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1.	Daniel, M., et al. (author) Pilot study : Textural features of mpMRI for response assessment in prostate cancer patients 2019 In: Radiotherapy and Oncology. - : Elsevier. - 0167-8140 .- 1879-0887. ; 133, s. S1113-S1113 Journal article (other academic/artistic)
2.	Adjeiwaah, Mary, 1980-, et al. (author) Dosimetric Impact of MRI Distortions : A Study on Head and Neck Cancers 2019 In: International Journal of Radiation Oncology, Biology, Physics. - : Elsevier. - 0360-3016 .- 1879-355X. ; 103:4, s. 994-1003 Journal article (peer-reviewed)abstract Purpose: To evaluate the effect of magnetic resonance (MR) imaging (MRI) geometric distortions on head and neck radiation therapy treatment planning (RTP) for an MRI-only RTP. We also assessed the potential benefits of patient-specific shimming to reduce the magnitude of MR distortions for a 3-T scanner.Methods and Materials: Using an in-house Matlab algorithm, shimming within entire imaging volumes and user-defined regions of interest were simulated. We deformed 21 patient computed tomography (CT) images with MR distortion fields (gradient nonlinearity and patient-induced susceptibility effects) to create distorted CT (dCT) images using bandwidths of 122 and 488 Hz/mm at 3 T. Field parameters from volumetric modulated arc therapy plans initially optimized on dCT data sets were transferred to CT data to compute a new plan. Both plans were compared to determine the impact of distortions on dose distributions.Results: Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2 mm from 15.4% to 2.0%. Using the user-defined region of interest (ROI) shimming strategy, (here the Planning target volume (PTV) was the chosen ROI volume) led to increased geometric for volumes outside the PTV, as such voxels within the spinal cord with geometric shifts above 2 mm increased from 11.5% to 32.3%. The worst phantom-measured residual system distortions after 3-dimensional gradient nonlinearity correction within a radial distance of 200 mm from the isocenter was 2.17 mm. For all patients, voxels with distortion shifts of more than 2 mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122 Hz/mm and 488 Hz/mm at 3 T. Dose differences between dCT and CT treatment plans in D-50 at the planning target volume were 0.4% +/- 0.6% and 0.3% +/- 0.5% at 122 and 488 Hz/mm, respectively.Conclusions: The overall effect of MRI geometric distortions on data used for RTP was minimal. Shimming over entire imaging volumes decreased distortions, but user-defined subvolume shimming introduced significant errors in nearby organs and should probably be avoided.
3.	Adjeiwaah, Mary, 1980- (author) Quality assurance for magnetic resonance imaging (MRI) in radiotherapy 2017 Licentiate thesis (other academic/artistic)abstract Magnetic resonance imaging (MRI) utilizes the magnetic properties of tissues to generate image-forming signals. MRI has exquisite soft-tissue contrast and since tumors are mainly soft-tissues, it offers improved delineation of the target volume and nearby organs at risk. The proposed Magnetic Resonance-only Radiotherapy (MR-only RT) work flow allows for the use of MRI as the sole imaging modality in the radiotherapy (RT) treatment planning of cancer. There are, however, issues with geometric distortions inherent with MR image acquisition processes. These distortions result from imperfections in the main magnetic field, nonlinear gradients, as well as field disturbances introduced by the imaged object. In this thesis, we quantified the effect of system related and patient-induced susceptibility geometric distortions on dose distributions for prostate as well as head and neck cancers. Methods to mitigate these distortions were also studied.In Study I, mean worst system related residual distortions of 3.19, 2.52 and 2.08 mm at bandwidths (BW) of 122, 244 and 488 Hz/pixel up to a radial distance of 25 cm from a 3T PET/MR scanner was measured with a large field of view (FoV) phantom. Subsequently, we estimated maximum shifts of 5.8, 2.9 and 1.5 mm due to patient-induced susceptibility distortions. VMAT-optimized treatment plans initially performed on distorted CT (dCT) images and recalculated on real CT datasets resulted in a dose difference of less than 0.5%. The magnetic susceptibility differences at tissue-metallic,-air and -bone interfaces result in local B0 magnetic field inhomogeneities. The distortion shifts caused by these field inhomogeneities can be reduced by shimming. Study II aimed to investigate the use of shimming to improve the homogeneity of local B0 magnetic field which will be beneficial for radiotherapy applications. A shimming simulation based on spherical harmonics modeling was developed. The spinal cord, an organ at risk is surrounded by bone and in close proximity to the lungs may have high susceptibility differences. In this region, mean pixel shifts caused by local B0 field inhomogeneities were reduced from 3.47±1.22 mm to 1.35±0.44 mm and 0.99±0.30 mm using first and second order shimming respectively. This was for a bandwidth of 122 Hz/pixel and an in-plane voxel size of 1×1 mm2. Also examined in Study II as in Study I was the dosimetric effect of geometric distortions on 21 Head and Neck cancer treatment plans. The dose difference in D50 at the PTV between distorted CT and real CT plans was less than 1.0%.In conclusion, the effect of MR geometric distortions on dose plans was small. Generally, we found patient-induced susceptibility distortions were larger compared with residual system distortions at all delineated structures except the external contour. This information will be relevant when setting margins for treatment volumes and organs at risk. The current practice of characterizing MR geometric distortions utilizing spatial accuracy phantoms alone may not be enough for an MR-only radiotherapy workflow. Therefore, measures to mitigate patient-induced susceptibility effects in clinical practice such as patient-specific correction algorithms are needed to complement existing distortion reduction methods such as high acquisition bandwidth and shimming.
4.	Adjeiwaah, Mary, 1980- (author) Quality assurance for magnetic resonance imaging (MRI) in radiotherapy 2019 Doctoral thesis (other academic/artistic)abstract The use of Magnetic Resonance Imaging (MRI) in the radiotherapy (RT) treatment planning workflow is increasing. MRI offers superior soft-tissue contrast compared to Computed Tomography (CT) and therefore improves the accuracy in target volume definitions. There are, however concerns with inherent geometric distortions from system- (gradient nonlinearities and main magnetic field inhomogeneities) and patient-related sources (magnetic susceptibility effect and chemical shift). The lack of clearly defined quality assurance (QA) procedures has also raised questions on the ability of current QA protocols to detect common image quality degradations under radiotherapy settings. To fully implement and take advantage of the benefits of MRI in radiotherapy, these concerns need to be addressed.In Papers I and II, the dosimetric impact of MR distortions was investigated. Patient CTs (CT) were deformed with MR distortion vector fields (from the residual system distortions after correcting for gradient nonlinearities and patient-induced susceptibility distortions) to create distorted CT (dCT) images. Field parameters from volumetric modulated arc therapy (VMAT) treatment plans initially optimized on dCT data sets were transferred to CT data to compute new treatment plans. Data from 19 prostate and 21 head and neck patients were used for the treatment planning. The dCT and CT treatment plans were compared to determine the impact of distortions on dose distributions. No clinically relevant dose differences between distorted CT and original CT treatment plans were found. Mean dose differences were < 1.0% and < 0.5% at the planning target volume (PTV) for the head and neck, and prostate treatment plans, respectively. Strategies to reduce geometric distortions were also evaluated in Papers I and II. Using the vendor-supplied gradient non-linearity correction algorithm reduced overall distortions to less than half of the original value. A high acquisition bandwidth of 488 Hz/pixel (Paper I) and 488 Hz/mm (Paper II) kept the mean geometric distortions at the delineated structures below 1 mm. Furthermore, a patient-specific active shimming method implemented in Paper II significantly reduced the number of voxels with distortion shifts > 2 mm from 15.4% to 2.0%.B0 maps from patient-induced magnetic field inhomogeneities obtained through direct measurements and by simulations that used MR-generated synthetic CT (sCT) data were compared in Paper III. The validation showed excellent agreement between the simulated and measured B0 maps.In Paper IV, the ability of current QA methods to detect common MR image quality degradations under radiotherapy settings were investigated. By evaluating key image quality parameters, the QA protocols were found to be sensitive to some of the introduced degradations. However, image quality issues such as those caused by RF coil failures could not be adequately detected.In conclusion, this work has shown the feasibility of using MRI data for radiotherapy treatment planning as distortions resulted in a dose difference of less than 1% between distorted and undistorted images. The simulation software can be used to produce accurate B0 maps, which could then be used as the basis for the effective correction of patient-induced field inhomogeneity distortions and for the QA verification of sCT data. Furthermore, the analysis of the strengths and weaknesses in current QA tools for MRI in RT contribute to finding better methods to efficiently identify image quality errors.
5.	Adjeiwaah, Mary, 1980-, et al. (author) Quality Assurance for MRI in Radiotherapy : Sensitivity Analysis of Current Methods Other publication (other academic/artistic)
6.	Adjeiwaah, Mary, et al. (author) Quantifying the Effect of 3T Magnetic Resonance Imaging Residual System Distortions and Patient-Induced Susceptibility Distortions on Radiation Therapy Treatment Planning for Prostate Cancer 2018 In: International Journal of Radiation Oncology, Biology, Physics. - : Elsevier. - 0360-3016 .- 1879-355X. ; 100:2, s. 317-324 Journal article (peer-reviewed)abstract Purpose: To investigate the effect of magnetic resonance system- and patient-induced susceptibility distortions from a 3T scanner on dose distributions for prostate cancers.Methods and Materials: Combined displacement fields from the residual system and patient-induced susceptibility distortions were used to distort 17 prostate patient CT images. VMAT dose plans were initially optimized on distorted CT images and the plan parameters transferred to the original patient CT images to calculate a new dose distribution.Results: Maximum residual mean distortions of 3.19 mm at a radial distance of 25 cm and maximum mean patient-induced susceptibility shifts of 5.8 mm were found using the lowest bandwidth of 122 Hz per pixel. There was a dose difference of <0.5% between distorted and undistorted treatment plans. The 90% confidence intervals of the mean difference between the dCT and CT treatment plans were all within an equivalence interval of (−0.5, 0.5) for all investigated plan quality measures.Conclusions: Patient-induced susceptibility distortions at high field strengths in closed bore magnetic resonance scanners are larger than residual system distortions after using vendor-supplied 3-dimensional correction for the delineated regions studied. However, errors in dose due to disturbed patient outline and shifts caused by patient-induced susceptibility effects are below 0.5%.
7.	Adjeiwaah, Mary, 1980-, et al. (author) Sensitivity analysis of different quality assurance methods for magnetic resonance imaging in radiotherapy 2020 In: Physics and Imaging in Radiation Oncology. - : Elsevier. - 2405-6316. ; 13, s. 21-27 Journal article (peer-reviewed)abstract Background and purpose: There are currently no standard quality assurance (QA) methods for magnetic resonance imaging (MRI) in radiotherapy (RT). This work was aimed at evaluating the ability of two QA protocols to detect common events that affect quality of MR images under RT settings.Materials and methods: The American College of Radiology (ACR) MRI QA phantom was repeatedly scanned using a flexible coil and action limits for key image quality parameters were derived. Using an exploratory survey, issues that reduce MR image quality were identified. The most commonly occurring events were introduced as provocations to produce MR images with degraded quality. From these images, detection sensitivities of the ACR MRI QA protocol and a commercial geometric accuracy phantom were determined.Results: Machine-specific action limits for key image quality parameters set at mean±3σ" role="presentation" style="box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative;">mean±3σ were comparable with the ACR acceptable values. For the geometric accuracy phantom, provocations from uncorrected gradient nonlinearity effects and a piece of metal in the bore of the scanner resulted in worst distortions of 22.2 mm and 3.4 mm, respectively. The ACR phantom was sensitive to uncorrected signal variations, electric interference and a piece of metal in the bore of the scanner but could not adequately detect individual coil element failures.Conclusions: The ACR MRI QA phantom combined with the large field-of-view commercial geometric accuracy phantom were generally sensitive in identifying some common MR image quality issues. The two protocols when combined may provide a tool to monitor the performance of MRI systems in the radiotherapy environment.
8.	Adjeiwaah, Mary, 1980-, et al. (author) Technical Note : Comparison between simulated and measured B0 field maps of head and neck MRI Other publication (other academic/artistic)
9.	Andersson, Jonas, 1975-, et al. (author) Artificial intelligence and the medical physics profession-A Swedish perspective 2021 In: Physica Medica-European Journal of Medical Physics. - : Elsevier BV. - 1120-1797 .- 1724-191X. ; 88, s. 218-225 Journal article (peer-reviewed)abstract Background: There is a continuous and dynamic discussion on artificial intelligence (AI) in present-day society. AI is expected to impact on healthcare processes and could contribute to a more sustainable use of resources allocated to healthcare in the future. The aim for this work was to establish a foundation for a Swedish perspective on the potential effect of AI on the medical physics profession. Materials and methods: We designed a survey to gauge viewpoints regarding AI in the Swedish medical physics community. Based on the survey results and present-day situation in Sweden, a SWOT analysis was performed on the implications of AI for the medical physics profession. Results: Out of 411 survey recipients, 163 responded (40%). The Swedish medical physicists with a professional license believed (90%) that AI would change the practice of medical physics but did not foresee (81%) that AI would pose a risk to their practice and career. The respondents were largely positive to the inclusion of AI in educational programmes. According to self-assessment, the respondents' knowledge of and workplace preparedness for AI was generally low. Conclusions: From the survey and SWOT analysis we conclude that AI will change the medical physics profession and that there are opportunities for the profession associated with the adoption of AI in healthcare. To overcome the weakness of limited AI knowledge, potentially threatening the role of medical physicists, and build upon the strong position in Swedish healthcare, medical physics education and training should include learning objectives on AI.
10.	Asklund, Thomas, et al. (author) Evaluation of advanced MR techniques for development of early biomarkers for treatment efficacy in malignant brain tumors 2010 In: Neuro-Oncology. - : Oxford University Press (OUP). - 1523-5866. Conference paper (peer-reviewed)
11.	Björeland, Ulrika, et al. (author) Diffusion-weighted MRI and 11C-acetate-PET/CT imaging in high-risk/very high-risk prostate cancer Other publication (other academic/artistic)
12.	Björeland, Ulrika, et al. (author) Hyaluronic acid spacer in prostate cancer radiotherapy : dosimetric effects, spacer stability and long-term toxicity and PRO in a phase II study 2023 In: Radiation Oncology. - : BioMed Central (BMC). - 1748-717X. ; 18:1 Journal article (peer-reviewed)abstract BACKGROUND: Perirectal spacers may be beneficial to reduce rectal side effects from radiotherapy (RT). Here, we present the impact of a hyaluronic acid (HA) perirectal spacer on rectal dose as well as spacer stability, long-term gastrointestinal (GI) and genitourinary (GU) toxicity and patient-reported outcome (PRO).METHODS: In this phase II study 81 patients with low- and intermediate-risk prostate cancer received transrectal injections with HA before external beam RT (78 Gy in 39 fractions). The HA spacer was evaluated with MRI four times; before (MR0) and after HA-injection (MR1), at the middle (MR2) and at the end (MR3) of RT. GI and GU toxicity was assessed by physician for up to five years according to the RTOG scale. PROs were collected using the Swedish National Prostate Cancer Registry and Prostate cancer symptom scale questionnaires.RESULTS: There was a significant reduction in rectal V70% (54.6 Gy) and V90% (70.2 Gy) between MR0 and MR1, as well as between MR0 to MR2 and MR3. From MR1 to MR2/MR3, HA thickness decreased with 28%/32% and CTV-rectum space with 19%/17% in the middle level. The cumulative late grade ≥ 2 GI toxicity at 5 years was 5% and the proportion of PRO moderate or severe overall bowel problems at 5 years follow-up was 12%. Cumulative late grade ≥ 2 GU toxicity at 5 years was 12% and moderate or severe overall urinary problems at 5 years were 10%.CONCLUSION: We show that the HA spacer reduced rectal dose and long-term toxicity.
13.	Björeland, Ulrika, et al. (author) Impact of neoadjuvant androgen deprivation therapy on magnetic resonance imaging features in prostate cancer before radiotherapy 2021 In: Physics and Imaging in Radiation Oncology. - : Elsevier. - 2405-6316. ; 17, s. 117-123 Journal article (peer-reviewed)abstract Background and purpose: In locally advanced prostate cancer (PC), androgen deprivation therapy (ADT) in combination with whole prostate radiotherapy (RT) is the standard treatment. ADT affects the prostate as well as the tumour on multiparametric magnetic resonance imaging (MRI) with decreased PC conspicuity and impaired localisation of the prostate lesion. Image texture analysis has been suggested to be of aid in separating tumour from normal tissue. The aim of the study was to investigate the impact of ADT on baseline defined MRI features in prostate cancer with the goal to investigate if it might be of use in radiotherapy planning.Materials and methods: Fifty PC patients were included. Multiparametric MRI was performed before, and three months after ADT. At baseline, a tumour volume was delineated on apparent diffusion coefficient (ADC) maps with suspected tumour content and a reference volume in normal prostatic tissue. These volumes were transferred to MRIs after ADT and were analysed with first-order -and invariant Haralick -features.Results: At baseline, the median value and several of the invariant Haralick features of ADC, showed a significant difference between tumour and reference volumes. After ADT, only ADC median value could significantly differentiate the two volumes.Conclusions: Invariant Haralick -features could not distinguish between baseline MRI defined PC and normal tissue after ADT. First-order median value remained significantly different in tumour and reference volumes after ADT, but the difference was less pronounced than before ADT.
14.	Björeland, Ulrika, et al. (author) Inter-fraction movements of the prostate and pelvic lymph nodes during IGRT 2018 In: Journal of radiation oncology. - : Springer. - 1948-7894 .- 1948-7908. ; 7:4, s. 357-366 Journal article (peer-reviewed)abstract Objectivities: The aim of this study was to evaluate inter-fraction movements of lymph node regions that are commonly included in the pelvic clinical target volume (CTV) for high-risk prostate cancer patients. We also aimed to evaluate if the movements affect the planning target volumes. Methods: Ten prostate cancer patients were included. The patients underwent six MRI scans, from treatment planning to near end of treatment. The CTV movements were analyzed with deformable registration technique with the CTV divided into sections. The validity of the deformable registration was assessed by comparing the results for individual lymph nodes that were possible to identify in all scans. Results: Using repetitive MRI, measurements showed that areas inside the CTV (lymph nodes) in some extreme cases were as mobile as the prostate and not fixed to the bones. The lymph node volumes closest to the prostate did not tend to follow the prostate motion. The more cranial lymph node volumes moved less, but still independently, and they were not necessarily fixed to the pelvic bones. In 95% of the cases, the lymph node motion in the R-L direction was 2-4mm, in the A-P direction 2-7mm, and in the C-C direction 2-5mm depending on the CTV section. Conclusion: Lymph nodes and prostate were most mobile in the A-P direction, followed by the C-C and R-L directions. This movement should be taken into account when deciding the margins for the planning target volumes (PTV).
15.	Björeland, Ulrika, 1974- (author) MRI in prostate cancer : implications for target volume 2023 Doctoral thesis (other academic/artistic)abstract Prostate cancer (PCa) is the most common cancer among men, with 10 000 new cases per year in Sweden [1]. To diagnose PCa, magnetic resonance imaging (MRI) is used to identify and classify the disease. The patient’s treatment strategy depends on PCa classification and clinical data, which are weighted together into a risk group classification from 1–5. For patients with higher risk classes (>3), radiotherapy together with hormone therapy is a common treatment option [2].In radiotherapy (RT), individual treatment plans are created based on the patient’s anatomy. These plans are based on computed tomography (CT), often supplemented with MRI images. MRI and CT complement each other, as MRI has better soft tissue contrast and CT has better bone contrast. Based on the images, the volumes to be treated (target) and the volumes to be avoided (risk organs) are defined. Prostate RT is complex, and there are uncertainties regarding the patient's internal movements and how the patient is positioned before each treatment. To account for these uncertainties, the radiation field is expanded (extended margins to target) to ensure that the treatment volume receives its radiotherapy. RT is most often given in fractions. Fractionation, dose, and treatment volume depend on the patient’s risk category. The treatment area can be, for example, only prostate, prostate with extra radiation dose (boost) to an intraprostatic tumour, or prostate with lymph node (LN) irradiation. LN irradiation is most often given for preventive purposes for PCa with a risk classification >4, which means no cancer has been identified, but any microscopic spread to the LNs is being treated profylactically.In RT, target identification is essential both in the treatment planning images (CT/MRI) and at treatment. Studies have shown that PCa often re-occurs in or near the volume of the dominant (often largest) intraprostatic tumour [3, 4], and this volume is relevant for boosting. For patients treated with hormone therapy before radiotherapy, tumour identification is complicated. Hormones change the tumour characteristics, affecting the image contrast and making the tumour difficult to identify. To study this, we investigated whether texture analysis could identify the tumour volume after hormone therapy (paper II). However, even with texture analysis, the tumour was difficult to identify. A follow-up study examined whether the image information in MRI images taken before hormone therapy could indicate how the treatment fell out (paper IV). However, no correlation was seen between image features and the progression of PCa.Identifying the target and correctly positioning the patient for each treatment fraction is the most important procedure in radiotherapy. The prostate is a mobile organ; therefore, intraprostatic fiducial markers are inserted before treatment planning to reduce positioning uncertainties. Each radiotherapy session begins with an X-ray image where the markers are visible, and the radiation can be delivered based on the markers' position. The markers are also used as guidance for large target volumes, such as for prostate with LN irradiation. With better knowledge of the prostate and LN movements, the margins can potentially be reduced, followed by reduced radiation dose to healthy tissue and therefore reduced side effects for patients. Movements in the radiotherapy volume were the focus of paper I. Using MRI images, the movements of the prostate and LNs were measured during the course of radiotherapy, and we found that LN movement is independent of the movement of the prostate and that the movement varies in the target volume.In addition to the recurrence of PCa in the tumour area, there is an increased risk of recurrence in the prostate periphery close to the rectum. Since the rectum and prostate are in contact for some patients, RT must be adapted to make rectum side effects tolerable. One way to increase the distance between the prostate and the rectum is to inject a gel between the two organs. The distance makes it easier to achieve a better dose distribution to the PCa. This idea resulted in paper III, where patients were given a gel between the prostate and rectum. MRI was used to check the stability of the gel during the course of RT and was evaluated together with long-term follow-up of the patient’s well-being and acceptance of the gel. We found that the radiation dose to the rectum was lower with a spacer, although the spacer was not completely stable during treatment.
16.	Brynolfsson, Patrik, et al. (author) ADC texture-An imaging biomarker for high-grade glioma? 2014 In: Medical physics (Lancaster). - : Wiley. - 0094-2405. ; 41:10, s. 101903- Journal article (peer-reviewed)abstract Purpose:Survival for high-grade gliomas is poor, at least partly explained by intratumoral heterogeneity contributing to treatment resistance. Radiological evaluation of treatment response is in most cases limited to assessment of tumor size months after the initiation of therapy. Diffusion-weighted magnetic resonance imaging (MRI) and its estimate of the apparent diffusion coefficient (ADC) has been widely investigated, as it reflects tumor cellularity and proliferation. The aim of this study was to investigate texture analysis of ADC images in conjunction with multivariate image analysis as a means for identification of pretreatment imaging biomarkers.Methods:Twenty-three consecutive high-grade glioma patients were treated with radiotherapy (2 Gy/60 Gy) with concomitant and adjuvant temozolomide. ADC maps and T1-weighted anatomical images with and without contrast enhancement were collected prior to treatment, and (residual) tumor contrast enhancement was delineated. A gray-level co-occurrence matrix analysis was performed on the ADC maps in a cuboid encapsulating the tumor in coronal, sagittal, and transversal planes, giving a total of 60 textural descriptors for each tumor. In addition, similar examinations and analyses were performed at day 1, week 2, and week 6 into treatment. Principal component analysis (PCA) was applied to reduce dimensionality of the data, and the five largest components (scores) were used in subsequent analyses. MRI assessment three months after completion of radiochemotherapy was used for classifying tumor progression or regression.Results:The score scatter plots revealed that the first, third, and fifth components of the pretreatment examinations exhibited a pattern that strongly correlated to survival. Two groups could be identified: one with a median survival after diagnosis of 1099 days and one with 345 days, p = 0.0001.Conclusions:By combining PCA and texture analysis, ADC texture characteristics were identified, which seems to hold pretreatment prognostic information, independent of known prognostic factors such as age, stage, and surgical procedure. These findings encourage further studies with a larger patient cohort. (C) 2014 Author(s).
17.	Brynolfsson, Patrik, 1981- (author) Applications of statistical methods in quantitative magnetic resonance imaging 2017 Doctoral thesis (other academic/artistic)abstract Magnetic resonance imaging, MRI, offers a vast range of imaging methods that can be employed in the characterization of tumors. MRI is generally used in a qualitative way, where radiologists interpret the images for e.g. diagnosis, follow ups, or assessment of treatment response. In the past decade, there has been an increasing interest for quantitative imaging, which give repeatable measurements of the anatomy. Quantitative imaging allows for objective analysis of the images, which are grounded in physical properties of the underlying tissues. The aim of this thesis was to improve quantitative measurements of Dynamic contrast enhanced MRI (DCE-MRI), and the texture analysis of diffusion weighted MRI (DW-MRI).DCE-MRI measures perfusion, which is the delivery of blood, oxygen and nutrients to the tissues. The exam involves continuously imaging the region of interest, e.g. a tumor, while injecting a contrast agent (CA) in the blood stream. By analyzing how fast and how much CA leaks out into the tissues, the cell density and the permeability of the capillaries can be estimated. Tumors often have an irregular and broken vasculature, and DCE-MRI can aid in tumor grading or treatment assessment. One step is crucial when performing DCE-MRI analysis, the quantification of CA in the tissue. The CA concentration is difficult to measure accurately due to uncertainties in the imaging, properties of the CA, and physiology of the patient. Paper I, the possibility of using two aspects of the MRI data, phase and magnitude, for improved CA quantification, is explored. We found that the combination of phase and magnitude information improved the CA quantification in regions with high CA concentration, and was more advantageous for high field strength scanners.DW-MRI measures the diffusion of water in and between cells, which reflects the cell density and structure of the tissue. The structure of a tumor can give insights into the prognosis of the disease. Tumors are heterogeneous, both genetically and in the distribution of cells, and tumors with high intratumoral heterogeneity have poorer prognosis. This heterogeneity can be measured using texture analysis. In 1973, Haralick et al. presented a texture analysis method using a gray level co-occurrence matrix, GLCM, to gauge the spatial distribution of gray levels in the image. This method of assessing texture in images has been successfully applied in many areas of research, from satellite images to medical applications. Texture analysis in treatment outcome assessment is studied in Paper II, where we showed that texture can distinguish between groups of patients with different survival times, in images acquired prior to treatment start.However, this type of texture analysis is not inherently quantitative in the way it is calculated today. This was studied in Paper III, where we investigated how texture features were affected by five parameters related to image acquisition and pre-processing. We found that the texture feature values were dependent on the choice of these imaging and preprocessing parameters. In Paper IV, a novel method for calculating Haralick texture features was presented, which makes the texture features asymptotically invariant to the size of the GLCM. This method allows for comparison of textures between images that have been analyzed in different ways.In conclusion, the work in this thesis has been aimed at improving quantitative analysis of tumors using MRI and texture analysis.
18.	Brynolfsson, Patrik, et al. (author) Gray-level invariant Haralick texture features 2018 In: Radiotherapy and Oncology. - : Elsevier. - 0167-8140 .- 1879-0887. ; 127, s. S279-S280 Journal article (other academic/artistic)
19.	Brynolfsson, Patrik, et al. (author) Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters 2017 In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 7 Journal article (peer-reviewed)abstract In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.
20.	Brynolfsson, Patrik, et al. (author) Technical note : adapting a GE SIGNA PET/MR scanner for radiotherapy 2018 In: Medical physics (Lancaster). - : Wiley-Blackwell Publishing Inc.. - 0094-2405. ; 45:8, s. 3546-3550 Journal article (peer-reviewed)abstract Purpose: Simultaneous collection of PET and MR data for radiotherapy purposes are useful for, for example, target definition and dose escalations. However, a prerequisite for using PET/MR in the radiotherapy workflow is the ability to image the patient in treatment position. The aim of this work was to adapt a GE SIGNA PET/MR scanner to image patients for radiotherapy treatment planning and evaluate the impact on signal-to-noise (SNR) of the MR images, and the accuracy of the PET attenuation correction. Method: A flat tabletop and a coil holder were developed to image patients in the treatment position, avoid patient contour deformation, and facilitate attenuation correction of flex coils. Attenuation corrections for the developed hardware and an anterior array flex coil were also measured and implemented to the PET/MR system to minimize PET quantitation errors. The reduction of SNR in the MR images due to the added distance between the coils and the patient was evaluated using a large homogenous saline-doped water phantom, and the activity quantitation errors in PET imaging were evaluated with and without the developed attenuation corrections. Result: We showed that the activity quantitation errors in PET imaging were within ±5% when correcting for attenuation of the flat tabletop, coil holder, and flex coil. The SNR of the MRI images were reduced to 74% using the tabletop, and 66% using the tabletop and coil holders. Conclusion: We present a tabletop and coil holder for an anterior array coil to be used with a GE SIGNA PET/MR scanner, for scanning patients in the radiotherapy work flow. Implementing attenuation correction of the added hardware from the radiotherapy setup leads to acceptable PET image quantitation. The drop in SNR in MR images may require adjustment of the imaging protocols.
21.	Bylund, Mikael, et al. (author) Using deep learning to generate synthetic CTs for radiotherapy treatment planning 2018 In: Radiotherapy and Oncology. - : Elsevier. - 0167-8140 .- 1879-0887. ; 127, s. S283-S283 Journal article (other academic/artistic)
22.	Combs, Stephanie E., et al. (author) ESTRO ACROP guideline for target volume delineation of skull base tumors 2021 In: Radiotherapy and Oncology. - : Elsevier. - 0167-8140 .- 1879-0887. ; 156, s. 80-94 Journal article (peer-reviewed)abstract Background and purpose: For skull base tumors, target definition is the key to safe high-dose treatments because surrounding normal tissues are very sensitive to radiation. In the present work we established a joint ESTRO ACROP guideline for the target volume definition of skull base tumors.Material and methods: A comprehensive literature search was conducted in PubMed using various combinations of the following medical subjects headings (MeSH) and free-text words: “radiation therapy” or “stereotactic radiosurgery” or “proton therapy” or “particle beam therapy” and “skull base neoplasms” “pituitary neoplasms”, “meningioma”, “craniopharyngioma”, “chordoma”, “chondrosarcoma”, “acoustic neuroma/vestibular schwannoma”, “organs at risk”, “gross tumor volume”, “clinical tumor volume”, “planning tumor volume”, “target volume”, “target delineation”, “dose constraints”. The ACROP committee identified sixteen European experts in close interaction with the ESTRO clinical committee who analyzed and discussed the body of evidence concerning target delineation.Results: All experts agree that magnetic resonance (MR) images with high three-dimensional spatial accuracy and tissue-contrast definition, both T2-weighted and volumetric T1-weighted sequences, are required to improve target delineation. In detail, several key issues were identified and discussed: i) radiation techniques and immobilization, ii) imaging techniques and target delineation, and iii) technical aspects of radiation treatments including planning techniques and dose-fractionation schedules. Specific target delineation issues with regard to different skull base tumors, including pituitary adenomas, meningiomas, craniopharyngiomas, acoustic neuromas, chordomas and chondrosarcomas are presented.Conclusions: This ESTRO ACROP guideline achieved detailed recommendations on target volume definition for skull base tumors, as well as comprehensive advice about imaging modalities and radiation techniques.
23.	Daniel, M., et al. (author) Impact of androgen deprivation therapy on apparent diffusion coefficient and T2w MRI for histogram and texture analysis with respect to focal radiotherapy of prostate cancer 2019 In: Strahlentherapie und Onkologie (Print). - : Springer Berlin/Heidelberg. - 0179-7158 .- 1439-099X. ; 195:5, s. 402-411 Journal article (peer-reviewed)abstract Purpose: Accurate prostate cancer (PCa) detection is essential for planning focal external beam radiotherapy (EBRT). While biparametric MRI (bpMRI) including T2-weighted (T2w) and diffusion-weighted images (DWI) is an accurate tool to localize PCa, its value is less clear in the case of additional androgen deprivation therapy (ADT). The aim of this study was to investigate the value of a textural feature (TF) approach on bpMRI analysis in prostate cancer patients with and without neoadjuvant ADT with respect to future dose-painting applications.Methods: 28 PCa patients (54–80 years) with (n = 14) and without (n = 14) ADT who underwent bpMRI with T2w and DWI were analyzed retrospectively. Lesions, central gland (CG), and peripheral zone (PZ) were delineated by an experienced urogenital radiologist based on localized pre-therapeutic histopathology. Histogram parameters and 20 Haralick TF were calculated. Regional differences (i. e., tumor vs. PZ, tumor vs. CG) were analyzed for all imaging parameters. Receiver-operating characteristic (ROC) analysis was performed to measure diagnostic performance to distinguish PCa from benign prostate tissue and to identify the features with best discriminative power in both patient groups.Results: The obtained sensitivities were equivalent or superior when utilizing the TF in the no-ADT group, while specificity was higher for the histogram parameters. However, in the ADT group, TF outperformed the conventional histogram parameters in both specificity and sensitivity. Rule-in and rule-out criteria for ADT patients could exclusively be defined with the aid of TF.Conclusions: The TF approach has the potential for quantitative image-assisted boost volume delineation in PCa patients even if they are undergoing neoadjuvant ADT.
24.	Edmund, Jens M., et al. (author) A review of substitute CT generation for MRI-only radiation therapy 2017 In: Radiation Oncology. - : Springer Science and Business Media LLC. - 1748-717X. ; 12 Research review (peer-reviewed)abstract Radiotherapy based on magnetic resonance imaging as the sole modality (MRI-only RT) is an area of growing scientific interest due to the increasing use of MRI for both target and normal tissue delineation and the development of MR based delivery systems. One major issue in MRI-only RT is the assignment of electron densities (ED) to MRI scans for dose calculation and a similar need for attenuation correction can be found for hybrid PET/MR systems. The ED assigned MRI scan is here named a substitute CT (sCT). In this review, we report on a collection of typical performance values for a number of main approaches encountered in the literature for sCT generation as compared to CT. A literature search in the Scopus database resulted in 254 papers which were included in this investigation. A final number of 50 contributions which fulfilled all inclusion criteria were categorized according to applied method, MRI sequence/contrast involved, number of subjects included and anatomical site investigated. The latter included brain, torso, prostate and phantoms. The contributions geometric and/or dosimetric performance metrics were also noted. The majority of studies are carried out on the brain for 5-10 patients with PET/MR applications in mind using a voxel based method. T1 weighted images are most commonly applied. The overall dosimetric agreement is in the order of 0.3-2.5%. A strict gamma criterion of 1% and 1mm has a range of passing rates from 68 to 94% while less strict criteria show pass rates > 98%. The mean absolute error (MAE) is between 80 and 200 HU for the brain and around 40 HU for the prostate. The Dice score for bone is between 0.5 and 0.95. The specificity and sensitivity is reported in the upper 80s% for both quantities and correctly classified voxels average around 84%. The review shows that a variety of promising approaches exist that seem clinical acceptable even with standard clinical MRI sequences. A consistent reference frame for method benchmarking is probably necessary to move the field further towards a widespread clinical implementation.
25.	Engvall, Gunn, 1955-, et al. (author) Children's experiences and responses towards an intervention for psychological preparation for radiotherapy. 2018 In: Radiation Oncology. - : Springer Science and Business Media LLC. - 1748-717X. ; 13 Journal article (peer-reviewed)abstract BACKGROUND: Children can experience distress when undergoing radiotherapy as a reaction to being scared of and unfamiliar with the procedure. The aim was to evaluate children's experiences and responses towards an intervention for psychological preparation for radiotherapy.METHODS: A case control design with qualitative content analysis of semi-structured interviews and statistical analysis of anxiety ratings were used for evaluating a strategy for psychological preparation and distraction. Fifty-seven children aged 2 to 18 years and their parents participated - 30 children in the baseline group and 27 in the intervention group. Child interviews were performed and the child and their parents rated the child's anxiety.RESULTS: The intervention was most appropriate for the younger children, who enjoyed the digital story, the stuffed animal and training with their parents. There were some technical problems and the digital story was not detailed enough to fit exactly with various cancer diagnoses. Children described suggestions for improvement of the intervention. The ratings of the child's anxiety during radiation treatment showed no differences between the baseline group and the intervention group.CONCLUSIONS: The children of all the age groups experienced their interventions as positive. The strength of the intervention was that it encouraged interaction within the family and provided an opportunity for siblings and peers to take part in what the child was going through. Future research on children's experiences to interventions should be encouraged. The intervention and the technical solutions could improve by further development.
26.	Engvall, Gunn, et al. (author) It Is Tough and Tiring but It Works - Children's Experiences of Undergoing Radiotherapy 2016 In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:4 Journal article (peer-reviewed)abstract Approximately 300 children ages 0 to 18 are diagnosed with cancer in Sweden every year, and 80 to 90 of them undergo radiotherapy treatment. The aim was to describe children's experiences of preparing for and undergoing radiotherapy, and furthermore to describe children's suggestions for improvement. Thirteen children between the ages of 5 and 15 with various cancer diagnoses were interviewed. Data was analyzed using qualitative content analysis. The findings revealed five categories: positive and negative experiences with hospital stays and practical arrangements; age-appropriate information, communication, and guidance to various degrees; struggle with emotions; use of distraction and other suitable coping strategies; and children's suggestions for improvement during radiotherapy. An overarching theme emerged: "It is tough and tiring but it works". Some key areas were: explanatory visits, the need for information and communication, being afraid, discomfort and suffering, the need for media distraction, dealing with emotions, and the need for support. A systematic, family-centered preparation program could possible help families prepare and individualized distraction during radiotherapy could contribute to reducing distress. Further studies with interventions could clarify successful programs.
27.	Fahlström, Markus, et al. (author) Dynamic contrast-enhanced magnetic resonance imaging may act as a biomarker for vascular damage in normal appearing brain tissue after radiotherapy in patients with glioblastoma 2018 In: Acta Radiologica Open. - : Sage Publications. - 2058-4601. ; 7:11 Journal article (peer-reviewed)abstract BackgroundDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising perfusion method and may be useful in evaluating radiation-induced changes in normal-appearing brain tissue.PurposeTo assess whether radiotherapy induces changes in vascular permeability (Ktrans) and the fractional volume of the extravascular extracellular space (Ve) derived from DCE-MRI in normal-appearing brain tissue and possible relationships to radiation dose given.Material and MethodsSeventeen patients with glioblastoma treated with radiotherapy and chemotherapy were included; five were excluded because of inconsistencies in the radiotherapy protocol or early drop-out. DCE-MRI, contrast-enhanced three-dimensional (3D) T1-weighted (T1W) images and T2-weighted fluid attenuated inversion recovery (T2-FLAIR) images were acquired before and on average 3.3, 30.6, 101.6, and 185.7 days after radiotherapy. Pre-radiotherapy CE T1W and T2-FLAIR images were segmented into white and gray matter, excluding all non-healthy tissue. Ktrans and Ve were calculated using the extended Kety model with the Parker population-based arterial input function. Six radiation dose regions were created for each tissue type, based on each patient’s computed tomography-based dose plan. Mean Ktrans and Ve were calculated over each dose region and tissue type.ResultsGlobal Ktrans and Ve demonstrated mostly non-significant changes with mean values higher for post-radiotherapy examinations in both gray and white matter compared to pre-radiotherapy. No relationship to radiation dose was found.ConclusionAdditional studies are needed to validate if Ktrans and Ve derived from DCE-MRI may act as potential biomarkers for acute and early-delayed radiation-induced vascular damages. No dose-response relationship was found.
28.	Fahlström, Markus, et al. (author) Perfusion magnetic resonance imaging changes in normal appearing brain tissue after radiotherapy in glioblastoma patients may confound longitudinal evaluation of treatment response 2018 In: Radiology and Oncology. - : Walter de Gruyter. - 1318-2099 .- 1581-3207. ; 52:2, s. 143-151 Journal article (peer-reviewed)abstract Background: The aim of this study was assess acute and early delayed radiation-induced changes in normal-appearing brain tissue perfusion as measured with perfusion magnetic resonance imaging (MRI) and the dependence of these changes on the fractionated radiotherapy (FRT) dose level.Patients and methods: Seventeen patients with glioma WHO grade III-IV treated with FRT were included in this prospective study, seven were excluded because of inconsistent FRT protocol or missing examinations. Dynamic susceptibility contrast MRI and contrast-enhanced 3D-T1-weighted (3D-T1w) images were acquired prior to and in average (standard deviation): 3.1 (3.3), 34.4 (9.5) and 103.3 (12.9) days after FRT. Pre-FRT 3D-T1w images were segmented into white-and grey matter. Cerebral blood volume (CBV) and cerebral blood flow (CBF) maps were calculated and co-registered patient-wise to pre-FRT 3D-T1w images. Seven radiation dose regions were created for each tissue type: 0-5 Gy, 5-10 Gy, 10-20 Gy, 20-30 Gy, 30-40 Gy, 40-50 Gy and 50-60 Gy. Mean CBV and CBF were calculated in each dose region and normalised (nCBV and nCBF) to the mean CBV and CBF in 0-5 Gy white-and grey matter reference regions, respectively.Results: Regional and global nCBV and nCBF in white-and grey matter decreased after FRT, followed by a tendency to recover. The response of nCBV and nCBF was dose-dependent in white matter but not in grey matter.Conclusions: Our data suggest that radiation-induced perfusion changes occur in normal-appearing brain tissue after FRT. This can cause an overestimation of relative tumour perfusion using dynamic susceptibility contrast MRI, and can thus confound tumour treatment evaluation.
29.	Fahlström, Markus (author) Perfusion MRI of the brain after radiotherapy in patients with glioblastoma – potential and problems 2018 Licentiate thesis (other academic/artistic)abstract Perfusion Magnetic Resonance Imaging (MRI) is a useful tool in diagnostic evaluation and treatment response assessment in patients with glioblastoma. The standard treatment regimen includes surgical resection, radiotherapy and adjuvant chemotherapy. However, prognosis is poor; relative 5-year survival is 3–5%. Radiotherapy sequelae may have considerable negative effects on the patients’ quality of life. Acute and early delayed radiation-induced injury is primarily considered damage to the cerebral vascular tissue. The general aim of this study was to evaluate how perfusion MRI evaluation, based on contrast agent administration (DSC- and DCE-MRI), is affected by or can be useful to assess radiation-induced changes in normal appearing brain tissue in patients with glioblastoma after radiotherapy. Paper I: Dynamic Susceptibility Contrast (DSC)-MRI is a common perfusion MRI method in clinical practice in patients with glioblastoma. Due to inherent limitations, cerebral blood volume (CBV) and cerebral blood flow (CBF) derived from DSC-MRI are normalized to contralateral normal appearing white matter. Ten patients with glioblastoma were examined. Regional and global normalized CBV and normalized CBF in white and gray matter decreased after radiotherapy, followed by a tendency to recover. The response of nCBV and nCBF was dose-dependent in white matter but not in gray matter. In conclusion, radiotherapy effects on normal appearing white matter can confound treatment evaluation with DSC-MRI in patients with glioblastoma. Paper II: Dynamic Contrast Enhanced (DCE)-MRI may be useful in evaluating radiation-induced damage in normal appearing brain tissue. DCE-MRI-derived parameters, vascular permeability (Ktrans) and the fractional volume of the extravascular extracellular space (Ve) are potential biomarkers. Twelve patients with glioblastoma were examined. A tendency toward increased Ktrans and Ve was seen, suggesting that these parameters may act as potential biomarkers for acute and early delayed radiation-induced vascular damage
30.	Fetty, L., et al. (author) Evaluating different generator networks of a conditional generative adversarial network 2019 In: Radiotherapy and Oncology. - : Elsevier. - 0167-8140 .- 1879-0887. ; 133, s. S555-S555 Journal article (other academic/artistic)
31.	Fetty, Lukas, et al. (author) Investigating conditional GAN performance with different generator architectures, an ensemble model, and different MR scanners for MR-sCT conversion 2020 In: Physics in Medicine and Biology. - : Institute of Physics Publishing (IOPP). - 0031-9155 .- 1361-6560. ; 65:10 Journal article (peer-reviewed)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.
32.	Fetty, Lukas, et al. (author) Latent space manipulation for high-resolution medical image synthesis via the StyleGAN 2020 In: Zeitschrift für Medizinische Physik. - : Elsevier. - 0939-3889 .- 1876-4436. ; 30:4, s. 305-314 Journal article (peer-reviewed)abstract Introduction: This paper explores the potential of the StyleGAN model as an high-resolution image generator for synthetic medical images. The possibility to generate sample patient images of different modalities can be helpful for training deep learning algorithms as e.g. a data augmentation technique.Methods: The StyleGAN model was trained on Computed Tomography (CT) and T2- weighted Magnetic Resonance (MR) images from 100 patients with pelvic malignancies. The resulting model was investigated with regards to three features: Image Modality, Sex, and Longitudinal Slice Position. Further, the style transfer feature of the StyleGAN was used to move images between the modalities. The root-mean-squard error (RMSE) and the Mean Absolute Error (MAE) were used to quantify errors for MR and CT, respectively.Results: We demonstrate how these features can be transformed by manipulating the latent style vectors, and attempt to quantify how the errors change as we move through the latent style space. The best results were achieved by using the style transfer feature of the StyleGAN (58.7 HU MAE for MR to CT and 0.339 RMSE for CT to MR). Slices below and above an initial central slice can be predicted with an error below 75 HU MAE and 0.3 RMSE within 4 cm for CT and MR, respectively.Discussion: The StyleGAN is a promising model to use for generating synthetic medical images for MR and CT modalities as well as for 3D volumes.
33.	Fetty, L., et al. (author) Solutions for MR-based RT planning with an open low field scanner using neural network tools 2019 In: Radiotherapy and Oncology. - : Elsevier. - 0167-8140 .- 1879-0887. ; 133, s. S567-S568 Journal article (other academic/artistic)
34.	Fransson, Samuel, et al. (author) Intrafractional motion models based on principal components in Magnetic Resonance guided prostate radiotherapy 2021 In: Physics and Imaging in Radiation Oncology. - : Elsevier. - 2405-6316. ; 20, s. 17-22 Journal article (peer-reviewed)abstract Background and purpose: Devices that combine an MR-scanner with a Linac for radiotherapy, referred to as MR-Linac systems, introduce the possibility to acquire high resolution images prior and during treatment. Hence, there is a possibility to acquire individualised learning sets for motion models for each fraction and the construction of intrafractional motion models. We investigated the feasibility for a principal component analysis (PCA) based, intrafractional motion model of the male pelvic region.Materials and methods: 4D-scans of nine healthy male volunteers were utilized, FOV covering the entire pelvic region including prostate, bladder and rectum with manual segmentation of each organ at each time frame. Deformable image registration with an optical flow algorithm was performed for each subject with the first time frame as reference. PCA was performed on a subset of the resulting displacement vector fields to construct individualised motion models evaluated on the remaining fields.Results: The registration algorithm produced accurate registration result, in general DICE overlap >0.95 across all time frames. Cumulative variance of the eigen values from the PCA showed that 50% or more of the motion is explained in the first component for all subjects. However, the size and direction for the components differed between subjects. Adding more than two components did not improve the accuracy significantly and the model was able to explain motion down to about 1 mm.onclusions: An individualised intrafractional male pelvic motion model is feasible. Geometric accuracy was about 1 mm based on 1-2 principal components.
35.	Garpebring, Anders, et al. (author) Density Estimation of Grey-Level Co-Occurrence Matrices for Image Texture Analysis 2018 In: Physics in Medicine and Biology. - : Institute of Physics and Engineering in Medicine. - 0031-9155 .- 1361-6560. ; 63:19, s. 9-15 Journal article (peer-reviewed)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.
36.	Georg, Dietmar, et al. (author) Clinical evaluation of monitor unit software and the application of action levels 2007 In: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140 .- 1879-0887. ; 85:2, s. 306-315 Journal article (peer-reviewed)abstract PURPOSE: The aim of this study was the clinical evaluation of an independent dose and monitor unit verification (MUV) software which is based on sophisticated semi-analytical modelling. The software was developed within the framework of an ESTRO project. Finally, consistent handling of dose calculation deviations applying individual action levels is discussed. MATERIALS AND METHODS: A Matlab-based software ("MUV") was distributed to five well-established treatment centres in Europe (Vienna, Graz, Basel, Copenhagen, and Umeå) and evaluated as a quality assurance (QA) tool in clinical routine. Results were acquired for 226 individual treatment plans including a total of 815 radiation fields. About 150 beam verification measurements were performed for a portion of the individual treatment plans, mainly with time variable fluence patterns. The deviations between dose calculations performed with a treatment planning system (TPS) and the MUV software were scored with respect to treatment area, treatment technique, geometrical depth, radiological depth, etc. RESULTS: In general good agreement was found between calculations performed with the different TPSs and MUV, with a mean deviation per field of 0.2+/-3.5% (1 SD) and mean deviations of 0.2+/-2.2% for composite treatment plans. For pelvic treatments less than 10% of all fields showed deviations larger than 3%. In general, when using the radiological depth for verification calculations the results and the spread in the results improved significantly, especially for head-and-neck and for thorax treatments. For IMRT head-and-neck beams, mean deviations between MUV and the local TPS were -1.0+/-7.3% for dynamic, and -1.3+/-3.2% for step-and-shoot IMRT delivery. For dynamic IMRT beams in the pelvis good agreement was obtained between MUV and the local TPS (mean: -1.6+/-1.5%). Treatment site and treatment technique dependent action levels between +/-3% and +/-5% seem to be clinically realistic if a radiological depth correction is performed, even for dynamic wedges and IMRT. CONCLUSION: The software MUV is well suited for patient specific treatment plan QA applications and can handle all currently available treatment techniques that can be applied with standard linear accelerators. The highly sophisticated dose calculation model implemented in MUV allows investigation of systematic TPS deviations by performing calculations in homogeneous conditions
37.	Georg, Dietmar, et al. (author) Patient-specific IMRT verification using independent fluence-based dose calculation software : experimental benchmarking and initial clinical experience 2007 In: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 52:16, s. 4981-4992 Journal article (peer-reviewed)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.
38.	Grönlund, Eric, et al. (author) Dose painting of prostate cancer based on Gleason score correlations with apparent diffusion coefficients 2018 In: Acta Oncologica. - : Taylor & Francis. - 0284-186X .- 1651-226X. ; 57:5, s. 574-581 Journal article (peer-reviewed)abstract Background: Gleason scores for prostate cancer correlates with an increased recurrence risk after radiotherapy (RT). Furthermore, higher Gleason scores correlates with decreasing apparent diffusion coefficient (ADC) data from diffusion weighted MRI (DWI-MRI). Based on these observations, we present a formalism for dose painting prescriptions of prostate volumes based on ADC images mapped to Gleason score driven dose-responses.Methods: The Gleason score driven dose-responses were derived from a learning data set consisting of pre-RT biopsy data and post-RT outcomes for 122 patients treated with a homogeneous dose to the prostate. For a test data set of 18 prostate cancer patients with pre-RT ADC images, we mapped the ADC data to the Gleason driven dose-responses by using probability distributions constructed from published Gleason score correlations with ADC data. We used the Gleason driven dose-responses to optimize dose painting prescriptions that maximize the tumor control probability (TCP) with equal average dose as for the learning sets homogeneous treatment dose.Results: The dose painting prescriptions increased the estimated TCP compared to the homogeneous dose by 0–51% for the learning set and by 4–30% for the test set. The potential for individual TCP gains with dose painting correlated with increasing Gleason score spread and larger prostate volumes. The TCP gains were also found to be larger for patients with a low expected TCP for the homogeneous dose prescription.Conclusions: We have from retrospective treatment data demonstrated a formalism that yield ADC driven dose painting prescriptions for prostate volumes that potentially can yield significant TCP increases without increasing dose burdens as compared to a homogeneous treatment dose. This motivates further development of the approach to consider more accurate ADC to Gleason mappings, issues with delivery robustness of heterogeneous dose distributions, and patient selection criteria for design of clinical trials.
39.	Grönlund, Eric, 1987-, et al. (author) Robust treatment planning of dose painting for prostate cancer based on ADC-to-Gleason score mappings : what is the potential to increase the tumor control probability? 2021 In: Acta Oncologica. - : Taylor & Francis. - 0284-186X .- 1651-226X. ; 60:2, s. 199-206 Journal article (peer-reviewed)abstract Background and Purpose The aim of this study was to evaluate the potential to increase the tumor control probability (TCP) with ‘dose painting by numbers’ (DPBN) plans optimized in a treatment planning system (TPS) compared to uniform dose plans. The DPBN optimization was based on our earlier published formalism for prostate cancer that is driven by dose-responses of Gleason scores mapped from apparent diffusion coefficients (ADC).Material and MethodsFor 17 included patients, a set of DPBN plans were optimized in a TPS by maximizing the TCP for an equal average dose to the prostate volume (CTVT) as for a conventional uniform dose treatment. For the plan optimizations we applied different photon energies, different precisions for the ADC-to-Gleason mappings, and different CTVT positioning uncertainties. The TCP increasing potential was evaluated by the DPBN efficiency, defined as the ratio of TCP increases for DPBN plans by TCP increases for ideal DPBN prescriptions (optimized without considering radiation transport phenomena, uncertainties of the CTVT positioning, and uncertainties of the ADC-to-Gleason mapping).ResultsThe median DPBN efficiency for the most conservative planning scenario optimized with a low precision ADC-to-Gleason mapping, and a positioning uncertainty of 0.6 cm was 10%, meaning that more than half of the patients had a TCP gain of at least 10% of the TCP for an ideal DPBN prescription. By increasing the precision of the ADC-to-Gleason mapping, and decreasing the positioning uncertainty the median DPBN efficiency increased by up to 40%.ConclusionsTCP increases with DPBN plans optimized in a TPS were found more likely with a high precision mapping of image data into dose-responses and a high certainty of the tumor positioning. These findings motivate further development to ensure precise mappings of image data into dose-responses and to ensure a high spatial certainty of the tumor positioning when implementing DPBN clinically.
40.	Gustafsson, Christian, et al. (author) Registration free automatic identification of gold fiducial markers in MRI target delineation images for prostate radiotherapy 2017 In: Medical physics (Lancaster). - : Wiley. - 0094-2405. ; 44:11, s. 5563-5574 Journal article (peer-reviewed)abstract Purpose: The superior soft tissue contrast of magnetic resonance imaging (MRI) compared to computed tomography (CT) has urged the integration of MRI and elimination of CT in radiotherapy treatment (RT) for prostate. An intraprostatic gold fiducial marker (GFM) appears hyperintense on CT. On T2-weighted (T2w) MRI target delineation images, the GFM appear as a small signal void similar to calcifications and post biopsy fibrosis. It can therefore be difficult to identify the markers without CT. Detectability of GFMs can be improved using additional MR images, which are manually registered to target delineation images. This task requires manual labor, and is associated with interoperator differences and image registration errors. The aim of this work was to develop and evaluate an automatic method for identification of GFMs directly in the target delineation images without the need for image registration.Methods: T2w images, intended for target delineation, and multiecho gradient echo (MEGRE) images intended for GFM identification, were acquired for prostate cancer patients. Signal voids in the target delineation images were identified as GFM candidates. The GFM appeared as round, symmetric, signal void with increasing area for increasing echo time in the MEGRE images. These image features were exploited for automatic identification of GFMs in a MATLAB model using a patient training dataset (n = 20). The model was validated on an independent patient dataset (n = 40). The distances between the identified GFM in the target delineation images and the GFM in CT images were measured. A human observatory study was conducted to validate the use of MEGRE images.Results: The sensitivity, specificity, and accuracy of the automatic method and the observatory study was 84%, 74%, 81% and 98%, 94%, 97%, respectively. The mean absolute difference in the GFM distances for the automatic method and observatory study was 1.28 1.25 mm and 1.14 +/- 1.06 mm, respectively.Conclusions: Multiecho gradient echo images were shown to be a feasible and reliable way to perform GFM identification. For clinical practice, visual inspection of the results from the automatic method is needed at the current stage.
41.	Hildeman, Anders, et al. (author) Hildeman, A., Bolin, D., Wallin, J., Johansson, A., Nyholm, T., Asklund, T., and Yu, J. Whole-brain substitute CT generation using Markov random field mixture models. 2016 Other publication (other academic/artistic)abstract Computed tomography (CT) equivalent information is needed for attenuation correction in PET imaging and for dose planning in radiotherapy. Prior work has shown that Gaussian mixture models can be used to generate a substitute CT (s-CT) image from a specific set of MRI modalities. This work introduces a more flexible class of mixture models for s-CT generation, that incorporates spatial dependency in the data through a Markov random field prior on the latent field of class memberships associated with a mixture model. Furthermore, the mixture distributions are extended from Gaussian to normal inverse Gaussian (NIG), allowing heavier tails and skewness. The amount of data needed to train a model for s-CT generation is of the order of 10^8 voxels. The computational efficiency of the parameter estimationand prediction methods are hence paramount, especially when spatial dependency is included in the models. A stochastic Expectation Maximization (EM) gradient algorithm is proposed in order to tackle this challenge. The advantages of the spatial model and NIG distributions are evaluated with a cross-validation study based ondata from 14 patients. The study show that the proposed model enhances the predictive quality of the s-CT images by reducing the mean absolute error with 17.9%. Also, the distribution of CT values conditioned on the MR images are better explainedby the proposed model as evaluated using continuous ranked probability scores.
42.	Hildeman, Anders, et al. (author) Whole-brain subsitute CT generation using Markov random field mixture models 2018 Other publication (other academic/artistic)
43.	Jamtheim Gustafsson, Christian, et al. (author) Deep learning-based classification and structure name standardization for organ at risk and target delineations in prostate cancer radiotherapy 2021 In: Journal of Applied Clinical Medical Physics. - : John Wiley & Sons. - 1526-9914. ; 22:12, s. 51-63 Journal article (peer-reviewed)abstract Radiotherapy (RT) datasets can suffer from variations in annotation of organ at risk (OAR) and target structures. Annotation standards exist, but their description for prostate targets is limited. This restricts the use of such data for supervised machine learning purposes as it requires properly annotated data. The aim of this work was to develop a modality independent deep learning (DL) model for automatic classification and annotation of prostate RT DICOM structures.Delineated prostate organs at risk (OAR), support- and target structures (gross tumor volume [GTV]/clinical target volume [CTV]/planning target volume [PTV]), along with or without separate vesicles and/or lymph nodes, were extracted as binary masks from 1854 patients. An image modality independent 2D InceptionResNetV2 classification network was trained with varying amounts of training data using four image input channels. Channel 1–3 consisted of orthogonal 2D projections from each individual binary structure. The fourth channel contained a summation of the other available binary structure masks. Structure classification performance was assessed in independent CT (n = 200 pat) and magnetic resonance imaging (MRI) (n = 40 pat) test datasets and an external CT (n = 99 pat) dataset from another clinic.A weighted classification accuracy of 99.4% was achieved during training. The unweighted classification accuracy and the weighted average F1 score among different structures in the CT test dataset were 98.8% and 98.4% and 98.6% and 98.5% for the MRI test dataset, respectively. The external CT dataset yielded the corresponding results 98.4% and 98.7% when analyzed for trained structures only, and results from the full dataset yielded 79.6% and 75.2%. Most misclassifications in the external CT dataset occurred due to multiple CTVs and PTVs being fused together, which was not included in the training data.Our proposed DL-based method for automated renaming and standardization of prostate radiotherapy annotations shows great potential. Clinic specific contouring standards however need to be represented in the training data for successful use. Source code is available at https://github.com/jamtheim/DicomRTStructRenamerPublic
44.	Johansson, Adam, et al. (author) CT substitute derived from MRI sequences with ultrashort echo time 2011 In: Medical physics (Lancaster). - : American Association of Physicists in Medicine. - 0094-2405. ; 38:5, s. 2708-2714 Journal article (peer-reviewed)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.
45.	Johansson, Adam, 1984-, et al. (author) CT substitutes derived from MR images reconstructed with parallel imaging 2014 In: Medical physics (Lancaster). - : Wiley. - 0094-2405. ; 41:8, s. 474-480 Journal article (peer-reviewed)abstract Purpose: Computed tomography (CT) substitute images can be generated from ultrashort echo time (UTE) MRI sequences with radial k-space sampling. These CT substitutes can be used as ordinary CT images for PET attenuation correction and radiotherapy dose calculations. Parallel imaging allows faster acquisition of magnetic resonance (MR) images by exploiting differences in receiver coil element sensitivities. This study investigates whether non-Cartesian parallel imaging reconstruction can be used to improve CT substitutes generated from shorter examination times.Methods: The authors used gridding as well as two non-Cartesian parallel imaging reconstruction methods, SPIRiT and CG-SENSE, to reconstruct radial UTE and gradient echo (GE) data into images of the head for 23 patients. For each patient, images were reconstructed from the full dataset and from a number of subsampled datasets. The subsampled datasets simulated shorter acquisition times by containing fewer radial k-space spokes (1000, 2000, 3000, 5000, and 10 000 spokes) than the full dataset (30 000 spokes). For each combination of patient, reconstruction method, and number of spokes, the reconstructed UTE and GE images were used to generate a CT substitute. Each CT substitute image was compared to a real CT image of the same patient.Results: The mean absolute deviation between the CT number in CT substitute and CT decreased when using SPIRiT as compared to gridding reconstruction. However, the reduction was small and the CT substitute algorithm was insensitive to moderate subsampling (≥5000 spokes) regardless of reconstruction method. For more severe subsampling (≤3000 spokes), corresponding to acquisition times less than aminute long, the CT substitute quality was deteriorated for all reconstructionmethods but SPIRiT gave a reduction in the mean absolute deviation of down to 25 Hounsfield units compared to gridding.Conclusions: SPIRiT marginally improved the CT substitute quality for a given number of radial spokes as compared to gridding. However, the increased reconstruction time of non-Cartesian parallel imaging reconstruction is difficult to motivate from this improvement. Because the CT substitute algorithm was insensitive to moderate subsampling, data for a CT substitute could be collected in as little as minute and reconstructed with gridding without deteriorating the CT substitute quality.
46.	Johansson, Adam, et al. (author) 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 In: Acta Oncologica. - 0284-186X .- 1651-226X. ; 52:7, s. 1369-1373 Journal article (peer-reviewed)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.
47.	Johansson, Adam, 1984- (author) Magnetic resonance imaging with ultrashort echo time as a substitute for X-ray computed tomography 2014 Doctoral thesis (other academic/artistic)abstract Radiotherapy dose calculations have evolved from simple factor based methods performed with pen and paper, into computationally intensive simulations based on Monte Carlo theory and energy deposition kernel convolution.Similarly, in the field of positron emission tomography (PET), attenuation correction, which was originally omitted entirely, is now a crucial component of any PET reconstruction algorithm.Today, both of these applications – radiotherapy and PET – derive their needed in-tissue radiation attenuation coefficients from images acquired with X-ray computed tomography (CT). Since X-ray images are themselves acquired using ionizing radiation, the intensity at a point in an image will reflect the radiation interaction properties of the tissue located at that point.Magnetic resonance imaging (MRI), on the other hand, does not use ionizing radiation. Instead MRI make use of the net transverse magnetization resulting from the spin polarization of hydrogen nuclei. MR image contrast can be varied to a greater extent than CT and the soft tissue contrast is, for most MR sequences, superior to that of CT. Therefore, for many cases, MR images provide a considerable advantage over CT when identifying or delineating tumors or other diseased tissues.For this reason, there is an interest to replace CT with MRI for a great number of diagnostic and therapeutic workflows. Also, replacing CT with MRI would reduce the exposure to ionizing radiation experienced by patients and, by extension, reduce the associated risk to induce cancer.In part MRI has already replaced CT, but for radiotherapy dose calculations and PET attenuation correction, CT examinations are still necessary in clinical practice. One of the reasons is that the net transverse magnetization imaged in MRI cannot be converted into attenuation coefficients for ionizing radiation in a straightforward way. More specifically, regions with similar appearance in magnetic resonance (MR) images, such as bone and air pockets, are found at different ends of the spectrum of attenuation coefficients present in the human body. In a CT image, bone will appear bright white and air as black corresponding to high and no attenuation, respectively. In an MR image, bone and air both appear dark due to the lack of net transverse magnetization.The weak net transverse magnetization of bone is a result of low hydrogen density and rapid transverse relaxation. A particular category of MRI sequences with so-called ultrashort echo time (UTE) can sample the MRI signal from bone before it is lost due to transverse relaxation. Thus, UTE sequences permit bone to be imaged with MRI albeit with weak intensity and poor resolution.Imaging with UTE in combination with careful image analysis can permit ionizing-radiation attenuation-maps to be derived from MR images. This dissertation and appended articles present a procedure for this very purpose. However, as attenuation coefficients are radiation-quality dependent the output of the method is a Hounsfield unit map, i.e. a substitute for a CT image. It can be converted into an attenuation map using conventional clinical procedure.Obviating the use of CT would reduce the number of examinations that patients have to endure during preparation for radiotherapy. It would also permit PET attenuation correction to be performed on images from the new imaging modality that combines PET and MRI in one scanner – PET/MR.
48.	Johansson, Adam, et al. (author) Voxel-wise uncertainty in CT substitute derived from MRI 2012 In: Medical physics (Lancaster). - : American Association of Physicists in Medicine. - 0094-2405. ; 39:6, s. 3283-3290 Journal article (peer-reviewed)abstract Purpose: In an earlier work, we demonstrated that substitutes for CT images can be derived from MR images using ultrashort echo time (UTE) sequences, conventional T2 weighted sequences, and Gaussian mixture regression (GMR). In this study, we extend this work by analyzing the uncertainties associated with the GMR model and the information contributions from the individual imaging sequences.Methods: An analytical expression for the voxel-wise conditional expected absolute deviation (EAD) in substitute CT (s-CT) images was derived. The expression depends only on MR images and can thus be calculated along with each s-CT image. The uncertainty measure was evaluated by comparing the EAD to the true mean absolute prediction deviation (MAPD) between the s-CT and CT images for 14 patients. Further, the influence of the different MR images included in the GMR model on the generated s-CTs was investigated by removing one or more images and evaluating the MAPD for a spectrum of predicted radiological densities.Results: The largest EAD was predicted at air-soft tissue and bone-soft tissue interfaces. The EAD agreed with the MAPD in both these regions and in regions with lower EADs, such as the brain. Two of the MR images included in the GMR model were found to be mutually redundant for the purpose of s-CT generation.Conclusions: The presented uncertainty estimation method accurately predicts the voxel-wise MAPD in s-CT images. Also, the non-UTE sequence previously used in the model was found to be redundant.
49.	Jonsson, Joakim H., et al. (author) Accuracy of inverse treatment planning on substitute CT images derived from MR data for brain lesions 2015 In: Radiation Oncology. - : Springer Science and Business Media LLC. - 1748-717X. ; 10 Journal article (peer-reviewed)abstract Background: In this pilot study we evaluated the performance of a substitute CT (s-CT) image derived from MR data of the brain, as a basis for optimization of intensity modulated rotational therapy, final dose calculation and derivation of reference images for patient positioning. Methods: S-CT images were created using a Gaussian mixture regression model on five patients previously treated with radiotherapy. Optimizations were compared using D-max, D-min, D-median and D-mean measures for the target volume and relevant risk structures. Final dose calculations were compared using gamma index with 1%/1 mm and 3%/3 mm acceptance criteria. 3D geometric evaluation was conducted using the DICE similarity coefficient for bony structures. 2D geometric comparison of digitally reconstructed radiographs (DRRs) was performed by manual delineation of relevant structures on the s-CT DRR that were transferred to the CT DRR and compared by visual inspection. Results: Differences for the target volumes in optimization comparisons were small in general, e.g. a mean difference in both D-min and D-max within similar to 0.3%. For the final dose calculation gamma evaluations, 100% of the voxels passed the 1%/1 mm criterion within the PTV. Within the entire external volume between 99.4% and 100% of the voxels passed the 3%/3 mm criterion. In the 3D geometric comparison, the DICE index varied between approximately 0.8-0.9, depending on the position in the skull. In the 2D DRR comparisons, no appreciable visual differences were found. Conclusions: Even though the present work involves a limited number of patients, the results provide a strong indication that optimization and dose calculation based on s-CT data is accurate regarding both geometry and dosimetry.
50.	Jonsson, Joakim H, et al. (author) Internal fiducial markers and susceptibility effects in MRI : simulation and measurement of spatial accuracy 2012 In: International Journal of Radiation Oncology, Biology, Physics. - : Elsevier BV. - 0360-3016 .- 1879-355X. ; 82:5, s. 1612-1618 Journal article (peer-reviewed)abstract BACKGROUND: It is well-known that magnetic resonance imaging (MRI) is preferable to computed tomography (CT) in radiotherapy target delineation. To benefit from this, there are two options available: transferring the MRI delineated target volume to the planning CT or performing the treatment planning directly on the MRI study. A precondition for excluding the CT study is the possibility to define internal structures visible on both the planning MRI and on the images used to position the patient at treatment. In prostate cancer radiotherapy, internal gold markers are commonly used, and they are visible on CT, MRI, x-ray, and portal images. The depiction of the markers in MRI are, however, dependent on their shape and orientation relative the main magnetic field because of susceptibility effects. In the present work, these effects are investigated and quantified using both simulations and phantom measurements.METHODS AND MATERIALS: Software that simulated the magnetic field distortions around user defined geometries of variable susceptibilities was constructed. These magnetic field perturbation maps were then reconstructed to images that were evaluated. The simulation software was validated through phantom measurements of four commercially available gold markers of different shapes and one in-house gold marker.RESULTS: Both simulations and phantom measurements revealed small position deviations of the imaged marker positions relative the actual marker positions (<1 mm).CONCLUSION: Cylindrical gold markers can be used as internal fiducial markers in MRI.

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