Evaluation of Deep Learning Clinical Target Volumes Auto-Contouring for Magnetic Resonance Imaging-Guided Online Adaptive Treatment of Rectal Cancer.

Purpose: Segmentation of clinical target volumes (CTV) on medical images can be time-consuming and is prone to interobserver variation (IOV). This is a problem for online adaptive radiation therapy, where CTV segmentation must be performed every treatment fraction, leading to longer treatment times and logistic challenges. Deep learning (DL)-based auto-contouring has the potential to speed up CTV contouring, but its current clinical use is limited. One reason for this is that it can be time-consuming to verify the accuracy of CTV contours produced using auto-contouring, and there is a risk of bias being introduced. To be accepted by clinicians, auto-contouring must be trustworthy. Therefore, there is a need for a comprehensive commissioning framework when introducing DL-based auto-contouring in clinical practice. We present such a framework and apply it to an in-house developed DL model for auto-contouring of the CTV in rectal cancer patients treated with MRI-guided online adaptive radiation therapy. Methods and Materials: The framework for evaluating DL-based auto-contouring consisted of 3 steps: (1) Quantitative evaluation of the model's performance and comparison with IOV; (2) Expert observations and corrections; and (3) Evaluation of the impact on expected volumetric target coverage. These steps were performed on independent data sets. The framework was applied to an in-house trained nnU-Net model, using the data of 44 rectal cancer patients treated at our institution. Results: The framework established that the model's performance after expert corrections was comparable to IOV, and although the model introduced a bias, this had no relevant impact on clinical practice. Additionally, we found a substantial time gain without reducing quality as determined by volumetric target coverage. Conclusions: Our framework provides a comprehensive evaluation of the performance and clinical usability of target auto-contouring models. Based on the results, we conclude that the model is eligible for clinical use.

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.

Investigating the impact of patient arm position in an MR-linac on liver SBRT treatment plans.

PURPOSE: The superior soft-tissue contrast offered by the integrated magnetic resonance imaging (MRI) of the Unity MR-linac compared to the x-ray-based image guidance on conventional linacs potentially allows for liver stereotactic body radiation therapy (SBRT) without the need for implanted markers or other surrogates. On conventional linacs, liver SBRT patients are typically positioned with their arms above their heads (arms-up) to minimize exposure to healthy tissue. However, the spatial confinement of the MRI-bore and increased treatment delivery times can make the arms-up position straining. Therefore, we assessed the plan quality for MR-linac treatment plans with the patient in the arms-up and in the arms-down position. Additionally, we compared the MR-linac plans with clinically used arms-up treatment plans made for a conventional linac. METHODS: Fifteen consecutively treated patients with oligometastatic liver disease were included in this retrospective study. For each patient, a planning computed tomography (CT) with delineations, a diagnostic MRI, and a 3 × 20 Gy dual-arc volumetric modulated arc therapy (VMAT) plan, which was used to treat the patient in an arms-up position on the conventional linac, were available. For the MR-linac, 15-beam step-and-shoot intensity-modulated radiation therapy (IMRT) plans were created for four patient positioning scenarios: arms-up, mimicking current clinical practice; arms-down, with treatment beams avoiding the arms on the entrance side; arms-through, arms are down but not avoided, and right-arm-up; only the right arm is up and the left arm is avoided on the entrance side. Resulting treatment plans were compared. Bonferroni-corrected two-sided Wilcoxon signed-ranks tests were used to assess statistical significance (P < 0.05). RESULTS: No significant differences were found in gross tumour volume (GTV) coverage (D 2 % , D 50 % , and D 98 % ) or liver sparing (liver-GTV V < 15 Gy ) between the clinical plans and any of the MR-linac plans. The median target conformity [exterior V 40 % /planning target volume (PTV)] was significantly better in the clinical plans (5.8) than in the MR-linac scenarios (arms-down: 6.6, arms-up/right-arm-up: 6.2, arms-through: 6.3). No MR-linac plan violated any additional organ-at-risk (OAR) constraint that was not already violated in the clinical plans. In the arms-down scenario a significantly increased median spinal cord D 1 % (14.5 Gy) was detected compared to the clinical setup (7.2 Gy). For the arms-down (arms-through) scenario, the median left arm D 1 % was 1.5 (2.7) Gy, the median right arm D 1 % was 5.8 (22.7) Gy, and the median right arm V 20 Gy was 0.0 (14.7) cc. These differences were statistically significant. For the right-arm-up scenario, the median left arm D 1 % (2.3 Gy) and V 5 Gy (0.0) were not significantly different compared to the arms-down scenario. CONCLUSIONS: Mimicking the current clinical practice by treating patients in the arms-up/right-arm-up position on the MR-linac leads to plans which are dosimetrically very similar to the conventional linac plans. Treating in the arms-down position is expected to increase patient comfort at the cost of a small reduction in OAR sparing for individual patients. Treating through the arms is not encouraged due to substantial dose deposition in the arms.

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.

Evaluation of plan quality in radiotherapy planning with an MR-linac.

BACKGROUND & PURPOSE: Clinical introduction of magnetic resonance (MR)-guided radiotherapy involves treatment planning while taking into account machine-specific characteristics. Our aim was to investigate the feasibility of high-quality MR-linac treatment planning for an MR-linac and to benchmark MR-linac plan quality (IMRT) against current clinical practice (VMAT). MATERIALS & METHODS: Data of eight rectal and eight prostate cancer patients, who received radiotherapy on a conventional CBCT-integrated linac, were selected. Clinically acquired CTs and associated delineations of target volumes and organs-at-risk (OARs) were used for MR-linac treatment planning in Monaco. To investigate treatment planning software bias 'quasi MR-linac plans' were generated in Pinnacle3 by mimicking MR-linac specific beam characteristics. MR-linac, quasi MR-linac, and clinical plans were compared and differences in target and OAR doses assessed. Differences in plan complexity were determined by the number of segments and monitor units. RESULTS: Compared to clinical plans, MR-linac plans showed a statistically significant decrease in plan homogeneity, an increase in PTV Dmean (prostate: 0.6 Gy; rectum: 0.8 Gy) and D1% (prostate: 1.9 Gy; rectum: 2.0 Gy), and increases in OAR dose. Quasi MR-linac plans were comparable to MR-linac plans with respect to OAR dose and plan homogeneity. For rectal cancer an increase was seen in PTV Dmean (0.12 Gy) and D1% (0.5 Gy) compared to regular MR-linac plans. All created plans were clinically equivalent to current clinical practice. CONCLUSIONS: This study demonstrates the feasibility of creating high-quality MR-linac treatment plans. The results supported the clinical introduction of an MR-linac.