Four-dimensional Plan Optimization for the Treatment of Lung Tumors Using Pencil-beam Scanning Proton Radiotherapy (original) (raw)
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Cancers, 2019
Background: Major challenges in the application of intensity-modulated proton therapy (IMPT) for lung cancer patients include the uncertainties associated with breathing motion, its mitigation and its consideration in IMPT optimization. The primary objective of this research was to evaluate the potential of four-dimensional robust optimization (4DRO) methodology to make IMPT dose distributions resilient to respiratory motion as well as to setup and range uncertainties; Methods: The effect of respiratory motion, characterized by different phases of 4D computed tomography (4DCT), was incorporated into an in-house 4DRO system. Dose distributions from multiple setup and range uncertainty scenarios were calculated for each of the ten phases of CT datasets. The 4DRO algorithm optimizes dose distributions to achieve target dose coverage and normal tissue sparing for multiple setup and range uncertainty scenarios as well as for all ten respiratory phases simultaneously. IMPT dose distributi...
International journal of radiation oncology, biology, physics, 2018
To investigate how spot size and spacing affect plan quality, robustness, and interplay effects of robustly optimized intensity modulated proton therapy (IMPT) for lung cancer. Two robustly optimized IMPT plans were created for 10 lung cancer patients: first by a large-spot machine with in-air energy-dependent large spot size at isocenter (σ: 6-15 mm) and spacing (1.3 σ), and second by a small-spot machine with in-air energy-dependent small spot size (σ: 2-6 mm) and spacing (5 mm). Both plans were generated by optimizing radiation dose to internal target volume on averaged 4-dimensional computed tomography scans using an in-house-developed IMPT planning system. The dose-volume histograms band method was used to evaluate plan robustness. Dose evaluation software was developed to model time-dependent spot delivery to incorporate interplay effects with randomized starting phases for each field per fraction. Patient anatomy voxels were mapped phase-to-phase via deformable image registra...
Advanced proton beam dosimetry part II: Monte Carlo vs. pencil beam- based planning for lung cancer
Background: Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients. Methods: With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung VRX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing. Results: In this ten-patient sample, CTV V95 decreased significantly from 99–100% for PBopt to 77–94% for MCrecalc and recovered to 99–100% for MCopt (P<10−5). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10−3). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =−1%) compared to MCrecalc (ΔD95 =−6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., VRX). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10−3). Conclusions: MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy.
Medical Physics
Purpose: Interplay effects in proton radiotherapy can create large distortions in the dose distribution and severely degrade the plan quality. Standard methods to mitigate these effects include abdominal compression, gating, and rescanning. We propose a new method to include the time structures of the delivery and organ motion in the framework of four-dimensional (4D) robust optimization to generate plans that are robust against interplay effects. Methods: The method considers multiple scenarios reflecting the uncertainties in the delivery and in the organ motion. In each scenario, the pencil beam scanning spots are distributed to different phases of the breathing cycle according to each individual spot time stamp, and a partial beam dose is calculated for each phase. The partial beam doses are accumulated on a reference phase through deformable image registrations. Minimax optimization is performed to take all scenarios into account simultaneously. For simplicity, the uncertainties in this proof of concept study are limited to variations in the breathing pattern. The method is evaluated for three different nonsmall cell lung cancer patients and compared to plans using conventional 4D robust optimization both with and without rescanning. We assess the ability of the method to mitigate distortions from the interplay effect over multiple evaluation scenarios using 4D dose calculations. This interplay evaluation is performed in an experimentally validated framework, which is independent of the optimization in the plan generation step. Results: For the three studied patients, 4D optimization including time structures is efficient, especially for large tumor motions, where rescanning of conventional 4D robustly optimized plans is not sufficient to mitigate the interplay effect. The most efficient approach of the new method is achieved when it is combined with rescanning. For the patient with the largest motion, the mean V95% is 99.2% and mean V107% is 3.65% for the best rescanned 4D plan optimized with time structure. This can be compared to conventional 4D optimized plans with mean V95% of 92.7% and mean V107% of 13.1%. Conclusions: The current study shows the potential of reducing interplay effects in proton pencil beam scanning radiotherapy by incorporating organ motion and delivery characteristics in a 4D robust optimization.
Acta Oncologica, 2014
Background. Accurate target volume segmentation is crucial for success in image-guided radiotherapy. However, variability in anatomical segmentation is one of the most signifi cant contributors to uncertainty in radiotherapy treatment planning. This is especially true for lung cancer where target volumes are subject to varying magnitudes of respiratory motion. Material and methods. This study aims to analyze multiple observer target volume segmentations and subsequent intensity-modulated radiotherapy (IMRT) treatment plans defi ned by those segmentations against a reference standard for lung cancer patients imaged with four-dimensional computed tomography (4D-CT). Target volume segmentations of 10 patients were performed manually by six physicians, allowing for the calculation of ground truth estimate segmentations via the simultaneous truth and performance level estimation (STAPLE) algorithm. Segmentation variability was assessed in terms of distance-and volume-based metrics. Treatment plans defi ned by these segmentations were then subject to dosimetric evaluation consisting of both physical and radiobiological analysis of optimized 3D dose distributions. Results. Signifi cant differences were noticed amongst observers in comparison to STAPLE segmentations and this variability directly extended into the treatment planning stages in the context of all dosimetric parameters used in this study. Mean primary tumor control probability (TCP) ranged from (22.6 Ϯ 11.9)% to (33.7 Ϯ 0.6)%, with standard deviation ranging from 0.5% to 11.9%. However, mean normal tissue complication probabilities (NTCP) based on treatment plans for each physician-derived target volume well as the NTCP derived from STAPLE-based treatment plans demonstrated no discernible trends and variability appeared to be patient-specifi c. This type of variability demonstrated the large-scale impact that target volume segmentation uncertainty can play in IMRT treatment planning. Conclusions. Signifi cant target volume segmentation and dosimetric variability exists in IMRT treatment planning amongst experts in the presence of a reference standard for 4D-CT-based lung cancer radiotherapy. Future work is needed to mitigate this uncertainty and ensure highly accurate and effective radiotherapy for lung cancer patients.
Medical Imaging 2008: Visualization, Image-guided Procedures, and Modeling, 2008
Due to respiratory motion, lung tumor can move up to several centimeters. If respiratory motion is not carefully considered during the radiation treatment planning, the highly conformal dose distribution with steep gradients could miss the target. To address this issue, the common strategy is to add a population-derived safety margin to the gross tumor volume (GTV). However, during a free breathing CT simulation, the images could be acquired at any phase of a breathing cycle. With such a generalized uniform margin, the planning target volume (PTV) may either include more normal lung tissue than required or miss the GTV at certain phases of a breathing cycle. Recently, respiration correlated CT (4DCT) has been developed and implemented. With 4DCT, it is now possible to trace the tumor 3D trajectories during a breathing cycle and to define the tumor volume as the union of these 3D trajectories. The tumor volume defined in this way is called the internal target volume (ITV). In this study, we introduced a novel parameter, the phase impact factor (PIF), to determine the optimal CT phase for intensity modulated radiation therapy (IMRT) treatment planning for lung cancer. A minimum PIF yields a minimum probability for the GTV to move out of the ITV during the course of an IMRT treatment, providing a minimum probability of a geometric miss. Once the CT images with the optimal phase were determined, an IMRT plan with three to five co-planner beams was computed and optimized using the inverse treatment planning technique.
4D robust optimization in pencil beam scanning proton therapy for hepatocellular carcinoma
Journal of Physics: Conference Series, 2019
The treatment of moving targets is a challenging task using high conformal radiation techniques such as pencil beam scanning (PBS) proton therapy and requires adequate motion mitigation. Recent guidelines propose 4D robust optimization to mitigate motion artefacts in PBS therapy of thoracic malignancies. However, the availability of dosimetric analyses supporting this recommendation is limited and even non-existing for other tumour sites. The objective of this study was therefore to analyse the effectiveness of 4D robust optimization for hepatocellular carcinoma (HCC), representative for moving abdominal targets. These are usually less affected by uncertainties due to tissue heterogeneities than thoracic targets. 4D robustly optimized plans were compared with beam-specific margin plans for 6 HCC patients based on 4D dynamic accumulated doses (4DDD). 4DDD computations were conducted in RayStation with an experimentally validated routine including a site-specific beam time model. Contrary to expectations based on thoracic studies, 4D robust optimization did not yield a more homogeneous target coverage except for shallow targets close to the ribs. A clear advantage of 4D robust optimization is the sparing of normal tissue. The average dose to the normal liver could be reduced by up to 12%.
Journal of Thoracic Oncology, 2015
Lung tumor delineation is frequently performed using 3D positron emission tomography (PET)/computed tomography (CT), particularly in the radiotherapy treatment planning position, by generating an internal target volume (ITV) from the slow acquisition PET. We investigate the dosimetric consequences of stereotactic ablative body radiotherapy (SABR) planning on 3D PET/CT in comparison with gated (4D) PET/CT. Methods: In a prospective clinical trial, patients with lung metastases were prescribed 26 Gy single-fraction SABR to the covering isodose. Contemporaneous 3D PET/CT and 4D PET/CT was performed in the same patient position. An ITV was generated from each data set, with the planning target volume (PTV) being a 5-mm isotropic expansion. Dosimetric parameters from the SABR plan derived using the 3D volumes were evaluated against the same plan applied to 4D volumes. Results: Ten lung targets were evaluated. All 3D plans were successfully optimized to cover 99% of the PTV by the 26 Gy prescription. In all cases, the calculated dose delivered to the 4D target was less than the expected dose to the PTV based on 3D planning. Coverage of the 4D-PTV by the prescription isodose ranged from 74.48% to 98.58% (mean of 90.05%). The minimum dose to the 4D-ITV derived by the 3D treatment plan (mean = 93.11%) was significantly lower than the expected dose to ITV based on 3D PET/CT calculation (mean = 111.28%), p < 0.01. In all but one case, the planned prescription dose did not cover the 4D-PET/CT derived ITV. Conclusions: Target delineation using 3D PET/CT without additional respiratory compensation techniques results in significant target underdosing in the context of SABR.
2015
Background: 4D-optimization takes into account all 4DCT phases to incorporate motion and range changes. The resulting 4D-treatment plans require a delivery synchronized to the patient's motion. Here, we address the question whether 4D-optimization is feasible also with variable breathing motion, by planning on one 4DCT and simulated delivery on serial 4DCTs. Material and Methods: For 4 patients, in total 6 weekly 4DCTs were available, so that 5 fractions could be simulated with a total dose of 47 Gy (RBE) corresponding to a BED of 120 Gy (a/b = 6Gy). Calculations were performed with GSI's TRiP4D and LEM IV. 4D-plans were optimized on the baseline CT, delivering a uniform dose to each motion phase. In this strategy (4D-rescanning), no gradients occur between phases resulting in an inherent rescanning effect. In addition, vector fields from deformable image registration were not necessary for the optimization, but for contour propagation and later forward dose calculation. Doses were calculated for each fraction and accumulated on the baseline end-exhale phase. Isotropic margins of 0, 3, 5 and 7 mm as well as field-specific range margins of 0, 2, 3 %/mm H2O were investigated. For comparison, a range ITV plan was computed for selected margins. Delivery was assumed to be perfectly synchronized; for the ITV plans each phase received 10% of the dose to eliminate interplay. Dose coverage was assessed by V95, with 95% assumed as clinically acceptable. Conformity index (CI) and homogeneity (D5-D95) as well as Lung V20 were compared between 4D and ITV plans. Results: Patient characteristics are shown in Table 1. For all patient, V95 > 95% could be achieved both in each fraction and total treatment, but with strongly varying margin size. In comparison to the ITV irradiations, CI and Lung V20 were always superior for the same margins. Conclusion: 4D-optimization is feasible also for a time series of 4DCTs similar to a clinical situation. It offers better conformity than an ITV strategy, but might further benefit from more precise patient positioning and breath control systems.