Advances in characterisation, calibration and data processing speed of optical coherence tomography systems

This thesis describes advances in the characterisation, calibration and data processing of optical coherence tomography (OCT) systems. Femtosecond (fs) laser inscription was used for producing OCT-phantoms. Transparent materials are generally inert to infra-red radiations, but with fs lasers material modification occurs via non-linear processes when the highly focused light source interacts with the materials. This modification is confined to the focal volume and is highly reproducible. In order to select the best inscription parameters, combination of different inscription parameters were tested, using three fs laser systems, with different operating properties, on a variety of materials. This facilitated the understanding of the key characteristics of the produced structures with the aim of producing viable OCT-phantoms. Finally, OCT-phantoms were successfully designed and fabricated in fused silica. The use of these phantoms to characterise many properties (resolution, distortion, sensitivity decay, scan linearity) of an OCT system was demonstrated. Quantitative methods were developed to support the characterisation of an OCT system collecting images from phantoms and also to improve the quality of the OCT images. Characterisation methods include the measurement of the spatially variant resolution (point spread function (PSF) and modulation transfer function (MTF)), sensitivity and distortion. Processing of OCT data is a computer intensive process. Standard central processing unit (CPU) based processing might take several minutes to a few hours to process acquired data, thus data processing is a significant bottleneck. An alternative choice is to use expensive hardware-based processing such as field programmable gate arrays (FPGAs). However, recently graphics processing unit (GPU) based data processing methods have been developed to minimize this data processing and rendering time. These processing techniques include standard-processing methods which includes a set of algorithms to process the raw data (interference) obtained by the detector and generate A-scans. The work presented here describes accelerated data processing and post processing techniques for OCT systems. The GPU based processing developed, during the PhD, was later implemented into a custom built Fourier domain optical coherence tomography (FD-OCT) system. This system currently processes and renders data in real time. Processing throughput of this system is currently limited by the camera capture rate. OCTphantoms have been heavily used for the qualitative characterization and adjustment/ fine tuning of the operating conditions of OCT system. Currently, investigations are under way to characterize OCT systems using our phantoms. The work presented in this thesis demonstrate several novel techniques of fabricating OCT-phantoms and accelerating OCT data processing using GPUs. In the process of developing phantoms and quantitative methods, a thorough understanding and practical knowledge of OCT and fs laser processing systems was developed. This understanding leads to several novel pieces of research that are not only relevant to OCT but have broader importance. For example, extensive understanding of the properties of fs inscribed structures will be useful in other photonic application such as making of phase mask, wave guides and microfluidic channels. Acceleration of data processing with GPUs is also useful in other fields.

Cost-effective optical coherence tomography spectrometer based on a tilted fiber Bragg grating

A compact, fiber-based spectrometer for biomedical application utilizing a tilted fiber Bragg grating (TFBG) as integrated dispersive element is demonstrated. Based on a 45° UV-written PS750 TFBG a refractive spectrometer with 2.06 radiant/μm dispersion and a numerical aperture of 0.1 was set up and tested as integrated detector for an optical coherence tomography (OCT) system. Featuring a 23 mm long active region at the fiber the spectrum is projected via a cylindrical lens for vertical beam collimation and focused by an achromatic doublet onto the detector array. Covering 740 nm to 860 nm the spectrometer was optically connected to a broadband white light interferometer and a wide field scan head and electronically to an acquisition and control computer. Tomograms of ophthalmic and dermal samples obtained by the frequency domain OCT-system were obtained achieving 2.84 μm axial and 7.6 μm lateral resolution. © 2014 SPIE.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

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.

Transmission electron tomography: quality assessment and enhancement for three-dimensional imaging of nanostructures

Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.

Applications Of Visual Evoked Potentials And Fourier-domain Optical Coherence Tomography In Parkinson's Disease: A Controlled Study.

The goal of this cross-sectional observational study was to quantify the pattern-shift visual evoked potentials (VEP) and the thickness as well as the volume of retinal layers using optical coherence tomography (OCT) across a cohort of Parkinson's disease (PD) patients and age-matched controls. Forty-three PD patients and 38 controls were enrolled. All participants underwent a detailed neurological and ophthalmologic evaluation. Idiopathic PD cases were included. Cases with glaucoma or increased intra-ocular pressure were excluded. Patients were assessed by VEP and high-resolution Fourier-domain OCT, which quantified the inner and outer thicknesses of the retinal layers. VEP latencies and the thicknesses of the retinal layers were the main outcome measures. The mean age, with standard deviation (SD), of the PD patients and controls were 63.1 (7.5) and 62.4 (7.2) years, respectively. The patients were predominantly in the initial Hoehn-Yahr (HY) disease stages (34.8% in stage 1 or 1.5, and 55.8 % in stage 2). The VEP latencies and the thicknesses as well as the volumes of the retinal inner and outer layers of the groups were similar. A negative correlation between the retinal thickness and the age was noted in both groups. The thickness of the retinal nerve fibre layer (RNFL) was 102.7 μm in PD patients vs. 104.2 μm in controls. The thicknesses of retinal layers, VEP, and RNFL of PD patients were similar to those of the controls. Despite the use of a representative cohort of PD patients and high-resolution OCT in this study, further studies are required to establish the validity of using OCT and VEP measurements as the anatomic and functional biomarkers for the evaluation of retinal and visual pathways in PD patients.

Effects Of Misalignments In The Retinal Nerve Fiber Layer Thickness Measurements With Spectral Domain Optical Coherence Tomography.

Purpose. To investigate misalignments (MAs) on retinal nerve fiber layer thickness (RNFLT) measurements obtained with Cirrus(©) SD-OCT. Methods. This was a retrospective, observational, cross-sectional study. Twenty-seven healthy and 29 glaucomatous eyes of 56 individuals with one normal exam and another showing MA were included. MAs were defined as an improper alignment of vertical vessels in the en face image. MAs were classified in complete MA (CMA) and partial MA (PMA), according to their site: 1 (superior, outside the measurement ring (MR)), 2 (superior, within MR), 3 (inferior, within MR), and 4 (inferior, outside MR). We compared RNFLT measurements of aligned versus misaligned exams in all 4 sectors, in the superior area (sectors 1 + 2), inferior area (sectors 3 + 4), and within the measurement ring (sectors 2 + 3). Results. RNFLT measurements at 12 clock-hour of eyes with MAs in the superior area (sectors 1 + 2) were significantly lower than those obtained in the same eyes without MAs (P = 0.043). No significant difference was found in other areas (sectors 1 + 2 + 3 + 4, sectors 3 + 4, and sectors 2 + 3). Conclusion. SD-OCT scans with superior MAs may present lower superior RNFLT measurements compared to aligned exams.

Vertical Bone Measurements From Cone Beam Computed Tomography Images Using Different Software Packages.

This article aimed at comparing the accuracy of linear measurement tools of different commercial software packages. Eight fully edentulous dry mandibles were selected for this study. Incisor, canine, premolar, first molar and second molar regions were selected. Cone beam computed tomography (CBCT) images were obtained with i-CAT Next Generation. Linear bone measurements were performed by one observer on the cross-sectional images using three different software packages: XoranCat®, OnDemand3D® and KDIS3D®, all able to assess DICOM images. In addition, 25% of the sample was reevaluated for the purpose of reproducibility. The mandibles were sectioned to obtain the gold standard for each region. Intraclass coefficients (ICC) were calculated to examine the agreement between the two periods of evaluation; the one-way analysis of variance performed with the post-hoc Dunnett test was used to compare each of the software-derived measurements with the gold standard. The ICC values were excellent for all software packages. The least difference between the software-derived measurements and the gold standard was obtained with the OnDemand3D and KDIS3D (-0.11 and -0.14 mm, respectively), and the greatest, with the XoranCAT (+0.25 mm). However, there was no statistical significant difference between the measurements obtained with the different software packages and the gold standard (p> 0.05). In conclusion, linear bone measurements were not influenced by the software package used to reconstruct the image from CBCT DICOM data.

Towards A Deeper Understanding Of Structural Biomass Recalcitrance Using Phase-contrast Tomography.

The development of technological routes to convert lignocellulosic biomass to liquid fuels requires an in-depth understanding of the cell wall architecture of substrates. Essential pretreatment processes are conducted to reduce biomass recalcitrance and usually increase the reactive surface area. Quantitative three-dimensional information about both bulk and surface structural features of substrates needs to be obtained to expand our knowledge of substrates. In this work, phase-contrast tomography (PCT) was used to gather information about the structure of a model lignocellulosic biomass (piassava fibers). The three-dimensional cellular organization of piassava fibers was characterized by PCT using synchrotron radiation. This technique enabled important physical features that describe the substrate piassava fibers to be visualized and quantified. The external surface area of a fiber and internal surface area of the pores in a fiber could be determined separately. More than 96% of the overall surface area available to enzymes was in the bulk substrate. The pore surface area and length exhibited a positive linear relationship, where the slope of this relationship depended on the plant tissue. We demonstrated that PCT is a powerful tool for the three-dimensional characterization of the cell wall features related to biomass recalcitrance. Original and relevant quantitative information about the structural features of the analyzed material were obtained. The data obtained by PCT can be used to improve processing routes to efficiently convert biomass feedstock into sugars.

Screening Of Miners And Millers At Decreasing Levels Of Asbestos Exposure: Comparison Of Chest Radiography And Thin-section Computed Tomography.

Chest radiography (CXR) is inferior to Thin-section computed tomography in the detection of asbestos related interstitial and pleural abnormalities. It remains unclear, however, whether these limitations are large enough to impair CXR´s ability in detecting the expected reduction in the frequency of these asbestos-related abnormalities (ARA) as exposure decreases. Clinical evaluation, CXR, Thin-section CT and spirometry were obtained in 1418 miners and millers who were exposed to progressively lower airborne concentrations of asbestos. They were separated into four groups according to the type, period and measurements of exposure and/or procedures for controlling exposure: Group I (1940-1966/tremolite and chrysotile, without measurements of exposure and procedures for controlling exposure); Group II (1967-1976/chrysotile only, without measurements of exposure and procedures for controlling exposure); Group III (1977-1980/chrysotile only, initiated measurements of exposure and procedures for controlling exposure) and Group IV (after 1981/chrysotile only, implemented measurements of exposure and a comprehensive procedures for controlling exposure). In all groups, CXR suggested more frequently interstitial abnormalities and less frequently pleural plaques than observed on Thin-section CT (p<0.050). The odds for asbestosis in groups of decreasing exposure diminished to greater extent at Thin-section CT than on CXR. Lung function was reduced in subjects who had pleural plaques evident only on Thin-section CT (p<0.050). In a longitudinal evaluation of 301 subjects without interstitial and pleural abnormalities on CXR and Thin-section CT in a previous evaluation, only Thin-section CT indicated that these ARA reduced as exposure decreased. CXR compared to Thin-section CT was associated with false-positives for interstitial abnormalities and false-negatives for pleural plaques, regardless of the intensity of asbestos exposure. Also, CXR led to a substantial misinformation of the effects of the progressively lower asbestos concentrations in the occurrence of asbestos-related diseases in miners and millers.

Correlation Between The Friedman Staging System And The Upper Airway Volume In Patients With Obstructive Sleep Apnea.

This study was designed to evaluate the correlation between computed tomography findings and data from the physical examination and the Friedman Staging System (FSS) in patients with obstructive sleep apnea (OSA). We performed a retrospective evaluation by reviewing the medical records of 33 patients (19 male and 14 female patients) with a mean body mass index of 30.38 kg/m(2) and mean age of 49.35 years. Among these patients, 14 presented with severe OSA, 7 had moderate OSA, 7 had mild OSA, and 5 were healthy. The patients were divided into 2 groups according to the FSS: Group A comprised patients with FSS stage I or II, and group B comprised patients with FSS stage III. By use of the Fisher exact test, a positive relationship between the FSS stage and apnea-hypopnea index (P = .011) and between the FSS stage and body mass index (P = .012) was found. There was no correlation between age (P = .55) and gender (P = .53) with the FSS stage. The analysis of variance test comparing the upper airway volume between the 2 groups showed P = .018. In this sample the FSS and upper airway volume showed an inverse correlation and were useful in analyzing the mechanisms of airway collapse in patients with OSA.

Herpes Zoster oftálmico e posterior acidente vascular cerebral: relato de caso

A sixty-nine year old man suffered a stroke fourteen weeks after the onset of right herpes zoster ophthalmicus (HZO). Hemispheric infarction was documented by a computed tomography which showed a small hypodense zone in the right internal capsula; after contrast there was enhancement of this hypodense area. Cerebral angiography and cerebral-spinal fluid were not done. Despite of a diagnosis of probability the authors report the case and review the literature. A long latency between the HZO and onset of neurological deficit is stressed. New antiviral agents may prevent the ictus.

Influence of intracanal post on apical periodontitis identified by cone-beam computed tomography

The determination of the success of endodontic treatment has been often discussed based on outcome obtained by periapical radiography. The aim of this study was to verify the influence of intracanal post on apical periodontitis detected by cone-beam computed tomography (CBCT). A consecutive sample of 1020 images (periapical radiographs and CBCT scans) taken from 619 patients (245 men; mean age, 50.1 years) between February 2008 and September 2009 were used in this study. Presence and intracanal post length (short, medium and long) were associated with apical periodontitis (AP). Chi-square test was used for statistical analyses. Significance level was set at p<0.01. The kappa value was used to assess examiner variability. From a total of 591 intracanal posts, AP was observed in 15.06%, 18.78% and 7.95% using periapical radiographs, into the different lengths, short, medium and long, respectively (p=0.466). Considering the same posts length it was verified AP in 24.20%, 26.40% and 11.84% observed by CBCT scans, respectively (p=0.154). From a total of 1,020 teeth used in this study, AP was detected in 397 (38.92%) by periapical radiography and in 614 (60.19%) by CBCT scans (p<0.001). The distribution of intracanal posts in different dental groups showed higher prevalence in maxillary anterior teeth (54.79%). Intracanal posts lengths did not influenced AP. AP was detected more frequently when CBCT method was used.

Method for determination of root curvature radius using cone-beam computed tomography images

This article describes and discusses a method to determine root curvature radius by using cone-beam computed tomography (CBCT). The severity of root canal curvature is essential to select instrument and instrumentation technique. The diagnosis and planning of root canal treatment have traditionally been made based on periapical radiography. However, the higher accuracy of CBCT images to identify anatomic and pathologic alterations compared to panoramic and periapical radiographs has been shown to reduce the incidence of false-negative results. In high-resolution images, the measurement of root curvature radius can be obtained by circumcenter. Based on 3 mathematical points determined with the working tools of Planimp® software, it is possible to calculate root curvature radius in both apical and coronal directions. The CBCT-aided method for determination of root curvature radius presented in this article is easy to perform, reproducible and allows a more reliable and predictable endodontic planning, which reflects directly on a more efficacious preparation of curved root canals.

Evaluation of simulated bone lesion in the head of the mandible by using multislice computed tomography

Conventional radiography has shown limitation in acquiring image of the ATM region, thus, computed tomography (CT) scanning has been the best option to the present date for diagnosis, surgical planning and treatment of bone lesions, owing to its specific properties. OBJECTIVE: The aim of the study was to evaluate images of simulated bone lesions at the head of the mandible by multislice CT. MATERIAL AND METHODS: Spherical lesions were made with dental spherical drills (sizes 1, 3, and 6) and were evaluated by using multislice CT (64 rows), by two observers in two different occasions, deploying two protocols: axial, coronal, and sagittal images, and parasagittal images for pole visualization (anterior, lateral, posterior, medial and superior). Acquired images were then compared with those lesions in the dry mandible (gold standard) to evaluate the specificity and sensibility of both protocols. Statistical methods included: Kappa statistics, validity test and chi-square test. Results demonstrated the advantage of associating axial, coronal, and sagittal slices with parasagittal slices for lesion detection at the head of the mandible. RESULTS: There was no statistically significant difference between the types of protocols regarding a particular localization of lesions at the poles. CONCLUSIONS: Protocols for the assessment of the head of the mandible were established to improve the visualization of alterations of each of the poles of the mandible's head. The anterior and posterior poles were better visualized in lateral-medial planes while lateral, medial and superior poles were better visualized in the anterior-posterior plane.

Comparison between cone-beam and multislice computed tomography for identification of simulated bone lesions

There are many studies that compare the accuracy of multislice (MSCT) and cone beam (CBCT) computed tomography for evaluations in the maxillofacial region. However, further studies comparing both acquisition techniques for the evaluation of simulated mandibular bone lesions are needed. The aim of this study was to compare the accuracy of MSCT and CBCT in the diagnosis of simulated mandibular bone lesions by means of cross sectional images and axial/MPR slices. Lesions with different dimensions, shape and locularity were produced in 15 dry mandibles. The images were obtained following the cross sectional and axial/MPR (Multiplanar Reconstruction) imaging protocols and were interpreted independently. CBCT and MSCT showed similar results in depicting the percentage of cortical bone involvement, with great sensitivity and specificity (p < 0.005). There were no significant intra- or inter-examiner differences between axial/MPR images and cross sectional images with regard to sensitivity and specificity. CBCT showed results similar to those of MSCT for the identification of the number of simulated bone lesions. Cross sectional slices and axial/MPR images presented high accuracy, proving useful for bone lesion diagnosis.