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Sökning: L773:1361 6560 > Nyholm Tufve

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1.
  • Speight, Richard, et al. (författare)
  • IPEM Topical Report : an international IPEM survey of MRI use for external beam radiotherapy treatment planning
  • 2021
  • Ingår i: Physics in Medicine and Biology. - : Institute of Physics (IOP). - 0031-9155 .- 1361-6560. ; 66:7
  • Tidskriftsartikel (refereegranskat)abstract
    • Introduction/Background: Despite growing interest in magnetic resonance imaging (MRI), integration in external beam radiotherapy (EBRT) treatment planning uptake varies globally. In order to understand the current international landscape of MRI in EBRT a survey has been performed in 11 countries. This work reports on differences and common themes identified.Methods: A multi-disciplinary Institute of Physics and Engineering in Medicine working party modified a survey previously used in the UK to understand current practice using MRI for EBRT treatment planning, investigate how MRI is currently used and managed as well as identify knowledge gaps. It was distributed electronically within 11 countries: Australia, Belgium, Denmark, Finland, France, Italy, the Netherlands, New Zealand, Sweden, the UK and the USA.Results: The survey response rate within the USA was <1% and hence these results omitted from the analysis. In the other 10 countries the survey had a median response rate of 77% per country. Direct MRI access, defined as either having a dedicated MRI scanner for radiotherapy (RT) or access to a radiology MRI scanner, varied between countries. France, Italy and the UK reported the lowest direct MRI access rates and all other countries reported direct access in ≥82% of centres. Whilst ≥83% of centres in Denmark and Sweden reported having dedicated MRI scanners for EBRT, all other countries reported ≤29%. Anatomical sites receiving MRI for EBRT varied between countries with brain, prostate, head and neck being most common. Commissioning and QA of image registration and MRI scanners varied greatly, as did MRI sequences performed, staffing models and training given to different staff groups. The lack of financial reimbursement for MR was a consistent barrier for MRI implementation for RT for all countries and MR access was a reported important barrier for all countries except Sweden and Denmark.Conclusion: No country has a comprehensive approach for MR in EBRT adoption and financial barriers are present worldwide. Variations between countries in practice, equipment, staffing models, training, QA and MRI sequences have been identified, and are likely to be due to differences in funding as well as a lack of consensus or guidelines in the literature. Access to dedicated MR for EBRT is limited in all but Sweden and Denmark, but in all countries there are financial challenges with ongoing per patient costs. Despite these challenges, significant interest exists in increasing MR guided EBRT planning over the next 5 years.
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2.
  • Fetty, Lukas, et al. (författare)
  • Investigating conditional GAN performance with different generator architectures, an ensemble model, and different MR scanners for MR-sCT conversion
  • 2020
  • Ingår i: Physics in Medicine and Biology. - : Institute of Physics Publishing (IOPP). - 0031-9155 .- 1361-6560. ; 65:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Recent developments in magnetic resonance (MR) to synthetic computed tomography (sCT) conversion have shown that treatment planning is possible without an initial planning CT. Promising conversion results have been demonstrated recently using conditional generative adversarial networks (cGANs). However, the performance is generally only tested on images from one MR scanner, which neglects the potential of neural networks to find general high-level abstract features. In this study, we explored the generalizability of the generator models, trained on a single field strength scanner, to data acquired with higher field strengths. T2-weighted 0.35T MRIs and CTs from 51 patients treated for prostate (40) and cervical cancer (11) were included. 25 of them were used to train four different generators (SE-ResNet, DenseNet, U-Net, and Embedded Net). Further, an ensemble model was created from the four network outputs. The models were validated on 16 patients from a 0.35T MR scanner. Further, the trained models were tested on the Gold Atlas dataset, containing T2-weighted MR scans of different field strengths; 1.5T(7) and 3T(12), and 10 patients from the 0.35T scanner. The sCTs were dosimetrically compared using clinical VMAT plans for all test patients. For the same scanner (0.35T), the results from the different models were comparable on the test set, with only minor differences in the mean absolute error (MAE) (35-51HU body). Similar results were obtained for conversions of 3T GE Signa and the 3T GE Discovery images (40-62HU MAE) for three of the models. However, larger differences were observed for the 1.5T images (48-65HU MAE). The overall best model was found to be the ensemble model. All dose differences were below 1%. This study shows that it is possible to generalize models trained on images of one scanner to other scanners and different field strengths. The best metric results were achieved by the combination of all networks.
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3.
  • Garpebring, Anders, et al. (författare)
  • Density Estimation of Grey-Level Co-Occurrence Matrices for Image Texture Analysis
  • 2018
  • Ingår i: Physics in Medicine and Biology. - : Institute of Physics and Engineering in Medicine. - 0031-9155 .- 1361-6560. ; 63:19, s. 9-15
  • Tidskriftsartikel (refereegranskat)abstract
    • The Haralick texture features are common in the image analysis literature, partly because of their simplicity and because their values can be interpreted. It was recently observed that the Haralick texture features are very sensitive to the size of the GLCM that was used to compute them, which led to a new formulation that is invariant to the GLCM size. However, these new features still depend on the sample size used to compute the GLCM, i.e. the size of the input image region-of-interest (ROI).The purpose of this work was to investigate the performance of density estimation methods for approximating the GLCM and subsequently the corresponding invariant features.Three density estimation methods were evaluated, namely a piece-wise constant distribution, the Parzen-windows method, and the Gaussian mixture model. The methods were evaluated on 29 different image textures and 20 invariant Haralick texture features as well as a wide range of different ROI sizes.The results indicate that there are two types of features: those that have a clear minimum error for a particular GLCM size for each ROI size, and those whose error decreases monotonically with increased GLCM size. For the first type of features, the Gaussian mixture model gave the smallest errors, and in particular for small ROI sizes (less than about 20×20).In conclusion, the Gaussian mixture model is the preferred method for the first type of features (in particular for small ROIs). For the second type of features, simply using a large GLCM size is preferred.
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4.
  • Kaushik, Sandeep S., et al. (författare)
  • Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network
  • 2023
  • Ingår i: Physics in Medicine and Biology. - : Institute of Physics (IOP). - 0031-9155 .- 1361-6560. ; 68:19
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT via an MR image. In this work, we aim to demonstrate a method to generate accurate synthetic CT (sCT) from an MR image to suit the radiation therapy (RT) treatment planning workflow. We show the feasibility of the method and make way for a broader clinical evaluation.Approach: We present a machine learning method for sCT generation from zero-echo-time (ZTE) MRI aimed at structural and quantitative accuracies of the image, with a particular focus on the accurate bone density value prediction. The misestimation of bone density in the radiation path could lead to unintended dose delivery to the target volume and results in suboptimal treatment outcome. We propose a loss function that favors a spatially sparse bone region in the image. We harness the ability of the multi-task network to produce correlated outputs as a framework to enable localization of region of interest (RoI) via segmentation, emphasize regression of values within RoI and still retain the overall accuracy via global regression. The network is optimized by a composite loss function that combines a dedicated loss from each task.Main results: We have included 54 brain patient images in this study and tested the sCT images against reference CT on a subset of 20 cases. A pilot dose evaluation was performed on 9 of the 20 test cases to demonstrate the viability of the generated sCT in RT planning. The average quantitative metrics produced by the proposed method over the test set were-(a) mean absolute error (MAE) of 70 ± 8.6 HU; (b) peak signal-to-noise ratio (PSNR) of 29.4 ± 2.8 dB; structural similarity metric (SSIM) of 0.95 ± 0.02; and (d) Dice coefficient of the body region of 0.984 ± 0.Significance: We demonstrate that the proposed method generates sCT images that resemble visual characteristics of a real CT image and has a quantitative accuracy that suits RT dose planning application. We compare the dose calculation from the proposed sCT and the real CT in a radiation therapy treatment planning setup and show that sCT based planning falls within 0.5% target dose error. The method presented here with an initial dose evaluation makes an encouraging precursor to a broader clinical evaluation of sCT based RT planning on different anatomical regions.
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5.
  • Kuess, Peter, et al. (författare)
  • Association between pathology and texture features of multi parametric MRI of the prostate
  • 2017
  • Ingår i: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 62:19, s. 7833-7854
  • Tidskriftsartikel (refereegranskat)abstract
    • The role of multi-parametric (mp)MRI in the diagnosis and treatment of prostate cancer has increased considerably. An alternative to visual inspection of mpMRI is the evaluation using histogram-based (first order statistics) parameters and textural features (second order statistics). The aims of the present work were to investigate the relationship between benign and malignant sub-volumes of the prostate and textures obtained from mpMR images. The performance of tumor prediction was investigated based on the combination of histogram-based and textural parameters. Subsequently, the relative importance of mpMR images was assessed and the benefit of additional imaging analyzed. Finally, sub-structures based on the PI-RADS classification were investigated as potential regions to automatically detect maligned lesions. Twenty-five patients who received mpMRI prior to radical prostatectomy were included in the study. The imaging protocol included T2, DWI, and DCE. Delineation of tumor regions was performed based on pathological information. First and second order statistics were derived from each structure and for all image modalities. The resulting data were processed with multivariate analysis, using PCA (principal component analysis) and OPLS-DA (orthogonal partial least squares discriminant analysis) for separation of malignant and healthy tissue. PCA showed a clear difference between tumor and healthy regions in the peripheral zone for all investigated images. The predictive ability of the OPLS-DA models increased for all image modalities when first and second order statistics were combined. The predictive value reached a plateau after adding ADC and T2, and did not increase further with the addition of other image information. The present study indicates a distinct difference in the signatures between malign and benign prostate tissue. This is an absolute prerequisite for automatic tumor segmentation, but only the first step in that direction. For the specific identified signature, DCE did not add complementary information to T2 and ADC maps.
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6.
  • Georg, Dietmar, et al. (författare)
  • Patient-specific IMRT verification using independent fluence-based dose calculation software : experimental benchmarking and initial clinical experience
  • 2007
  • Ingår i: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 52:16, s. 4981-4992
  • Tidskriftsartikel (refereegranskat)abstract
    • Experimental methods are commonly used for patient-specific intensity-modulated radiotherapy (IMRT) verification. The purpose of this study was to investigate the accuracy and performance of independent dose calculation software ( denoted as 'MUV' ( monitor unit verification)) for patient-specific quality assurance (QA). 52 patients receiving step-and-shoot IMRT were considered. IMRT plans were recalculated by the treatment planning systems (TPS) in a dedicated QA phantom, in which an experimental 1D and 2D verification (0.3 cm(3) ionization chamber; films) was performed. Additionally, an independent dose calculation was performed. The fluence-based algorithm of MUV accounts for collimator transmission, rounded leaf ends, tongue-and-groove effect, backscatter to the monitor chamber and scatter from the flattening filter. The dose calculation utilizes a pencil beam model based on a beam quality index. DICOM RT files from patient plans, exported from the TPS, were directly used as patient-specific input data in MUV. For composite IMRT plans, average deviations in the high dose region between ionization chamber measurements and point dose calculations performed with the TPS and MUV were 1.6 +/- 1.2% and 0.5 +/- 1.1% ( 1 S. D.). The dose deviations between MUV and TPS slightly depended on the distance from the isocentre position. For individual intensity-modulated beams ( total 367), an average deviation of 1.1 +/- 2.9% was determined between calculations performed with the TPS and with MUV, with maximum deviations up to 14%. However, absolute dose deviations were mostly less than 3 cGy. Based on the current results, we aim to apply a confidence limit of 3% ( with respect to the prescribed dose) or 6 cGy for routine IMRT verification. For off-axis points at distances larger than 5 cm and for low dose regions, we consider 5% dose deviation or 10 cGy acceptable. The time needed for an independent calculation compares very favourably with the net time for an experimental approach. The physical effects modelled in the dose calculation software MUV allow accurate dose calculations in individual verification points. Independent calculations may be used to replace experimental dose verification once the IMRT programme is mature.
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7.
  • Nyholm, Tufve, et al. (författare)
  • Modelling lateral beam quality variations in pencil kernel based photon dose calculations
  • 2006
  • Ingår i: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 51:16, s. 4111-4118
  • Tidskriftsartikel (refereegranskat)abstract
    • Standard treatment machines for external radiotherapy are designed to yield flat dose distributions at a representative treatment depth. The common method to reach this goal is to use a flattening filter to decrease the fluence in the centre of the beam. A side effect of this filtering is that the average energy of the beam is generally lower at a distance from the central axis, a phenomenon commonly referred to as off-axis softening. The off-axis softening results in a relative change in beam quality that is almost independent of machine brand and model. Central axis dose calculations using pencil beam kernels show no drastic loss in accuracy when the off-axis beam quality variations are neglected. However, for dose calculated at off-axis positions the effect should be considered, otherwise errors of several per cent can be introduced. This work proposes a method to explicitly include the effect of off-axis softening in pencil kernel based photon dose calculations for arbitrary positions in a radiation field. Variations of pencil kernel values are modelled through a generic relation between half value layer (HVL) thickness and off-axis position for standard treatment machines. The pencil kernel integration for dose calculation is performed through sampling of energy fluence and beam quality in sectors of concentric circles around the calculation point. The method is fully based on generic data and therefore does not require any specific measurements for characterization of the off-axis softening effect, provided that the machine performance is in agreement with the assumed HVL variations. The model is verified versus profile measurements at different depths and through a model self-consistency check, using the dose calculation model to estimate HVL values at off-axis positions. A comparison between calculated and measured profiles at different depths showed a maximum relative error of 4% without explicit modelling of off-axis softening. The maximum relative error was reduced to 1% when the off-axis softening was accounted for in the calculations.
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8.
  • Nyholm, Tufve, et al. (författare)
  • Pencil kernel correction and residual error estimation for quality-index-based dose calculations
  • 2006
  • Ingår i: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 51:23, s. 6245-6262
  • Tidskriftsartikel (refereegranskat)abstract
    • Experimental data from 593 photon beams were used to quantify the errors in dose calculations using a previously published pencil kernel model. A correction of the kernel was derived in order to remove the observed systematic errors. The remaining residual error for individual beams was modelled through uncertainty associated with the kernel model. The methods were tested against an independent set of measurements. No significant systematic error was observed in the calculations using the derived correction of the kernel and the remaining random errors were found to be adequately predicted by the proposed method.
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9.
  • Olofsson, Jörgen, et al. (författare)
  • Optimization of photon beam flatness for radiation therapy
  • 2007
  • Ingår i: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 52:6, s. 1735-1746
  • Tidskriftsartikel (refereegranskat)abstract
    • In this work, we investigate the relation between lateral fluence/dose distributions and photon beam uniformity, possibly identifying ways to improve these characteristics. The calculations included treatment head scatter properties associated with three common types of linear accelerators in order to study their impact on the results. For 6 and 18 MV photon beams the lateral fluence distributions were optimized with respect to the resulting calculated flatness, as defined by the International Electrotechnical Commission (IEC), at 10 cm depth in six different field sizes. The limits proposed by IEC for maximum dose ratios ('horns') at the depth of dose maximum have also been accounted for in the optimization procedure. The conclusion was that typical head scatter variations among different types of linear accelerators have a very limited effect on the optimized results, which implies that the existing differences in measured off-axis dose distributions are related to non-equivalent optimization objectives. Finally, a comparison between the theoretically optimized lateral dose distributions and corresponding dose measurements for the three investigated accelerator types was performed. Although the measured data generally fall within the IEC requirements the optimized distributions show better results overall for the evaluated uniformity parameters, indicating that there is room for improved flatness performance in clinical photon beams.
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