221 resultados para lung CT

em Queensland University of Technology - ePrints Archive


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Adolescent Idiopathic Scoliosis (AIS) has been associated with reduced pulmonary function believed to be due to a restriction of lung volume by the deformed thoracic cavity. A recent study by our group examined the changes in lung volume pre and post anterior thoracoscopic scoliosis correction using pulmonary function testing (1), however the anatomical changes in ribcage shape and left/right lung volume after thoracoscopic surgery which govern overall respiratory capacity are unknown. The aim of this study was to use 3D rendering from CT scan data to compare lung and ribcage anatomical changes from pre to two years post thoracoscopic anterior scoliosis correction. The study concluded that 3D volumetric reconstruction from CT scans is a powerful means of evaluating changes in pulmonary and thoracic anatomy following surgical AIS correction. Most likely, lung volume changes following thoracoscopic scoliosis correction are multifactorial and affected by changes in height (due to residual growth), ribcage shape, diaphragm positioning, Cobb angle correction in the thoracic spine. Further analysis of the 3D reconstructions will be performed to assess how each of these factors affect lung volume in this patient cohort.

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Aims: To develop clinical protocols for acquiring PET images, performing CT-PET registration and tumour volume definition based on the PET image data, for radiotherapy for lung cancer patients and then to test these protocols with respect to levels of accuracy and reproducibility. Method: A phantom-based quality assurance study of the processes associated with using registered CT and PET scans for tumour volume definition was conducted to: (1) investigate image acquisition and manipulation techniques for registering and contouring CT and PET images in a radiotherapy treatment planning system, and (2) determine technology-based errors in the registration and contouring processes. The outcomes of the phantom image based quality assurance study were used to determine clinical protocols. Protocols were developed for (1) acquiring patient PET image data for incorporation into the 3DCRT process, particularly for ensuring that the patient is positioned in their treatment position; (2) CT-PET image registration techniques and (3) GTV definition using the PET image data. The developed clinical protocols were tested using retrospective clinical trials to assess levels of inter-user variability which may be attributed to the use of these protocols. A Siemens Somatom Open Sensation 20 slice CT scanner and a Philips Allegro stand-alone PET scanner were used to acquire the images for this research. The Philips Pinnacle3 treatment planning system was used to perform the image registration and contouring of the CT and PET images. Results: Both the attenuation-corrected and transmission images obtained from standard whole-body PET staging clinical scanning protocols were acquired and imported into the treatment planning system for the phantom-based quality assurance study. Protocols for manipulating the PET images in the treatment planning system, particularly for quantifying uptake in volumes of interest and window levels for accurate geometric visualisation were determined. The automatic registration algorithms were found to have sub-voxel levels of accuracy, with transmission scan-based CT-PET registration more accurate than emission scan-based registration of the phantom images. Respiration induced image artifacts were not found to influence registration accuracy while inadequate pre-registration over-lap of the CT and PET images was found to result in large registration errors. A threshold value based on a percentage of the maximum uptake within a volume of interest was found to accurately contour the different features of the phantom despite the lower spatial resolution of the PET images. Appropriate selection of the threshold value is dependant on target-to-background ratios and the presence of respiratory motion. The results from the phantom-based study were used to design, implement and test clinical CT-PET fusion protocols. The patient PET image acquisition protocols enabled patients to be successfully identified and positioned in their radiotherapy treatment position during the acquisition of their whole-body PET staging scan. While automatic registration techniques were found to reduce inter-user variation compared to manual techniques, there was no significant difference in the registration outcomes for transmission or emission scan-based registration of the patient images, using the protocol. Tumour volumes contoured on registered patient CT-PET images using the tested threshold values and viewing windows determined from the phantom study, demonstrated less inter-user variation for the primary tumour volume contours than those contoured using only the patient’s planning CT scans. Conclusions: The developed clinical protocols allow a patient’s whole-body PET staging scan to be incorporated, manipulated and quantified in the treatment planning process to improve the accuracy of gross tumour volume localisation in 3D conformal radiotherapy for lung cancer. Image registration protocols which factor in potential software-based errors combined with adequate user training are recommended to increase the accuracy and reproducibility of registration outcomes. A semi-automated adaptive threshold contouring technique incorporating a PET windowing protocol, accurately defines the geometric edge of a tumour volume using PET image data from a stand alone PET scanner, including 4D target volumes.

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INTRODUCTION: Performance status (PS) 2 patients with non-small cell lung cancer (NSCLC) experience more toxicity, lower response rates, and shorter survival times than healthier patients treated with standard chemotherapy. Paclitaxel poliglumex (PPX), a macromolecule drug conjugate of paclitaxel and polyglutamic acid, reduces systemic exposure to peak concentrations of free paclitaxel and may lead to increased concentrations in tumors due to enhanced vascular permeability. METHODS: Chemotherapy-naive PS 2 patients with advanced NSCLC were randomized to receive carboplatin (area under the curve = 6) and either PPX (210 mg/m/10 min without routine steroid premedication) or paclitaxel (225 mg/m/3 h with standard premedication) every 3 weeks. The primary end point was overall survival. RESULTS: A total of 400 patients were enrolled. Alopecia, arthralgias/myalgias, and cardiac events were significantly less frequent with PPX/carboplatin, whereas grade ≥3 neutropenia and grade 3 neuropathy showed a trend of worsening. There was no significant difference in the incidence of hypersensitivity reactions despite the absence of routine premedication in the PPX arm. Overall survival was similar between treatment arms (hazard ratio, 0.97; log rank p = 0.769). Median and 1-year survival rates were 7.9 months and 31%, for PPX versus 8 months and 31% for paclitaxel. Disease control rates were 64% and 69% for PPX and paclitaxel, respectively. Time to progression was similar: 3.9 months for PPX/carboplatin versus 4.6 months for paclitaxel/carboplatin (p = 0.210). CONCLUSION: PPX/carboplatin failed to provide superior survival compared with paclitaxel/carboplatin in the first-line treatment of PS 2 patients with NSCLC, but the results with respect to progression-free survival and overall survival were comparable and the PPX regimen was more convenient. © 2008International Association for the Study of Lung Cancer.

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Different human activities like combustion of fossil fuels, biomass burning, industrial and agricultural activities, emit a large amount of particulates into the atmosphere. As a consequence, the air we inhale contains significant amount of suspended particles, including organic and inorganic solids and liquids, as well as various microorganism, which are solely responsible for a number of pulmonary diseases. Developing a numerical model for transport and deposition of foreign particles in realistic lung geometry is very challenging due to the complex geometrical structure of the human lung. In this study, we have numerically investigated the airborne particle transport and its deposition in human lung surface. In order to obtain the appropriate results of particle transport and deposition in human lung, we have generated realistic lung geometry from the CT scan obtained from a local hospital. For a more accurate approach, we have also created a mucus layer inside the geometry, adjacent to the lung surface and added all apposite mucus layer properties to the wall surface. The Lagrangian particle tracking technique is employed by using ANSYS FLUENT solver to simulate the steady-state inspiratory flow. Various injection techniques have been introduced to release the foreign particles through the inlet of the geometry. In order to investigate the effects of particle size on deposition, numerical calculations are carried out for different sizes of particles ranging from 1 micron to 10 micron. The numerical results show that particle deposition pattern is completely dependent on its initial position and in case of realistic geometry; most of the particles are deposited on the rough wall surface of the lung geometry instead of carinal region.

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Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc. The geometric and dosimetric accuracy of CTCombine’s output has been assessed by simulating simple and complex treatments applied to a rotated planar phantom and a rotated humanoid phantom and comparing the resulting virtual EPID images with the images acquired using experimental measurements and independent simulations of equivalent phantoms. It is expected that CTCombine will be useful for Monte Carlo studies of EPID dosimetry as well as other EPID imaging applications.

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Over the last few years various research groups around the world have employed X-ray Computed Tomography (CT) imaging in the study of mummies – Toronto-Boston (1,2), Manchester(3). Prior to the development of CT scanners, plane X-rays were used in the investigation of mummies. Xeroradiography has also been employed(4). In a xeroradiograph, objects of similar X-ray density (very difficult to see on a conventional X-ray) appear edge-enhanced and so are seen much more clearly. CT scanners became available in the early 1970s. A CT scanner produces cross-sectional X-rays of objects. On a conventional X-radiograph individual structures are often very difficult to see because all the structures lying in the path of the X-ray beam are superimposed, a problem that does not occur with CT. Another advantage of CT is that the information in a series of consecutive images may be combined to produce a three-dimensional reconstruction of an object. Slices of different thickness and magnification may be chosen. Why CT a mummy? Prior to the availability of CT scanners, the only way of finding out about the inside of a mummy in any detail was to unwrap and dissect it. This has been done by various research groups – most notably the Manchester, UK and Pennsylvania University, USA mummy projects(5,6). Unwrapping a mummy and carrying out an autopsy is obviously very destructive. CT studies hold the possibility of producing a lot more information than is possible from plain X-rays and are able to show the undisturbed arrangement of the wrapped body. CT is also able to provide information about the internal structure of bones, organ packs, etc that wouldn’t be possible without sawing through the bones etc. The mummy we have scanned is encased in a coffin which would have to have been broken open in order to remove the body.

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A pragmatic method for assessing the accuracy and precision of a given processing pipeline required for converting computed tomography (CT) image data of bones into representative three dimensional (3D) models of bone shapes is proposed. The method is based on coprocessing a control object with known geometry which enables the assessment of the quality of resulting 3D models. At three stages of the conversion process, distance measurements were obtained and statistically evaluated. For this study, 31 CT datasets were processed. The final 3D model of the control object contained an average deviation from reference values of −1.07±0.52 mm standard deviation (SD) for edge distances and −0.647±0.43 mm SD for parallel side distances of the control object. Coprocessing a reference object enables the assessment of the accuracy and precision of a given processing pipeline for creating CTbased 3D bone models and is suitable for detecting most systematic or human errors when processing a CT-scan. Typical errors have about the same size as the scan resolution.