Validation of a 4D-MRI guided liver stereotactic body radiation therapy strategy for implementation on the MR-linac.

Purpose. Accurate tumor localization for image-guided liver stereotactic body radiation therapy (SBRT) is challenging due to respiratory motion and poor tumor visibility on conventional x-ray based images. Novel integrated MRI and radiotherapy systems enable direct in-room tumor visualization, potentially increasing treatment accuracy. As these systems currently do not provide a 4D image-guided radiotherapy strategy, we developed a 4D-MRI guided liver SBRT workflow and validated all steps for implementation on the Unity MR-linac.Materials and Methods. The proposed workflow consists of five steps: (1) acquisition of a daily 4D-MRI scan, (2) 4D-MRI to mid-position planning-CT rigid tumor registration, (3) calculation of daily tumor midP misalignment, (4) plan adaptation using adapt-to-position (ATP) with segment-weights optimization and (5) adapted plan delivery. The workflow was first validated in a motion phantom, performing regular motion at different baselines (±5 to ±10 mm) and patient-derived respiratory signals with varying degrees of irregularity. 4D-MRI derived respiratory signals and 4D-MRI to planning CT registrations were compared to the phantom input, and gamma and dose-area-histogram analyses were performed on the delivered dose distributions on film. Additionally, 4D-MRI to CT registration performance was evaluated in patient images using the full-circle method (transitivity analysis). Plan adaption was further analyzedin-silicoby creating adapted treatment plans for 15 patients with oligometastatic liver disease.Results. Phantom trajectories could be reliably extracted from 4D-MRI scans and 4D-MRI to CT registration showed submillimeter accuracy. The DAH-analysis demonstrated excellent coverage of the dose evaluation structures GTV and GTVTD. The median daily rigid 4D-MRI to midP-CT registration precision in patient images was <2 mm. The ATP strategy restored the target dose without increased exposure to the OARs and plan quality was independent from 3D shift distance in the range of 1-26 mm.Conclusions. The proposed 4D-MRI guided strategy showed excellent performance in all workflow tests in preparation of the clinical introduction on the Unity MR-linac.

Correcting geometric image distortions in slice-based 4D-MRI on the MR-linac.

PURPOSE: The importance of four-dimensional-magnetic resonance imaging (4D-MRI) is increasing in guiding online plan adaptation in thoracic and abdominal radiotherapy. Many 4D-MRI sequences are based on multislice two-dimensional (2D) acquisitions which provide contrast flexibility. Intrinsic to MRI, however, are machine- and subject-related geometric image distortions. Full correction of slice-based 4D-MRIs acquired on the Unity MR-linac (Elekta AB, Stockholm, Sweden) is challenging, since through-plane corrections are currently not available for 2D sequences. In this study, we implement a full three-dimensional 3D correction and quantify the geometric and dosimetric effects of machine-related (residual) geometric image distortions. METHODS: A commercial three-dimensional (3D) geometric QA phantom (Philips, Best, the Netherlands) was used to quantify the effect of gradient nonlinearity (GNL) and static-field inhomogeneity (B0I) on geometric accuracy. Additionally, the effectiveness of 2D (in-plane, machine-generic), 3D (machine-generic), and in-house developed 3D + (machine-specific) corrections was investigated. Corrections were based on deformable vector fields derived from spherical harmonics coefficients. Three patients with oligometastases in the liver were scanned with axial 4D-MRIs on our MR-linac (total: 10 imaging sessions). For each patient, a step-and-shoot IMRT plan (3 × 20 Gy) was created based on the simulation mid-position (midP)-CT. The 4D-MRIs were then warped into a daily midP-MRI and geometrically corrected. Next, the treatment plan was adapted according to the position offset of the tumor between midP-CT and the 3D-corrected midP-MRIs. The midP-CT was also deformably registered to the daily midP-MRIs (different corrections applied) to quantify the dosimetric effects of (residual) geometric image distortions. RESULTS: Using phantom data, median GNL distortions were 0.58 mm (no correction), 0.42-0.48 mm (2D), 0.34 mm (3D), and 0.34 mm (3D + ), measured over a diameter of spherical volume (DSV) of 200 mm. Median B0I distortions were 0.09 mm for the same DSV. For DSVs up to 500 mm, through-plane corrections are necessary to keep the median residual GNL distortion below 1 mm. 3D and 3D + corrections agreed within 0.15 mm. 2D-corrected images featured uncorrected through-plane distortions of up to 21.11 mm at a distance of 20-25 cm from the machine's isocenter. Based on the 4D-MRI patient scans, the average external body contour distortions were 3.1 mm (uncorrected) and 1.2 mm (2D-corrected), with maximum local distortions of 9.5 mm in the uncorrected images. No (residual) distortions were visible for the metastases, which were all located within 10 cm of the machine's isocenter. The interquartile range (IQR) of dose differences between planned and daily dose caused by variable patient setup, patient anatomy, and online plan adaptation was 1.37 Gy/Fx for the PTV D95%. When comparing dose on 3D-corrected with uncorrected (2D-corrected) images, the IQR was 0.61 (0.31) Gy/Fx. CONCLUSIONS: GNL is the main machine-related source of image distortions on the Unity MR-linac. For slice-based 4D-MRI, a full 3D correction can be applied after respiratory sorting to maximize spatial fidelity. The machine-specific 3D + correction did not substantially reduce residual geometric distortions compared to the machine-generic 3D correction for our MR-linac. In our patients, dosimetric variations in the target not related to geometric distortions were larger than those caused by geometric distortions.

Retrospective self-sorted 4D-MRI for the liver.

PURPOSE: Daily MRI-guidance for liver radiotherapy is becoming possible on an MR-Linac. The purpose of this study was to develop a 4D-MRI strategy using an image-based respiratory signal with an acquisition-reconstruction time <5 min, providing T2-weighting for non-contrast enhanced tumor visibility. MATERIALS AND METHODS: Images were acquired using an axial multi-slice 2D Turbo Spin Echo (TSE) sequence, repeated a variable number of times (dynamics). A self-sorting signal (SsS) was retrieved from the data by computing correlation coefficients between all acquired slices. Images were sorted into 10 phases and missing data were interpolated. The method was validated in a phantom and 10 healthy volunteers. The SsS, image quality (SSIM index: structural similarity index) and quantified liver motion were assessed as a function of the number of dynamics. Tumor visibility was demonstrated in two patients with liver metastasis on the Elekta Unity MR-Linac. RESULTS: SsS was in good agreement with the reference navigator signal. Missing data increased from 0.4 ±â€¯0.6% to 37.1 ±â€¯6.6% for 60 to 10 dynamics. The SSIM index for the interpolated slices was ∼0.6. The RMSD of quantified motion was <1 mm in phantom experiments and in volunteers <1 mm for >10 dynamics. CONCLUSION: For 30 dynamics, acquisition-reconstruction time was <5 min and showed good performance in the validation experiments. The tumor was clearly visible in the patient images.

An MRI-based mid-ventilation approach for radiotherapy of the liver.

MRI is increasingly being used in radiotherapy of the liver. The purpose of this study was to develop and validate a strategy to acquire MR images for treatment planning and image guidance in the presence of respiratory motion. By interleaving two navigator triggered MRI sequences, a fast but low-resolution image in mid-ventilation (midV) and a high-resolution image in exhale were acquired efficiently. Deformable registration was applied to map the exhale image to the midV anatomy. Cine-MRI scans were acquired for motion quantification. The method was validated with a motion phantom, 10 volunteers and 1 patient with a liver tumor. The time-weighted mean position of a local structure in a cine-scan was defined as the midV-position ground truth and used to determine the accuracy of the midV-triggering method. Deformable registration accuracy was validated using the SIFT algorithm. Acquisition time of the midV/exhale-scan was 3-5min. The accuracy of the midV-position was ⩽0.5±0.5mm for phantom motion and ⩽0.9±1.2mm for the volunteers. Mean residuals after deformable registration were ⩽0.2±1.8mm. The accuracy and reproducibility of the method are within inter- and intra-fraction liver position variability (Case et al., 2009) and could in the future be incorporated in a conventional liver radiotherapy or MR-linac workflow.