Christian Gustafsson

Assessment of dosimetric impact of system specific geometric distortion in an MRI only based radiotherapy workflow for prostate

Dosimetric errors in a magnetic resonance imaging (MRI) only radiotherapy workflow may be caused by system specific geometric distortion from MRI. The aim of this study was to evaluate the impact on planned dose distribution and delineated structures for prostate patients, originating from this distortion. A method was developed, in which computer tomography (CT) images were distorted using the MRI distortion field. The displacement map for an optimized MRI treatment planning sequence was measured using a dedicated phantom in a 3 T MRI system. To simulate the distortion aspects of a synthetic CT (electron density derived from MR images), the displacement map was applied to CT images, referred to as distorted CT images. A volumetric modulated arc prostate treatment plan was applied to the original CT and the distorted CT, creating a reference and a distorted CT dose distribution. By applying the inverse of the displacement map to the distorted CT dose distribution, a dose distribution in the same geometry as the original CT images was created. For 10 prostate cancer patients, the dose difference between the reference dose distribution and inverse distorted CT dose distribution was analyzed in isodose level bins. The mean magnitude of the geometric distortion was 1.97 mm for the radial distance of 200-250 mm from isocenter. The mean percentage dose differences for all isodose level bins, were  ⩽0.02% and the radiotherapy structure mean volume deviations were  <0.2%. The method developed can quantify the dosimetric effects of MRI system specific distortion in a prostate MRI only radiotherapy workflow, separated from dosimetric effects originating from synthetic CT generation. No clinically relevant dose difference or structure deformation was found when 3D distortion correction and high acquisition bandwidth was used. The method could be used for any MRI sequence together with any anatomy of interest.

Registration free automatic identification of gold fiducial markers in MRI target delineation images for prostate radiotherapy

Purpose: The superior soft tissue contrast of magnetic resonance imaging (MRI) compared to computed tomography (CT) has urged the integration of MRI and elimination of CT in radiotherapy treatment (RT) for prostate. An intraprostatic gold fiducial marker (GFM) appears hyperintense on CT. On T2‐weighted (T2w) MRI target delineation images, the GFM appear as a small signal void similar to calcifications and post biopsy fibrosis. It can therefore be difficult to identify the markers without CT. Detectability of GFMs can be improved using additional MR images, which are manually registered to target delineation images. This task requires manual labor, and is associated with interoperator differences and image registration errors. The aim of this work was to develop and evaluate an automatic method for identification of GFMs directly in the target delineation images without the need for image registration. Methods: T2w images, intended for target delineation, and multiecho gradient echo (MEGRE) images intended for GFM identification, were acquired for prostate cancer patients. Signal voids in the target delineation images were identified as GFM candidates. The GFM appeared as round, symmetric, signal void with increasing area for increasing echo time in the MEGRE images. These image features were exploited for automatic identification of GFMs in a MATLAB model using a patient training dataset (n = 20). The model was validated on an independent patient dataset (n = 40). The distances between the identified GFM in the target delineation images and the GFM in CT images were measured. A human observatory study was conducted to validate the use of MEGRE images. Results: The sensitivity, specificity, and accuracy of the automatic method and the observatory study was 84%, 74%, 81% and 98%, 94%, 97%, respectively. The mean absolute difference in the GFM distances for the automatic method and observatory study was 1.28 ± 1.25 mm and 1.14 ± 1.06 mm, respectively. Conclusions: Multiecho gradient echo images were shown to be a feasible and reliable way to perform GFM identification. For clinical practice, visual inspection of the results from the automatic method is needed at the current stage.

Intensity-based dual model method for generation of synthetic CT images from standard T2-weighted MR images – Generalized technique for four different MR scanners

BACKGROUND AND PURPOSE Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2w) MR images of the pelvis. MATERIALS AND METHODS This study developed a generalized dual model HU conversion method to convert standard T2w MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancer patients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors. RESULTS For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16 ± 6 HUs (34 HUs) and -46 ± 56 HUs (181 HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6 ± 0.4% (-1.3%). CONCLUSIONS The study provides a generalized method for sCT creation from standard T2w images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences.

Dose integration and dose rate characteristics of a NiPAM polymer gel MRI dosimeter system

The normoxic polymer gel dosimeter based on N-isopropyl acrylamide (NiPAM) is a promising full 3D-dosimeter with high spatial resolution and near tissue equivalency. NiPAM gel samples were irradiated to different doses using a linear accelerator. The absorbed dose was evaluated using MRI and statistical significance of the analysed data was calculated. The analysis was carried out using an in-house developed software. It was found that the gel dosimeter responded linearly to the absorbed dose. The gel exhibited a dose rate dependence, as well as a dependence on the sequential beam irradiation scheme. A higher dose rate, as well as a higher dose per sequential beam, resulted in a lower dose response.

MR and CT data with multiobserver delineations of organs in the pelvic area—Part of the Gold Atlas project

PURPOSE We describe a public dataset with MR and CT images of patients performed in the same position with both multiobserver and expert consensus delineations of relevant organs in the male pelvic region. The purpose was to provide means for training and validation of segmentation algorithms and methods to convert MR to CT like data, i.e., so called synthetic CT (sCT). ACQUISITION AND VALIDATION METHODS T1- and T2-weighted MR images as well as CT data were collected for 19 patients at three different departments. Five experts delineated nine organs for each patient based on the T2-weighted MR images. An automatic method was used to fuse the delineations. Starting from each fused delineation, a consensus delineation was agreed upon by the five experts for each organ and patient. Segmentation overlap between user delineations with respect to the consensus delineations was measured to describe the spread of the collected data. Finally, an open-source software was used to create deformation vector fields describing the relation between MR and CT images to further increase the usability of the dataset. DATA FORMAT AND USAGE NOTES The dataset has been made publically available to be used for academic purposes, and can be accessed from https://zenodo.org/record/583096. POTENTIAL APPLICATIONS The dataset provides a useful source for training and validation of segmentation algorithms as well as methods to convert MR to CT-like data (sCT). To give some examples: The T2-weighted MR images with their consensus delineations can directly be used as a template in an existing atlas-based segmentation engine; the expert delineations are useful to validate the performance of a segmentation algorithm as they provide a way to measure variability among users which can be compared with the result of an automatic segmentation; and the pairwise deformably registered MR and CT images can be a source for an atlas-based sCT algorithm or for validation of sCT algorithm.

Cone beam CT for QA of synthetic CT in MRI only for prostate patients

Abstract Purpose Magnetic resonance imaging (MRI)‐only radiotherapy is performed without computed tomography (CT). A synthetic CT (sCT) is used for treatment planning. The aim of this study was to develop a clinically feasible quality assurance (QA) procedure for sCT using the kV‐cone beam CT (CBCT), in an MRI‐only workflow for prostate cancer patients. Material and method Three criteria were addressed; stability in Hounsfield Units (HUs), deviations in HUs between the CT and CBCT, and validation of the QA procedure. For the two first criteria, weekly phantom measurements were performed. For the third criteria, sCT, CT, and CBCT for ten patients were used. Treatment plans were created based on the sCT (MriPlannerTM). CT and CBCT images were registered to the sCT. The treatment plan was copied to the CT and CBCT and recalculated. Dose–volume histogram (DVH) metrics were used to evaluate dosimetric differences between the sCT plan and the recalculated CT and CBCT plans. HU distributions in sCT, CT, and CBCT were compared. Well‐defined errors were introduced in the sCT for one patient to evaluate efficacy of the QA procedure. Results The kV‐CBCT system was stable in HU over time (standard deviation <40 HU). Variation in HUs between CT and CBCT was <60 HU. The differences between sCT–CT and sCT–CBCT dose distributions were below or equal to 1.0%. The highest mean dose difference for the CT and CBCT dose distribution was 0.6%. No statistically significant difference was found between total mean dose deviations from recalculated CT and CBCT plans, except for femoral head. Comparing HU distributions, the CBCT appeared to be similar to the CT. All introduced errors were identified by the proposed QA procedure, except all tissue compartments assigned as water. Conclusion The results in this study shows that CBCT can be used as a clinically feasible QA procedure for MRI‐only radiotherapy of prostate cancer patients.

Using C-Arm X-ray images from marker insertion to confirm the gold fiducial marker identification in an MRI-only prostate radiotherapy workflow

Abstract Prostate cancer radiotherapy workflows, solely based on magnetic resonance imaging (MRI), are now in clinical use. In these workflows, intraprostatic gold fiducial markers (GFM) show similar signal behavior as calcifications and bleeding in T2‐weighted MRI‐images. Accurate GFM identification in MRI‐only radiotherapy workflows is therefore a major challenge. C‐arm X‐ray images (CkV‐images), acquired at GFM implantation, could provide GFM position information and be used to confirm correct identification in T2‐weighted MRI‐images. This would require negligible GFM migration between implantation and MRI‐imaging. Marker migration was therefore investigated. The aim of this study was to show the feasibility of using CkV‐images to confirm GFM identification in an MRI‐only prostate radiotherapy workflow. An anterior‐posterior digitally reconstructed radiograph (DRR)‐image and a mirrored posterior‐anterior CkV‐image were acquired two weeks apart for 16 patients in an MRI‐only radiotherapy workflow. The DRR‐image originated from synthetic CT‐images (created from MRI‐images). A common image geometry was defined between the DRR‐ and CkV‐image for each patient. A rigid registration between the GFM center of mass (CoM) coordinates was performed and the distance between each of the GFM in the DRR‐ and registered CkV‐image was calculated. The same methodology was used to assess GFM migration for 31 patients in a CT‐based radiotherapy workflow. The distance calculated was considered a measure of GFM migration. A statistical test was performed to assess any difference between the cohorts. The mean absolute distance difference for the GFM CoM between the DRR‐ and CkV‐image in the MRI‐only cohort was 1.7 ± 1.4 mm. The mean GFM migration was 1.2 ± 0.7 mm. No significant difference between the measured total distances of the two cohorts could be detected (P = 0.37). This demonstrated that, a C‐Arm X‐ray image acquired from the GFM implantation procedure could be used to confirm GFM identification from MRI‐images. GFM migration was present but did not constitute a problem.