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  • 1.
    Wallstén, Elin
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Axelsson, J.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Jonsson, J. H.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Thellenberg Karlsson, C.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Larsson, A.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    PET/MRI attenuation correction in the pelvic region with a statistical decomposition method2019In: European Journal of Nuclear Medicine and Molecular Imaging, ISSN 1619-7070, E-ISSN 1619-7089, Vol. 46, no SUPPL 1, p. S289-S290Article in journal (Other academic)
    Abstract [en]

    Aim/Introduction: Quantification in PET/MRI is of importance, and its accuracy is currently limited by the MR based attenuation correction estimate. A common method for attenuation correction of the pelvic region is based on a 2-echo Dixon MRI sequence for segmentation of fat and water and does not account for bone. In this work, we evaluate a new method for attenuation correction using an algorithm based on statistical decomposition of a T2 weighted MRI scan.

    Materials and Methods: Substitute CT images (sCTs) were calculated from T2 weighted MRI scans with a statistical decomposition algorithm, originally developed for MRI-based radiotherapy dose-planning [1]. These sCTs benefits from having bone density information included, in addition to fat and water information. Prostate cancer patients from the PARAPLY study [2] were retrospectivelyselected, scanned with PET/MRI 11C-Acatate and CT the same day. The stand-alone CT images were transformed to the same geometry as the PET and MR images, using a non-rigid registration. CT images, generated sCT images, and the Dixonbased attenuation maps (MRAC), all in the same geometry, were together with the PET raw data used to reconstruct attenuation-corrected PET images using the PETrecon toolbox [GE Healthcare]. The two MR-based attenuation corrections were compared to the CT-based attenuation correction with root mean squared error (RMSE). Lesion analysis will also be reported. PET/MRI images were acquired on a Signa PET/MRI (GE Healthcare), and the CT images on a Brilliance Big Bore (Phillips Healthcare). The study will include 12 patients and a subset of 6 patients has been analyzed so far and is presented here.

    Results: Soft tissue in-between pelvic bone structures were overestimated with 13% in MRAC-PET, and the error was reduced to 5% with sCT attenuation corrected PET (sCT-PET). For the whole patient volume, an average underestimation of 6% was found in the MRAC-PET, compared to 1% for sCTPET. RMSE within the body was reduced with a factor 2.5 with sCT-PET (RMSE=3.6%), compared to MRAC-PET (RMSE=8.8%).

    Conclusion: Applying sCT from statistical decomposition as a base for calculation of attenuation maps reduces quantification errors in PET-images of the pelvic region compared to the common Dixon based method.

  • 2.
    Wallstén, Elin
    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.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Riklund, Katrine
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    A Study of Dynamic PET Frame-Binning on the Reference Logan Binding Potential2017In: IEEE Transactions on Radiation and Plasma Medical Sciences, ISSN 2469-7311, Vol. 1, no 2, p. 128-135Article in journal (Refereed)
    Abstract [en]

    Objective: The reference Logan plot is a tool for determining the non-displaceable binding potential for dynamic PET exams using tracers with reversible bindings. Dynamic frame protocols affect noise in PET images and short frames can lead to quantitative uncertainties and noise-induced reconstruction bias. The aim of this study was to analyze the effect of frame binning on 11C-Raclopride striatal binding potential from reference Logan analysis. Methods: 12 healthy volunteers were scanned in list mode using 11C-raclopride, and the image data were reconstructed into 9 different frame binning schemes whereof 3 clinical schemes. Reconstruction was performed with 3 different algorithms, one based on filtered back projection (FBP) and two based on ordered subset expectation maximization (OSEM); one including resolution recovery. Logan plots were used for calculating the non-displaceable binding potential. Variation in binding potential was evaluated using Students t-tests. Results: It was found that frame lengths of up to 60 s gave significantly different results compared to the reference clinical protocol for OSEM, both with and without resolution recovery (maximum deviation: 10.3 % for the 15 s protocol). For FBP, frame lengths of up to 30 s gave significantly different results with a maximum deviation of 2.8 %. The higher sampling dependence of OSEM compared to FBP is likely due to noise-dependent bias in the OSEM algorithm, most apparent at high noise levels. Conclusions: Bias related to OSEM reconstruction of high-noise data is an important factor for dynamic PET protocols. Time frames of 120 s or more generate the most stable values for the striatum binding potential with the reference Logan plot for 11C-Raclopride brain PET.

  • 3.
    Wallstén, Elin
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Axelsson, Jan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Riklund, Katrine
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Häggström, I.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    The Influence of Time Sampling on Parameters in the Logan Plot2013In: 2013 IEEE NUCLEAR SCIENCE SYMPOSIUM AND MEDICAL IMAGING CONFERENCE (NSS/MIC), 2013Conference paper (Refereed)
    Abstract [en]

    The Logan plot is a graphical method for reversible tracer bindings. The bias and uncertainties of this method have previously been analyzed with respect to noise, but little is known about the direct effects from varying the time sampling scheme. This study aims to investigate the effect of time sampling on the binding potential from the reference Logan plot. Image data from seven healthy subjects imaged with [11C]raclopride was reconstructed into six dynamic series of equal length time frames with frame times between 15 s and 480 s. Images were reconstructed using both filtered back projection (FBP) and a resolution enhanced ordered subset expectation maximization (OSEM) algorithm, SharpIR. For each sampling scheme, the nondisplaceable binding potential (BPND) parameter was calculated from the reference Logan plot with cerebellum as a reference region. The variation in BPND was analyzed as percentage deviations from the BPND for the 480 s scheme. R-2 of the linear fit was also analyzed. Comparison between all sampling schemes showed that the largest deviation in BPND was 7.4% between the 15 s sampling scheme and the 480 s sampling scheme reconstructed with SharpIR. The corresponding deviation for FBP images was 1.6%. R-2 was highest for long time frames, but all R-2 values were above 0.997 in this study.

  • 4.
    Wallstén, Elin
    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.
    Sundström, Torbjörn
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Riklund, Katrine
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Subcentimeter Tumor Lesion Delineation for High-Resolution 18F-FDG PET Images: Optimizing Correction for Partial-Volume Effects.2013In: Journal of Nuclear Medicine Technology, ISSN 0091-4916, E-ISSN 1535-5675, Vol. 41, no 2, p. 85-91Article in journal (Refereed)
    Abstract [en]

    In PET, partial-volume effects cause errors in estimation of size and activity for small objects with radiopharmaceutical uptake. Recent methods for image reconstruction, compared with traditional reconstruction techniques, include algorithms for resolution recovery that result in images with higher resolution and enable quantification of size and activity of smaller objects. The purpose of this study was to evaluate a combination of 2 algorithms for volume delineation and partial-volume correction on uptake volumes smaller than 0.7 mL using image reconstruction algorithms with and without resolution recovery.

    METHODS: Volumes of interests (VOIs) were delineated using a threshold intensity calculated as a weighted sum of tumor and background intensities. These VOIs were used for calculating correction factors by convolving a tumor mask with the system point-spread function. The methods algorithms were evaluated using a phantom constructed from 5 small different-sized balloons filled with (18)F-FDG in background activity. Six different backgrounds were used. Data were acquired using a PET/CT scanner, and the images were reconstructed using 2 iterative algorithms, one of which used a resolution recovery algorithm.

    RESULTS: For the images reconstructed using the resolution recovery algorithm, the method for volume delineation resulted in VOI sizes that were correct within 1 SD for all balloons of a volume of 0.35 mL (equivalent diameter, 8.8 mm) and larger, in all backgrounds. For the images reconstructed without resolution recovery, the VOI sizes were background-dependent and generally less accurate. Correct volume delineations generally led to accurate activity estimates.

    CONCLUSION: The algorithms tested on the phantom developed for this study could, for this PET camera and these reconstruction algorithms, be used for accurate volume delineation and activity quantification of lesions 0.35 mL and larger.

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