982 resultados para CONE BEAM COMPUTED TOMOGRAPHY


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This paper studies the fracturing process in low-porous rocks during uniaxial compressive tests considering the original defects and the new mechanical cracks in the material. For this purpose, five different kinds of rocks have been chosen with carbonate mineralogy and low porosity (lower than 2%). The characterization of the fracture damage is carried out using three different techniques: ultrasounds, mercury porosimetry and X-ray computed tomography. The proposed methodology allows quantifying the evolution of the porous system as well as studying the location of new cracks in the rock samples. Intercrystalline porosity (the smallest pores with pore radius < 1 μm) shows a limited development during loading, disappearing rapidly from the porosimetry curves and it is directly related to the initial plastic behaviour in the stress–strain patterns. However, the biggest pores (corresponding to the cracks) suffer a continuous enlargement until the unstable propagation of fractures. The measured crack initiation stress varies between 0.25 σp and 0.50 σp for marbles and between 0.50 σp and 0.85 σp for micrite limestone. The unstable propagation of cracks is assumed to occur very close to the peak strength. Crack propagation through the sample is completely independent of pre-existing defects (porous bands, stylolites, fractures and veins). The ultrasonic response in the time-domain is less sensitive to the fracture damage than the frequency-domain. P-wave velocity increases during loading test until the beginning of the unstable crack propagation. This increase is higher for marbles (between 15% and 30% from initial vp values) and lower for micrite limestones (between 5% and 10%). When the mechanical cracks propagate unstably, the velocity stops to increase and decreases only when rock damage is very high. Frequency analysis of the ultrasonic signals shows clear changes during the loading process. The spectrum of treated waveforms shows two main frequency peaks centred at low (~ 20 kHz) and high (~ 35 kHz) values. When new fractures appear and grow the amplitude of the high-frequency peak decreases, while that of the low-frequency peak increases. Besides, a slight frequency shift is observed towards higher frequencies.

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The aim of analogue model experiments in geology is to simulate structures in nature under specific imposed boundary conditions using materials whose rheological properties are similar to those of rocks in nature. In the late 1980s, X-ray computed tomography (CT) was first applied to the analysis of such models. In early studies only a limited number of cross-sectional slices could be recorded because of the time involved in CT data acquisition, the long cooling periods for the X-ray source and computational capacity. Technological improvements presently allow an almost unlimited number of closely spaced serial cross-sections to be acquired and calculated. Computer visualization software allows a full 3D analysis of every recorded stage. Such analyses are especially valuable when trying to understand complex geological structures, commonly with lateral changes in 3D geometry. Periodic acquisition of volumetric data sets in the course of the experiment makes it possible to carry out a 4D analysis of the model, i.e. 3D analysis through time. Examples are shown of 4D analysis of analogue models that tested the influence of lateral rheological changes on the structures obtained in contractional and extensional settings.

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OBJECTIVES We sought to determine whether the transmural extent of scar (TES) explains discordances between dobutamine echocardiography (DbE) and thallium single-photon emission computed tomography (Tl-SPECT) in the detection of viable myocardium (VM). BACKGROUND Discrepancies between DbE and Tl-SPECT are often attributed to differences between contractile reserve and membrane integrity, but may also reflect a disproportionate influence of nontransmural scar on thickening at DbE. METHODS Sixty patients (age 62 +/- 12 years; 10 women and 50 men) with postinfarction left ventricular dysfunction underwent standard rest-late redistribution Tl-SPECT and DbE. Viable myocardium was identified when dysfunctional segments showed Tl activity >60% on the late-redistribution image or by low-dose augmentation at DbE. Contrast-enhanced magnetic resonance imaging (ceMRI) was used to divide TES into five groups: 0%, 75% of the wall thickness replaced by scar. RESULTS As TES increased, both the mean Tl uptake and change in wall motion score decreased significantly (both p < 0.001). However, the presence of subendocardial scar was insufficient to prevent thickening; >50% of segments still showed contractile function with TES of 25% to 75%, although residual function was uncommon with TES >75%. The relationship of both tests to increasing TES was similar, but Tl-SPECT identified VM more frequently than DbE in all groups. Among segments without scar or with small amounts of scar (50% were viable by SPECT. CONCLUSIONS Both contractile reserve and perfusion are sensitive to the extent of scar. However, contractile reserve may be impaired in the face of no or minor scar, and thickening may still occur with extensive scar. (C) 2004 by the American College of Cardiology Foundation.

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Left ventricular (LV) volumes have important prognostic implications in patients with chronic ischemic heart disease. We sought to examine the accuracy and reproducibility of real-time 3D echo (RT-3DE) compared to TI-201 single photon emission computed tomography (SPECT) and cardiac magnetic resonance imaging (MRI). Thirty (n = 30) patients (age 62±9 years, 23 men) with chronic ischemic heart disease underwent LV volume assessment with RT-3DE, SPECT, and MRI. Ano vel semi-automated border detection algorithmwas used by RT-3DE. End diastolic volumes (EDV) and end systolic volumes (ESV) measured by RT3DE and SPECT were compared to MRI as the standard of reference. RT-3DE and SPECT volumes showed excellent correlation with MRI (Table). Both RT- 3DE and SPECT underestimated LV volumes compared to MRI (ESV, SPECT 74±58 ml versus RT-3DE 95±48 ml versus MRI 96±54 ml); (EDV, SPECT 121±61 ml versus RT-3DE 169±61 ml versus MRI 179±56 ml). The degree of ESV underestimation with RT-3DE was not significant.

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A presente pesquisa avaliou a angulação mésio-distal e a distalização dos primeiros e dos segundos molares superiores permanentes em pacientes tratados com o aparelho Forsus® em conjunto com o aparelho ortodôntico fixo. A amostra foi composta por 44 teleradiografias, (22 do lado direito e 22 do lado esquerdo), obtidas por meio de 11 tomografias computadorizadas, de 11 pacientes, realizadas em dois tempos: antes (T1) e após (T2) a instalação do aparelho Forsus®, tratados na clínica de Pós-Graduação em Odontologia, área de Ortodontia, da Universidade Metodista de São Paulo. Após a obtenção dos cortes tipo telerradiografia, foi realizada a marcação dos pontos, linhas e planos, e realizada a mensuração das variáveis de interesse. Para avaliação do espaço para os terceiros molares superiores, utilizou-se uma linha referencial (linha PTVR), demarcada a partir do ponto PTV, perpendicular ao plano de Frankfurt. O espaço avaliado compreendeu entre a Linha PTVR, até a face distal do primeiro molar e do segundo superior permanente. Para avaliar o longo eixo dos primeiros e segundos molares superiores, mensurou-se o ângulo formado entre esses dentes e o plano palatino. Para auxílio das mensurações, foi utilizado o software Radiocef Studio 2. Na análise estatística usou-se o teste t pareado. Concluiu-se que houve distalização e aumento da angulação distal dos primeiros e segundos molares superiores, sendo que nos segundos molares a distalização e angulação distal da coroa ocorreram em menor quantidade; os efeitos do lado direito e esquerdo foram semelhantes; pode-se também constatar que ocorreu uma redução na probabilidade de erupção dos terceiros molares superiores.

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O objetivo deste estudo prospectivo foi avaliar os efeitos do aparelho Forsus® nos incisivos centrais superiores e inferiores. A amostra constituiu-se de 22 tomografias computadorizadas de 11 pacientes (sexo masculino e feminino) idade média de 15,8 anos com má oclusão de Classe II que foram tratados com o aparelho Forsus® na clínica do programa de pós-graduação em Odontologia, área de concentração Ortodontia, da Universidade Metodista de São Paulo. As tomografias foram obtidas em dois momentos T1 (final de nivelamento e antes da instalação do Forsus® e T2 (remoção do Forsus®). Para avaliar a distância do ápice até a tábua óssea, as imagens a serem examinadas foram obtidas com o auxílio do viewer do próprio i-CAT® , o iCATVision® e examinadas com o CorelDRAW X5® já para as medidas cefalométricas IMPA e 1.PP as imagens cefalométricas ortogonais foram obtidas em proporção 1:1 com auxílio do software Dolphin 3D® (Dolphin Imaging and Management Solutions, Chatsworth, EUA) e em seguida examinadas com o software Radiocef Studio 2 (Radio Memory, Belo Horizonte, Brasil). Para a obtenção do erro intra-examinador foi feito o teste t de Student pareado para o erro sistemático e a fórmula de DAHLBERG para estimar a ordem de grandeza dos erros casuais e na análise estatística dos resultados utilizou-se: o teste t para a determinação das diferenças entres as fases de observação e o teste de correlação de Pearson para avaliar a correlação entres as alterações. Observou-se: um aumento significativo (p<0,05) tanto no IMPA quanto no 1.PP, aproximação do ápice dos incisivos inferiores da tábua óssea lingual, aproximação do ápice dos incisivos superiores da tábua óssea vestibular, uma correlação negativa muito forte entre o IMPA e a distância do ápice do incisivo até a tábua óssea lingual e uma correlação negativa moderada entre 1.PP e a distância do ápice do incisivo até a tábua óssea vestibular. Sendo assim o aparelho Forsus® no tratamento da Classe II teve como efeito: vestibularização significativa dos incisivos centrais inferiores, uma verticalização significativa dos incisivos centrais superiores, aproximação do ápice dos incisivos inferiores da cortical óssea lingual e aproximação do ápice dos incisivos superiores da cortical óssea vestibular.

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Radiolarians in the Arctic Ocean have been studied lately in both plankton and sediment trap samples in the Chukchi Sea area. These studies have shed light on new radiolarian taxa, especially within the order Entactinaria, including two new species of Joergensenium, Joergensenium arcticum from the western Arctic Ocean, so far restricted to the Pacific Winter Water in the Chukchi Sea, and Joergensenium clevei hitherto found in the northern part of the Norwegian Sea south of the Fram Strait. The taxonomic position of the order Entactinaria is discussed and the genus Joergensenium has been emended. We have also observed in detail the internal structure of J. arcticum using Microfocus X-ray Computed Tomography and have utilized three-dimensional imaging for the first time in a species description.

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18-Fluorodeoxyglucose (FDG-PET/CT) is an established imaging modality that has been proven to be of benefit in the management of aggressive B-cell non-Hodgkin's lymphoma, such as diffuse large B-cell lymphoma and advanced stage follicular lymphoma. The combination of anatomic and functional imaging afforded by FDG-PET/CT has led to superior sensitivity and specificity in the primary staging, restaging, and assessment of response to treatment of hematological malignancies when compared to FDG-PET and CT alone. The use of FDG-PET/CT for post treatment surveillance imaging remains controversial, and further study is needed to ascertain whether this modality is cost effective and appropriate for use in this setting.

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Objective. To critically evaluate the current literature in an effort to establish the current role of radiologic imaging, advances in computed tomography (CT) and standard film radiography in the diagnosis, and characterization of urinary tract calculi. Conclusion. CT has a valuable role when utilized prudently during surveillance of patients following endourological therapy. In this paper, we outline the basic principles relating to the effects of exposure to ionizing radiation as a result of CT scanning. We discuss the current developments in low-dose CT technology, which have resulted in significant reductions in CT radiation doses (to approximately one-third of what they were a decade ago) while preserving image quality. Finally, we will discuss an important recent development now commercially available on the latest generation of CT scanners, namely, dual energy imaging, which is showing promise in urinary tract imaging as a means of characterizing the composition of urinary tract calculi.

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Patient awareness and concern regarding the potential health risks from ionizing radiation have peaked recently (Coakley et al., 2011) following widespread press and media coverage of the projected cancer risks from the increasing use of computed tomography (CT) (Berrington et al., 2007). The typical young and educated patient with inflammatory bowel disease (IBD) may in particular be conscious of his/her exposure to ionising radiation as a result of diagnostic imaging. Cumulative effective doses (CEDs) in patients with IBD have been reported as being high and are rising, primarily due to the more widespread and repeated use of CT (Desmond et al., 2008). Radiologists, technologists, and referring physicians have a responsibility to firstly counsel their patients accurately regarding the actual risks of ionizing radiation exposure; secondly to limit the use of those imaging modalities which involve ionising radiation to clinical situations where they are likely to change management; thirdly to ensure that a diagnostic quality imaging examination is acquired with lowest possible radiation exposure. In this paper, we synopsize available evidence related to radiation exposure and risk and we report advances in low-dose CT technology and examine the role for alternative imaging modalities such as ultrasonography or magnetic resonance imaging which avoid radiation exposure.

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X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

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Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables full spectrum CT in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical eects in the detector and are very noisy due to photon starvation. In this work, we proposed two methods based on machine learning to address the spectral distortion issue and to improve the material decomposition. This rst approach is to model distortions using an articial neural network (ANN) and compensate for the distortion in a statistical reconstruction. The second approach is to directly correct for the distortion in the projections. Both technique can be done as a calibration process where the neural network can be trained using 3D printed phantoms data to learn the distortion model or the correction model of the spectral distortion. This replaces the need for synchrotron measurements required in conventional technique to derive the distortion model parametrically which could be costly and time consuming. The results demonstrate experimental feasibility and potential advantages of ANN-based distortion modeling and correction for more accurate K-edge imaging with a PCXD. Given the computational eciency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.