Bjorn Stemkens

Optimizing 4-Dimensional Magnetic Resonance Imaging Data Sampling for Respiratory Motion Analysis of Pancreatic Tumors

PURPOSE To determine the optimum sampling strategy for retrospective reconstruction of 4-dimensional (4D) MR data for nonrigid motion characterization of tumor and organs at risk for radiation therapy purposes. METHODS AND MATERIALS For optimization, we compared 2 surrogate signals (external respiratory bellows and internal MRI navigators) and 2 MR sampling strategies (Cartesian and radial) in terms of image quality and robustness. Using the optimized protocol, 6 pancreatic cancer patients were scanned to calculate the 4D motion. Region of interest analysis was performed to characterize the respiratory-induced motion of the tumor and organs at risk simultaneously. RESULTS The MRI navigator was found to be a more reliable surrogate for pancreatic motion than the respiratory bellows signal. Radial sampling is most benign for undersampling artifacts and intraview motion. Motion characterization revealed interorgan and interpatient variation, as well as heterogeneity within the tumor. CONCLUSIONS A robust 4D-MRI method, based on clinically available protocols, is presented and successfully applied to characterize the abdominal motion in a small number of pancreatic cancer patients.

Image-driven, model-based 3D abdominal motion estimation for MR-guided radiotherapy.

Respiratory motion introduces substantial uncertainties in abdominal radiotherapy for which traditionally large margins are used. The MR-Linac will open up the opportunity to acquire high resolution MR images just prior to radiation and during treatment. However, volumetric MRI time series are not able to characterize 3D tumor and organ-at-risk motion with sufficient temporal resolution. In this study we propose a method to estimate 3D deformation vector fields (DVFs) with high spatial and temporal resolution based on fast 2D imaging and a subject-specific motion model based on respiratory correlated MRI. In a pre-beam phase, a retrospectively sorted 4D-MRI is acquired, from which the motion is parameterized using a principal component analysis. This motion model is used in combination with fast 2D cine-MR images, which are acquired during radiation, to generate full field-of-view 3D DVFs with a temporal resolution of 476 ms. The geometrical accuracies of the input data (4D-MRI and 2D multi-slice acquisitions) and the fitting procedure were determined using an MR-compatible motion phantom and found to be 1.0-1.5 mm on average. The framework was tested on seven healthy volunteers for both the pancreas and the kidney. The calculated motion was independently validated using one of the 2D slices, with an average error of 1.45 mm. The calculated 3D DVFs can be used retrospectively for treatment simulations, plan evaluations, or to determine the accumulated dose for both the tumor and organs-at-risk on a subject-specific basis in MR-guided radiotherapy.

Towards fast online intrafraction replanning for free-breathing stereotactic body radiation therapy with the MR-linac

The hybrid MRI-radiotherapy machines, like the MR-linac (Elekta AB, Stockholm, Sweden) installed at the UMC Utrecht (Utrecht, The Netherlands), will be able to provide real-time patient imaging during treatment. In order to take advantage of the systems capabilities and enable online adaptive treatments, a new generation of software should be developed, ranging from motion estimation to treatment plan adaptation. In this work we present a proof of principle adaptive pipeline designed for high precision stereotactic body radiation therapy (SBRT) suitable for sites affected by respiratory motion, like renal cell carcinoma (RCC). We utilized our research MRL treatment planning system (MRLTP) to simulate a single fraction 25 Gy free-breathing SBRT treatment for RCC by performing inter-beam replanning for two patients and one volunteer. The simulated pipeline included a combination of (pre-beam) 4D-MRI and (online) 2D cine-MR acquisitions. The 4DMRI was used to generate the mid-position reference volume, while the cine-MRI, via an in-house motion model, provided three-dimensional (3D) deformable vector fields (DVFs) describing the anatomical changes during treatment. During the treatment fraction, at an inter-beam interval, the mid-position volume of the patient was updated and the delivered dose was accurately reconstructed on the underlying motion calculated by the model. Fast online replanning, targeting the latest anatomy and incorporating the previously delivered dose was then simulated with MRLTP. The adaptive treatment was compared to a conventional mid-position SBRT plan with a 3 mm planning target volume margin reconstructed on the same motion trace. We demonstrate that our system produced tighter dose distributions and thus spared the healthy tissue, while delivering more dose to the target. The pipeline was able to account for baseline variations/drifts that occurred during treatment ensuring target coverage at the end of the treatment fraction.

4D MR imaging using robust internal respiratory signal.

The purpose of this study is to investigate the feasibility of using internal respiratory (IR) surrogates to sort four-dimensional (4D) magnetic resonance (MR) images. The 4D MR images were constructed by acquiring fast 2D cine MR images sequentially, with each slice scanned for more than one breathing cycle. The 4D volume was then sorted retrospectively using the IR signal. In this study, we propose to use multiple low-frequency components in the Fourier space as well as the anterior body boundary as potential IR surrogates. From these potential IR surrogates, we used a clustering algorithm to identify those that best represented the respiratory pattern to derive the IR signal. A study with healthy volunteers was performed to assess the feasibility of the proposed IR signal. We compared this proposed IR signal with the respiratory signal obtained using respiratory bellows. Overall, 99% of the IR signals matched the bellows signals. The average difference between the end inspiration times in the IR signal and bellows signal was 0.18 s in this cohort of matching signals. For the acquired images corresponding to the other 1% of non-matching signal pairs, the respiratory motion shown in the images was coherent with the respiratory phases determined by the IR signal, but not the bellows signal. This suggested that the IR signal determined by the proposed method could potentially correct the faulty bellows signal. The sorted 4D images showed minimal mismatched artefacts and potential clinical applicability. The proposed IR signal therefore provides a feasible alternative to effectively sort MR images in 4D.

An optimization framework to maximize signal-to-noise ratio in simultaneous multi-slice body imaging

Parallel imaging is essential for the acceleration of abdominal and pelvic 2D multi‐slice imaging, in order to reduce scan time and mitigate motion artifacts. Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration (CAIPIRINHA) accelerated imaging has been shown to increase the signal‐to‐noise ratio (SNR) significantly compared with in‐plane parallel imaging with similar acceleration. We hypothesize that for CAIPIRINHA‐accelerated abdominal imaging the consistency of image quality and SNR is more difficult to achieve due to the subject‐specific coil sensitivity profiles, caused by (1) flexible coil placement; (2) variations in anatomy; and (3) variations in scan coverage along the superior–inferior direction. To test this, a mathematical framework is introduced that calculates the (retained) SNR for in‐plane and simultaneous multi‐slice (SMS)‐accelerated acquisitions. Moreover, this framework was used to optimize the sampling pattern by maximizing the local SNR within a region of interest (ROI) through non‐linear, RF‐induced CAIPIRINHA slice shifts. The framework was evaluated on 14 healthy subjects and the optimized sampling pattern was compared with in‐plane acceleration and CAIPIRINHA acceleration with linear slice shifts, which are primarily used in brain imaging. We demonstrate that the field of view (FOV) in the superior–inferior direction, the coil positioning and the individual anatomy have a large impact on the image SNR (changes up to 50% for varying coil positions and 40% differences between subjects) and image artifacts for simultaneous multi‐slice acceleration. Consequently, sampling patterns have to be optimized for acquisitions employing different FOVs and ideally on an individual basis. Optimization of the sampling pattern, which exploits non‐linear shifts between slices, showed a considerable SNR increase (10–30%) for higher acceleration factors. The framework outlined in this article can be used to optimize sampling patterns for a broad range of accelerated body acquisitions on an individual basis. Copyright

Effect of intra-fraction motion on the accumulated dose for free-breathing MR-guided stereotactic body radiation therapy of renal-cell carcinoma

Stereotactic body radiation therapy (SBRT) has shown great promise in increasing local control rates for renal-cell carcinoma (RCC). Characterized by steep dose gradients and high fraction doses, these hypo-fractionated treatments are, however, prone to dosimetric errors as a result of variations in intra-fraction respiratory-induced motion, such as drifts and amplitude alterations. This may lead to significant variations in the deposited dose. This study aims to develop a method for calculating the accumulated dose for MRI-guided SBRT of RCC in the presence of intra-fraction respiratory variations and determine the effect of such variations on the deposited dose. For this, RCC SBRT treatments were simulated while the underlying anatomy was moving, based on motion information from three motion models with increasing complexity: (1) STATIC, in which static anatomy was assumed, (2) AVG-RESP, in which 4D-MRI phase-volumes were time-weighted, and (3) PCA, a method that generates 3D volumes with sufficient spatio-temporal resolution to capture respiration and intra-fraction variations. Five RCC patients and two volunteers were included and treatments delivery was simulated, using motion derived from subject-specific MR imaging. Motion was most accurately estimated using the PCA method with root-mean-squared errors of 2.7, 2.4, 1.0 mm for STATIC, AVG-RESP and PCA, respectively. The heterogeneous patient group demonstrated relatively large dosimetric differences between the STATIC and AVG-RESP, and the PCA reconstructed dose maps, with hotspots up to [Formula: see text] of the D99 and an underdosed GTV in three out of the five patients. This shows the potential importance of including intra-fraction motion variations in dose calculations.

Intrafraction motion quantification and planning target volume margin determination of head-and-neck tumors using cine magnetic resonance imaging

PURPOSE To quantify intrafractional motion to determine population-based radiotherapy treatment margins for head-and-neck tumors. METHODS Cine MR imaging was performed in 100 patients with head-and-neck cancer on a 3T scanner in a radiotherapy treatment setup. MR images were analyzed using deformable image registration (optical flow algorithm) and changes in tumor contour position were used to calculate the tumor motion. The tumor motion was used together with patient setup errors (450 patients) to calculate population-based PTV margins. RESULTS Tumor motion was quantified in 84 patients (12/43/29 nasopharynx/oropharynx/larynx, 16 excluded). The mean maximum (95th percentile) tumor motion (swallowing excluded) was: 2.3 mm in superior, 2.4 mm in inferior, 1.8 mm in anterior and 1.7 mm in posterior direction. PTV margins were: 2.8 mm isotropic for nasopharyngeal tumors, 3.2 mm isotropic for oropharyngeal tumors and 4.3 mm in inferior-superior and 3.2 mm in anterior-posterior for laryngeal tumors, for our institution. CONCLUSIONS Intrafractional head-and-neck tumor motion was quantified and population-based PTV margins were calculated. Although the average tumor motion was small (95th percentile motion <3.0 mm), tumor motion varied considerably between patients (0.1-12.0 mm). The intrafraction motion expanded the CTV-to-PTV with 1.7 mm for laryngeal tumors, 0.6 mm for oropharyngeal tumors and 0.2 mm for nasopharyngeal tumors.

Adaptive bulk motion exclusion for improved robustness of abdominal magnetic resonance imaging

Non‐Cartesian magnetic resonance imaging (MRI) sequences have shown great promise for abdominal examination during free breathing, but break down in the presence of bulk patient motion (i.e. voluntary or involuntary patient movement resulting in translation, rotation or elastic deformations of the body). This work describes a data‐consistency‐driven image stabilization technique that detects and excludes bulk movements during data acquisition. Bulk motion is identified from changes in the signal intensity distribution across different elements of a multi‐channel receive coil array. A short free induction decay signal is acquired after excitation and used as a measure to determine alterations in the load distribution. The technique has been implemented on a clinical MR scanner and evaluated in the abdomen. Six volunteers were scanned and two radiologists scored the reconstructions. To show the applicability to other body areas, additional neck and knee images were acquired. Data corrupted by bulk motion were successfully detected and excluded from image reconstruction. An overall increase in image sharpness and reduction of streaking and shine‐through artifacts were seen in the volunteer study, as well as in the neck and knee scans. The proposed technique enables automatic real‐time detection and exclusion of bulk motion during MR examinations without user interaction. It may help to improve the reliability of pediatric MRI examinations without the use of sedation.

SU-D-207A-07: The Effects of Inter-Cycle Respiratory Motion Variation On Dose Accumulation in Single Fraction MR-Guided SBRT Treatment of Renal Cell Carcinoma.

PURPOSE To assess the dose deposition in simulated single-fraction MR-Linac treatments of renal cell carcinoma, when inter-cycle respiratory motion variation is taken into account using online MRI. METHODS Three motion characterization methods, with increasing complexity, were compared to evaluate the effect of inter-cycle motion variation and drifts on the accumulated dose for an SBRT kidney MR-Linac treatment: 1) STATIC, in which static anatomy was assumed, 2) AVG-RESP, in which 4D-MRI phase-volumes were time-weighted, based on the respiratory phase and 3) PCA, in which 3D volumes were generated using a PCA-model, enabling the detection of inter-cycle variations and drifts. An experimental ITV-based kidney treatment was simulated in a 1.5T magnetic field on three volunteer datasets. For each volunteer a retrospectively sorted 4D-MRI (ten respiratory phases) and fast 2D cine-MR images (temporal resolution = 476ms) were acquired to simulate MR-imaging during radiation. For each method, the high spatio-temporal resolution 3D volumes were non-rigidly registered to obtain deformation vector fields (DVFs). Using the DVFs, pseudo-CTs (generated from the 4D-MRI) were deformed and the dose was accumulated for the entire treatment. The accuracies of all methods were independently determined using an additional, orthogonal 2D-MRI slice. RESULTS Motion was most accurately estimated using the PCA method, which correctly estimated drifts and inter-cycle variations (RMSE=3.2, 2.2, 1.1mm on average for STATIC, AVG-RESP and PCA, compared to the 2DMRI slice). Dose-volume parameters on the ITV showed moderate changes (D99=35.2, 32.5, 33.8Gy for STATIC, AVG-RESP and PCA). AVG-RESP showed distinct hot/cold spots outside the ITV margin, which were more distributed for the PCA scenario, since inter-cycle variations were not modeled by the AVG-RESP method. CONCLUSION Dose differences were observed when inter-cycle variations were taken into account. The increased inter-cycle randomness in motion as captured by the PCA model mitigates the local (erroneous) hotspots estimated by the AVG-RESP method.

WE-G-BRD-01: A Data-Driven 4D-MRI Motion Model to Estimate Full Field-Of-View Abdominal Motion From 2D Image Navigators During MR-Linac Treatment

Purpose: To estimate full field-of-view abdominal respiratory motion from fast 2D image navigators using a 4D-MRI based motion model. This will allow for radiation dose accumulation mapping during MR-Linac treatment. Methods: Experiments were conducted on a Philips Ingenia 1.5T MRI. First, a retrospectively ordered 4D-MRI was constructed using 3D transient-bSSFP with radial in-plane sampling. Motion fields were calculated through 3D non-rigid registration. From these motion fields a PCA-based abdominal motion model was constructed and used to warp a 3D reference volume to fast 2D cine-MR image navigators that can be used for real-time tracking. To test this procedure, a time-series consisting of two interleaved orthogonal slices (sagittal and coronal), positioned on the pancreas or kidneys, were acquired for 1m38s (dynamic scan-time=0.196ms), during normal, shallow, or deep breathing. The coronal slices were used to update the optimal weights for the first two PCA components, in order to warp the 3D reference image and construct a dynamic 4D-MRI time-series. The interleaved sagittal slices served as an independent measure to test the model’s accuracy and fit. Spatial maps of the root-mean-squared error (RMSE) and histograms of the motion differences within the pancreas and kidneys were used to evaluate the method. Results: Cranio-caudal motion was accurately calculated within the pancreas using the model for normal and shallow breathing with an RMSE of 1.6mm and 1.5mm and a histogram median and standard deviation below 0.2 and 1.7mm, respectively. For deep-breathing an underestimation of the inhale amplitude was observed (RMSE=4.1mm). Respiratory-induced antero-posterior and lateral motion were correctly mapped (RMSE=0.6/0.5mm). Kidney motion demonstrated good motion estimation with RMSE-values of 0.95 and 2.4mm for the right and left kidney, respectively. Conclusion: We have demonstrated a method that can calculate dynamic 3D abdominal motion in a large volume, while acquiring real-time cine-MR images for MR-guided radiotherapy.