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  • 1.
    Dunås, Tora
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Ambarki, Khalid
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Zarrinkoob, Laleh
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Birgander, Richard
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Eklund, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Automatic labeling of cerebral arteries in magnetic resonance angiography2016In: Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN 0968-5243, E-ISSN 1352-8661, Vol. 29, no 1, p. 39-47Article in journal (Refereed)
    Abstract [en]

    In order to introduce 4D flow magnetic resonance imaging (MRI) as a standard clinical instrument for studying the cerebrovascular system, new and faster postprocessing tools are necessary. The objective of this study was to construct and evaluate a method for automatic identification of individual cerebral arteries in a 4D flow MRI angiogram. Forty-six elderly individuals were investigated with 4D flow MRI. Fourteen main cerebral arteries were manually labeled and used to create a probabilistic atlas. An automatic atlas-based artery identification method (AAIM) was developed based on vascular-branch extraction and the atlas was used for identification. The method was evaluated by comparing automatic with manual identification in 4D flow MRI angiograms from 67 additional elderly individuals. Overall accuracy was 93 %, and internal carotid artery and middle cerebral artery labeling was 100 % accurate. Smaller and more distal arteries had lower accuracy; for posterior communicating arteries and vertebral arteries, accuracy was 70 and 89 %, respectively. The AAIM enabled fast and fully automatic labeling of the main cerebral arteries. AAIM functionality provides the basis for creating an automatic and powerful method to analyze arterial cerebral blood flow in clinical routine.

  • 2.
    Garpebring, Anders
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Wirestam, Ronnie
    Yu, Jun
    SLU, Centre of Biostochastics.
    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.
    Phase-based arterial input functions in humans applied to dynamic contrast-enhanced MRI: potential usefulness and limitations2011In: Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN 0968-5243, E-ISSN 1352-8661, Vol. 24, no 4, p. 233-245Article in journal (Refereed)
    Abstract [en]

    Object: Phase-based arterial input functions (AIFs) provide a promising alternative to standard magnitude-based AIFs, for example, because inflow effects are avoided. The usefulness of phase-based AIFs in clinical dynamic contrast-enhanced MRI (DCE-MRI) was investigated, and relevant pitfalls and sources of uncertainty were identified.

    Materials and methods: AIFs were registered from eight human subjects on, in total, 21 occasions. AIF quality was evaluated by comparing AIFs from right and left internal carotid arteries and by assessing the reliability of blood plasma volume estimates.

    Results: Phase-based AIFs yielded an average bolus peak of 3.9 mM and a residual concentration of 0.37 mM after 3 min, (0.033 mmol/kg contrast agent injection). The average blood plasma volume was 2.7% when using the AIF peak in the estimation, but was significantly different (p < 0.0001) and less physiologically reasonable when based on the AIF tail concentration. Motion-induced phase shifts and accumulation of contrast agent in background tissue regions were identified as main sources of uncertainty.

    Conclusions: Phase-based AIFs are a feasible alternative to magnitude AIFs, but sources of errors exist, making quantification difficult, especially of the AIF tail. Improvement of the technique is feasible and also required for the phase-based AIF approach to reach its full potential.

  • 3.
    Larsson, Anne
    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.
    Axelsson, Jan
    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, Radiation Physics.
    Riklund, Katrine
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Evaluation of an attenuation correction method for PET/MR imaging of the head based on substitute CT images2013In: Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN 0968-5243, E-ISSN 1352-8661, Vol. 26, no 1, p. 127-136Article in journal (Refereed)
    Abstract [en]

    The aim of this study was to evaluate MR-based attenuation correction of PET emission data of the head, based on a previously described technique that calculates substitute CT (sCT) images from a set of MR images. Images from eight patients, examined with F-18-FLT PET/CT and MRI, were included. sCT images were calculated and co-registered to the corresponding CT images, and transferred to the PET/CT scanner for reconstruction. The new reconstructions were then compared with the originals. The effect of replacing bone with soft tissue in the sCT-images was also evaluated. The average relative difference between the sCT-corrected PET images and the CT-corrected PET images was 1.6 % for the head and 1.9 % for the brain. The average standard deviations of the relative differences within the head were relatively high, at 13.2 %, primarily because of large differences in the nasal septa region. For the brain, the average standard deviation was lower, 4.1 %. The global average difference in the head when replacing bone with soft tissue was 11 %. The method presented here has a high rate of accuracy, but high-precision quantitative imaging of the nasal septa region is not possible at the moment.

  • 4.
    Stenman, Katarina
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Hauksson, Jón
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Gröbner, Gerhard
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Stattin, Pär
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Urology and Andrology.
    Bergh, Anders
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Riklund, Katrine
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Detection of polyunsaturated omega-6 fatty acid in human malignant prostate tissue by 1D and 2D high-resolution magic angle spinning NMR spectroscopy2009In: Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN 0968-5243, E-ISSN 1352-8661, Vol. 22, no 6, p. 327-331Article in journal (Refereed)
    Abstract [en]

    OBJECT: Polyunsaturated omega-6 fatty acids (PUFAs) have been shown to promote prostate cancer. Here, we describe the use of HRMAS NMR spectroscopy to detect omega-6 PUFA species in prostate tissues. MATERIALS AND METHODS: Samples originating from non-malignant (n = 54) and malignant (n = 27) prostate tissues (from 27 prostatectomized men) were studied by 1D (1)H, 2D (1)H-(1)H and (1)H-(13)C HRMAS NMR spectroscopy followed by histopathological characterization. RESULTS: HRMAS NMR proved to be a powerful, non-destructive method to identify and characterize PUFAs. The omega-6 PUFA was found in 15% of examined human prostate tumors. CONCLUSION: It is possible to detect PUFAs in prostate tissues using our NMR-based spectroscopic approach.

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