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

Simulation of Focal Boosting in Online Adaptive MRI-Guided SBRT for Patients With Locally Advanced Prostate Cancer With Seminal Vesicle Involvement

PURPOSE

To evaluate the feasibility and accuracy of focal boosting in online adaptive MRI-guided stereotactic body radiation therapy (SBRT) for patients with prostate cancer (PCa) with seminal vesicle invasion (T3b) by analyzing the impact of intrafraction motion on the dose planned for the gross tumor volume (GTV) and clinical target volume (CTV).

METHODS AND MATERIALS

Data from 23 patients with T1-T3a PCa who received focal boosting SBRT on a 1.5T MR-Linac was used. A radiation oncologist replaced clinical GTVs with artificial GTVs representative for T3b tumor(s). For each MRI used for daily adaptation (MRIadapt), an automated treatment plan was generated (Df1-5) using the adapted contours. Patients were planned to receive 35 Gy to the CTV, with an isotoxic focal boost to the GTV up to 50 Gy. During each fraction, an additional MRI was acquired to assess intrafraction motion (MRIduring). Dose accumulation of all fractions was performed by deformable registration of MRIadapt, f2-5 to MRIadapt, f1 (DACC, planned). The Df1-5 were projected to their corresponding MRIduring, which were used to reconstruct DACC, delivered, likewise. Our results were compared to patients with tumor(s) without seminal vesicle invasion (T1-T3a).

RESULTS

The median (10th-90th percentile) D98%ACC, planned to the GTV, which correlates most strongly with outcome, was 41.1 Gy (40.1-43.0 Gy) in the plans for patients with artificial T3b tumors, compared to 43.0 Gy (40.4-47.2 Gy) in the plans for patients with T1-T3a tumors. The D98%ACC, delivered to the GTV, taking into account intrafraction motion, was 41.0 Gy (39.3-42.6 Gy) and 42.5 Gy (40.0-46.6 Gy) in the plans for the artificial and clinical GTVs, respectively.

CONCLUSIONS

MRI-guidance can ensure high accuracy of focal boosting in patients with T3b disease. Because of the unfavorable location of the GTV, a lower boost dose was feasible compared to patients with T1-T3a PCa.

A patient-specific auto-planning method for MRI-guided adaptive radiotherapy in prostate cancer

BACKGROUND AND PURPOSE

Fast and automated generation of treatment plans is desirable for magnetic resonance imaging (MRI)-guided adaptive radiotherapy (MRIgART). This study proposed a novel patient-specific auto-planning method and validated its feasibility in improving the existing online planning workflow.

MATERIALS AND METHODS

Data from 40 patients with prostate cancer were collected retrospectively. A patient-specific auto-planning method was proposed to generate adaptive treatment plans. First, a population dose-prediction model (M0) was trained using data from previous patients. Second, a patient-specific model (Mps) was created for each new patient by fine-tuning M0 with the patient's data. Finally, an auto plan was optimized using the parameters derived from the predicted dose distribution by Mps. The auto plans were compared with manual plans in terms of plan quality, efficiency, dosimetric verification, and clinical evaluation.

RESULTS

The auto plans improved target coverage, reduced irradiation to the rectum, and provided comparable protection to other organs-at-risk. Target coverage for the planning target volume (+0.61 %, P = 0.023) and clinical target volume 4000 (+1.60 %, P < 0.001) increased. V2900cGy (-1.06 %, P = 0.004) and V1810cGy (-2.49 %, P < 0.001) to the rectal wall and V1810cGy (-2.82 %, P = 0.012) to the rectum were significantly reduced. The auto plans required less planning time (-3.92 min, P = 0.001), monitor units (-46.48, P = 0.003), and delivery time (-0.26 min, P = 0.004), and their gamma pass rates (3 %/2 mm) were higher (+0.47 %, P = 0.014).

CONCLUSION

The proposed patient-specific auto-planning method demonstrated a robust level of automation and was able to generate high-quality treatment plans in less time for MRIgART in prostate cancer.

Evaluating the effect of higher Monte Carlo statistical uncertainties on accumulated doses after daily adaptive fractionated radiotherapy in prostate cancer

Background and purpose

Monte Carlo (MC) based dose calculations are widely used in radiotherapy with a low statistical uncertainty, being accurate but slow. Increasing the uncertainty accelerates the calculation, but reduces quality. In online adaptive planning, however, dose is recalculated every treatment fraction, potentially decreasing the cumulative calculation error. This study aimed to evaluate the effect of higher MC statistical uncertainty in the context of daily online plan adaptation.

Materials and methods

For twenty prostate cancer patients, daily plans were simulated for 5 fractions and three modes of variation: rigid whole body translations, local-rigid prostate translations and local-rigid prostate rotations. For each mode and fraction, adaptive plans were generated from a clinical reference plan using three MC uncertainty values: 1 % (standard), 2 % and 3 % per plan. Dose-volume criteria were evaluated for accumulated doses, checking plan acceptability and comparing higher uncertainty plans to the standard.

Results

Increasing the statistical uncertainty setting from 1 % to 2-3 % caused an accumulated median target D98 % reduction of 0.1 Gy, with interquartile ranges (IQRs) up to 0.12 Gy. Rectum V35Gy increased in median up to 0.16 cm3 with IQRs up to 0.33 cm3. The bladder V28Gy and V32Gy showed median increases up to 0.24 %-point, with IQRs up to 0.54 %-point. Using 2 % uncertainty reduced calculation times by more than a minute for all modes of variation, with no further time gain when increasing to 3 %.

Conclusion

A 2-3 % MC statistical uncertainty was clinically feasible. Using a 2 % uncertainty setting reduced calculation times at the cost of limited relative dose-volume differences.

MRI-Guided Adaptive Radiation Therapy

Magnetic resonance imaging-guided radiation therapy (MRIgRT) has improved soft tissue contrast over computed tomography (CT) based image-guided RT. Superior visualization of the target and surrounding radiosensitive structures has the potential to improve oncological outcomes partly due to safer dose-escalation and adaptive planning. In this review, we highlight the workflow of adaptive MRIgRT planning, which includes simulation imaging, daily MRI, identifying isocenter shifts, contouring, plan optimization, quality control, and delivery. Increased utilization of MRIgRT will depend on addressing technical limitations of this technology, while addressing treatment efficacy, cost-effectiveness, and workflow training.

Full daily re-optimization improves plan quality during online adaptive radiotherapy

Background and purpose

Daily online treatment plan adaptation requires a fast workflow and planning process. Current online planning consists of adaptation of a predefined reference plan, which might be suboptimal in cases of large anatomic changes. The aim of this study was to investigate plan quality differences between the current online re-planning approach and a complete re-optimization.

Material and methods

Magnetic resonance linear accelerator reference plans for ten prostate cancer patients were automatically generated using particle swarm optimization (PSO). Adapted plans were created for each fraction using (1) the current re-planning approach and (2) full PSO re-optimization and evaluated overall compliance with institutional dose-volume criteria compared to (3) clinically delivered fractions. Relative volume differences between reference and daily anatomy were assessed for planning target volumes (PTV60, PTV57.6), rectum and bladder and correlated with dose-volume results.

Results

The PSO approach showed significantly higher adherence to dose-volume criteria than the reference approach and clinical fractions (p < 0.001). In 74 % of PSO plans at most one criterion failed compared to 56 % in the reference approach and 41 % in clinical plans. A fair correlation between PTV60 D98% and relative bladder volume change was observed for the reference approach. Bladder volume reductions larger than 50 % compared to the reference plan recurrently decreased PTV60 D98% below 56 Gy.

Conclusion

Complete re-optimization maintained target coverage and organs at risk sparing even after large anatomic variations. Re-planning based on daily magnetic resonance imaging was sufficient for small variations, while large variations led to decreasing target coverage and organ-at-risk sparing.