| 1. |
- Mu, Xiangkui, et al.
(författare)
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Does electron and proton therapy reduce the risk of radiation induced cancer after spinal irradiation for childhood medulloblastoma? A comparative treatment planning study.
- 2005
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Ingår i: Acta oncologica (Stockholm, Sweden). - : Informa UK Limited. - 0284-186X .- 1651-226X. ; 44:6, s. 554-62
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this treatment planning comparison study was to explore different spinal irradiation techniques with respect to the risk of late side-effects, particularly radiation-induced cancer. The radiotherapy techniques compared were conventional photon therapy, intensity modulated x-ray therapy (IMXT), conventional electron therapy, intensity/energy modulated electron therapy (IMET) and proton therapy (IMPT).CT images for radiotherapy use from five children, median age 8 and diagnosed with medulloblastoma, were selected for this study. Target volumes and organs at risk were defined in 3-D. Treatment plans using conventional photon therapy, IMXT, conventional electron therapy, IMET and IMPT were set up. The probability of normal tissue complication (NTCP) and the risk of cancer induction were calculated using models with parameters-sets taken from published data for the general population; dose data were taken from dose volume histograms (DVH).Similar dose distributions in the targets were achieved with all techniques but the absorbed doses in the organs-at-risk varied significantly between the different techniques. The NTCP models based on available data predicted very low probabilities for side-effects in all cases. However, the effective mean doses outside the target volumes, and thus the predicted risk of cancer induction, varied significantly between the techniques. The highest lifetime risk of secondary cancers was estimated for IMXT (30%). The lowest risk was found with IMPT (4%). The risks associated with conventional photon therapy, electron therapy and IMET were 20%, 21% and 15%, respectively.This model study shows that spinal irradiation of young children with photon and electron techniques results in a substantial risk of radiation-induced secondary cancers. Multiple beam IMXT seems to be associated with a particularly high risk of secondary cancer induction. To minimise this risk, IMPT should be the treatment of choice. If proton therapy is not available, advanced electron therapy may provide a better alternative.
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| 2. |
- Garpebring, Anders, et al.
(författare)
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Uncertainty estimation in dynamic contrast-enhanced MRI
- 2013
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Ingår i: Magnetic Resonance in Medicine. - : Wiley-Blackwell. - 0740-3194 .- 1522-2594. ; 69:4, s. 992-1002
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Tidskriftsartikel (refereegranskat)abstract
- Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK parameters. Uncertainties in the PK parameters were investigated for the modified Kety model. The method was evaluated with Monte Carlo simulations and exemplified with in vivo brain tumor data. PK parameter uncertainties due to noise in dynamic data were accurately estimated. Noise with standard deviation up to 15% in the baseline signal and the baseline T1 map gave estimated uncertainties in good agreement with the Monte Carlo simulations. Good agreement was also found for up to 15% errors in the arterial input function amplitude. The method was less accurate for errors in the bolus arrival time with disagreements of 23%, 32%, and 29% for Ktrans, ve, and vp, respectively, when the standard deviation of the bolus arrival time error was 5.3 s. In conclusion, the proposed method provides efficient means for calculation of uncertainty maps, and it was applicable to a wide range of sources of uncertainty.
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| 3. |
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| 4. |
- Glimelius, B., et al.
(författare)
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Number of patients potentially eligible for proton therapy
- 2005
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Ingår i: Acta Oncol. - : Informa UK Limited. - 0284-186X .- 1651-226X. ; 44:8, s. 836-49
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Tidskriftsartikel (refereegranskat)abstract
- A group of Swedish radiation oncologists and hospital physicists have estimated the number of patients in Sweden suitable for proton beam therapy in a facility where one of the principal aims is to facilitate randomized and other studies in which the advantage of protons can be shown and the magnitude of the differences compared with optimally administered conventional radiation treatment, also including intensity-modulated radiation therapy (IMRT) and brachytherapy, can be shown. The estimations have been based on current statistics of tumour incidence in Sweden, number of patients potentially eligible for radiation treatment, scientific support from clinical trials and model dose planning studies and knowledge of the dose-response relations of different tumours together with information on normal tissue complication rates. In Sweden, it is assessed that between 2200 and 2500 patients annually are eligible for proton beam therapy, and that for these patients the potential therapeutic benefit is so great as to justify the additional expense of proton therapy. This constitutes between 14-15% of all irradiated patients annually.
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| 5. |
- Häggström, Ida, 1982-, et al.
(författare)
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A Monte Carlo study of the dependence of early frame sampling on uncertainty and bias in pharmacokinetic parameters from dynamic PET
- 2015
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Ingår i: Journal of Nuclear Medicine Technology. - : Society of Nuclear Medicine. - 0091-4916 .- 1535-5675. ; 43:1, s. 53-60
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Tidskriftsartikel (refereegranskat)abstract
- Compartmental modeling of dynamic PET data enables quantifi- cation of tracer kinetics in vivo, through the calculated model parameters. In this study, we aimed to investigate the effect of early frame sampling and reconstruction method on pharmacokinetic parameters obtained from a 2-tissue model, in terms of bias and uncertainty (SD). Methods: The GATE Monte Carlo software was used to simulate 2 · 15 dynamic 3′-deoxy-3′-18F-fluorothymidine (18F-FLT) brain PET studies, typical in terms of noise level and kinetic parameters. The data were reconstructed by both 3- dimensional (3D) filtered backprojection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM) into 6 dynamic image sets with different early frame durations of 1, 2, 4, 6, 10, and 15 s. Bias and SD were evaluated for fitted parameter estimates, calculated from regions of interest. Results: The 2-tissue-model parameter estimates K1, k2, and fraction of arterial blood in tissue depended on early frame sampling, and a sampling of 6–15 s generally minimized bias and SD. The shortest sampling of 1 s yielded a 25% and 42% larger bias than the other schemes, for 3DRP and OSEM, respectively, and a parameter uncertainty that was 10%–70% higher. The schemes from 4 to 15 s were generally not significantly different in regards to bias and SD. Typically, the reconstruction method 3DRP yielded less framesampling dependence and less uncertain results, compared with OSEM, but was on average more biased. Conclusion: Of the 6 sampling schemes investigated in this study, an early frame duration of 6–15 s generally kept both bias and uncertainty to a minimum, for both 3DRP and OSEM reconstructions. Veryshort frames of 1 s should be avoided because they typically resulted in the largest parameter bias and uncertainty. Furthermore, 3DRP may be p
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| 6. |
- Häggström, Ida, 1982-
(författare)
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Quantitative methods for tumor imaging with dynamic PET
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- There is always a need and drive to improve modern cancer care. Dynamic positron emission tomography (PET) offers the advantage of in vivo functional imaging, combined with the ability to follow the physiological processes over time. In addition, by applying tracer kinetic modeling to the dynamic PET data, thus estimating pharmacokinetic parameters associated to e.g. glucose metabolism, cell proliferation etc., more information about the tissue's underlying biology and physiology can be determined. This supplementary information can potentially be a considerable aid when it comes to the segmentation, diagnosis, staging, treatment planning, early treatment response monitoring and follow-up of cancerous tumors.We have found it feasible to use kinetic parameters for semi-automatic tumor segmentation, and found parametric images to have higher contrast compared to static PET uptake images. There are however many possible sources of errors and uncertainties in kinetic parameters obtained through compartment modeling of dynamic PET data. The variation in the number of detected photons caused by the random nature of radioactive decay, is of course always a major source. Other sources may include: the choice of an appropriate model that is suitable for the radiotracer in question, camera detectors and electronics, image acquisition protocol, image reconstruction algorithm with corrections (attenuation, random and scattered coincidences, detector uniformity, decay) and so on. We have found the early frame sampling scheme in dynamic PET to affect the bias and uncertainty in calculated kinetic parameters, and that scatter corrections are necessary for most but not all parameter estimates. Furthermore, analytical image reconstruction algorithms seem more suited for compartment modeling applications compared to iterative algorithms.This thesis and included papers show potential applications and tools for quantitative pharmacokinetic parameters in oncology, and help understand errors and uncertainties associated with them. The aim is to contribute to the long-term goal of enabling the use of dynamic PET and pharmacokinetic parameters for improvements of today's cancer care.
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| 7. |
- Häggström, Ida, 1982-, et al.
(författare)
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Semi-automatic tumour segmentation by selective navigation in a three-parameter volume, obtained by voxel-wise kinetic modelling of C-11-acetate
- 2010
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Ingår i: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 0144-8420 .- 1742-3406. ; 139:1-3, s. 214-218
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Tidskriftsartikel (refereegranskat)abstract
- Positron emission tomography (PET) is increasingly used for delineation of tumour tissue in, for example, radiotherapy treatment planning. The most common method used is to outline volumes with a certain per cent uptake over background in a static image. However, PET data can also be collected dynamically and analysed by kinetic models, which potentially represent the underlying biology better. In the present study, a three-parameter kinetic model was used for voxel-wise evaluation of C-11-acetate data of head/neck tumours. These parameters which represent the tumour blood volume, the uptake rate and the clearance rate of the tissue were derived for each voxel using a linear regression method and used for segmentation of active tumour tissue. This feasibility study shows that it is possible to segment images based on derived model parameters. There is, however, room for improvements concerning the PET data acquisition, noise reduction and the kinetic modelling. In conclusion, this early study indicates a strong potential of the method even though no 'true' tumour volume was available for validation.
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| 8. |
- Häggström, Ida, et al.
(författare)
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The influence of time sampling scheme on kinetic parameters obtained from compartmental modeling of a dynamic PET study : a Monte Carlo study
- 2012
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Ingår i: IEEE Nuclear Science Symposium Conference Record. - Anaheim : IEEE conference proceedings. - 9781467320306 ; , s. 3101-3107
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Konferensbidrag (refereegranskat)abstract
- Compartmental modeling of dynamic PET data enables quantification of tracer kinetics in vivo, through the obtained model parameters. The dynamic data is sorted into frames during or after the acquisition, with a sampling interval usually ranging from 10 s to 300 s. In this study we wanted to investigate the effect of the chosen sampling interval on kinetic parameters obtained from a 2-tissue model, in terms of bias and standard deviation, using a complete Monte Carlo simulated dynamic F-18-FLT PET study. The results show that the bias and standard deviation in parameter K-1 is small regardless of sampling scheme or noise in the time-activity curves (TACs), and that the bias and standard deviation in k(4) is large for all cases. The bias in V-a is clearly dependent on sampling scheme, increasing for increased sampling interval. In general, a too short sampling interval results in very noisy images and a large bias of the parameter estimate, and a too long sampling interval also increases bias. Noise in the TACs is the largest source of bias.
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| 9. |
- Johansson, Adam, et al.
(författare)
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CT substitute derived from MRI sequences with ultrashort echo time
- 2011
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Ingår i: Medical physics (Lancaster). - : American Association of Physicists in Medicine. - 0094-2405. ; 38:5, s. 2708-2714
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Methods for deriving computed tomography (CT) equivalent information from MRI are needed for attenuation correction in PET/MRI applications, as well as for patient positioning and dose planning in MRI based radiation therapy workflows. This study presents a method for generating a drop in substitute for a CT image from a set of magnetic resonance (MR)images. Methods:A Gaussian mixture regression model was used to link the voxel values in CT images to the voxel values in images from three MRI sequences: one T2 weighted 3D spin echo based sequence and two dual echo ultrashort echo time MRI sequences with different echo times and flip angles. The method used a training set of matched MR and CT data that after training was able to predict a substitute CT (s-CT) based entirely on the MR information for a new patient. Method validation was achieved using datasets covering the heads of five patients and applying leave-one-out cross-validation (LOOCV). During LOOCV, the model was estimated from the MR and CT data of four patients (training set) and applied to the MR data of the remaining patient (validation set) to generate an s-CT image. This procedure was repeated for all five training and validation data combinations. Results: The mean absolute error for the CT number in the s-CT images was 137 HU. No large differences in method accuracy were noted for the different patients, indicating a robust method. The largest errors in the s-CT images were found at air–tissue and bone–tissue interfaces. The model accurately discriminated between air and bone, as well as between soft tissues and nonsoft tissues. Conclusions: The s-CT method has the potential to provide an accurate estimation of CT information without risk of geometrical inaccuracies as the model is voxel based. Therefore, s-CT images could be well suited as alternatives to CT images for dose planning in radiotherapy and attenuation correction in PET/MRI.
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| 10. |
- Johansson, Adam, et al.
(författare)
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Improved quality of computed tomography substitute derived from magnetic resonance (MR) data by incorporation of spatial information : potential application for MR-only radiotherapy and attenuation correction in positron emission tomography
- 2013
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Ingår i: Acta Oncologica. - 0284-186X .- 1651-226X. ; 52:7, s. 1369-1373
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Tidskriftsartikel (refereegranskat)abstract
- Background: Estimation of computed tomography (CT) equivalent data, i.e. a substitute CT (s-CT), from magnetic resonance (MR) images is a prerequisite both for attenuation correction of positron emission tomography (PET) data acquired with a PET/MR scanner and for dose calculations in an MR-only radiotherapy workflow. It has previously been shown that it is possible to estimate Hounsfield numbers based on MR image intensities, using ultra short echo-time imaging and Gaussian mixture regression (GMR). In the present pilot study we investigate the possibility to also include spatial information in the GMR, with the aim to improve the quality of the s-CT. Material and methods: MR and CT data for nine patients were used in the present study. For each patient, GMR models were created from the other eight patients, including either both UTE image intensities and spatial information on a voxel by voxel level, or only UTE image intensities. The models were used to create s-CT images for each respective patient. Results: The inclusion of spatial information in the GMR model improved the accuracy of the estimated s-CT. The improvement was most pronounced in smaller, complicated anatomical regions as the inner ear and post-nasal cavities. Conclusions: This pilot study shows that inclusion of spatial information in GMR models to convert MR data to CT equivalent images is feasible. The accuracy of the s-CT is improved and the spatial information could make it possible to create a general model for the conversion applicable to the whole body.
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