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Magnetic resonance imaging (MRI) offers high soft-tissue contrast compared to computed tomography (CT). This contrast is helpful in many cases, not least for delineating tumours for radiotherapy treatment, and has led to increasing use in radiotherapy treatment planning (RTP).

When RTP is based on CT images, the treatment planning system can get the approximate electron density of the tissues from the electron density equivalent information that constitutes the CT images. This information is needed to calculate the dose to the patient from radiotherapy. Therefore, for an MR-only workflow, the MRI image must be transformed into information that can yield electron density information. The predominant way is to convert the MRI images into CT-like images, also known as substitute CT (sCT).

Positron emission tomography (PET) imaging can benefit from being combined with anatomical imaging, and the PET/CT hybrid machine is well established. The soft tissue contrast properties of the MRI images are also valuable for a PET/MRI hybrid system. However, it also adds the option for simultaneous acquisition of PET and anatomical (MRI) images which is not feasible with CT images for a PET/CT system. However, the PET/MRI combination is more technically challenging. While most of the concerns have been solved or mitigated, and PET/MRI systems have been commercially available for some years, there are still outstanding issues. The attenuation maps used in the reconstruction of PET acquisitions are one of the concerns that have yet to be solved entirely. These attenuation maps in the PET/MRI systems are approximations where, e.g., bone is not fully accounted for in all parts of the body.

The MRI images suffer from geometric distortions dependent on the MRI scanner as well as the imaged patient itself. These distortions can affect the sCT conversion for RTP and the attenuation maps for PET reconstruction.

This thesis aimed to investigate the size of the geometric MRI distortions for different settings on the MRI scanner and their effect on the resulting RTP and reconstructed PET images. Such information can aid in optimising the MRI imaging for different purposes. It can also give some information needed to determine tests to run in a quality assurance (QA) regime.

In Paper I, we studied the machine-dependent MRI gradient-field nonlinearity distortions and their effect on PET reconstruction. We simulated different levels of incomplete corrections for gradient-field nonlinearities in CT images from PET/CT acquisitions. The resulting distorted images were then used for rerunning the reconstruction of PET data, and the effect on reconstructed standardised uptake value (SUV) was studied. We found that residual gradient-field nonlinearity dependent geometrical distortions of ±2.3 mm at 15 cm radius from the scanner isocenter lead to SUV quantification errors below 5%. This is also below the test-retest variability caused by instrumentation and intra-patient factors for PET/CT systems.

In Paper II, we developed a method for simulating the patient-induced susceptibility effect based on CT images. The method consisted of converting the CT images to magnetic susceptibility maps. These magnetic susceptibility maps were then used in the simulation by calculating the local shifts in the main magnetic field (B0). From these local shifts in B0, a displacement map was calculated, and this was, in turn, applied to the original CT images. The simulation was validated through comparisons between the simulation and analytical results for both a homogeneous sphere and a homogeneous cylinder. This method was tested on a set of eight prostate cancer patients. We found that setting the frequency encoding bandwidth to a minimum of twice the water-fat shift would keep the maximum distortion from the patient-induced susceptibility effect below 1 pixel. However, the required frequency encoding bandwidth was shown to be dependent on the imaged area, and lower bandwidth could, e.g., be used for the pelvic area.

The simulation method from Paper II was then used in Paper III, where we investigated the dosimetric impact of residual MRI system distortions, patient-induced susceptibility effects and patient-specific shimming. The latter was simulated using an in-house Matlab algorithm. The residual system distortions were determined using phantom measurements. These distortions were then combined with a simulated patient-induced susceptibility effect and patient-specific shimming. The combined distortions and patient-specific shimming were then applied to patient CT images. The distorted patient images were then used for RTP, and the resulting treatment plan was transferred to the original patient CT datasets and recalculated. This allowed for isolating the effect of the applied distortions on the dose distribution. We concluded that the dosimetric impact of MRI distortions within the target volume and nearby organs at risk is small for high bandwidth spin echo sequences. We also saw a worsening in field variations for the user-defined region ofinterest shimming.

Paper IV presented a proof of concept for patient-specific QA of sCTs and attenuation maps. In this study, we compared measured B0-maps with ones simulated using Paper II’s method. The simulations were based on sCT images from MRI acquisitions from the same imaging session as the measured B0-maps. This method shows potential for identifying errors or problematic areas of sCTs and attenuation maps. It should also be feasible to make the method fast enough to use while the patient is still in the scanner so that images could be retaken without having to recall thepatient if a problem is detected.

This work has contributed to the knowledge and methods needed for the necessary considerations for optimisation and setting up a QA protocol aimed at PET/MRI and MR-only radiotherapy.

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.

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%.

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.

Purpose: Attenuation correction is a requirement for quantification of the activity distribution in PET. The need to base attenuation correction on MRI instead of CT has arisen with the introduction of integrated PET/MRI systems. The aim was to describe the effect of residual gradient field nonlinearity distortions on PET attenuation correction.

Methods: MRI distortions caused by gradient field nonlinearity were simulated in CT images used for attenuation correction in PET reconstructions. The simulations yielded radial distortion of up to  at 15 cm from the scanner isocentre for distortion corrected images. The mean radial distortion of uncorrected images were 6.3 mm at the same distance. Reconstructions of PET data were performed using the distortion corrected images as well as the images where no correction had been applied.

Results: The mean relative difference in reconstructed PET uptake intensity due to incomplete distortion correction was less than ±5%. The magnitude of this difference varied between patients and the size of the distortions remaining after distortion correction.

Conclusions: Radial distortions of 2 mm at 15 cm radius from the scanner isocentre lead to PET attenuation correction errors smaller than 5%. Keeping the gradient field nonlinearity distortions below this limit can be a reasonable goal for MRI systems used for attenuation correction in PET for quantification purposes. A higher geometrical accuracy may, however, be warranted for quantification of peripheral lesions. These distortions can, e.g., be controlled at acceptance testing and subsequent quality assurance intervals.

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.

Background/Introduction: In October 2014, Västerbotten County (VLL), Sweden, installed Sectra DoseTrack1 for radiation exposure monitoring in radiology. A versatile and robust IT-solution for exposure monitoring to assist with follow-up of the processes of justification and optimization had been discussed in multidisciplinary X-ray modality specific forums prior to the procurement.

Description of activity and work performed: The installation of Sectra DoseTrack is fairly straightforward from the user end, involving the configuration of sending RDSR and MPPS metadata from an X-ray unit to be connected to the service. During the installation process some assistance from certified service engineers is required due to restrictions in X-ray equipment software.

Conclusion and Recommendations: VLL has used the Sectra DoseTrack radiation exposure monitoring IT-solution since October 2014. Since then, 34 different X-ray units have been connected to the service and DICOM metadata associated with approximately 170 000 examinations and interventional procedures have been recorded. Sectra DoseTrack offers a robust infrastructure for collecting DICOM metadata and presenting macroscopic information on radiation exposure levels, which may be used to improve the processes of justification and optimization for healthcare providers.