of the 5f orbitals in the actinides compared to the 4f orbitals in the lanthanides accounts for this behavior. However, recent computational studies on lanthanide and actinide complexes with sulfur-donor atom ligands suggest that while calculated metrics of bond covalency could increase for actinide complexes with sulfur ligands, the overall stability of the complexes decreased. While many studies of actinide covalency were conducted in the condensed phases, this work investigates the intrinsic interaction between actinides and soft-donor ligands compared with oxygen in the gas phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Gas-Phase Coordination of Phosphine-Chalcogenides to the Uranyl Cation

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Collaboratory on Mathematics for Mesoscopic Modeling of Materials (CM4)(Final Technical Report)

Our work on the CM4 grant focused on new mathematical and computational approaches for stochastic methods for mesoscopic systems. Our work included continuum SPDEs, molecular coarse-grained models, and hybrid particle-continuum approaches. This work was motivated by applications in soft materials, fluidic devices, and interfacial phenomena. Throughout the project we collaborated with several staff researchers, including from Pacific Northwest National Laboratories (PNNL) and Sandia National Laboratory (SNL) as well as other members of the CM4 project. Below we summarize briefly a few specific accomplishments from this work over the funding period. A full list of published papers and software releases supported by the grant are listed at the end.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system

New ways to integrate energy systems to maximize efficiency are being sought to meet carbon emissions goals. Nuclear-renewable integrated energy system (NR-IES) concepts are a leading solution that couples a nuclear power plant with renewable energy, hydrogen generation plants, and energy storage systems, such that thermal and electrical power are dispatchable to fulfill grid-flexibility requirements while also producing hydrogen and maximizing revenue. Here, this paper introduces a deep reinforcement learning (DRL)-based framework to address the complex decision-making tasks for NR-IES. The objective is to maximize revenue by generating and selling hydrogen and electricity simultaneously according to their time-varying prices while keeping the energy flow in the subsystems in balance. A Python-based simulator for a NR-IES concept has been developed to integrate with OpenAI Gym and Ray/RLlib to enable an efficient and flexible computational framework for DRL research and development. Three state-of-the-art DRL algorithms have been investigated, including two-delayed deep deterministic policy gradient (TD3), soft-actor critic (SAC), proximal policy optimization (PPO), to illustrate DRL’s superiority for controlling NR-IES by comparing it with a conventional control approach, particle swarm optimization (PSO). In this effort, PPO has shown more-stable performance and also better generalization capability than SAC and TD3. Comparisons with PSO have demonstrated that, on average, PPO can achieve 13.9% more mean episode returns from the training process and 29.4% more mean episode returns from the testing process when different hydrogen-production targets are applied.

08 HYDROGEN↗

DOE OSTI2012

Pulmonary Masses: Initial Results of Cone-beam CT Guidance with Needle Planning Software for Percutaneous Lung Biopsy

Purpose: To evaluate the outcome of percutaneous lung biopsy (PLB) findings using cone-beam computed tomographic (CT) guidance (CBCT guidance) and compared to conventional biopsy guidance techniques. Methods: CBCT guidance is a stereotactic technique for needle interventions, combining 3D soft-tissue cone-beam CT, needle planning software, and real-time fluoroscopy. Between March 2007 and August 2010, we performed 84 Tru-Cut PLBs, where bronchoscopy did not provide histopathologic diagnosis. Mean patient age was 64.6 (range 24-85) years; 57 patients were men, and 25 were women. Records were prospectively collected for calculating sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. We also registered fluoroscopy time, room time, interventional time, dose-area product (DAP), and complications. Procedures were divided into subgroups (e.g., location, size, operator). Results: Mean lesion diameter was 32.5 (range 3.0-93.0) mm, and the mean number of samples per biopsy procedure was 3.2 (range 1-7). Mean fluoroscopy time was 161 (range 104-551) s, room time was 34 (range 15-79) min, mean DAP value was 25.9 (range 3.9-80.5) Gy{center_dot}cm{sup -2}, and interventional time was 18 (range 5-65) min. Of 84 lesions, 70 were malignant (83.3%) and 14 were benign (16.7%). Seven (8.3%) of the biopsy samples were nondiagnostic. All nondiagnostic biopsied lesions proved to be malignant during surgical resection. The outcome for sensitivity, specificity, positive predictive value, negative predictive value, and accuracy was 90% (95% confidence interval [CI] 86-96), 100% (95% CI 82-100), 100% (95% CI 96-100), 66.7% (95% CI 55-83), and 91.7% (95% CI 86-96), respectively. Sixteen patients (19%) had minor and 2 (2.4%) had major complications. Conclusion: CBCT guidance is an effective method for PLB, with results comparable to CT/CT fluoroscopy guidance.

62 RADIOLOGY AND NUCLEAR MEDICINE↗