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Quantifying the effect of 3T MRI residual system and patient-induced susceptibility distortions on radiotherapy treatment planning for prostate cancer
Umeå University, Faculty of Medicine, Department of Radiation Sciences.
Umeå University, Faculty of Medicine, Department of Radiation Sciences.
Umeå University, Faculty of Medicine, Department of Radiation Sciences.
Umeå University, Faculty of Medicine, Department of Radiation Sciences.
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2018 (English)In: International Journal of Radiation Oncology, Biology, Physics, ISSN 0360-3016, E-ISSN 1879-355X, Vol. 100, no 2, p. 317-324Article in journal (Refereed) Published
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%.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 100, no 2, p. 317-324
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:umu:diva-142319DOI: 10.1016/j.ijrobp.2017.10.021ISI: 000423097500011PubMedID: 29229326OAI: oai:DiVA.org:umu-142319DiVA, id: diva2:1160459
Available from: 2017-11-27 Created: 2017-11-27 Last updated: 2018-03-05Bibliographically approved

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Adjeiwaah, MaryBylund, MikaelLundman, Josef A.Thellenberg Karlsson, CamillaJonsson, Joakim H.Nyholm, Tufve
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