Abstract: Objective: We aim to investigate if anatomical and functional properties of the upper airway using computerized 3D models derived from computed tomography (CT) scans better predict obstructive sleep apnea (OSA) severity than standard clinical markers. Methods: Consecutive children with suspected OSA underwent polysomnography, clinical assessment of upper airway patency, and a CT scan while awake. A three-dimensional (3D) reconstruction of the pharyngeal airway was built from these images, and computational fluid dynamics modeling of low inspiratory flow was performed using open-source software. Results: Thirty-three children were included (23 boys; mean age, was 6.0 +/- 3.2 y). OSA was diagnosed in 23 patients. Children with OSA had a significantly lower volume of the overlap region between tonsils and the adenoids (median volume, 1408 mm compared to 2173 mm; p = 0.04), a lower mean cross-sectional area at this location (median volume, 69.3 mm(2) compared to 114.3 mm(2); p = 0.04), and a lower minimal cross-sectional area (median volume, 17.9 mm(2) compared to 25.9 mm(2); p = 0.05). Various significant correlations were found between several imaging parameters and the severity of OSA, most pronounced for upper airway conductance (r = -0.46) (p < 0.01) for correlation between upper airway conductance and the apnea-hypopnea index. No differences or significant correlations were observed with clinical parameters of upper airway patency. Preliminary data after treatment showed that none of the patients with residual OSA had their smallest cross-sectional area located in segment 3, and this frequency was significantly lower than in their peers whose sleep study normalized (64%; p = 0.05). Conclusion: Functional imaging parameters are highly correlated with OSA severity and are a more powerful correlate than clinical scores of upper airway patency. Preliminary data also showed that we could identify differences in the upper airway of those subjects who did not benefit from a local upper airway treatment. (c) 2013 Elsevier B.V. All rights reserved.

Abstract: Background: Inhaled formulations using extrafine particles of long-acting beta(2)-agonists and corticosteroids were developed to optimize asthma treatment. Findings that these combinations reach and treat smaller airways more effectively are predominantly based on general non-specific outcomes with little information on regional characteristics. Objectives: This study aims to assess long-term effects of extrafine beclomethasone/formoterol on small airways of asthmatic patients using novel functional imaging methods. Methods: Twenty-four stable asthma patients were subdivided into three groups (steroid naive, n = 7; partially controlled, n = 6; well controlled, n = 11). Current treatment was switched to a fixed combination of extrafine beclomethasone/formoterol (Foster (R); Chiesi Pharmaceuticals, Parma, Italy). Patients underwent lung function evaluation and thorax high-resolution computerized tomography (HRCT) scan. Local airway resistance was obtained from computational fluid dynamics (CFD). Results: After 6 months, the entire population showed improvement in pre-bronchodilation imaging parameters, including small airway volume (p = 0.0007), resistance (p = 0.011), and asthma control score (p = 0.016). Changes in small airway volume correlated with changes in asthma control score (p = 0.004). Forced expiratory volume in 1 s (p = 0.044) and exhaled nitric oxide (p = 0.040) also improved. Functional imaging provided more detail and clinical relevance compared to lung function tests, especially in the well-controlled group where only functional imaging parameters showed significant improvement, while the correlation with asthma control score remained. Conclusions: Extrafine beclomethasone/formoterol results in a significant reduction of small airway obstruction, detectable by functional imaging (HRCT/CFD). Changes in imaging parameters correlated significantly with clinically relevant improvements. This indicates that functional imaging is a useful tool for sensitive assessment of changes in the respiratory system after asthma treatment. Copyright (C) 2013 S. Karger AG, Basel

Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.

Abstract: Context: Asthma affects 20 million Americans resulting in an economic burden of approximately $18 billion in the US alone (Allergies and Asthma Foundation 2000; National Center for Environmental Health (NCEH) 1999). Research studies based on differences in patient-specific airway morphology for asthma and the associated effect on deposition of inhaled aerosols are currently not available in the literature. Therefore, the role of morphological variations such as upper airway (extrathoracic) occlusion is not well documented. Objective: Functional imaging based computational fluid dynamics (CFD) of the respiratory airways for five asthmatic subjects is performed in this study using computed tomography (CT) based patient-specific airway models and boundary conditions. Methods: CT scans for 5 asthma patients were used to reconstruct 3D lung models using segmentation software. An averaged inhalation profile and patient-specific lobar flow distribution were used to perform the simulation. The simulations were used to obtain deposition for BDP/Formoterol (R) HFA pMDI in the patient-specific airway models. Results: The lung deposition obtained using CFD was in excellent agreement with available in vivo data using the same product. Specifically, CFD resulted in 30% lung deposition, whereas in vivo lung deposition was reported to be approximately 31%. Conclusion: It was concluded that a combination of patient-specific airway models and lobar boundary conditions can be used to obtain accurate lung deposition estimates. Lower lung deposition can be expected for patients with higher extrathoracic resistance. Novel respiratory drug delivery devices need to accommodate population subgroups based on these morphological and anatomical differences in addition to subject age.

Abstract: Urban atmospheres in modern cities carry characteristic mixtures of particulate pollution which are potentially aggravating for chronic respiratory patients (CRP). Although air quality surveys can be detailed, the obtained information is not always useful to evaluate human health effects. This paper presents a novel approach to estimate particle deposition rates in airways of CRP, based on real air pollution data. By combining computational fluid dynamics with physical-chemical characteristics of particulate pollution, deposition rates are estimated for particles of different toxicological relevance, that is, minerals, iron oxides, sea salts, ammonium salts, and carbonaceous particles. Also, it enables some qualitative evaluation of the spatial, temporal, and patient specific effects on the particle dose upon exposure to the urban atmosphere. Results show how heavy traffic conditions increases the deposition of anthropogenic particles in the trachea and lungs of respiratory patients (here, +0.28 and +1.5 μg·h1, respectively). In addition, local and synoptic meteorological conditions were found to have a strong effect on the overall dose. However, the pathology and age of the patient was found to be more crucial, with highest deposition rates for toxic particles in adults with a mild anomaly, followed by mild asthmatic children and adults with severe respiratory dysfunctions (7, 5, and 3 μg·h1, respectively).

Abstract: Statistical parameter estimation theory is proposed as a quantitative method to measure unknown structure parameters from electron microscopy images. Images are then purely considered as data planes from which structure parameters have to be determined as accurately and precisely as possible using a parametric statistical model of the observations. For this purpose, an efficient algorithm is proposed for the estimation of atomic column positions and intensities from high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) images. Furthermore, the so-called CramérRao lower bound (CRLB) is reviewed to determine the limits to the precision with which continuous parameters such as atomic column positions and intensities can be estimated. Since this lower bound can only be derived for continuous parameters, alternative measures using the principles of detection theory are introduced for problems concerning the estimation of discrete parameters such as atomic numbers. An experimental case study is presented to show the practical use of these measures for the optimization of the experiment design if the purpose is to decide between the presence of specific atom types using STEM images.

Abstract: A thorough understanding of the three-dimensional (3D) atomic structure and composition of coreshell nanostructures is indispensable to obtain a deeper insight on their physical behavior. Such 3D information can be reconstructed from two-dimensional (2D) projection images using electron tomography. Recently, different electron tomography techniques have enabled the 3D characterization of a variety of nanostructures down to the atomic level. However, these methods have all focused on the investigation of nanomaterials containing only one type of chemical element. Here, we combine statistical parameter estimation theory with compressive sensing based tomography to determine the positions and atom type of each atom in heteronanostructures. The approach is applied here to investigate the interface in coreshell Au@Ag nanorods but it is of great interest in the investigation of a broad range of nanostructures.

Abstract: In two subjects with a unilateral diaphragmatic paralysis and complaints of dyspnea, a completely different treatment approach was chosen despite similar anatomical and physiological abnormalities. These decisions were supported by the results generated by Functional Respiratory Imaging (FRI). FRI was able to generate functional information with respect to lobar ventilation and local drug deposition. In one subject, it was found that some lobes were poorly ventilated and drug deposition simulation showed that some regions were undertreated. This subject underwent a diaphragm plication to restore the ventilation. In the other subject, it was found that all lobes were still ventilated. A conservative approach with regular follow-up was chosen to wait for spontaneous recovery of the diaphragmatic function. Both subjects improved subjectively and objectively. These cases demonstrate how novel medical imaging techniques such as FRI can be used to personalize respiratory treatment in subjects with unilateral diaphragmatic paralysis.

Abstract: We report an innovative method to explore the optimal experimental settings to detect light atoms from scanning transmission electron microscopy (STEM) images. Since light elements play a key role in many technologically important materials, such as lithium-battery devices or hydrogen storage applications, much effort has been made to optimize the STEM technique in order to detect light elements. Therefore, classical performance criteria, such as contrast or signal-to-noise ratio, are often discussed hereby aiming at improvements of the direct visual interpretability. However, when images are interpreted quantitatively, one needs an alternative criterion, which we derive based on statistical detection theory. Using realistic simulations of technologically important materials, we demonstrate the benefits of the proposed method and compare the results with existing approaches.

Abstract: Quantitative annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique to characterise nano-particles on an atomic scale. Because of their limited size and beam sensitivity, the atomic structure of such particles may become extremely challenging to determine. Therefore keeping the incoming electron dose to a minimum is important. However, this may reduce the reliability of quantitative ADF STEM which will here be demonstrated for nano-particle atom-counting. Based on experimental ADF STEM images of a real industrial catalyst, we discuss the limits for counting the number of atoms in a projected atomic column with single atom sensitivity. We diagnose these limits by combining a thorough statistical method and detailed image simulations.

Abstract: The three-dimensional (3D) atomic structure of nanomaterials, including strain, is crucial to understand their properties. Here, we investigate lattice strain in Au nanodecahedra using electron tomography. Although different electron tomography techniques enabled 3D characterizations of nanostructures at the atomic level, a reliable determination of lattice strain is not straightforward. We therefore propose a novel model-based approach from which atomic coordinates are measured. Our findings demonstrate the importance of investigating lattice strain in 3D.

Abstract: The increasing need for precise determination of the atomic arrangement of non-periodic structures in materials design and the control of nanostructures explains the growing interest in quantitative transmission electron microscopy. The aim is to extract precise and accurate numbers for unknown structure parameters including atomic positions, chemical concentrations and atomic numbers. For this purpose, statistical parameter estimation theory has been shown to provide reliable results. In this theory, observations are considered purely as data planes, from which structure parameters have to be determined using a parametric model describing the images. As such, the positions of atom columns can be measured with a precision of the order of a few picometres, even though the resolution of the electron microscope is still one or two orders of magnitude larger. Moreover, small differences in average atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark-field scanning transmission electron microscopy images. In addition, this theory allows one to measure compositional changes at interfaces, to count atoms with single-atom sensitivity, and to reconstruct atomic structures in three dimensions. This feature article brings the reader up to date, summarizing the underlying theory and highlighting some of the recent applications of quantitative model-based transmisson electron microscopy.

Abstract: Ru catalysts are part of a set of late transition metal nanocatalysts that have garnered much interest for catalytic applications such as ammonia synthesis and fuel cell production. Their performance varies greatly depending on their morphology and size, these catalysts are widely studied using electron microscopy. Using recent developments in Annular Dark Field (ADF) Scanning Transmission Electron Microscopy (STEM) quantification techniques, a rapid atom counting procedure was utilized to document the evolution of a heterogeneous Ru catalyst supported on carbon black. Areas of the catalyst were imaged for approximately 15 minutes using ADF STEM. When the Ru clusters were exposed to the electron beam, the clusters changed phase from amorphous to crystalline. To quantify the thickness of the crystalline clusters, two techniques were applied (simulation and statistical decomposition) and compared. These techniques show that stable face centredcubic crystal structures in the form of rafts, between 2 and 8 atoms thick, were formed after the initial wetting of the carbon support.