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  • 1.
    Adjeiwaah, Mary
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Bylund, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Lundman, Josef A.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Söderström, Karin
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Zackrisson, Björn
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Jonsson, Joakim H.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers2019In: International Journal of Radiation Oncology, Biology, Physics, ISSN 0360-3016, E-ISSN 1879-355X, Vol. 103, no 4, p. 994-1003Article in journal (Refereed)
    Abstract [en]

    Purpose: To evaluate the effect of magnetic resonance (MR) imaging (MRI) geometric distortions on head and neck radiation therapy treatment planning (RTP) for an MRI-only RTP. We also assessed the potential benefits of patient-specific shimming to reduce the magnitude of MR distortions for a 3-T scanner.

    Methods and Materials: Using an in-house Matlab algorithm, shimming within entire imaging volumes and user-defined regions of interest were simulated. We deformed 21 patient computed tomography (CT) images with MR distortion fields (gradient nonlinearity and patient-induced susceptibility effects) to create distorted CT (dCT) images using bandwidths of 122 and 488 Hz/mm at 3 T. Field parameters from volumetric modulated arc therapy plans initially optimized on dCT data sets were transferred to CT data to compute a new plan. Both plans were compared to determine the impact of distortions on dose distributions.

    Results: Shimming across entire patient volumes decreased the percentage of voxels with distortions of more than 2 mm from 15.4% to 2.0%. Using the user-defined region of interest (ROI) shimming strategy, (here the Planning target volume (PTV) was the chosen ROI volume) led to increased geometric for volumes outside the PTV, as such voxels within the spinal cord with geometric shifts above 2 mm increased from 11.5% to 32.3%. The worst phantom-measured residual system distortions after 3-dimensional gradient nonlinearity correction within a radial distance of 200 mm from the isocenter was 2.17 mm. For all patients, voxels with distortion shifts of more than 2 mm resulting from patient-induced susceptibility effects were 15.4% and 0.0% using bandwidths of 122 Hz/mm and 488 Hz/mm at 3 T. Dose differences between dCT and CT treatment plans in D-50 at the planning target volume were 0.4% +/- 0.6% and 0.3% +/- 0.5% at 122 and 488 Hz/mm, respectively.

    Conclusions: The overall effect of MRI geometric distortions on data used for RTP was minimal. Shimming over entire imaging volumes decreased distortions, but user-defined subvolume shimming introduced significant errors in nearby organs and should probably be avoided.

  • 2.
    Adjeiwaah, Mary
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Bylund, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Lundman, Josef A.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Thellenberg Karlsson, Camilla
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Jonsson, Joakim H.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Medical Radiation Physics, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Quantifying the effect of 3T MRI residual system and patient-induced susceptibility distortions on radiotherapy treatment planning for prostate cancer2018In: International Journal of Radiation Oncology, Biology, Physics, ISSN 0360-3016, E-ISSN 1879-355X, Vol. 100, no 2, p. 317-324Article in journal (Refereed)
    Abstract [en]

    Purpose: To investigate the effect of magnetic resonance system- and patient-induced susceptibility distortions from a 3T scanner on dose distributions for prostate cancers.

    Methods and Materials: Combined displacement fields from the residual system and patient-induced susceptibility distortions were used to distort 17 prostate patient CT images. VMAT dose plans were initially optimized on distorted CT images and the plan parameters transferred to the original patient CT images to calculate a new dose distribution.

    Results: Maximum residual mean distortions of 3.19 mm at a radial distance of 25 cm and maximum mean patient-induced susceptibility shifts of 5.8 mm were found using the lowest bandwidth of 122 Hz per pixel. There was a dose difference of <0.5% between distorted and undistorted treatment plans. The 90% confidence intervals of the mean difference between the dCT and CT treatment plans were all within an equivalence interval of (−0.5, 0.5) for all investigated plan quality measures.

    Conclusions: Patient-induced susceptibility distortions at high field strengths in closed bore magnetic resonance scanners are larger than residual system distortions after using vendor-supplied 3-dimensional correction for the delineated regions studied. However, errors in dose due to disturbed patient outline and shifts caused by patient-induced susceptibility effects are below 0.5%.

  • 3.
    Bylund, Mikael
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Jonsson, Joakim
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Lundman, Josef
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Brynolfsson, Patrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Löfstedt, Tommy
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Using deep learning to generate synthetic CTs for radiotherapy treatment planning2018In: Radiotherapy and Oncology, ISSN 0167-8140, E-ISSN 1879-0887, Vol. 127, p. S283-S283Article in journal (Other academic)
  • 4.
    Lundman, Josef Axel
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Bylund, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Thellenberg Karlsson, Camilla
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Patient-induced susceptibility effects simulation in magnetic resonance imaging2017In: Physics and Imaging in Radiation Oncology, ISSN 2405-6316, Vol. 1, p. 41-45Article in journal (Refereed)
    Abstract [en]

    Background and purpose A fundamental requirement for safe use of magnetic resonance imaging (MRI) in radiotherapy is geometrical accuracy. One factor that can introduce geometrical distortion is patient-induced susceptibility effects. This work aims at developing a method for simulating these distortions. The specific goal being to help objectively identifying a balanced acquisition bandwidth, keeping these distortions within acceptable limits for radiotherapy.

    Materials and methods A simulation algorithm was implemented in Medical Interactive Creative Environment (MICE). The algorithm was validated by comparison between simulations and analytical solutions for a cylinder and a sphere. Simulations were performed for four body regions; neck, lungs, thorax with the lungs excluded, and the pelvic region. This was done using digital phantoms created from patient CT images, after converting the CT Hounsfield units to magnetic susceptibility values through interpolation between known values.

    Results The simulations showed good agreement with analytical solutions, with only small discrepancies due to pixelation of the phantoms. The calculated distortions in digital phantoms based on patient CT data showed maximal 95th percentile distortions of 39%, 32%, 28%, and 25% of the fat-water shift for the neck, lungs, thorax with the lungs excluded, and pelvic region, respectively.

    Conclusions The presented results show the expected pixel distortions for various body parts, and how they scale with bandwidth and field strength. This information can be used to determine which bandwidth is required to keep the patient-induced susceptibility distortions within an acceptable range for a given field strength.

  • 5. Wiesinger, Florian
    et al.
    Bylund, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Yang, Jaewon
    Kaushik, Sandeep
    Shanbhag, Dattesh
    Ahn, Sangtae
    Jonsson, Joakim
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Lundman, Josef
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Hope, Thomas
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Uppsala University, Uppsala, Sweden.
    Larson, Peder
    Cozzini, Cristina
    Zero TE-based pseudo-CT image conversion in the head and its application in PET/MR attenuation correction and MR-guided radiation therapy planning2018In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 80, no 4, p. 1440-1451Article in journal (Refereed)
    Abstract [en]

    Purpose: To describe a method for converting Zero TE (ZTE) MR images into Xray attenuation information in the form of pseudo-CT images and demonstrate its performance for (1) attenuation correction (AC) in PET/MR and (2) dose planning in MR-guided radiation therapy planning (RTP).

    Methods: Proton density-weighted ZTE images were acquired as input for MRbased pseudo-CT conversion, providing (1) efficient capture of short-lived bone signals, (2) flat soft-tissue contrast, and (3) fast and robust 3D MR imaging. After bias correction and normalization, the images were segmented into bone, soft-tissue, and air by means of thresholding and morphological refinements. Fixed Hounsfield replacement values were assigned for air (-1000 HU) and soft-tissue (142 HU), whereas continuous linear mapping was used for bone.

    Results: The obtained ZTE-derived pseudo-CT images accurately resembled the true CT images (i. e., Dice coefficient for bone overlap of 0.73 +/- 0.08 and mean absolute error of 123 +/- 25 HU evaluated over the whole head, including errors from residual registration mismatches in the neck and mouth regions). The linear bone mapping accounted for bone density variations. Averaged across five patients, ZTE-based AC demonstrated a PET error of -0.04 +/- 1.68% relative to CT-based AC. Similarly, for RTP assessed in eight patients, the absolute dose difference over the target volume was found to be 0.23 +/- 0.42%.

    Conclusion: The described method enables MR to pseudo-CT image conversion for the head in an accurate, robust, and fast manner without relying on anatomical prior knowledge. Potential applications include PET/MR-AC, and MR-guided RTP.

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