1000 resultados para EPIC-[mu]CT


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Introduction: Recent advances in the planning and delivery of radiotherapy treatments have resulted in improvements in the accuracy and precision with which therapeutic radiation can be administered. As the complexity of the treatments increases it becomes more difficult to predict the dose distribution in the patient accurately. Monte Carlo (MC) methods have the potential to improve the accuracy of the dose calculations and are increasingly being recognised as the ‘gold standard’ for predicting dose deposition in the patient [1]. This project has three main aims: 1. To develop tools that enable the transfer of treatment plan information from the treatment planning system (TPS) to a MC dose calculation engine. 2. To develop tools for comparing the 3D dose distributions calculated by the TPS and the MC dose engine. 3. To investigate the radiobiological significance of any errors between the TPS patient dose distribution and the MC dose distribution in terms of Tumour Control Probability (TCP) and Normal Tissue Complication Probabilities (NTCP). The work presented here addresses the first two aims. Methods: (1a) Plan Importing: A database of commissioned accelerator models (Elekta Precise and Varian 2100CD) has been developed for treatment simulations in the MC system (EGSnrc/BEAMnrc). Beam descriptions can be exported from the TPS using the widespread DICOM framework, and the resultant files are parsed with the assistance of a software library (PixelMed Java DICOM Toolkit). The information in these files (such as the monitor units, the jaw positions and gantry orientation) is used to construct a plan-specific accelerator model which allows an accurate simulation of the patient treatment field. (1b) Dose Simulation: The calculation of a dose distribution requires patient CT images which are prepared for the MC simulation using a tool (CTCREATE) packaged with the system. Beam simulation results are converted to absolute dose per- MU using calibration factors recorded during the commissioning process and treatment simulation. These distributions are combined according to the MU meter settings stored in the exported plan to produce an accurate description of the prescribed dose to the patient. (2) Dose Comparison: TPS dose calculations can be obtained using either a DICOM export or by direct retrieval of binary dose files from the file system. Dose difference, gamma evaluation and normalised dose difference algorithms [2] were employed for the comparison of the TPS dose distribution and the MC dose distribution. These implementations are spatial resolution independent and able to interpolate for comparisons. Results and Discussion: The tools successfully produced Monte Carlo input files for a variety of plans exported from the Eclipse (Varian Medical Systems) and Pinnacle (Philips Medical Systems) planning systems: ranging in complexity from a single uniform square field to a five-field step and shoot IMRT treatment. The simulation of collimated beams has been verified geometrically, and validation of dose distributions in a simple body phantom (QUASAR) will follow. The developed dose comparison algorithms have also been tested with controlled dose distribution changes. Conclusion: The capability of the developed code to independently process treatment plans has been demonstrated. A number of limitations exist: only static fields are currently supported (dynamic wedges and dynamic IMRT will require further development), and the process has not been tested for planning systems other than Eclipse and Pinnacle. The tools will be used to independently assess the accuracy of the current treatment planning system dose calculation algorithms for complex treatment deliveries such as IMRT in treatment sites where patient inhomogeneities are expected to be significant. Acknowledgements: Computational resources and services used in this work were provided by the HPC and Research Support Group, Queensland University of Technology, Brisbane, Australia. Pinnacle dose parsing made possible with the help of Paul Reich, North Coast Cancer Institute, North Coast, New South Wales.

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The methodology undertaken, the channel model and the system model created for developing a novel adaptive equalization method and a novel channel tracking method for uplink of MU-MIMO-OFDM systems is presented in this paper. The results show that the channel tracking method works with 97% accuracy, while the training-based initial channel estimation method shows poor performance in estimating the actual channel comparatively.

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Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

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INTRODUCTION It is known that the vascular morphology and functionality are changed following closed soft tissue trauma (CSTT) [1], and bone fractures [2]. The disruption of blood vessels may lead to hypoxia and necrosis. Currently, most clinical methods for the diagnosis and monitoring of CSTT with or without bone fractures are primarily based on qualitative measures or practical experience, making the diagnosis subjective and inaccurate. There is evidence that CSTT and early vascular changes following the injury delay the soft tissue tissue and bone healing [3]. However, a precise qualitative and quantitative morphological assessment of vasculature changes after trauma is currently missing. In this research, we aim to establish a diagnostic framework to assess the 3D vascular morphological changes after standardized CSTT in a rat model qualitatively and quantitatively using contrast-enhanced micro-CT imaging. METHODS An impact device was used for the application of a controlled reproducible CSTT to the left thigh (Biceps Femoris) of anaesthetized male Wistar rats. After euthanizing the animals at 6 hours, 24 hours, 3 days, 7 days, or 14 days after trauma, CSTT was qualitatively evaluated by macroscopic visual observation of the skin and muscles. For visualization of the vasculature, the blood vessels of sacrificed rats were flushed with heparinised saline and then perfused with a radio-opaque contrast agent (Microfil, MV 122, Flowtech, USA) using an infusion pump. After allowing the contrast agent to polymerize overnight, both hind-limbs were dissected, and then the whole injured and contra-lateral control limbs were imaged using a micro-CT scanner (µCT 40, Scanco Medical, Switzerland) to evaluate the vascular morphological changes. Correlated biopsy samples were also taken from the CSTT region of both injured and control legs. The morphological parameters such as the vessel volume ratio (VV/TV), vessel diameter (V.D), spacing (V.Sp), number (V.N), connectivity (V.Conn) and the degree of anisotropy (DA) were then quantified by evaluating the scans of biopsy samples using the micro-CT imaging system. RESULTS AND DISCUSSION A qualitative evaluation of the CSTT has shown that the developed impact protocols were capable of producing a defined and reproducible injury within the region of interest (ROI), resulting in a large hematoma and moderate swelling in both lateral and medial sides of the injured legs. Also, the visualization of the vascular network using 3D images confirmed the ability to perfuse the large vessels and a majority of the microvasculature consistently (Figure 1). Quantification of the vascular morphology obtained from correlated biopsy samples has demonstrated that V.D and V.N and V.Sp were significantly higher in the injured legs 24 hours after impact in comparison with the control legs (p<0.05). The evaluation of the other time points is currently progressing. CONCLUSIONS The findings of this research will contribute to a better understanding of the changes to the vascular network architecture following traumatic injuries and during healing process. When interpreted in context of functional changes, such as tissue oxygenation, this will allow for objective diagnosis and monitoring of CSTT and serve as validation for future non-invasive clinical assessment modalities.

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INTRODUCTION There is evidence that the reduction of blood perfusion caused by closed soft tissue trauma (CSTT) delays the healing of the affected soft tissues and bone [1]. We hypothesise that the characterisation of vascular morphology changes (VMC) following injury allows us to determine the effect of the injury on tissue perfusion and thereby the severity of the injury. This research therefore aims to assess the VMC following CSTT in a rat model using contrast-enhanced micro-CT imaging. METHODOLOGY A reproducible CSTT was created on the left leg of anaesthetized rats (male, 12 weeks) with an impact device. After euthanizing the animals at 6 and 24 hours following trauma, the vasculature was perfused with a contrast agent (Microfil, Flowtech, USA). Both hind-limbs were dissected and imaged using micro-CT for qualitative comparison of the vascular morphology and quantification of the total vascular volume (VV). In addition, biopsy samples were taken from the CSTT region and scanned to compare morphological parameters of the vasculature between the injured and control limbs. RESULTS AND DISCUSSION While the visual observation of the hindlimb scans showed consistent perfusion of the microvasculature with microfil, enabling the identification of all major blood vessels, no clear differences in the vascular architecture were observed between injured and control limbs. However, overall VV within the region of interest (ROI)was  measured to be higher for the injured limbs after 24h. Also, scans of biopsy samples demonstrated that vessel diameter and density were higher in the injured legs 24h after impact. CONCLUSION We believe these results will contribute to the development of objective diagnostic methods for CSTT based on changes to the microvascular morphology as well as aiding in the validation of future non-invasive clinical assessment modalities.

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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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The introduction of Systematized Nomenclature of Medicine - Clinical Terms (Snomed CT) for diagnosis coding in emergency departments (EDs) in New South Wales (NSW) has implications for injury surveillance abilities. This study aimed to assess the consequences of its introduction, as implemented as part of the ED information system in NSW, for identifying road trauma-related injuries in EDs. It involved a retrospective analysis of road trauma-related injuries identified in linked police, ED and mortality records during March 2007 to December 2009. Between 53.7% to 78.4% of all Snomed CT classifications in the principal provisional diagnosis field referred to the type of injury or symptom experienced by the individual. Of the road users identified by police, 3.2% of vehicle occupants, 6% of motorcyclists, 10.0% of pedal cyclists and 5.2% of pedestrians were identified using Snomed CT classifications in the principal provisional diagnosis field. The introduction of Snomed CT may provide flexible terminologies for clinicians. However, unless carefully implemented in information systems, its flexibility can lead to mismatches between the intention and actual use of defined data fields. Choices available in Snomed CT to indicate either symptoms, diagnoses, or injury mechanisms need to be controlled and these three concepts need to be retained in separate data fields to ensure a clear distinction between their classification in the ED.

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This study extends the ‘zero scan’ method for CT imaging of polymer gel dosimeters to include multi-slice acquisitions. Multi slice CT images consisting of 24 slices of 1.2 mm thickness were acquired of an irradiated polymer gel dosimeter, and processed with the zero scan technique. The results demonstrate that zero scan based gel readout can be successfully applied to generate a three dimensional image of the irradiated gel field. Compared to the raw CT images the processed figures and cross gel profiles demonstrated reduced noise and clear visibility of the penumbral region. Moreover these improved results further highlight the suitability of this method in volumetric reconstruction with reduced CT data acquisition per slice. This work shows that 3D volumes of irradiated polymer gel dosimeters can be acquired and processed with x-ray CT.

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Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

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In the structure of title compound [Rb2(C7H5N2O4)2(H2O)2]n the asymmetric unit comprises two independent and different seven-coordinate Rb centres, one RbO7, the other RbO6N, with both having irregular stereochemistry. The RbO7 coordination comprises bridging oxygen donors from two water molecules, three carboxylate groups, and a nitro group, with one doubly bridging. The RbO6N coordination comprises the two bridging water molecules, one monodentate amine N donor, one carboxyl O donor and three O donors from nitro groups (one from the chelate bridge). The extension of the dinuclear unit gives a three-dimensional polymeric structure which is stabilized by both intra- and intermolecular amine N-H...O and water O-H...O hydrogen bonds to carboxyl and water O-atom acceptors, as well as a number of inter-ring \p--\p interactions [minimum ring centroid separation, 3.364(2) \%A]. This complex is both isostructural with the analogous Cs -nitroanthranilate monohydrate complex.

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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...

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Introduction Intervertebral stapling is a leading method of fusionless scoliosis treatment which attempts to control growth by applying pressure to the convex side of a scoliotic curve in accordance with the Hueter-Volkmann principle. In addition to that, staples have the potential to damage surrounding bone during insertion and subsequent loading. The aim of this study was to assess the extent of bony structural damage including epiphyseal injury as a result of intervertebral stapling using an in vitro bovine model. Materials and Methods Thoracic spines from 6-8 week old calves were dissected and divided into motion segments including levels T4-T11 (n=14). Each segment was potted in polymethylemethacrylate. An Instron Biaxial materials testing machine with a custom made jig was used for testing. The segments were tested in flexion/extension, lateral bending and axial rotation at 37⁰C and 100% humidity, using moment control to a maximum 1.75 Nm with a loading rate of 0.3 Nm per second for 10 cycles. The segments were initially tested uninstrumented with data collected from the tenth load cycle. Next an anterolateral 4-prong Shape Memory Alloy (SMA) staple (Medtronic Sofamor Danek, USA) was inserted into each segment. Biomechanical testing was repeated as before. The staples were cut in half with a diamond saw and carefully removed. Micro-CT scans were performed and sagittal, transverse and coronal reformatted images were produced using ImageJ (NIH, USA).The specimens were divided into 3 grades (0, 1 and 2) according to the number of epiphyses damaged by the staple prongs. Results: There were 9 (65%) segments with grade 1 staple insertions and 5 (35%) segments with grade 2 insertions. There were no grade 0 staples. Grade 2 spines had a higher stiffness level than grade 1 spines, in all axes of movement, by 28% (p=0.004). This was most noted in flexion/extension with an increase of 49% (p=0.042), followed by non-significant change in lateral bending 19% (p=0.129) and axial rotation 8% (p=0.456) stiffness. The cross sectional area of bone destruction from the prongs was only 0.4% larger in the grade 2 group compared to the grade 1 group (p=0.961). Conclusion Intervertebral staples cause epiphyseal damage. There is a difference in stiffness between grade 1 and grade 2 staple insertion segments in flexion/extension only. There is no difference in the cross section of bone destruction as a result of prong insertion and segment motion.

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Introduction This investigation aimed to assess the consistency and accuracy of radiation therapists (RTs) performing cone beam computed tomography (CBCT) alignment to fiducial markers (FMs) (CBCTFM) and the soft tissue prostate (CBCTST). Methods Six patients receiving prostate radiation therapy underwent daily CBCTs. Manual alignment of CBCTFM and CBCTST was performed by three RTs. Inter-observer agreement was assessed using a modified Bland–Altman analysis for each alignment method. Clinically acceptable 95% limits of agreement with the mean (LoAmean) were defined as ±2.0 mm for CBCTFM and ±3.0 mm for CBCTST. Differences between CBCTST alignment and the observer-averaged CBCTFM (AvCBCTFM) alignment were analysed. Clinically acceptable 95% LoA were defined as ±3.0 mm for the comparison of CBCTST and AvCBCTFM. Results CBCTFM and CBCTST alignments were performed for 185 images. The CBCTFM 95% LoAmean were within ±2.0 mm in all planes. CBCTST 95% LoAmean were within ±3.0 mm in all planes. Comparison of CBCTST with AvCBCTFM resulted in 95% LoA of −4.9 to 2.6, −1.6 to 2.5 and −4.7 to 1.9 mm in the superior–inferior, left–right and anterior–posterior planes, respectively. Conclusions Significant differences were found between soft tissue alignment and the predicted FM position. FMs are useful in reducing inter-observer variability compared with soft tissue alignment. Consideration needs to be given to margin design when using soft tissue matching due to increased inter-observer variability. This study highlights some of the complexities of soft tissue guidance for prostate radiation therapy.

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Knowledge of CT anatomy is increasingly vital in daily radiotherapy practice, especially with more widespread use of cross-sectional image-guided radiotherapy (IGRT) techniques. Existing CT anatomy texts are predominantly written for the diagnostic practitioner and do not always address the radiotherapy issues while emphasising structures that are not common to radiotherapy practice. CT Anatomy for Radiotherapy is a new radiotherapy-specific text that is intended to prepare the reader for CT interpretation for both IGRT and treatment planning. It is suitable for undergraduate students, qualified therapy radiographers, dosimetrists and may be of interest to oncologists and registrars engaged in treatment planning. All essential structures relevant to radiotherapy are described and depicted on 3D images generated from radiotherapy planning systems. System-based labelled CT images taken in relevant imaging planes and patient positions build up understanding of relational anatomy and CT interpretation. Images are accompanied by comprehensive commentary to aid with interpretation. This simplified approach is used to empower the reader to rapidly gain image interpretation skills. The book pays special attention to lymph node identification as well as featuring a unique section on Head and Neck Deep Spaces to help understanding of common pathways of tumour spread. Fully labelled CT images using radiotherapy-specific views and positioning are complemented where relevant by MR and fusion images. A brief introduction to image interpretation using IGRT devices is also covered. The focus of the book is on radiotherapy and some images of common tumour pathologies are utilised to illustrate some relevant abnormal anatomy. Short self-test questions help to keep the reader engaged throughout.