Online Adaptive MRI-Guided Radiotherapy for Primary Tumor and Lymph Node Boosting in Rectal Cancer.

The purpose of this study was to characterize the motion and define the required treatment margins of the pathological mesorectal lymph nodes (GTVln) for two online adaptive MRI-guided strategies for sequential boosting. Secondly, we determine the margins required for the primary gross tumor volume (GTVprim). Twenty-eight patients treated on a 1.5T MR-Linac were included in the study. On T2-weighted images for adaptation (MRIadapt) before and verification after irradiation (MRIpost) of five treatment fractions per patient, the GTVln and GTVprim were delineated. With online adaptive MRI-guided radiotherapy, daily plan adaptation can be performed through the use of two different strategies. In an adapt-to-shape (ATS) workflow the interfraction motion is effectively corrected by redelineation and the only relevant motion is intrafraction motion, while in an adapt-to-position (ATP) workflow the margin (for GTVln) is dominated by interfraction motion. The margin required for GTVprim will be identical to the ATS workflow, assuming each fraction would be perfectly matched on GTVprim. The intrafraction motion was calculated between MRIadapt and MRIpost for the GTVln and GTVprim separately. The interfraction motion of the GTVln was calculated with respect to the position of GTVprim, assuming each fraction would be perfectly matched on GTVprim. PTV margins were calculated for each strategy using the Van Herk recipe. For GTVln we randomly sampled the original dataset 20 times, with each subset containing a single randomly selected lymph node for each patient. The resulting margins for ATS ranged between 3 and 4 mm (LR), 3 and 5 mm (CC) and 5 and 6 mm (AP) based on the 20 randomly sampled datasets for GTVln. For ATP, the margins for GTVln were 10-12 mm in LR and AP and 16-19 mm in CC. The margins for ATS for GTVprim were 1.7 mm (LR), 4.7 mm (CC) and 3.2 mm anterior and 5.6 mm posterior. Daily delineation using ATS of both target volumes results in the smallest margins and is therefore recommended for safe dose escalation to the primary tumor and lymph nodes.

Explaining the dosimetric impact of contouring errors in head and neck radiotherapy.

Objective. Auto-contouring of organs at risk (OAR) is becoming more common in radiotherapy. An important issue in clinical decision making is judging the quality of the auto-contours. While recent studies considered contour quality by looking at geometric errors only, this does not capture the dosimetric impact of the errors. In this work, we studied the relationship between geometrical errors, the local dose and the dosimetric impact of the geometrical errors.Approach. For 94 head and neck patients, unmodified atlas-based auto-contours and clinically used delineations of the parotid glands and brainstem were retrieved. VMAT plans were automatically optimized on the auto-contours and evaluated on both contours. We defined the dosimetric impact on evaluation (DIE) as the difference in the dosimetric parameter of interest between the two contours. We developed three linear regression models to predict the DIE using: (1) global geometric metrics, (2) global dosimetric metrics, (3) combined local geometric and dosimetric metrics. For model (3), we next determined the minimal amount of editing information required to produce a reliable prediction. Performance was assessed by the root mean squared error (RMSE) of the predicted DIE using 5-fold cross-validation.Main results. In model (3), the median RMSE of the left parotid was 0.4 Gy using 5% of the largest editing vectors. For the right parotid and brainstem the results were 0.5 Gy using 10% and 0.4 Gy using 1% respectively. The median RMS of the DIE was 0.6 Gy, 0.7 Gy and 0.9 Gy for the left parotid, the right parotid and the brainstem, respectively. Model (3), combining local dosimetric and geometric quantities, outperformed the models that used only geometric or dosimetric information.Significance. We showed that the largest local errors plus the local dose suffice to accurately predict the dosimetric impact, opening the door to automated dosimetric QA of auto-contours.

A margin recipe for the management of intra-fraction target motion in radiotherapy.

Background and purpose: Strategies to limit the impact of intra-fraction motion during treatment are common in radiotherapy. Margin recipes, however, are not designed to incorporate these strategies. This work aimed to provide a framework to determine how motion management strategies influence treatment margins. Materials and methods: Two models of intra-fraction motion were considered. In model 1 motion was instantaneous, before treatment starts and in model 2 motion was a continuous drift during treatment. Motion management strategies were modelled by truncating the underlying error distribution at cσ, with σ the standard deviation of the distribution and c a free parameter. Using Monte Carlo simulations, we determined how motion management changed the required margin. The analysis was performed for different number of treatment fractions and different standard deviations of the underlying random and systematic errors. Results: The required margin for a continuous drift was found to be well approximated by an average position of the target at ¾ of the drift. Introducing a truncation at cσ, the relative change in the margin was equal to 0.3c. This result held for both models, was independent of σ or the number of fractions and naturally generalizes to the situation with a residual (systematic) error. Conclusion: Treatment margins can be determined when motion management strategies are applied. Moreover, our analysis can be used to study the potential benefit of different motion management strategies. This allows to discuss and determine the most appropriate strategy for margin reduction.

Effect of intrafraction adaptation on PTV margins for MRI guided online adaptive radiotherapy for rectal cancer.

PURPOSE: To determine PTV margins for intrafraction motion in MRI-guided online adaptive radiotherapy for rectal cancer and the potential benefit of performing a 2nd adaptation prior to irradiation. METHODS: Thirty patients with rectal cancer received radiotherapy on a 1.5 T MR-Linac. On T2-weighted images for adaptation (MRIadapt), verification prior to (MRIver) and after irradiation (MRIpost) of 5 treatment fractions per patient, the primary tumor GTV (GTVprim) and mesorectum CTV (CTVmeso) were delineated. The structures on MRIadapt were expanded to corresponding PTVs. We determined the required expansion margins such that on average over 5 fractions, 98% of CTVmeso and 95% of GTVprim on MRIpost was covered in 90% of the patients. Furthermore, we studied the benefit of an additional adaptation, just prior to irradiation, by evaluating the coverage between the structures on MRIver and MRIpost. A threshold to assess the need for a secondary adaptation was determined by considering the overlap between MRIadapt and MRIver. RESULTS: PTV margins for intrafraction motion without 2nd adaptation were 6.4 mm in the anterior direction and 4.0 mm in all other directions for CTVmeso and 5.0 mm isotropically for GTVprim. A 2nd adaptation, applied for all fractions where the motion between MRIadapt and MRIver exceeded 1 mm (36% of the fractions) would result in a reduction of the PTVmeso margin to 3.2 mm/2.0 mm. For PTVprim a margin reduction to 3.5 mm is feasible when a 2nd adaptation is performed in fractions where the motion exceeded 4 mm (17% of the fractions). CONCLUSION: We studied the potential benefit of intrafraction motion monitoring and a 2nd adaptation to reduce PTV margins in online adaptive MRIgRT in rectal cancer. Performing 2nd adaptations immediately after online replanning when motion exceeded 1 mm and 4 mm for CTVmeso and GTVprim respectively, could result in a 30-50% margin reduction with limited reduction of dose to the bowel.

Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer.

Background/purpose: In daily plan adaptation the radiotherapy treatment plan is adjusted just prior to delivery. A simple approach is taking the planning objectives of the reference plan and directly applying these in re-optimization. Here we present a tested method to verify whether daily adaptation without tweaking of the objectives can maintain the plan quality throughout treatment. Materials/methods: For fifteen rectal cancer patients, automated treatment planning was used to generate plans mimicking manual reference plans on the planning scans. For 74 fraction scans (4-5 per patient) an automated plan and a daily adapted plan were generated, where the latter re-optimizes the reference plan objectives without any tweaking. To evaluate the robustness of the daily adaptation, the adapted plans were compared to the autoplanning plans. Results: Median differences between the autoplanning plans on the planning scans and the reference plans were between -1 and 0.2 Gy. The largest interquartile range (1 Gy) was seen for the Lumbar Skin D2%. For the daily scans the PTV D2% and D98% differences between autoplanning and adapted plans were within ± 0.7 Gy, with mean differences within ± 0.3 Gy. Positive differences indicate higher values were obtained using autoplanning. For the Bowelarea + Bladder and the Lumbar Skin the D2% and Dmean differences were all within ± 2.6 Gy, with mean differences between -0.9 and 0.1 Gy. Conclusion: Automated treatment planning can be used to benchmark daily adaptation techniques. The investigated adaptation workflow can robustly perform high quality adaptations without daily adjusting of the patient-specific planning objectives for rectal cancer radiotherapy.

First multicentre experience of SABR for lymph node and liver oligometastatic disease on the unity MR-Linac.

The treatment of oligometastatic disease using MR guidance is an evolving field. Since August 2018 patients are treated on a 1.5 Tesla MR-Linac (MRL). We present current workflows and practice standards from seven institutions for the initial patients treated for lymph node and liver metastases.

Clinical workflow for treating patients with a metallic hip prosthesis using magnetic resonance imaging-guided radiotherapy.

BACKGROUND & PURPOSE: Metallic prostheses distort the magnetic field during magnetic resonance imaging (MRI), leading to geometric distortions and signal loss. The purpose of this work was to develop a method to determine eligibility for MRI-guided radiotherapy (MRIgRT) on a per patient basis by estimating the magnitude of geometric distortions inside the clinical target volume (CTV). MATERIALS & METHODS: Three patients with prostate cancer and hip prosthesis, treated using MRIgRT, were included. Eligibility for MRIgRT was based on computed tomography and associated CTV delineations, together with a field-distortion (B0) map and anatomical images acquired during MR simulation. To verify the method, B0 maps made during MR simulation and each MRIgRT treatment fraction were compared. RESULTS: Estimates made during MR simulation of the magnitude of distortions inside the CTV were 0.43 mm, 0.19 mm and 2.79 mm compared to the average over all treatment fractions of 1.40 mm, 0.32 mm and 1.81 mm, per patient respectively. CONCLUSIONS: B0 map acquisitions prior to treatment can be used to estimate the magnitude of distortions during MRIgRT to guide the decision on eligibility for MRIgRT of prostate cancer patients with metallic hip implants.

The use of real-world evidence to audit normal tissue complication probability models for acute esophageal toxicity in non-small cell lung cancer patients.

INTRODUCTION: The aim of this work is to assess the validity of real world data (RWD) derived from an electronic toxicity registration (ETR). As a showcase, the NTCP-models of acute esophageal toxicity (AET) for concurrent chemoradiation (CCRT) for NSCLC patients were used to validate the ETR of AET before/after dose de-escalation to the mediastinal lymph nodes. MATERIAL AND METHODS: One hundred and one patients received 24 × 2.75 Gy and 116 patients received de-escalated dose of 24 × 2.42 Gy to the mediastinal lymph nodes. The validity and completeness of the ETR was analyzed. The grade ≥2 AET probability was defined according the V50 Gy and V60 Gy NTCP-models from literature. Validity of the models was assessed by calibration and discrimination. Furthermore, sensitivity and specificity for different cut-off points were determined. RESULTS: The compliance of ETR was 73-80%, with sensitivity and specificity rates of 83% and 86% for grade ≥2 AET, respectively. Discrimination of both NTCP-models demonstrated a moderate accuracy (V50 model, AUC 0.71; V60-model, AUC 0.69). Dose de-escalation did not influence the accuracy of the V50-model; AUC before: 0.69, and AUC after: 0.71. For the V60-model the model-accuracy decreased after dose de-escalation; AUC before: 0.72 and AUC after: 0.62, respectively. CONCLUSION: RWD is a useful method to audit NTCP models in clinical practice. The NTCP models to predict AET in NSCLC patients showed moderate predictive accuracy. For clinical practice, the V50Gy seems to be most stable for dose de-escalation without compromising safety and efficacy.

Knowledge-Based Assessment of Focal Dose Escalation Treatment Plans in Prostate Cancer.

PURPOSE: In a randomized focal dose escalation radiation therapy trial for prostate cancer (FLAME), up to 95 Gy was prescribed to the tumor in the dose-escalated arm, with 77 Gy to the entire prostate in both arms. As dose constraints to organs at risk had priority over dose escalation and suboptimal planning could occur, we investigated how well the dose to the tumor was boosted. We developed an anatomy-based prediction model to identify plans with suboptimal tumor dose and performed replanning to validate our model. METHODS AND MATERIALS: We derived dose-volume parameters from planned dose distributions of 539 FLAME trial patients in 4 institutions and compared them between both arms. In the dose-escalated arm, we determined overlap volume histograms and derived features representing patient anatomy. We predicted tumor D98% with a linear regression on anatomic features and performed replanning on 21 plans. RESULTS: In the dose-escalated arm, the median tumor D50% and D98% were 93.0 and 84.7 Gy, and 99% of the tumors had a dose escalation greater than 82.4 Gy (107% of 77 Gy). In both arms organs at risk constraints were met. Five out of 73 anatomic features were found to be predictive for tumor D98%. Median predicted tumor D98% was 4.4 Gy higher than planned D98%. Upon replanning, median tumor D98% increased by 3.0 Gy. A strong correlation between predicted increase in D98% and realized increase upon replanning was found (ρ = 0.86). CONCLUSIONS: Focal dose escalation in prostate cancer was feasible with a dose escalation to 99% of the tumors. Replanning resulted in an increased tumor dose that correlated well with the prediction model. The model was able to identify tumors on which a higher boost dose could be planned. The model has potential as a quality assessment tool in focal dose escalated treatment plans.

Geometrical and dosimetric evaluation of breast target volume auto-contouring.

BACKGROUND AND PURPOSE: Automatic delineations are often used as a starting point in the radiotherapy contouring workflow, after which they are manually reviewed and adapted. The purpose of this work was to quantify the geometric differences between automatic and manually edited breast clinical target volume (CTV) contours and evaluate the dosimetric impact of such differences. MATERIALS AND METHODS: Eighty-seven automatically generated and manually edited contours of the left breast were retrieved from our clinical database. The automatic contours were obtained with a commercial auto-segmentation toolbox. The geometrical comparison was performed both locally and globally using the Dice score and the 95% Hausdorff distance (HD). Two treatment plans were generated for each patient and the obtained dosimetric differences were quantified using dose-volume histogram (DVH) parameters in the lungs, heart and planning target volume (PTV). An inter-observer variability study with four observers was performed on a subset of ten patients. RESULTS: A median Dice score of 0.95 and a median 95% HD of 9.7 mm were obtained. Larger breasts were consistently under-contoured. Cranial under-contouring resulted in more than 5% relative decrease in PTV coverage in 15% of the patients while lateroposterior over-contouring increased the lung V20Gy by a maximum of 2%. The inter-observer variability of the PTV coverage was smaller than the difference between PTV coverage achieved by the automatic and the consensus contours. CONCLUSIONS: Cranial under-contouring resulted in under-treatment, while lateroposterior over-contouring resulted in an increased lung dosage that is clinically irrelevant, showing the need to consider dose distributions to assess the clinical impact of local geometrical differences.

Independent knowledge-based treatment planning QA to audit Pinnacle autoplanning.

BACKGROUND AND PURPOSE: With the advent of automatic treatment planning options like Pinnacle's Autoplanning (PAP), the challenge arises how to assess the quality of a plan that no dosimetrist did work on. The aim of this study was to assess plan quality consistency of PAP prostate cancer patients in clinical practice. MATERIALS AND METHODS: 100 prostate cancer patients were included from NKI and 129 from RadboudUMC (RUMC). Per institute a previously developed [1] treatment planning QA model, based on overlap volume histograms, was trained on PAP plans to predict achievable dose metrics which were then compared to the clinical PAP plans. A threshold of 3 Gy (DVH dose parameters)/3% (DVH volume parameters) was used to detect outliers. For the outlier plans, the PAP technique was adjusted with the aim of meeting the threshold. RESULTS: The average difference between the prediction and the clinically achieved value was <0.5 Gy (mean dose parameters) and <1.2% (volume parameters), with standard deviation of 1.9 Gy/1.5% respectively. We found 8% (NKI)/25% (RUMC) of patients to exceed the 3 Gy/3% threshold, with deviations up to 6.7 Gy (mean dose rectum) and 6% (rectal wall V64Gy). In all cases the plans could be improved to fall within the thresholds, without compromising the other dose metrics. CONCLUSION: Independent treatment planning QA was used successfully to assess the quality of clinical PAP in a multi-institutional setting. Respectively 8% and 25% suboptimal clinical PAP plans were detected that all could be improved with replanning. Therefore we recommend the use of independent treatment plan QA in combination with PAP for prostate cancer patients.

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.

Target volume delineation in external beam partial breast irradiation: less inter-observer variation with preoperative- compared to postoperative delineation.

The challenge of adequate target volume definition in external beam partial breast irradiation (PBI) could be overcome with preoperative irradiation, due to less inter-observer variation. We compared the target volume delineation for external beam PBI on preoperative versus postoperative CT scans of twenty-four breast cancer patients.

Probabilistic objective functions for margin-less IMRT planning.

We present a method to implement probabilistic treatment planning of intensity-modulated radiation therapy using custom software plugins in a commercial treatment planning system. Our method avoids the definition of safety-margins by directly including the effect of geometrical uncertainties during optimization when objective functions are evaluated. Because the shape of the resulting dose distribution implicitly defines the robustness of the plan, the optimizer has much more flexibility than with a margin-based approach. We expect that this added flexibility helps to automatically strike a better balance between target coverage and dose reduction for surrounding healthy tissue, especially for cases where the planning target volume overlaps organs at risk. Prostate cancer treatment planning was chosen to develop our method, including a novel technique to include rotational uncertainties. Based on population statistics, translations and rotations are simulated independently following a marker-based IGRT correction strategy. The effects of random and systematic errors are incorporated by first blurring and then shifting the dose distribution with respect to the clinical target volume. For simplicity and efficiency, dose-shift invariance and a rigid-body approximation are assumed. Three prostate cases were replanned using our probabilistic objective functions. To compare clinical and probabilistic plans, an evaluation tool was used that explicitly incorporates geometric uncertainties using Monte-Carlo methods. The new plans achieved similar or better dose distributions than the original clinical plans in terms of expected target coverage and rectum wall sparing. Plan optimization times were only about a factor of two higher than in the original clinical system. In conclusion, we have developed a practical planning tool that enables margin-less probability-based treatment planning with acceptable planning times, achieving the first system that is feasible for clinical implementation.