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Quantifying the Effect of 3T Magnetic Resonance Imaging Residual System Distortions and Patient-Induced Susceptibility Distortions on Radiation Therapy 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: 2019-11-04Bibliographically approved
In thesis
1. Quality assurance for magnetic resonance imaging (MRI) in radiotherapy
Open this publication in new window or tab >>Quality assurance for magnetic resonance imaging (MRI) in radiotherapy
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Kvalitetssäkring av magnetisk resonanstomografi (MRI/MRT) inom radioterapi
Abstract [en]

The use of Magnetic Resonance Imaging (MRI) in the radiotherapy (RT) treatment planning workflow is increasing. MRI offers superior soft-tissue contrast compared to Computed Tomography (CT) and therefore improves the accuracy in target volume definitions. There are, however concerns with inherent geometric distortions from system- (gradient nonlinearities and main magnetic field inhomogeneities) and patient-related sources (magnetic susceptibility effect and chemical shift). The lack of clearly defined quality assurance (QA) procedures has also raised questions on the ability of current QA protocols to detect common image quality degradations under radiotherapy settings. To fully implement and take advantage of the benefits of MRI in radiotherapy, these concerns need to be addressed.

In Papers I and II, the dosimetric impact of MR distortions was investigated. Patient CTs (CT) were deformed with MR distortion vector fields (from the residual system distortions after correcting for gradient nonlinearities and patient-induced susceptibility distortions) to create distorted CT (dCT) images. Field parameters from volumetric modulated arc therapy (VMAT) treatment plans initially optimized on dCT data sets were transferred to CT data to compute new treatment plans. Data from 19 prostate and 21 head and neck patients were used for the treatment planning. The dCT and CT treatment plans were compared to determine the impact of distortions on dose distributions. No clinically relevant dose differences between distorted CT and original CT treatment plans were found. Mean dose differences were < 1.0% and < 0.5% at the planning target volume (PTV) for the head and neck, and prostate treatment plans, respectively. 

Strategies to reduce geometric distortions were also evaluated in Papers I and II. Using the vendor-supplied gradient non-linearity correction algorithm reduced overall distortions to less than half of the original value. A high acquisition bandwidth of 488 Hz/pixel (Paper I) and 488 Hz/mm (Paper II) kept the mean geometric distortions at the delineated structures below 1 mm. Furthermore, a patient-specific active shimming method implemented in Paper II significantly reduced the number of voxels with distortion shifts > 2 mm from 15.4% to 2.0%.

B0 maps from patient-induced magnetic field inhomogeneities obtained through direct measurements and by simulations that used MR-generated synthetic CT (sCT) data were compared in Paper III. The validation showed excellent agreement between the simulated and measured B0 maps.

In Paper IV, the ability of current QA methods to detect common MR image quality degradations under radiotherapy settings were investigated. By evaluating key image quality parameters, the QA protocols were found to be sensitive to some of the introduced degradations. However, image quality issues such as those caused by RF coil failures could not be adequately detected.

In conclusion, this work has shown the feasibility of using MRI data for radiotherapy treatment planning as distortions resulted in a dose difference of less than 1% between distorted and undistorted images. The simulation software can be used to produce accurate B0 maps, which could then be used as the basis for the effective correction of patient-induced field inhomogeneity distortions and for the QA verification of sCT data. Furthermore, the analysis of the strengths and weaknesses in current QA tools for MRI in RT contribute to finding better methods to efficiently identify image quality errors.

Place, publisher, year, edition, pages
Umeå: Medical Faculty, Umeå University, 2019. p. 78
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 2057
Keywords
magnetic resonance imaging, MRI, radiotherapy, RT, geometric distortions, magnetic susceptibility, B0 maps, quality assurance
National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
radiation physics
Identifiers
urn:nbn:se:umu:diva-164771 (URN)978-91-7855-130-9 (ISBN)
Public defence
2019-11-29, Hörsal 933, byggnad 3, Norrlands universitetssjukhus, Umeå, 09:00 (English)
Opponent
Supervisors
Funder
Cancerforskningsfonden i Norrland, AMP 18-905
Note

PhD Study of Author partially funded by The Schlumberger Faculty for the Future Foundation (FFTF)

Available from: 2019-11-08 Created: 2019-10-31 Last updated: 2019-11-06Bibliographically approved

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

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