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  • 1.
    Adjeiwaah, Mary
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Quality assurance for magnetic resonance imaging (MRI) in radiotherapy2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    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.

  • 2.
    Ahlgren, Ulf
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Molecular Medicine (UCMM).
    Kostromina, Elena
    Umeå University, Faculty of Medicine, Umeå Centre for Molecular Medicine (UCMM).
    Imaging the pancreatic beta cell: chapter 132011In: Type 1 diabetes: pathogenesis, genetics and immunotherapy / [ed] David Wagner, InTech, 2011Chapter in book (Refereed)
    Abstract [en]

    This book is a compilation of reviews about the pathogenesis of Type 1 Diabetes. T1D is a classic autoimmune disease. Genetic factors are clearly determinant but cannot explain the rapid, even overwhelming expanse of this disease. Understanding etiology and pathogenesis of this disease is essential. A number of experts in the field have covered a range of topics for consideration that are applicable to researcher and clinician alike. This book provides apt descriptions of cutting edge technologies and applications in the ever going search for treatments and cure for diabetes. Areas including T cell development, innate immune responses, imaging of pancreata, potential viral initiators, etc. are considered.

  • 3.
    Axelsson, Jan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Imlook4d: introducing an extendable research 4d analysis software2014In: XII Turku PET Symposium, 24-27 May 2014, Turku, Finland: the symposium of Nordic Association for Clinical Physics (NACP), 2014, p. 63-63Conference paper (Other academic)
    Abstract [en]

    Imlook4d (http://www.dicom-port.com) is a free Matlab based graphical user interface (GUI) tool useful for static, dynamic and gated PET studies.  It supports reading and writing DICOM, Nifti, Analyze, ECAT.  The DICOM reader is orders of magnitude faster than the Matlab imaging toolbox.  Imlook4d requires no additional Matlab toolboxes.

    The main benefit with imlook4d is that it is easily extendable with scripts, accessing exported variables such as the image matrix (4D) and a region-of-interest (ROI) matrix.  Scripts are available via a menu in the imlook4d GUI, and can be used to manipulate the image-matrix and ROI data.  There is also a menu option to export and import these variables to the Matlab workspace for interactive manipulation, useful for one-off fixes or for script development.  There are presently about 30 scripts in categories such as ROI, Matrix, Header info etc.  There is also direct export to ImageJ [1] and import back from ImageJ, thus giving access to all tools available within ImageJ.

    Imlook4d has a built in volume-of-interest editor, with a brush tool for quick interactive ROI delineation, and via scripts, different ways of thresholding ROIs from parts of the image.  Time activity data is saved to a tab-delimited text file.

    The principal-component (PC) based Hotelling filter is an integrated part of the program, which allows for interactive noise reduction without loss of quantitation [2].  A typical work flow for a dynamic data set is to turn on the filter for ROI delineation, and then there is the choice of turning it off for export of time-activity data.  Also the PC images can be used to draw ROIs on, which under some circumstances gives enhanced contrast.

    Calculation of parametric pharmacokinetic modelling images can be performed interactively, calculated slice by slice as the user scrolls through the volume.  Reference models for Patlak, Logan and Averaged Simple Flow Model [3]  applied on 15O-water are implemented, and it is relatively easy to implement other kinetic models.  Similarly, scripts have been developed for regional Patlak and Logan models on ROI data.

    [1] Rasband, WS, ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, http://imagej.nih.gov/ij/, 1997-2014

    [2] Axelsson J, Sörensen J, The 2D Hotelling filter - a quantitative noise-reducing principal-component filter for dynamic PET data, with applications in patient dose reduction. BMC Med Phys. 2013 Apr 10;13:1. doi: 10.1186/1756-6649-13-1.

    [3] Yoshida, K, Mullani, N and Gould KL, Coronary Flow and Flow Reserve by PET Simplified for Clinical Applications Using Rubidium-82 or Nitrogen-13-Ammonia, J Nucl Med 1996; 37:1701-1712

    Figure 1.  The imlook4d GUI with the user SCRIPTS menu selected.  The group of ROI scripts was further selected.  In the underlying image, a rough ROI is created.  

  • 4.
    Axelsson, Jan
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Sörensen, Jens
    PET-center, Department of Radiology, Oncology and Radiation Sciences, Uppsala University, Uppsala, Sweden.
    The 2D Hotelling filter: a quantitativenoise-reducing principal-component filter fordynamic PET data, with applications in patientdose reduction2013In: BMC Medical Physics, ISSN 1756-6649, Vol. 13, no 1Article in journal (Refereed)
    Abstract [en]

    Background: In this paper we apply the principal-component analysis filter (Hotelling filter) to reduce noise fromdynamic positron-emission tomography (PET) patient data, for a number of different radio-tracer molecules. Wefurthermore show how preprocessing images with this filter improves parametric images created from suchdynamic sequence.We use zero-mean unit variance normalization, prior to performing a Hotelling filter on the slices of a dynamictime-series. The Scree-plot technique was used to determine which principal components to be rejected in thefilter process. This filter was applied to [11C]-acetate on heart and head-neck tumors, [18F]-FDG on liver tumors andbrain, and [11C]-Raclopride on brain. Simulations of blood and tissue regions with noise properties matched to realPET data, was used to analyze how quantitation and resolution is affected by the Hotelling filter. Summing varyingparts of a 90-frame [18F]-FDG brain scan, we created 9-frame dynamic scans with image statistics comparable to 20MBq, 60 MBq and 200 MBq injected activity. Hotelling filter performed on slices (2D) and on volumes (3D) werecompared.Results: The 2D Hotelling filter reduces noise in the tissue uptake drastically, so that it becomes simple to manuallypick out regions-of-interest from noisy data. 2D Hotelling filter introduces less bias than 3D Hotelling filter in focalRaclopride uptake. Simulations show that the Hotelling filter is sensitive to typical blood peak in PET prior to tissueuptake have commenced, introducing a negative bias in early tissue uptake. Quantitation on real dynamic data isreliable. Two examples clearly show that pre-filtering the dynamic sequence with the Hotelling filter prior toPatlak-slope calculations gives clearly improved parametric image quality. We also show that a dramatic dosereduction can be achieved for Patlak slope images without changing image quality or quantitation.Conclusions: The 2D Hotelling-filtering of dynamic PET data is a computer-efficient method that gives visuallyimproved differentiation of different tissues, which we have observed improve manual or automated regionof-interest delineation of dynamic data. Parametric Patlak images on Hotelling-filtered data display improved clarity,compared to non-filtered Patlak slope images without measurable loss of quantitation, and allow a dramaticdecrease in patient injected dose.

  • 5.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Kuljus, Kristi
    Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Bolin, David
    Department of Mathematical Sciences, Chalmers and University of Gothenburg, Gothenburg, Sweden.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Prediction of CT images from MR images with hidden Markov and random field models2016In: Proceedings of the 8th International Workshop on Spatio-Temporal Modelling / [ed] A. Iftimi, J. Mateu and F. Montes, 2016, p. 163-163Conference paper (Other academic)
  • 6.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Liu, Xijia
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Statistical learning in computed tomography image estimation2018In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 45, no 12, p. 5450-5460Article in journal (Refereed)
    Abstract [en]

    Purpose: There is increasing interest in computed tomography (CT) image estimations from magneticresonance (MR) images. The estimated CT images can be utilized for attenuation correction, patientpositioning, and dose planning in diagnostic and radiotherapy workflows. This study aims to introducea novel statistical learning approach for improving CT estimation from MR images and to compare theperformance of our method with the existing model-based CT image estimation methods.

    Methods: The statistical learning approach proposed here consists of two stages. At the trainingstage, prior knowledge about tissue types from CT images was used together with a Gaussian mixturemodel (GMM) to explore CT image estimations from MR images. Since the prior knowledge is notavailable at the prediction stage, a classifier based on RUSBoost algorithm was trained to estimatethe tissue types from MR images. For a new patient, the trained classifier and GMMs were used topredict CT image from MR images. The classifier and GMMs were validated by using voxel-leveltenfold cross-validation and patient-level leave-one-out cross-validation, respectively.

    Results: The proposed approach has outperformance in CT estimation quality in comparison withthe existing model-based methods, especially on bone tissues. Our method improved CT image estimationby 5% and 23% on the whole brain and bone tissues, respectively.

    Conclusions: Evaluation of our method shows that it is a promising method to generate CTimage substitutes for the implementation of fully MR-based radiotherapy and PET/MRI applications

  • 7.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Model-based Estimation of Computed Tomography Images2017Conference paper (Other academic)
  • 8.
    Bayisa, Fekadu
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Model-based Estimation of Computed Tomography Images2017Manuscript (preprint) (Other academic)
    Abstract [en]

    There is a growing interest to get a fully MR based radiotherapy. The most important development needed is to obtain improved bone tissue estimation. Existing model-based methods have performed poorly on bone tissues. This paper aims to obtainimproved estimation of bone tissues. Skew-Gaussian mixture model (SGMM) isproposed to further investigate CT image estimation from MR images. The estimation quality of the proposed model is evaluated using leave-one-out cross-validation method on real data. In comparison with the existing model-based approaches, the approach utilized in this paper outperforms in estimation of bone tissues, especiallyon dense bone tissues.

  • 9.
    Björnfot, Cecilia
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Multiband functional magnetic resonance imaging (fMRI) for functional connectivity assessments2018Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    During resting state the brain exhibits synchronized activity within all major brain networks. Using blood oxygen level dependent (BOLD) resting state functional magnetic resonance imaging (fMRI) based detection it is possible to quantify the degree of correlation, connectivity, between regions of interest and assess information regarding the integrity of the inter-regional functional integration. A newly available multiband echo planar imaging (EPI) fMRI sequence allows for faster scan times which possibly allows us to better examine large-scale networks and increase the understanding of brain function/dysfunction. This thesis will assess how the newly developed sequence compares to a conventional EPI sequence for detecting resting state connectivity of canonical brain networks. The data acquisitions were made on a 3 Tesla scanner using a 32 channel head coil. The hypothesis was that the multiband sequence would produce a better result since it has faster sampling rate, thus more data points in its time-series to support the statistical analyses.

    Using Pearson’s linear correlation between the average time-series (approximately 12 minutes long) within a seed-region and all voxels contained in the image volume, correlation maps where created for each of the eight participants using data normalized to Montreal Neurological Institute (MNI) space. The resting state networks (RSN) were then found by performing a one sample T-test on group level. Six seed-coordinates, based on literature, where used revealing the the homotopic connections in anterior Hippocampus, Motor cortex, Dorsal attention, Visual and the Default mode network (DMN) as well for an anterior-posterior connection in the DMN.

    By comparing the maximum T-values within the regions for the RSN no systematic difference could be found between the multiband and conventional fMRI data. Further tests were conducted to evaluate if the sequences would differentiate in their results if the acquisition time was shortened, i.e shortening the time-series in the voxels. However no such difference could be established.Importantly, the results are specific to the 32 channel head coil used in the current study. Presumably recently available and improved coil designs could better exploit the multiband technique.

  • 10. Brolin, Gustav
    et al.
    Edenbrandt, Lars
    Granerus, Goeran
    Olsson, Anna
    Afzelius, David
    Gustafsson, Agneta
    Jonsson, Cathrine
    Hagerman, Jessica
    Johansson, Lena
    Riklund, Katrine
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. EQUALIS AB, Uppsala, Sweden.
    Ljungberg, Michael
    The accuracy of quantitative parameters in Tc-99m-MAG3 dynamic renography: a national audit based on virtual image data2016In: Clinical Physiology and Functional Imaging, ISSN 1475-0961, E-ISSN 1475-097X, Vol. 36, no 2, p. 146-154Article in journal (Refereed)
    Abstract [en]

    Assessment of image analysis methods and computer software used in Tc-99m-MAG3 dynamic renography is important to ensure reliable study results and ultimately the best possible care for patients. In this work, we present a national multicentre study of the quantification accuracy in Tc-99m-MAG3 renography, utilizing virtual dynamic scintigraphic data obtained by Monte Carlo-simulated scintillation camera imaging of digital phantoms with time-varying activity distributions. Three digital phantom studies were distributed to the participating departments, and quantitative evaluation was performed with standard clinical software according to local routines. The differential renal function (DRF) and time to maximum renal activity (T-max) were reported by 21 of the 28 Swedish departments performing Tc-99m-MAG3 studies as of 2012. The reported DRF estimates showed a significantly lower precision for the phantom with impaired renal uptake than for the phantom with normal uptake. The T-max estimates showed a similar trend, but the difference was only significant for the right kidney. There was a significant bias in the measured DRF for all phantoms caused by different positions of the left and right kidney in the anterior-posterior direction. In conclusion, this study shows that virtual scintigraphic studies are applicable for quality assurance and that there is a considerable uncertainty associated with standard quantitative parameters in dynamic Tc-99m-MAG3 renography, especially for patients with impaired renal function.

  • 11.
    Brynolfsson, Patrik
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Wirestam, Ronnie
    Lund University.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. CJ Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, Netherlands.
    Combining phase and magnitude information for contrast agent quantification in dynamic contrast-enhanced MRI using statistical modeling2015In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 74, no 4, p. 1156-1164Article in journal (Refereed)
    Abstract [en]

    Purpose: The purpose of this study was to investigate, using simulations, a method for improved contrast agent (CA) quantification in DCE-MRI.

    Methods: We developed a maximum likelihood estimator that combines the phase signal in the DCE-MRI image series with an additional CA estimate, e.g. the estimate obtained from magnitude data. A number of simulations were performed to investigate the ability of the estimator to reduce bias and noise in CA estimates. Noise levels ranging from that of a body coil to that of a dedicated head coil were investigated at both 1.5T and 3T.

    Results: Using the proposed method, the root mean squared error in the bolus peak was reduced from 2.24 to 0.11 mM in the vessels and 0.16 to 0.08 mM in the tumor rim for a noise level equivalent of a 12-channel head coil at 3T. No improvements were seen for tissues with small CA uptake, such as white matter.

    Conclusion: Phase information reduces errors in the estimated CA concentrations. A larger phase response from higher field strengths or higher CA concentrations yielded better results. Issues such as background phase drift need to be addressed before this method can be applied in vivo.

  • 12. Bujila, Robert
    et al.
    Kull, Love
    Danielsson, Mats
    Andersson, Jonas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Applying three different methods of measuring CTDIfree air to the extended CTDI formalism for wide-beam scanners (IEC 60601-2-44): a comparative study2018In: Journal of Applied Clinical Medical Physics, ISSN 1526-9914, E-ISSN 1526-9914, Vol. 19, no 4, p. 281-289Article in journal (Refereed)
    Abstract [en]

    Purpose: The weighted CT dose index (CTDIw) has been extended for a nominal total collimation width (nT) greater than 40 mm and relies on measurements of CTDfree air. The purpose of this work was to compare three methods of measuring CTDIfree air and subsequent calculations of CTDIw to investigate their clinical appropriateness.

    Methods: The CTDIfree air, for multiple nTs up to 160 mm, was calculated from (1) high-resolution air kerma profiles from a step-and-shoot translation of a liquid ionization chamber (LIC) (considered to be a dosimetric reference), (2) pencil ionization chamber (PIC) measurements at multiple contiguous positions, and (3) air kerma profiles obtained through the continuous translation of a solid-state detector. The resulting CTDIfree air was used to calculate the CTDIw, per the extended formalism, and compared.

    Results: The LIC indicated that a 40 mm nT should not be excluded from the extension of the CTDIw formalism. The solid-state detector differed by as much as 8% compared to the LIC. The PIC was the most straightforward method and gave equivalent results to the LIC.

    Conclusions: The CTDIw calculated with the latest CTDI formalism will differ most for 160 mm nTs (e.g., whole-organ perfusion or coronary CT angiography) compared to the previous CTDI formalism. Inaccuracies in the measurement of CTDIfree air will subsequently manifest themselves as erroneous calculations of the CTDIw, for nTs greater than 40 mm, with the latest CTDI formalism. The PIC was found to be the most clinically feasible method and was validated against the LIC.

  • 13.
    Börlin, Niclas
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science.
    Thien, Truike
    Katholieke Universiteit Nijmegen, Nijmegen, Holland.
    Kärrholm, Johan
    Sahlgrenska University Hospital, Göteborg, Sweden.
    The precision of radiostereometric measurements: manual vs. digital measurements2002In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 35, no 1, p. 69-79Article in journal (Refereed)
    Abstract [en]

    The precision of digital vs. manual radiostereometric measurements in total hip arthroplasty was evaluated using repeated stereoradiographic exposures with an interval of 10–15 min. Ten Lubinus SP2 stems cemented into bone specimens and 12 patients with the same stem design were used to evaluate the precision of stem translations and rotations. The precision of translations and rotations of the cup and femoral head penetration was studied in 12 patients with whole polyethylene cups.

    The use of a measurement method based on digitised radiographs improved the precision for some of the motion parameters, whereas many of them did not change. A corresponding pattern was observed for both the intra- and interobserver error. Of the wear parameters, the most pronounced improvements were the 3D wear and in the proximal-distal direction, although the anterior-posterior precision was also improved. The mean errors of rigid body and elliptic fitting decreased in all evaluations but one, consistent with a more reproducible identification of the markers centres and the edge of the femoral head.

    Increased precision of radiostereometric measurements may be used to increase the statistical power of future randomised studies and to study new fields in orthopaedics requiring higher precision than has been available with RSA based on manual measurements.

  • 14. Chen, Hanwei
    et al.
    Jiang, Jinzhao
    Gao, Junling
    Liu, Dan
    Axelsson, Jan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Cui, Minyi
    Gong, Nan-Jie
    Feng, Shi-Ting
    Luo, Liangping
    Huang, Bingsheng
    Tumor Volumes Measured From Static and Dynamic F-18-fluoro-2-deoxy-D-glucose Positron Emission Tomography-Computed Tomography Scan: Comparison of Different Methods Using Magnetic Resonance Imaging as the Criterion Standard2014In: Journal of computer assisted tomography, ISSN 0363-8715, E-ISSN 1532-3145, Vol. 38, no 2, p. 209-215Article in journal (Refereed)
    Abstract [en]

    Objective: The objective of this study was to compare the accuracy of calculating the primary tumor volumes using a gradient-based method and fixed threshold methods on the standardized uptake value (SUV) maps and the net influx of FDG (Ki) maps from positron emission tomography-computed tomography (PET-CT) images. Materials and Methods: Newly diagnosed patients with head and neck cancer were recruited, and dynamic PET-CT scan and T2-weighted magnetic resonance imaging were performed. The maps of Ki and SUV were calculated from PET-CT images. The tumor volumes were calculated using a gradient-based method and a fixed threshold method at 40% of maximal SUV or maximal Ki. Four kinds of volumes, VOLKi-Gra (from the Ki maps using the gradient-based method), VOLKi-40% (from the Ki maps using the threshold of 40% maximal Ki), VOLSUV-Gra (from the SUV maps using the gradient-based method), and VOLSUV-40% (from the SUV maps using the threshold of 40% maximal SUV), were acquired and compared with VOLMRI (the volumes acquired on T2-weighted images) using the Pearson correlation, paired t test, and similarity analysis. Results: Eighteen patients were studied, of which 4 had poorly defined tumors (PDT). The positron emission tomography-derived volumes were as follows: VOLSUV-40%, 2.1 to 41.2 cm(3) (mean [SD], 12.3 [10.6]); VOLSUV-Gra, 2.2 to 28.1 cm(3) (mean [SD], 13.2 [8.4]); VOLKi-Gra, 2.4 to 17.0 cm(3) (mean [SD], 9.5 [4.6]); and VOLKi-40%, 2.7 to 20.3 cm(3) (mean [SD], 12.0 [6.0]). The VOLMRI ranged from 2.9 to 18.1 cm(3) (mean [SD], 9.1 [3.9]). The VOLKi-Gra significantly correlated with VOLMRI with the highest correlation coefficient (PDT included, R = 0.673, P = 0.002; PDT excluded, R = 0.841, P < 0.001) and presented no difference from VOLMRI (P = 0.672 or 0.561, respectively, PDT included and excluded). The difference between VOLKi-Gra and VOLMRI was also the smallest. Conclusions: The tumor volumes delineated on the Ki maps using the gradient-based method are more accurate than those on the SUV maps and using the fixed threshold methods.

  • 15.
    Duvaldt, Maria
    Umeå University, Faculty of Science and Technology, Department of Physics. Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF). Karolinska Universitetssjukhuset Huddinge.
    Developing a Semi-Automatised Tool for Grading Brain Tumours with Susceptibility-Weighted MRI2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Gliomas are a common type of brain tumour and for the treatment of a patient it is important to determine the tumour’s grade of malignancy. This is done today by a biopsy, a histopathological analysis of the tumourous tissue, that is classified by the World Health Organization on a malignancy scale from I to IV. Recent studies have shown that the local image variance (LIV) and the intratumoural susceptibility signal (ITSS) in susceptibility-weighted MR images correlate to the tumour grade. This thesis project aims to develop a software program as aid for the radiologists when grading a glioma. The software should by image analysis be able to separate the gliomas into low grade (I-II) and high grade (III-IV). The result is a graphical user interface written in Python 3.4.3. The user chooses an image, draws a region of interest and starts the analysis. The analyses implemented in the program are LIV and ITSS mentioned above, and the code can be extended to contain other types of analyses as research progresses. To validate the image analysis, 16 patients with glioma grades confirmed by biopsy are included in the study. Their susceptibility-weighted MR images were analysed with respect to LIV and ITSS, and the outcome of those image analyses was tested versus the known grades of the patients. No statistically significant difference could be seen between the high and the low grade group, in the case of LIV. This was probably due to hemorrhage and calcification, characteristic for some tumours and interpreted as blood vessels. Concerning ITSS a statistically significant difference could be seen between the high and the low grade group (p < 0.02). The sensitivity and specificity was 80% and 100% respec- tively. Among these 16 gliomas, 11 were astrocytic tumours and between low and high grade astrocytomas a statistically significant difference was shown. The degree of LIV was significantly different between the two groups (p < 0.03) and the sensitivity and specificity were 86% and 100% respectively. The degree of ITSS was significantly different between the two groups (p < 0.04) and the sensitivity and specificity were 86% and 100% respectively. Spearman correlation showed a correlation between LIV and tumour grade (for all gliomas r = 0.53 and p < 0.04, for astrocytomas r = 0.84 and p < 0.01). A correlation was also found between ITSS and tumour grade (for all gliomas r = 0.69 and p < 0.01, for astrocytomas r = 0.63 and p < 0.04). The results indicate that SWI is useful for distinguishing between high and low grade astrocytoma with 1.5T imaging within this cohort. It also seems possible to distinguish between high and low grade glioma with ITSS.

  • 16.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Contributions to quantitative dynamic contrast-enhanced MRI2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Background: Dynamic contrast-enhanced MRI (DCE-MRI) has the potential to produce images of physiological quantities such as blood flow, blood vessel volume fraction, and blood vessel permeability. Such information is highly valuable, e.g., in oncology. The focus of this work was to improve the quantitative aspects of DCE-MRI in terms of better understanding of error sources and their effect on estimated physiological quantities.

    Methods: Firstly, a novel parameter estimation algorithm was developed to overcome a problem with sensitivity to the initial guess in parameter estimation with a specific pharmacokinetic model. Secondly, the accuracy of the arterial input function (AIF), i.e., the estimated arterial blood contrast agent concentration, was evaluated in a phantom environment for a standard magnitude-based AIF method commonly used in vivo. The accuracy was also evaluated in vivo for a phase-based method that has previously shown very promising results in phantoms and in animal studies. Finally, a method was developed for estimation of uncertainties in the estimated physiological quantities.

    Results: The new parameter estimation algorithm enabled significantly faster parameter estimation, thus making it more feasible to obtain blood flow and permeability maps from a DCE-MRI study. The evaluation of the AIF measurements revealed that inflow effects and non-ideal radiofrequency spoiling seriously degrade magnitude-based AIFs and that proper slice placement and improved signal models can reduce this effect. It was also shown that phase-based AIFs can be a feasible alternative provided that the observed difficulties in quantifying low concentrations can be resolved. The uncertainty estimation method was able to accurately quantify how a variety of different errors propagate to uncertainty in the estimated physiological quantities.

    Conclusion: This work contributes to a better understanding of parameter estimation and AIF quantification in DCE-MRI. The proposed uncertainty estimation method can be used to efficiently calculate uncertainties in the parametric maps obtained in DCE-MRI.

  • 17.
    Garpebring, Anders
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Brynolfsson, Patrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Yu, Jun
    Sveriges lantbruksuniversitet, Centre of Biostochastiscs.
    Wirestam, Ronnie
    Lunds universitet, Medicinsk strålningsfysik.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Asklund, Thomas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Uncertainty estimation in dynamic contrast-enhanced MRI2013In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 69, no 4, p. 992-1002Article in journal (Refereed)
    Abstract [en]

    Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK parameters. Uncertainties in the PK parameters were investigated for the modified Kety model. The method was evaluated with Monte Carlo simulations and exemplified with in vivo brain tumor data. PK parameter uncertainties due to noise in dynamic data were accurately estimated. Noise with standard deviation up to 15% in the baseline signal and the baseline T1 map gave estimated uncertainties in good agreement with the Monte Carlo simulations. Good agreement was also found for up to 15% errors in the arterial input function amplitude. The method was less accurate for errors in the bolus arrival time with disagreements of 23%, 32%, and 29% for Ktrans, ve, and vp, respectively, when the standard deviation of the bolus arrival time error was 5.3 s. In conclusion, the proposed method provides efficient means for calculation of uncertainty maps, and it was applicable to a wide range of sources of uncertainty.

  • 18.
    Garpebring, Anders
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Östlund, Nils
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    A novel estimation method for physiological parameters in dynamic contrast-enhanced MRI: application of a distributed parameter model using Fourier-domain calculations2009In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 28, no 9, p. 1375-1383Article in journal (Refereed)
    Abstract [en]

    Dynamic contrast-enhanced magnetic resonance imaging (MRI) is a promising tool in the evaluation of tumor physiology. From rapidly acquired images and a model for contrast agent pharmacokinetics, physiological parameters are derived. One pharmacokinetic model, the tissue homogeneity model, enables estimation of both blood flow and vessel permeability together with parameters that describe blood volume and extracellular extravascular volume fraction. However, studies have shown that parameter estimation with this model is unstable. Therefore, several initial guesses are needed for accurate estimates, which makes the estimation slow. In this study a new estimation algorithm for the tissue homogeneity model, based on Fourier domain calculations, was derived and implemented as a Matlab program. The algorithm was tested with Monte-Carlo simulations and the results were compared to an existing method that uses the adiabatic approximation. The algorithm was also tested on data from a metastasis in the brain. The comparison showed that the new algorithm gave more accurate results on the 2.5th and 97.5th percentile levels, for instance the error in blood volume was reduced by 21%. In addition, the time needed for the computations was reduced with a factor 25. It was concluded that the new algorithm can be used to speed up parameter estimation while accuracy can be gained at the same time.

  • 19.
    Gavelin, Daniel
    et al.
    Umeå University, Faculty of Medicine, Department of Nursing.
    Svensson, Robert
    Umeå University, Faculty of Medicine, Department of Nursing.
    eHälsa och distanskommunikation: Nuvarande och framtida utmaningar för vårdpersonal i arbetet med vård på distans.2015Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Introduction. The current age structure in Sweden is changing. At the same time, life expectancy is increasing in many parts of the world. This will lead to greater demands of accessible care resources and its application. Well implemented communication is paramount when the healthcare system is as information-intensive as it is. For maintenance of good healthcare, demands will be set on new kinds of services. With eHealth, information and healthpromotion through communication-based technology, healthcare can be performed efficiently with secure output within the healthcare sector. Aim. The aim of this study was to examine challanges for health professionals in the process of patient care through care at a distance. Method. An empirical study of six (6) people was conducted by semistructured interviews. Result. Indicated result show a result of the need of eHealth within the current use of healthcare, and that the technology can be of comparable quality to physical meetings. However, technical solutions should be seen as a complement within healthcare, and not as a substitute of physical interaction. Conclusion. eHealth services is not something that will become relevant within a timeperiod of ten to fifteen years. It is a currently usable service that can be established to be of comparable quality to the person-centered care the nursing profession is striving for.

  • 20. Ginley, Brandon
    et al.
    Emmons, Tiffany
    Sasankan, Prabhu
    Urban, Constantin
    Umeå University, Faculty of Medicine, Department of Clinical Microbiology, Immunology/Immunchemistry.
    Segal, Brahm H.
    Sarder, Pinaki
    Identification and characterization of neutrophil extracellular trap shapes in flow cytometry2017In: Medical Imaging 2017: Digital Pathology / [ed] Gurcan, MN Tomaszewski, JE, 2017, article id 101400DConference paper (Refereed)
    Abstract [en]

    Neutrophil extracellular trap (NET) formation is an alternate immunologic weapon used mainly by neutrophils. Chromatin backbones fused with proteins derived from granules are shot like projectiles onto foreign invaders. It is thought that this mechanism is highly anti-microbial, aids in preventing bacterial dissemination, is used to break down structures several sizes larger than neutrophils themselves, and may have several more uses yet unknown. NETs have been implied to be involved in a wide array of systemic host immune defenses, including sepsis, autoimmune diseases, and cancer. Existing methods used to visually quantify NETotic versus non-NETotic shapes are extremely time-consuming and subject to user bias. These limitations are obstacles to developing NETs as prognostic biomarkers and therapeutic targets. We propose an automated pipeline for quantitatively detecting neutrophil and NET shapes captured using a flow cytometry-imaging system. Our method uses contrast limited adaptive histogram equalization to improve signal intensity in dimly illuminated NETs. From the contrast improved image, fixed value thresholding is applied to convert the image to binary. Feature extraction is performed on the resulting binary image, by calculating region properties of the resulting foreground structures. Classification of the resulting features is performed using Support Vector Machine. Our method classifies NETs from neutrophils without traps at 0.97/0.96 sensitivity/specificity on n = 387 images, and is 1500X faster than manual classification, per sample. Our method can be extended to rapidly analyze whole-slide immunofluorescence tissue images for NET classification, and has potential to streamline the quantification of NETs for patients with diseases associated with cancer and autoimmunity.

  • 21.
    Grönlund, Christer
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Albano, Amanda
    Gustavsson, Sandra
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Cardiology.
    Wiklund, Urban
    Henein, Michael Y
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Cardiology.
    Lindqvist, Per
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Clinical Physiology.
    Significant beat-to-beat variability of E/e’ irrespective of respiration2013In: International cardiovascular forum, ISSN 2409-3424, Vol. 1, no 2, p. 88-89Article in journal (Refereed)
    Abstract [en]

    The E/e’ ratio is commonly used in Doppler echocardiographic examinations to estimate the pulmonary capillary wedge pressure. The rationale of using this ratio is to combine left ventricular (LV) filling (E) and relaxation (e’) velocities to indirectly assess left atrial pressure. However, the accuracy of this index has recently been questioned, particularly in patients with controlled heart failure. Likewise, the potential beat-to-beat variability of such measurements remains undetermined. The cardiovascular system is subject to several oscillations with the potential of influencing LV function and its intra-cavitary pressures, hence measurements of its filling and relaxation velocities. The aim of this pilot study was to assess the beat-to-beat variability of the E/e’ ratio in one minute long examination in healthy subjects, and patients with various severity of amyloid heart disease. The results show that despite critical application of the standard echocardiographic recording recommendations, E/e’ beat-to-beat variability was 36 % (22 to 50%) in healthy subjects and 17 % (11-26%) in patients, and where the most severe amyloid heart disease had the least variability. Thus, clinical use of a single or few cardiac beats might not necessarily reflect an accurate ratio between the two velocities, and hence casts doubt over their diagnostic value.

  • 22.
    Grönlund, Christer
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF).
    Claesson, Kenji
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Holtermannz, Andreas
    Imaging two-dimensional mechanical waves of skeletal muscle contraction2013In: Ultrasound in Medicine and Biology, ISSN 0301-5629, E-ISSN 1879-291X, Vol. 39, no 2, p. 360-369Article in journal (Refereed)
    Abstract [en]

    Skeletal muscle contraction is related to rapid mechanical shortening and thickening. Recently, specialized ultrasound systems have been applied to demonstrate and quantify transient tissue velocities and one-dimensional (1-D) propagation of mechanical waves during muscle contraction. Such waves could potentially provide novel information on musculoskeletal characteristics, function and disorders. In this work, we demonstrate two-dimensional (2-D) mechanical wave imaging following the skeletal muscle contraction. B-mode image acquisition during multiple consecutive electrostimulations, speckle-tracking and a time-stamp sorting protocol were used to obtain 1.4 kHz frame rate 2-D tissue velocity imaging of the biceps brachii muscle contraction. The results present novel information on tissue velocity profiles and mechanical wave propagation. In particular, counter-propagating compressional and shear waves in the longitudinal direction were observed in the contracting tissue (speed 2.8-4.4 m/s) and a compressional wave in the transverse direction of the non-contracting muscle tissue (1.2-1.9 m/s). In conclusion, analysing transient 2-D tissue velocity allows simultaneous assessment of both active and passive muscle tissue properties. (E-mail: christer.gronlund@vll.se) (C) 2013 World Federation for Ultrasound in Medicine & Biology.

  • 23.
    Hanga, Alexander
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Optimization of image reconstruction of 123I DAT SPECT with a LEGP collimator2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In SPECT, diagnoses based on quantitative measurements may be uncertain due to high noise levels and low spatial resolution. 123I DAT SPECT has been shown to have a relatively high sensitivity and specificity, but improving image quality could potentially increase these values even further, especially for early cases with parkinsonian syndromes. The aim of the study was to optimise the reconstruction protocol for 123I DAT SPECT with a LEGP collimator, using a resolution recovery algorithm included in the iterative reconstruction, and compare to images reconstructed without resolution recovery. The optimization concentrated on critical frequency of the post-reconstruction Butterworth filter and the number of reconstruction iterations. Monte Carlo simulations of a morphological brain phantom with typical DAT SPECT uptake were used for this part of the study. From contrast-to-noise diagrams, it was found that a critical frequency of 0.50 cm-1 (power factor 8) was the most optimal of the studied filters. The optimal number of OSEM iterations was evaluated by a radiologist, specialized in nuclear medicine, and 8 iterations with 6 subsets were chosen. A group of 20 subjects diagnosed with Parkinson’s disease (PD) were then be compared to a group of 20 healthy controls, with respect to uptake ratios for caudate nucleus, putamen and the whole striatum (background region: whole cortex or the occipital lobe). Uptake ratios were calculated using the software Exini DAT for images reconstructed both with and without resolution recovery. It was found that the group differences were highly significant both with and without resolution recovery. However, in putamen, where early stages of PD first manifests, the group significance of uptake ratios improved from 7.2E-14 to 8.2E-15 (background: occipital lobe) or 2.4E-14 to 8.4E-16 (background: whole cortex) when using resolution recovery. A higher spatial resolution seems to be an advantage for quantitative evaluation of 123I DAT SPECT.

  • 24.
    Hedman, Angelica
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Swedish Defence Research Agency, Division of CBRN Defence and Security, SE-90182 Umeå, Sweden.
    Gogani, J. Bahar
    Swedish Defence Research Agency, Division of CBRN Defence and Security, SE-90182 Umeå, Sweden.
    Granström, M.
    Swedish Defence Research Agency, Division of CBRN Defence and Security, SE-90182 Umeå, Sweden.
    Johansson, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Andersson, Jonas S.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Ramebäck, H.
    Swedish Defence Research Agency, Division of CBRN Defence and Security, SE-90182 Umeå, Sweden; Chalmers University of Technology, Department of Chemical and Biological Engineering, Nuclear Chemistry, SE-41296 Göteborg, Sweden.
    Characterization of HPGe detectors using Computed Tomography2015In: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, ISSN 0168-9002, E-ISSN 1872-9576, Vol. 785, no 11 June 2015, p. 21-25Article in journal (Refereed)
    Abstract [en]

    Computed Tomography (CT) high resolution imaging have been used to investigate if there is a significant change in the crystal-to-window distance, i.e. the air gap thickness, in a small n-type detector cooled to 77 K, and in a medium sized p-type HPGe detector when cooled to 100 K. The findings were compared to detector dimension data made available by the manufacturer. The air gap thickness increased by (0.38 +/- 0.07) mm for the n-type detector and by (0.40 +/- 0.15) mm for the p-type detector when the detectors were cooled to 77 resp. 100 K compared to at room temperature. Monte Carlo calculations indicate that these differences have a significant impact on the efficiency in close geometries (< 5 cm). In the energy range of 40-700 keV with a source placed directly on endcap, the change in detector efficiency with temperature is 1.9-2.9% for the n-type detector and 0.3-2.1% for the p-type detector. The measured air gap thickness when cooling the detector was 1.1 mm thicker than manufacturer data for the n-type detector and 0.2 mm thicker for the p-type detector. In the energy range of 40-700 keV and with a source on endcap, this result in a change in detector efficiency of 5.2-7.1% for the n-type detector and 0.2-1.0% for the p-type detector, Le the detector efficiency is overestimated using data available by the manufacturer. (C) 2015 Elsevier B.V. All rights reserved.

  • 25.
    Hildeman, Anders
    et al.
    Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
    Bolin, David
    Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
    Wallin, Jonas
    Department of Statistics, Lund University.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Asklund, Thomas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    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.2016Manuscript (preprint) (Other academic)
    Abstract [en]

    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.

  • 26.
    Holmberg, August
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Investigation of Attenuation Corrections for External Hardware in PET/MR Imaging2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
  • 27.
    Holmberg, Daniel
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Optimisation of image acquisition and reconstruction of 111In-pentetrotide SPECT2012Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The aim of this study is to optimise the acquisition and reconstruction for SPECT with 111In- pentetrotide with the iterative reconstruction software OSEMS. For 111In-pentetrotide SPECT, the uptake in the tumour is usually high compared to uptake in normal tissue. It may, however, be difficult to detect small tumours with the SPECT method because of high noise levels and the low spatial resolution. The liver is a common region for somatostatin-positive metastases, and to visually detect small tumours in the liver, as early as possible, is important for an effective treatment of the cancer disease.

    The study concentrates on the acquired number of projections, the subset size in the OSEM reconstruction and evaluates contrast as a function of noise for a range of OSEM iterations. The raw-data projections are produced using Monte Carlo simulations of an anthropomorphic phantom, including tumours in the liver. Two General Electric (GE) collimators are evaluated, the extended low-energy general-purpose (ELEGP) and the medium energy general-purpose (MEGP) collimator. Three main areas of reconstruction are investigated. First the reconstructions are performed for so called full time scans with the acquisition time used clinically. Also the effect of performing the examination in half-time or with half the injected activity is evaluated with the most optimal settings gained from the full time scans for both collimators. In addition images reconstructed without model-based compensation are also included for comparison.

    This study is a continuation of a previous study on 111In-pentetrotide SPECT where collimator choice and model-based compensation were evaluated for a cylindrical phantom representing small tumours in liver background. As in the previous study, ELEGP proved to be the better collimator. For ELEGP, the most optimal setting was 30 projection angles and a subset size of 6 projections in the OSEM reconstruction, and for MEGP optimal setting was 60 projections and 4 subsets. The difference between the different collimator settings were, however, rather small but proven significant. For both collimators the half-time scan including model-based compensation was better compared to the full-time reconstructions without model-based compensation.

  • 28.
    Häggström, Ida
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Quantitative methods for tumor imaging with dynamic PET2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    There is always a need and drive to improve modern cancer care. Dynamic positron emission tomography (PET) offers the advantage of in vivo functional imaging, combined with the ability to follow the physiological processes over time. In addition, by applying tracer kinetic modeling to the dynamic PET data, thus estimating pharmacokinetic parameters associated to e.g. glucose metabolism, cell proliferation etc., more information about the tissue's underlying biology and physiology can be determined. This supplementary information can potentially be a considerable aid when it comes to the segmentation, diagnosis, staging, treatment planning, early treatment response monitoring and follow-up of cancerous tumors.

    We have found it feasible to use kinetic parameters for semi-automatic tumor segmentation, and found parametric images to have higher contrast compared to static PET uptake images. There are however many possible sources of errors and uncertainties in kinetic parameters obtained through compartment modeling of dynamic PET data. The variation in the number of detected photons caused by the random nature of radioactive decay, is of course always a major source. Other sources may include: the choice of an appropriate model that is suitable for the radiotracer in question, camera detectors and electronics, image acquisition protocol, image reconstruction algorithm with corrections (attenuation, random and scattered coincidences, detector uniformity, decay) and so on. We have found the early frame sampling scheme in dynamic PET to affect the bias and uncertainty in calculated kinetic parameters, and that scatter corrections are necessary for most but not all parameter estimates. Furthermore, analytical image reconstruction algorithms seem more suited for compartment modeling applications compared to iterative algorithms.

    This thesis and included papers show potential applications and tools for quantitative pharmacokinetic parameters in oncology, and help understand errors and uncertainties associated with them. The aim is to contribute to the long-term goal of enabling the use of dynamic PET and pharmacokinetic parameters for improvements of today's cancer care.

  • 29.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Axelsson, Jan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York 10065, USA.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Johansson, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Sörensen, Jens
    Medical Sciences, Nuclear Medicine, Uppsala University Hospital, Uppsala, Sweden.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    A Monte Carlo study of the dependence of early frame sampling on uncertainty and bias in pharmacokinetic parameters from dynamic PET2015In: Journal of Nuclear Medicine Technology, ISSN 0091-4916, E-ISSN 1535-5675, Vol. 43, no 1, p. 53-60Article in journal (Refereed)
    Abstract [en]

    Compartmental modeling of dynamic PET data enables quantifi- cation of tracer kinetics in vivo, through the calculated model parameters. In this study, we aimed to investigate the effect of early frame sampling and reconstruction method on pharmacokinetic parameters obtained from a 2-tissue model, in terms of bias and uncertainty (SD). Methods: The GATE Monte Carlo software was used to simulate 2 · 15 dynamic 3′-deoxy-3′-18F-fluorothymidine (18F-FLT) brain PET studies, typical in terms of noise level and kinetic parameters. The data were reconstructed by both 3- dimensional (3D) filtered backprojection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM) into 6 dynamic image sets with different early frame durations of 1, 2, 4, 6, 10, and 15 s. Bias and SD were evaluated for fitted parameter estimates, calculated from regions of interest. Results: The 2-tissue-model parameter estimates K1, k2, and fraction of arterial blood in tissue depended on early frame sampling, and a sampling of 6–15 s generally minimized bias and SD. The shortest sampling of 1 s yielded a 25% and 42% larger bias than the other schemes, for 3DRP and OSEM, respectively, and a parameter uncertainty that was 10%–70% higher. The schemes from 4 to 15 s were generally not significantly different in regards to bias and SD. Typically, the reconstruction method 3DRP yielded less framesampling dependence and less uncertain results, compared with OSEM, but was on average more biased. Conclusion: Of the 6 sampling schemes investigated in this study, an early frame duration of 6–15 s generally kept both bias and uncertainty to a minimum, for both 3DRP and OSEM reconstructions. Veryshort frames of 1 s should be avoided because they typically resulted in the largest parameter bias and uncertainty. Furthermore, 3DRP may be p

  • 30.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Beattie, Bradley J
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies2016In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 43, no 6, p. 3104-3116Article in journal (Refereed)
    Abstract [en]

    Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator ofTracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment,postprocessing choices, etc., on dynamic and parametric images.

    Methods: The tool was developed in PETSTEP using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated foreach voxel of the input parametric image, whereby effects of imaging system blurring, counting noise,scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed intoimages according to the user specified method, settings, and corrections. Reconstructed images werecompared to MC data, and simple Gaussian noised time activity curves (GAUSS).

    Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root meansquare error that was within 4% on average of that of MC images, whereas the GAUSS images werewithin 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatterplot histograms, and statistically by tumor region of interest histogram comparisons that showed nosignificant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreedbetter with MC.

    Conclusions: The authors have developed a fast and easy one-stop solution for simulationsof dynamic PET and parametric images, and demonstrated that it generates both images andsubsequent parametric images with very similar noise properties to those of MC images, in afraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, andrealistic results, however since it uses simple scatter and random models it may not be suitablefor studies investigating these phenomena. dPETSTEP can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.

  • 31.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Johansson, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Östlund, Nils
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Sörensen, Jens
    Medical Sciences, Nuclear Medicine, Uppsala University Hospital, Uppsala, Sweden.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Semi-automatic tumour segmentation by selective navigation in a three-parameter volume, obtained by voxel-wise kinetic modelling of 11C-acetate2010In: Radiation Protection Dosimetry, ISSN 0144-8420, E-ISSN 1742-3406, Vol. 139, no 1-3, p. 214-218Article in journal (Refereed)
    Abstract [en]

    Positron emission tomography (PET) is increasingly used for delineation of tumour tissue in, for example, radiotherapy treatment planning. The most common method used is to outline volumes with a certain per cent uptake over background in a static image. However, PET data can also be collected dynamically and analysed by kinetic models, which potentially represent the underlying biology better. In the present study, a three-parameter kinetic model was used for voxel-wise evaluation of (11)C-acetate data of head/neck tumours. These parameters which represent the tumour blood volume, the uptake rate and the clearance rate of the tissue were derived for each voxel using a linear regression method and used for segmentation of active tumour tissue. This feasibility study shows that it is possible to segment images based on derived model parameters. There is, however, room for improvements concerning the PET data acquisition, noise reduction and the kinetic modelling. In conclusion, this early study indicates a strong potential of the method even though no 'true' tumour volume was available for validation.

  • 32.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Axelsson, Jan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Johansson, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Sörensen, Jens
    Medical Sciences, Nuclear Medicine, Uppsala University Hospital, Uppsala, Sweden.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    The influence of time sampling scheme on kinetic parameters obtained from compartmental modeling of a dynamic PET study: a Monte Carlo study2012In: IEEE Nuclear Science Symposium Conference Record / [ed] B. Yu, Anaheim: IEEE conference proceedings, 2012, p. 3101-3107Conference paper (Refereed)
    Abstract [en]

    Compartmental modeling of dynamic PET data enables quantification of tracer kinetics in vivo, through the obtained model parameters. The dynamic data is sorted into frames during or after the acquisition, with a sampling interval usually ranging from 10 s to 300 s. In this study we wanted to investigate the effect of the chosen sampling interval on kinetic parameters obtained from a 2-tissue model, in terms of bias and standard deviation, using a complete Monte Carlo simulated dynamic F-18-FLT PET study. The results show that the bias and standard deviation in parameter K-1 is small regardless of sampling scheme or noise in the time-activity curves (TACs), and that the bias and standard deviation in k(4) is large for all cases. The bias in V-a is clearly dependent on sampling scheme, increasing for increased sampling interval. In general, a too short sampling interval results in very noisy images and a large bias of the parameter estimate, and a too long sampling interval also increases bias. Noise in the TACs is the largest source of bias.

  • 33.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Compartment Modeling of Dynamic Brain PET: The Effect of Scatter Corrections on Parameter Errors2014Conference paper (Other academic)
    Abstract [en]

    Purpose: To investigate the effects of corrections for random and scattered coincidences on kinetic parameters in brain tumors, by using ten Monte Carlo (MC) simulated dynamic FLT-PET brain scans.

     

    Methods: The GATE MC software was used to simulate ten repetitions of a 1 hour dynamic FLT-PET scan of a voxelized head phantom. The phantom comprised six normal head tissues, plus inserted regions for blood and tumor tissue. Different time-activity-curves (TACs) for all eight tissue types were used in the simulation and were generated in Matlab using a 2-tissue model with preset parameter values (K1,k2,k3,k4,Va,Ki). The PET data was reconstructed into 28 frames by both ordered-subset expectation maximization (OSEM) and 3D filtered back-projection (3DFBP). Five image sets were reconstructed, all with normalization and different additional corrections C (A=attenuation, R=random, S=scatter): Trues (AC), trues+randoms (ARC), trues+scatters (ASC), total counts (ARSC) and total counts (AC). Corrections for randoms and scatters were based on real random and scatter sinograms that were back-projected, blurred and then forward projected and scaled to match the real counts. Weighted non-linear-least-squares fitting of TACs from the blood and tumor regions was used to obtain parameter estimates.

     

    Results: The bias was not significantly different for trues (AC), trues+randoms (ARC), trues+scatters (ASC) and total counts (ARSC) for either 3DFBP or OSEM (p<0.05). Total counts with only AC stood out however, with an up to 160% larger bias. In general, there was no difference in bias found between 3DFBP and OSEM, except in parameter Va and Ki.

     

    Conclusion: According to our results, the methodology of correcting the PET data for randoms and scatters performed well for the dynamic images where frames have much lower counts compared to static images. Generally, no bias was introduced by the corrections and their importance was emphasized since omitting them increased bias extensively.

  • 34.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York 10065.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Compartment modeling of dynamic brain PET: the impact of scatter corrections on parameter errors2014In: Medical physics, ISSN 0094-2405, Vol. 41, no 11, p. 111907-Article in journal (Refereed)
    Abstract [en]

    Purpose: The aim of this study was to investigate the effect of scatter and its correction on kinetic parameters in dynamic brain positron emission tomography (PET) tumor imaging. The 2-tissue compartment model was used, and two different reconstruction methods and two scatter correction (SC) schemes were investigated.

    Methods: The gate Monte Carlo (MC) softwarewas used to perform 2×15 full PET scan simulations of a voxelized head phantom with inserted tumor regions. The two sets of kinetic parameters of all tissues were chosen to represent the 2-tissue compartment model for the tracer 3′-deoxy- 3′-(18F)fluorothymidine (FLT), and were denoted FLT1 and FLT2. PET data were reconstructed with both 3D filtered back-projection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM). Images including true coincidences with attenuation correction (AC) and true+scattered coincidences with AC and with and without one of two applied SC schemes were reconstructed. Kinetic parameters were estimated by weighted nonlinear least squares fitting of image derived time–activity curves. Calculated parameters were compared to the true input to the MC simulations.

    Results: The relative parameter biases for scatter-eliminated data were 15%, 16%, 4%, 30%, 9%, and 7% (FLT1) and 13%, 6%, 1%, 46%, 12%, and 8% (FLT2) for K1, k2, k3, k4,Va, and Ki, respectively. As expected, SC was essential for most parameters since omitting it increased biases by 10 percentage points on average. SC was not found necessary for the estimation of Ki and k3, however. There was no significant difference in parameter biases between the two investigated SC schemes or from parameter biases from scatter-eliminated PET data. Furthermore, neither 3DRP nor OSEM yielded the smallest parameter biases consistently although therewas a slight favor for 3DRP which produced less biased k3 and Ki estimates while OSEM resulted in a less biased Va. The uncertainty in OSEM parameterswas about 26% (FLT1) and 12% (FLT2) larger than for 3DRP although identical postfilters were applied.

    Conclusions: SC was important for good parameter estimations. Both investigated SC schemes performed equally well on average and properly corrected for the scattered radiation, without introducing further bias. Furthermore, 3DRP was slightly favorable over OSEM in terms of kinetic parameter biases and SDs.

  • 35.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Do scatter and random corrections affect the errors in kinetic parameters in dynamic PET?: a Monte Carlo study2013In: 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), IEEE conference proceedings, 2013, , p. 4Conference paper (Refereed)
    Abstract [en]

    Dynamic positron emission tomography (PET) data can be evaluated by compartmental models, yielding model specific kinetic parameters. For the parameters to be of quantitative use however, understanding and estimation of errors and uncertainties associated with them are crucial.

    The aim in this study was to investigate the effects of the inclusion of scattered and random counts and their respective corrections on kinetic parameter errors.

    The MC software GATE was used to simulate two dynamic PET scans of a phantom containing three regions; blood, tissue and a static background. The two sets of time-activity-curves (TACs) used were generated for a 2-tissue compartment model with preset parameter values (K1, k2, k3, k4 and Va). The PET data was reconstructed into 19 frames by both ordered-subset expectation maximization (OSEM) and 3D filtered back-projection with reprojection (3DFBPRP) with normalization and additional corrections (A=attenuation, R=random, S=scatter, C=correction): True counts (AC), true+random counts (ARC), true+scattered counts (ASC) and total counts (ARSC).

    The results show that parameter estimates from true counts (AC), true+random counts (ARC), true+scattered counts (ASC) and total counts (ARSC) were not significantly different, with the exception of Va where the bias increased with added corrections. Thus, the inclusion of and correction for scattered and random counts did not affect the bias in parameter estimates K1, k2, k3, k4 and Ki. Uncorrected total counts (only AC) resulted in biases of hundreds or even thousands of percent, emphasizing the need for proper corrections. Reconstructions with 3DFBPRP resulted in overall 20-40% less biased estimates compared to OSEM.

  • 36.
    Johan, Wallgren
    Umeå University, Faculty of Science and Technology, Department of Physics. Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Graphical user interface for evaluation of knee proprioception and how it is affected by an anterior cruciate ligament (ACL) injury- a functional brain imaging study: Ett grafiskt användargränssnitt för utvärdering av knäproprioception och hur det påverkas av en korsbandsskada - en funktionell magnetresonanstomografisk studie2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    There is a big risk that neuroreceptors located in the knee, responsible for our proprioceptive ability, are damaged after an anterior cruciate ligament (ACL) injury occurs. This may cause miscommunication between the neuroreceptors and motoric function in the brain. Due to the brains plasticity, it has been shown that brain activity patterns, presented as blood oxygen dependent level-signal (BOLD-signal), achieved from functional magnetic resonance imaging (fMRI) differs between healthy and injured individuals when performing certain tasks involving knee movement. As there is little consensus on how a proprioceptive test should be performed, a unique test were participants uses blindfold during a knee bending exercise was created at U Motion Lab, Umeå University. A Matlab based general user interface (GUI) was created for evaluation of the proprioceptive test. This GUI is communicating with the third party toolbox SPM12 and performs necessary preprocessing fMRI-image steps for statistical analysis and statistical parametric mapping of the BOLD-signal for both a healthy control- and ACL-injured group. The fMRIimages preprocessed by the GUI were generated by a 3 T GE scanner and the motion data was collected using an eight-camera 3D-motion analysis system. Time events for three different tasks was investigated. These were passive resting, memorizing and proprioceptive events. For both the control (5 participants)- and ACL (2 participants) group the main area of brain activation during the proprioceptive tests occurred in the frontal lobe. For the control group, brain activation was found in the cerebellum anterior lobe which is a possible origin for unconscious proprioception. For the ACL group activation was found in the inferior parietal lobule which involves visuomotor integration. Activation was also found in the inferior frontal gyrus which according to previous studies, may indicate risk-taking/”out of character” decisions. The results of this study indicates that the proprioceptive test seems to be a promising tool for evaluation of proprioceptive ability. However, more subjects need to be included to validate the result of this study.

  • 37.
    Jonsson, Joakim
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Detecting Cardiac Pulsatility and Respiration using Multiband fMRI2018Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Purpose: Arterial stiffening poses an increased risk of cerebrovascular diseases, cognitive impairments, and even dementia as cardiac pulsations reach further into the brain causing white matter hyperintensities and microbleeds. Therefore it is of interest to obtain methods to estimate and map cardiac related pulsatility in the brain. Improvements of functional magnetic resonance imaging (fMRI) sequences is potentially allowing detection of rapid physiological processes in the echo-planar imaging (EPI) signal in the brainthrough a higher sampling rate. Specifically in this thesis, estimation and localization of cardiac pulsation and respiration is conducted through analysis of resting state data obtained with a multiband EPI sequence that permits whole brain imaging at a shorter repetition time (TR) than conventional EPI. The origin of these physiological signals are likely a mixture of inflow and compartment volume shifts during the cardiac- and respiratory cycles. As the amount of physiologically related signal in the multiband sequence used at the Biomedical Engineering Dept. R&D, Umeå University Hospital is unknown, the aim of this project is to find and map cardiac pulsatility and respiration for future research.

    Methods: Multiband fMRI data from 8 subjects was used, collected in a 3 Tesla scanner using a 32-channel head coil. The physiological signals were estimated through an algorithm that was developed to down-sample and temporally shift copies of simultaneous recordings of pulse and respiration. These signals were obtained using the scanner’s built-in pulse oximeter and a respiration belt. The shifted copies were voxel-wise, and slice by slice, correlated to the fMRI data using Pearson correlation. The time shift yielding maximum mean correlation within the brain was, for each slice, used to create statistical maps for significant voxels to show the localization and magnitude of correlation for cardiac pulsation andrespiration.

    Results: Many voxels around and nearby larger vessels and ventricles were highly correlated with the down-sampled, time shifted signals of the cardiac pulsation for all subjects. The cardiac pulsation maps resembled cerebral vasculature and were mostly localized around the Circle of Willis, brainstem, and the ventricles. Respiration signal was also highly correlated, and spatially located at the sides of the brain although mostly concentrated at the parietal- and occipital lobes.

    Conclusion: The results demonstrated that many voxels in the brain were highly correlated with cardiac pulsation and respiration using multiband EPI, and the statistical maps revealed distinct patterns for both of the physiological signals. This method and results for mapping cardiac related pulsatility, and respiration could be used for future research in order to better understand cerebral diseases and impairments, and alsoto improve fMRI filtering.

    Keywords: Arterial stiffness, Functional magnetic resonance imaging, Resting state, Multiband, CardiacPulsation, Respiration, Correlation analysis

  • 38.
    Jonsson, Joakim
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Integration of MRI into the radiotherapy workflow2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The modern day radiotherapy treatments are almost exclusively based on computed tomography (CT) images. The CT images are acquired using x-rays, and therefore reflect the radiation interaction properties of the material. This information is used to perform accurate dose calculation by the treatment planning system, and the data is also well suited for creating digitally reconstructed radiographs for comparing patient set up at the treatment machine where x-ray images are routinely acquired for this purpose.

    The magnetic resonance (MR) scanner has many attractive features for radiotherapy purposes. The soft tissue contrast as compared to CT is far superior, and it is possible to vary the sequences in order to visualize different anatomical and physiological properties of an organ. Both of these properties may contribute to an increase in accuracy of radiotherapy treatment.

    Using the MR images by themselves for treatment planning is, however, problematic. MR data reflects the magnetic properties of protons, and thus have no connection to the radiointeraction properties of the material. MRI also has inherent difficulty in imaging bone, which will appear in images as areas of no signal similar to air. This makes both dose calculation and patient positioning at the treatment machine troublesome.

    There are several clinics that use MR images together with CT images to perform treatment planning. The images are registered to a common coordinate system, a process often described as image fusion. In these cases, the MR images are primarily used for target definition and the CT images are used for dose calculations. This method is now not ideal, however, since the image fusion may introduce systematic uncertainties into the treatment due to the fact that the tumor is often able to move relatively freely with respect to the patients’ bony anatomy and outer contour, especially when the image registration algorithms take the entire patient anatomy in the volume of interest into account.

    The work presented in the thesis “Integration of MRI into the radiotherapy workflow” aim towards investigating the possibilities of workflows based entirely on MRI without using image registration, as well as workflows using image registration methods that are better suited for targets that can move with respect to surrounding bony anatomy, such as the prostate.

  • 39.
    Jonsson, Joakim
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Söderström, Karin
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Asklund, Thomas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Treatment planning of intracranial targets on MRI derived substitute CT data2013In: Radiotherapy and Oncology, ISSN 0167-8140, E-ISSN 1879-0887, Vol. 108, no 1, p. 118-122Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The use of magnetic resonance imaging (MRI) as a complement to computed tomography (CT) in the target definition procedure for radiotherapy is increasing. To eliminate systematic uncertainties due to image registration, a workflow based entirely on MRI may be preferable. In the present pilot study, we investigate dose calculation accuracy for automatically generated substitute CT (s-CT) images of the head based on MRI. We also produce digitally reconstructed radiographs (DRRs) from s-CT data to evaluate the feasibility of patient positioning based on MR images. METHODS AND MATERIALS: Five patients were included in the study. The dose calculation was performed on CT, s-CT, s-CT data without inhomogeneity correction and bulk density assigned MRI images. Evaluation of the results was performed using point dose and dose volume histogram (DVH) comparisons, and gamma index evaluation. RESULTS: The results demonstrate that the s-CT images improves the dose calculation accuracy compared to the method of non-inhomogeneity corrected dose calculations (mean improvement 2.0 percentage points) and that it performs almost identically to the method of bulk density assignment. The s-CT based DRRs appear to be adequate for patient positioning of intra-cranial targets, although further investigation is needed on this subject. CONCLUSIONS: The s-CT method is very fast and yields data that can be used for treatment planning without sacrificing accuracy.

  • 40. Kaiser, Franz-Joachim
    et al.
    Bassler, Niels
    Tölli, Heikki
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Jäkel, Oliver
    Initial recombination in the track of heavy charged particles: numerical solution for air filled ionization chambers2012In: Acta Oncologica, ISSN 0284-186X, E-ISSN 1651-226X, Vol. 51, no 3, p. 368-375Article in journal (Refereed)
    Abstract [en]

    Introduction. Modern particle therapy facilities enable sub-millimeter precision in dose deposition. Here, also ionization chambers (ICs) are used, which requires knowledge of the recombination effects. Up to now, recombination is corrected using phenomenological approaches for practical reasons. In this study the effect of the underlying dose distribution on columnar recombination, a quantitative model for initial recombination, is investigated.

    Material and methods. Jaffé's theory, formulated in 1913 quantifies initial recombination by elemental processes, providing an analytical (closed) solution. Here, we investigate the effect of the underlying charged carrier distribution around a carbon ion track. The fundamental partial differential equation, formulated by Jaffé, is solved numerically taking into account more realistic charge carrier distributions by the use of a computer program (Gascoigne 3D). The investigated charge carrier distributions are based on track structure models, which follow a 1∕r(2) behavior at larger radii and show a constant value at small radii. The results of the calculations are compared to the initial formulation and to data obtained in experiments using carbon ion beams.

    Results. The comparison between the experimental data and the calculations shows that the initial approach made by Jaffé is able to reproduce the effects of initial recombination. The amorphous track structure based charge carrier distribution does not reproduce the experimental data well. A small additional correction in the assessment of the saturation current or charge is suggested by the data.

    Conclusion. The established model of columnar recombination reproduces the experimental data well, whereas the extensions using track structure models do not show such an agreement. Additionally, the effect of initial recombination on the saturation curve (i.e. Jaffé plot) does not follow a linear behavior as suggested by current dosimetry protocols, therefore higher order corrections (such as the investigated ones) might be necessary.

  • 41.
    Kuljus, Kristi
    et al.
    University of Tartu, Estonia.
    Bayisa, Fekadu
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Bolin, David
    Chalmers University of Technology, Sweden.
    Lember, Jüri
    University of Tartu, Estonia.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Comparison of hidden Markov chain models and hidden Markov random field models in estimation of computed tomography images2017Manuscript (preprint) (Other academic)
    Abstract [en]

    There is an interest to replace computed tomography (CT) images withmagnetic resonance (MR) images for a number of diagnostic and therapeuticworkflows. In this article, predicting CT images from a number of magnetic resonance imaging (MRI) sequences using regression approach isexplored. Two principal areas of application for estimated CT images aredose calculations in MRI based radiotherapy treatment planning and attenuationcorrection for positron emission tomography (PET)/MRI. Themain purpose of this work is to investigate the performance of hidden Markov (chain) models (HMMs) in comparison to hidden Markov random field (HMRF) models when predicting CT images of head. Ourstudy shows that HMMs have clear advantages over HMRF models in this particular application. Obtained results suggest that HMMs deservea further study for investigating their potential in modeling applications where the most natural theoretical choice would be the class of HMRFmodels.

  • 42.
    Kuljus, Kristi
    et al.
    University of Tartu, Estonia.
    Bayisa, Fekadu
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Bolin, David
    Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
    Lember, Jüri
    University of Tartu, Estonia.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Comparison of hidden Markov chain models and hidden Markov random field models in estimation of computed tomography images2018In: Communications in Statistics: Case Studies, Data Analysis and Applications, ISSN 2373-7484, Vol. 4, no 1, p. 46-55Article in journal (Refereed)
    Abstract [en]

    Two principal areas of application for estimated computed tomography (CT) images are dose calculations in magnetic resonance imaging (MRI) based radiotherapy treatment planning and attenuation correction for positron emission tomography (PET)/MRI. The main purpose of this work is to investigate the performance of hidden Markov (chain) models (HMMs) in comparison to hidden Markov random field (HMRF) models when predicting CT images of head. Obtained results suggest that HMMs deserve a further study for investigating their potential in modeling applications, where the most natural theoretical choice would be the class of HMRF models.

  • 43.
    Kumar, Keshav
    Umeå University, Faculty of Medicine, Department of Molecular Biology (Faculty of Medicine).
    Discrete wavelet assisted correlation optimised warping of chromatograms: optimizing the computational time for correcting the drifts in peak positions2017In: Analytical Methods, ISSN 1759-9660, E-ISSN 1759-9679, Vol. 9, no 13, p. 2049-2058Article in journal (Refereed)
    Abstract [en]

    Correlation optimised warping (COW) has been the most favourite chromatographic peak alignment approach in recent years. After optimization of the two parameters, slack and segment length, COW works well in aligning the chromatograms. However, one of the serious disadvantages of COW is that it is computationally time consuming. Often several segment lengths and slack parameters need to be tested to find the optimum combination for achieving the alignment that makes the whole analysis take several hours. In the present work, it has been shown that with the application of wavelet analysis prior to alignment it is possible to provide the necessary computational economy to the COW algorithm.

  • 44.
    Leffler, Klara
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Häggström, Ida
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Intelligent data sampling promotes accelerated medical imaging: sharper positron emission tomography2018Conference paper (Refereed)
  • 45.
    Leffler, Klara
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Zhou, Zhiyong
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    An Extended Block Restricted Isometry Property for Sparse Recovery with Non-Gaussian Noise2018Conference paper (Refereed)
  • 46.
    Lundberg, Thorbjörn
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Westman, Göran
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Hellström, Sten
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Otorhinolaryngology.
    Sandström, Herbert
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Digital imaging and telemedicine as a tool for studying inflammatory conditions in the middle ear: evaluation of image quality and agreement between examiners2008In: International Journal of Pediatric Otorhinolaryngology, ISSN 0165-5876, E-ISSN 1872-8464, Vol. 72, no 1, p. 73-79Article in journal (Other academic)
    Abstract [en]

    Objective: To evaluate digital imaging of the tympanic membrane by telemedicine technology and study interpersonal agreement in assessing image quality.

    Methods: In an open consecutive study, 64 children aged 2-16 years who attended three rural health care centres in Northern Sweden with otalgia were examined with video endoscopic photography of their tympanic membrane in a telemedical environment. One hundred and twenty-four images were stored in a central database and Later assessed independently regarding image quality by an ENT specialist, a general practitioner and a registrar in general practice. The overall image quality was graded (0-2) regarding assessment of signs of tympanic membrane inflammation. ALL images were also assessed regarding 8 different components, four image-related components and four anatomically related components.

    Results: Overall image quality was good, with 82.3% of acceptable or excellent quality. The position and thickness of the TM were found to be the most important factors of the images to be able to assess inflammatory disease. Image quality tended to be higher later in the study as a sign of improved skills of examiners. Interpersonal agreement between examiners was acceptable. Overall grade showed k 0.56, 0.49 and 0.66 respectively, and focus, light and existence of obscuring objects were the components with the highest agreement.

    Conclusions: The image quality of video endoscopy of the tympanic membrane was good overall. Interpersonal agreement in evaluating image quality was acceptable but not excellent. The use of digital imaging of good quality in clinical studies can offer an objective clinical evaluation of the TM in retrospect by independent reviewers using strict criteria.

  • 47.
    Löthgren, Pia
    et al.
    Biostokastikum, SLU.
    Yu, Jun
    Biostokastikum, SLU.
    Maximum likelihood estimation of the distributional parameters of the magnitude and phase in magnetic resonance spectroscopy signals2012Conference paper (Refereed)
  • 48.
    Nyberg, Lars
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Lövdén, Martin
    Aging Research Center, Karolinska Institutet, Stockholm, Sweden.
    Riklund, Katrine
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Lindenberger, Ulman
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.
    Bäckman, Lars
    Aging Research Center, Karolinska Institutet, Stockholm, Sweden.
    Memory aging and brain maintenance2012In: Trends in cognitive sciences, ISSN 1364-6613, E-ISSN 1879-307X, Vol. 16, no 5, p. 292-305Article in journal (Refereed)
    Abstract [en]

    Episodic memory and working memory decline with advancing age. Nevertheless, large-scale population-based studies document well-preserved memory functioning in some older individuals. The influential 'reserve' notion holds that individual differences in brain characteristics or in the manner people process tasks allow some individuals to cope better than others with brain pathology and hence show preserved memory performance. Here, we discuss a complementary concept, that of brain maintenance (or relative lack of brain pathology), and argue that it constitutes the primary determinant of successful memory aging. We discuss evidence for brain maintenance at different levels: cellular, neurochemical, gray- and white-matter integrity, and systems-level activation patterns. Various genetic and lifestyle factors support brain maintenance in aging and interventions may be designed to promote maintenance of brain structure and function in late life.

  • 49.
    Nyholm, Tufve
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Svensson, Stina
    Andersson, Sebastian
    Jonsson, Joakim
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Sohlin, Maja
    Gustafsson, Christian
    Kjellén, Elisabeth
    Söderström, Karin
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Albertsson, Per
    Blomqvist, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.
    Zackrisson, Björn
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Olsson, Lars E.
    Gunnlaugsson, Adalsteinn
    MR and CT data with multiobserver delineations of organs in the pelvic area: Part of the Gold Atlas project2018In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 45, no 3, p. 1295-1300Article in journal (Refereed)
    Abstract [en]

    Purpose: We describe a public dataset with MR and CT images of patients performed in the same position with both multiobserver and expert consensus delineations of relevant organs in the male pelvic region. The purpose was to provide means for training and validation of segmentation algorithms and methods to convert MR to CT like data, i.e., so called synthetic CT (sCT).

    Acquisition and validation methods: T1- and T2-weighted MR images as well as CT data were collected for 19 patients at three different departments. Five experts delineated nine organs for each patient based on the T2-weighted MR images. An automatic method was used to fuse the delineations. Starting from each fused delineation, a consensus delineation was agreed upon by the five experts for each organ and patient. Segmentation overlap between user delineations with respect to the consensus delineations was measured to describe the spread of the collected data. Finally, an open-source software was used to create deformation vector fields describing the relation between MR and CT images to further increase the usability of the dataset.

    Data format and usage notes: The dataset has been made publically available to be used for academic purposes, and can be accessed from . Potential applicationsThe dataset provides a useful source for training and validation of segmentation algorithms as well as methods to convert MR to CT-like data (sCT). To give some examples: The T2-weighted MR images with their consensus delineations can directly be used as a template in an existing atlas-based segmentation engine; the expert delineations are useful to validate the performance of a segmentation algorithm as they provide a way to measure variability among users which can be compared with the result of an automatic segmentation; and the pairwise deformably registered MR and CT images can be a source for an atlas-based sCT algorithm or for validation of sCT algorithm.

  • 50. Peolsson, Anneli
    et al.
    Peterson, Gunnel
    Trygg, Johan
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Nilsson, David
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Multivariate analysis of ultrasound-recorded dorsal strain sequences: Investigation of dynamic neck extensions in women with chronic whiplash associated disorders2016In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, article id 30415Article in journal (Refereed)
    Abstract [en]

    Whiplash Associated Disorders (WAD) refers to the multifaceted and chronic burden that is common after a whiplash injury. Tools to assist in the diagnosis of WAD and an increased understanding of neck muscle behaviour are needed. We examined the multilayer dorsal neck muscle behaviour in nine women with chronic WAD versus healthy controls during the entire sequence of a dynamic low-loaded neck extension exercise, which was recorded using real-time ultrasound movies with high frame rates. Principal component analysis and orthogonal partial least squares were used to analyse mechanical muscle strain (deformation in elongation and shortening). The WAD group showed more shortening during the neck extension phase in the trapezius muscle and during both the neck extension and the return to neutral phase in the multifidus muscle. For the first time, a novel non-invasive method is presented that is capable of detecting altered dorsal muscle strain in women with WAD during an entire exercise sequence. This method may be a breakthrough for the future diagnosis and treatment of WAD.

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