5 research outputs found

    Direct aperture optimization as a means of reducing the complexity of intensity modulated radiation therapy plans

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    Intensity Modulated Radiation Therapy (IMRT) is a means of delivering radiation therapy where the intensity of the beam is varied within the treatment field. This is done by dividing a large beam into many small beamlets. Dose constraints are assigned to both the target and sensitive structures and computerised inverse optimization is performed to find the individual weights of this large number of beamlets. The computer adjusts the intensities of these beamlets according to the required planning dose objectives. The optimized intensity patterns are then decomposed into a series of deliverable multi leaf collimator (MLC) shapes in the sequencing step

    Registration accuracy for MR images of the prostate using a subvolume based registration protocol

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    <p>Abstract</p> <p>Background</p> <p>In recent years, there has been a considerable research effort concerning the integration of magnetic resonance imaging (MRI) into the external radiotherapy workflow motivated by the superior soft tissue contrast as compared to computed tomography. Image registration is a necessary step in many applications, e.g. in patient positioning and therapy response assessment with repeated imaging. In this study, we investigate the dependence between the registration accuracy and the size of the registration volume for a subvolume based rigid registration protocol for MR images of the prostate.</p> <p>Methods</p> <p>Ten patients were imaged four times each over the course of radiotherapy treatment using a T2 weighted sequence. The images were registered to each other using a mean square distance metric and a step gradient optimizer for registration volumes of different sizes. The precision of the registrations was evaluated using the center of mass distance between the manually defined prostates in the registered images. The optimal size of the registration volume was determined by minimizing the standard deviation of these distances.</p> <p>Results</p> <p>We found that prostate position was most uncertain in the anterior-posterior (AP) direction using traditional full volume registration. The improvement in standard deviation of the mean center of mass distance between the prostate volumes using a registration volume optimized to the prostate was 3.9 mm (p < 0.001) in the AP direction. The optimum registration volume size was 0 mm margin added to the prostate gland as outlined in the first image series.</p> <p>Conclusions</p> <p>Repeated MR imaging of the prostate for therapy set-up or therapy assessment will both require high precision tissue registration. With a subvolume based registration the prostate registration uncertainty can be reduced down to the order of 1 mm (1 SD) compared to several millimeters for registration based on the whole pelvis.</p

    DCE-MRI perfusion and permeability parameters as predictors of tumor response to CCRT in patients with locally advanced NSCLC

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    In this prospective study, 36 patients with stage III non-small cell lung cancers (NSCLC), who underwent dynamic contrast-enhanced MRI (DCE-MRI) before concurrent chemo-radiotherapy (CCRT) were enrolled. Pharmacokinetic analysis was carried out after non-rigid motion registration. The perfusion parameters including Blood Flow (BF), Blood Volume (BV), Mean Transit Time (MTT) and permeability parameters including endothelial transfer constant (Ktrans), reflux rate (Kep), fractional extravascular extracellular space volume (Ve), fractional plasma volume (Vp) were calculated, and their relationship with tumor regression was evaluated. The value of these parameters on predicting responders were calculated by receiver operating characteristic (ROC) curve. Multivariate logistic regression analysis was conducted to find the independent variables. Tumor regression rate is negatively correlated with V e and its standard variation V e-SD and positively correlated with K trans and Kep. Significant differences between responders and non-responders existed in Ktrans, Kep, Ve, Ve-SD, MTT, BV-SD and MTT-SD (P &lt; 0.05). ROC indicated that Ve &lt; 0.24 gave the largest area under curve of 0.865 to predict responders. Multivariate logistic regression analysis also showed Ve was a significant predictor. Baseline perfusion and permeability parameters calculated from DCE-MRI were seen to be a viable tool for predicting the early treatment response after CCRT of NSCLC. © 2016 The Author(s)

    Development and Validation of Automated 2D–3D Bronchial Airway Matching to Track Changes in Regional Bronchial Morphology Using Serial Low-Dose Chest CT Scans in Children with Chronic Lung Disease

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    To address potential concern for cumulative radiation exposure with serial spiral chest computed tomography (CT) scans in children with chronic lung disease, we developed an approach to match bronchial airways on low-dose spiral and low-dose high-resolution CT (HRCT) chest images to allow serial comparisons. An automated algorithm matches the position and orientation of bronchial airways obtained from HRCT slices with those in the spiral CT scan. To validate this algorithm, we compared manual matching vs automatic matching of bronchial airways in three pediatric patients. The mean absolute percentage difference between the manually matched spiral CT airway and the index HRCT airways were 9.4 ± 8.5% for the internal diameter measurements, 6.0 ± 4.1% for the outer diameter measurements, and 10.1 ± 9.3% for the wall thickness measurements. The mean absolute percentage difference between the automatically matched spiral CT airway measurements and index HRCT airway measurements were 9.2 ± 8.6% for the inner diameter, 5.8 ± 4.5% for the outer diameter, and 9.9 ± 9.5% for the wall thickness. The overall difference between manual and automated methods was 2.1 ± 1.2%, which was significantly less than the interuser variability of 5.1 ± 4.6% (p < 0.05). Tests of equivalence had p < 0.05, demonstrating no significant difference between the two methods. The time required for matching was significantly reduced in the automated method (p < 0.01) and was as accurate as manual matching, allowing efficient comparison of airways obtained on low-dose spiral CT imaging with low-dose HRCT scans
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