Online adaptive MR-guided radiotherapy: Conformity of contour adaptation for prostate cancer, rectal cancer and lymph node oligometastases among radiation therapists and radiation oncologists.

Background and purpose: Online adaptive MR-guided treatment planning workflows facilitate daily contour adaptation to the actual anatomy. Allocating contour adaptation to radiation therapists (RTTs) instead of radiation oncologists (ROs) might allow for increasing workflow efficiency. This study investigates conformity of adapted target contours provided by dedicated RTTs and ROs. Materials and methods: In a simulated online procedure, 6 RTTs and 6 ROs recontoured targets and organs at risk (OAR) in prostate cancer (n = 2), rectal cancer (n = 2) and lymph node-oligometastases (n = 2) cases. RTTs gained contouring competence beforehand by following a specific in-house training program. For all target contours and the reference delineations volumetric differences were determined and Dice similarity coefficient (DSC), conformity index (CI) and generalized CI were calculated. Delineation time and -confidence were registered for targets and OAR. Impact of contour adaptation on treatment plan quality was investigated. Results: Delineation conformity was generally high with DSC, CI and generalized CI values in the range of 0.81-0.94, 0.87-0.95 and 0.63-0.85 for prostate cancer, rectal cancer and LN-oligometastasis, respectively. Target volumes were comparable for both, RTTs and ROs. Time needed and confidence in contour adaptation was comparable as well. Treatment plans derived with adapted contours did not violate dose volume constrains as used in clinical routine. Conclusion: After tumor site specific training, daily contour adaptations as needed in adaptive online radiotherapy workflows can be accurately performed by RTTs. Conformity of the derived contours is high and comparable to contours as provided by ROs.

Impact of a vacuum cushion on intrafraction motion during online adaptive MR-guided SBRT for pelvic and para-aortic lymph node oligometastases.

BACKGROUND AND PURPOSE: Vacuum cushion immobilization is commonly used during stereotactic body radiotherapy (SBRT) to reduce intrafraction motion. We investigated target and bony anatomy intrafraction motion (translations and rotations) during online adaptive SBRT on an MR-linac for pelvic/para-aortic lymph node metastases with and without vacuum cushion. MATERIALS AND METHODS: Thirty-nine patients underwent 5x7 Gy SBRT on a 1.5T MR-linac, 19 patients were treated with vacuum cushion, 19 without and 1 patient sequentially with and without. Intrafraction motion was calculated for target lymph nodes (GTVs) and nearby bony anatomy, for three time intervals (pre-position verification (PV), pre-post, PV-post, relating to the online MRI scans) per treatment fraction. RESULTS: Vacuum cushion immobilization significantly reduced anterior-posterior translations for the pre-PV and pre-post intervals, for bony anatomy and pre-post interval for GTV (p < 0.05). Mean GTV intrafraction motion reduction in posterior direction was 0.7 mm (95% confidence interval 0.3-1.1 mm) for pre-post interval (mean time = 32 min). Shifts in other directions were not significantly reduced. More motion occurred in pre-PV interval than in PV-post interval (mean time = 16 min for both); vacuum cushion immobilization did not reduce intrafraction motion during the beam-on period. CONCLUSION: A vacuum cushion reduces GTV and bony anatomy intrafraction motion in posterior direction during pelvic/para-aortic lymph node SBRT. This motion reduction was found for the first 16 min per session. For single targets this motion can be corrected for directly with an MR-linac. Intrafraction motion was not reduced during the second half of the session, the period of radiotherapy delivery on an MR-linac. Vacuum cushion immobilization may not be necessary for patients with single lymph node oligometastases undergoing SBRT on an MR-linac.

Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy.

BACKGROUND: Structure delineation is a necessary, yet time-consuming manual procedure in radiotherapy. Recently, convolutional neural networks have been proposed to speed-up and automatise this procedure, obtaining promising results. With the advent of magnetic resonance imaging (MRI)-guided radiotherapy, MR-based segmentation is becoming increasingly relevant. However, the majority of the studies investigated automatic contouring based on computed tomography (CT). PURPOSE: In this study, we investigate the feasibility of clinical use of deep learning-based automatic OARs delineation on MRI. MATERIALS AND METHODS: We included 150 patients diagnosed with prostate cancer who underwent MR-only radiotherapy. A three-dimensional (3D) T1-weighted dual spoiled gradient-recalled echo sequence was acquired with 3T MRI for the generation of the synthetic-CT. The first 48 patients were included in a feasibility study training two 3D convolutional networks called DeepMedic and dense V-net (dV-net) to segment bladder, rectum and femurs. A research version of an atlas-based software was considered for comparison. Dice similarity coefficient, 95% Hausdorff distances (HD95), and mean distances were calculated against clinical delineations. For eight patients, an expert RTT scored the quality of the contouring for all the three methods. A choice among the three approaches was made, and the chosen approach was retrained on 97 patients and implemented for automatic use in the clinical workflow. For the successive 53 patients, Dice, HD95 and mean distances were calculated against the clinically used delineations. RESULTS: DeepMedic, dV-net and the atlas-based software generated contours in 60 s, 4 s and 10-15 min, respectively. Performances were higher for both the networks compared to the atlas-based software. The qualitative analysis demonstrated that delineation from DeepMedic required fewer adaptations, followed by dV-net and the atlas-based software. DeepMedic was clinically implemented. After retraining DeepMedic and testing on the successive patients, the performances slightly improved. CONCLUSION: High conformality for OARs delineation was achieved with two in-house trained networks, obtaining a significant speed-up of the delineation procedure. Comparison of different approaches has been performed leading to the succesful adoption of one of the neural networks, DeepMedic, in the clinical workflow. DeepMedic maintained in a clinical setting the accuracy obtained in the feasibility study.

Target coverage and dose criteria based evaluation of the first clinical 1.5T MR-linac SBRT treatments of lymph node oligometastases compared with conventional CBCT-linac treatment.

BACKGROUND AND PURPOSE: Patients were treated at our institute for single and multiple lymph node oligometastases on the 1.5T MR-linac since August 2018. The superior soft-tissue contrast and additional software features of the MR-linac compared to CBCT-linacs allow for online adaptive treatment planning. The purpose of this study was to perform a target coverage and dose criteria based evaluation of the clinically delivered online adaptive radiotherapy treatment compared with conventional CBCT-linac treatment. MATERIALS AND METHODS: Patient data was used from 14 patients with single lymph node oligometastases and 6 patients with multiple (2-3) metastases. All patients were treated on the 1.5T MR-linac with a prescribed dose of 5 × 7 Gy to 95% of the PTV and a CBCT-linac plan was created for each patient. The difference in target coverage between these plans was compared and plans were evaluated based on dose criteria for each fraction after calculating the CBCT-plan on the daily anatomy. The GTV coverage was evaluated based on the online planning and the post-delivery MRI. RESULTS: For both single and multiple lymph node oligometastases the GTV V35Gy had a median value of 100% for both the MR-linac plans and CBCT-plans pre- and post-delivery and did not significantly differ. The percentage of plans that met all dose constraints was improved from 19% to 84% and 20% to 67% for single and multiple lymph node cases, respectively. CONCLUSION: Target coverage and dose criteria based evaluation of the first clinical 1.5T MR-linac SBRT treatments of lymph node oligometastases compared with conventional CBCT-linac treatment shows a smaller amount of unplanned violations of high dose criteria. The GTV coverage was comparable. Benefit is primarily gained in patients treated for multiple lymph node oligometastases: geometrical deformations are accounted for, dose can be delivered in one plan and margins can be reduced.

Evaluation of gold fiducial marker manual localisation for magnetic resonance-only prostate radiotherapy.

BACKGROUND: The use of intraprostatic gold fiducial markers (FMs) ensures highly accurate and precise image-guided radiation therapy for patients diagnosed with prostate cancer thanks to the ease of localising FMs on photon-based imaging, like Computed Tomography (CT) images. Recently, Magnetic Resonance (MR)-only radiotherapy has been proposed to simplify the workflow and reduce possible systematic uncertainties. A critical, determining factor in the accuracy of such an MR-only simulation will be accurate FM localisation using solely MR images. PURPOSE: The aim of this study is to evaluate the performances of manual MR-based FM localisation within a clinical environment. METHODS: We designed a study in which 5 clinically involved radiation therapy technicians (RTTs) independently localised the gold FMs implanted in 16 prostate cancer patients in two scenarios: employing a single MR sequence or a combination of sequences. Inter-observer precision and accuracy were assessed for the two scenarios for localisation in terms of 95% limit of agreement on single FMs (LoA)/ centre of mass (LoA CM) and inter-marker distances (IDs), respectively. RESULTS: The number of precisely located FMs (LoA <2 mm) increased from 38/48 to 45/48 FMs when localisation was performed using multiple sequences instead of single one. When performing localisation on multiple sequences, imprecise localisation of the FMs (3/48 FMs) occurred for 1/3 implanted FMs in three different patients. In terms of precision, we obtained LoA CM within 0.25 mm in all directions over the precisely located FMs. In terms of accuracy, IDs difference of manual MR-based localisation versus CT-based localisation was on average (±1 STD) 0.6 ±0.6 mm. CONCLUSIONS: For both the investigated scenarios, the results indicate that when FM classification was correct, the precision and accuracy are high and comparable to CT-based FM localisation. We found that use of multiple sequences led to better localisation performances compared with the use of single sequence. However, we observed that, due to the presence of calcification and motion, the risk of mislocated patient positioning is still too high to allow the sole use of manual FM localisation. Finally, strategies to possibly overcome the current challenges were proposed.

Evaluation of an automatic MR-based gold fiducial marker localisation method for MR-only prostate radiotherapy.

An MR-only radiotherapy planning (RTP) workflow would reduce the cost, radiation exposure and uncertainties introduced by CT-MRI registrations. In the case of prostate treatment, one of the remaining challenges currently holding back the implementation of an RTP workflow is the MR-based localisation of intraprostatic gold fiducial markers (FMs), which is crucial for accurate patient positioning. Currently, MR-based FM localisation is clinically performed manually. This is sub-optimal, as manual interaction increases the workload. Attempts to perform automatic FM detection often rely on being able to detect signal voids induced by the FMs in magnitude images. However, signal voids may not always be sufficiently specific, hampering accurate and robust automatic FM localisation. Here, we present an approach that aims at automatic MR-based FM localisation. This method is based on template matching using a library of simulated complex-valued templates, and exploiting the behaviour of the complex MR signal in the vicinity of the FM. Clinical evaluation was performed on seventeen prostate cancer patients undergoing external beam radiotherapy treatment. Automatic MR-based FM localisation was compared to manual MR-based and semi-automatic CT-based localisation (the current gold standard) in terms of detection rate and the spatial accuracy and precision of localisation. The proposed method correctly detected all three FMs in 15/17 patients. The spatial accuracy (mean) and precision (STD) were 0.9 mm and 0.5 mm respectively, which is below the voxel size of [Formula: see text] mm3 and comparable to MR-based manual localisation. FM localisation failed (3/51 FMs) in the presence of bleeding or calcifications in the direct vicinity of the FM. The method was found to be spatially accurate and precise, which is essential for clinical use. To overcome any missed detection, we envision the use of the proposed method along with verification by an observer. This will result in a semi-automatic workflow facilitating the introduction of an MR-only workflow.