“…Recently, a number of studies have been performed using IMPT to treat lung cancer with 4D robust optimization 19,[49][50][51][52] instead of the previous 3D robust optimization without breathing motion considered. 19,49,[51][52][53] The 4D robust optimization involves full 4D-CT-based planning, while 3D robust optimization is planned on 4D-averaged CTs.…”
Purpose
Intensity‐modulated proton therapy (IMPT) is sensitive to uncertainties from patient setup and proton beam range, as well as interplay effect. In addition, respiratory motion may vary from cycle to cycle, and also from day to day. These uncertainties can severely degrade the original plan quality and potentially affect patient’s outcome. In this work, we developed a new tool to comprehensively consider the impact of all these uncertainties and provide plan robustness evaluation under them.
Methods
We developed a comprehensive plan robustness evaluation tool that considered both uncertainties from patient setup and proton beam range, as well as respiratory motion simultaneously. To mimic patients' respiratory motion, the time spent in each phase was randomly sampled based on patient‐specific breathing pattern parameters as acquired during the four‐dimensional (4D)‐computed tomography (CT) simulation. Spots were then assigned to one specific phase according to the temporal relationship between spot delivery sequence and patients’ respiratory motion. Dose in each phase was calculated by summing contributions from all the spots delivered in that phase. The final 4D dynamic dose was obtained by deforming all doses in each phase to the maximum exhalation phase. Three hundred (300) scenarios (10 different breathing patterns with 30 different setup and range uncertainty scenario combinations) were calculated for each plan. The dose‐volume histograms (DVHs) band method was used to assess plan robustness. Benchmarking the tool as an application’s example, we compared plan robustness under both three‐dimensional (3D) and 4D robustly optimized IMPT plans for 10 nonrandomly selected patients with non‐small cell lung cancer.
Results
The developed comprehensive plan robustness tool had been successfully applied to compare the plan robustness between 3D and 4D robustly optimized IMPT plans for 10 lung cancer patients. In the presence of interplay effect with uncertainties considered simultaneously, 4D robustly optimized plans provided significantly better CTV coverage (D95%, P = 0.002), CTV homogeneity (D5%‐D95%, P = 0.002) with less target hot spots (D5%, P = 0.002), and target coverage robustness (CTV D95% bandwidth, P = 0.004) compared to 3D robustly optimized plans. Superior dose sparing of normal lung (lung Dmean, P = 0.020) favoring 4D plans and comparable normal tissue sparing including esophagus, heart, and spinal cord for both 3D and 4D plans were observed. The calculation time for all patients included in this study was 11.4 ± 2.6 min.
Conclusion
A comprehensive plan robustness evaluation tool was successfully developed and benchmarked for plan robustness evaluation in the presence of interplay effect, setup and range uncertainties. The very high efficiency of this tool marks its clinical adaptation, highly practical and versatile nature, including possible real‐time intra‐fractional interplay effect evaluation as a potential application for future use.
“…Recently, a number of studies have been performed using IMPT to treat lung cancer with 4D robust optimization 19,[49][50][51][52] instead of the previous 3D robust optimization without breathing motion considered. 19,49,[51][52][53] The 4D robust optimization involves full 4D-CT-based planning, while 3D robust optimization is planned on 4D-averaged CTs.…”
Purpose
Intensity‐modulated proton therapy (IMPT) is sensitive to uncertainties from patient setup and proton beam range, as well as interplay effect. In addition, respiratory motion may vary from cycle to cycle, and also from day to day. These uncertainties can severely degrade the original plan quality and potentially affect patient’s outcome. In this work, we developed a new tool to comprehensively consider the impact of all these uncertainties and provide plan robustness evaluation under them.
Methods
We developed a comprehensive plan robustness evaluation tool that considered both uncertainties from patient setup and proton beam range, as well as respiratory motion simultaneously. To mimic patients' respiratory motion, the time spent in each phase was randomly sampled based on patient‐specific breathing pattern parameters as acquired during the four‐dimensional (4D)‐computed tomography (CT) simulation. Spots were then assigned to one specific phase according to the temporal relationship between spot delivery sequence and patients’ respiratory motion. Dose in each phase was calculated by summing contributions from all the spots delivered in that phase. The final 4D dynamic dose was obtained by deforming all doses in each phase to the maximum exhalation phase. Three hundred (300) scenarios (10 different breathing patterns with 30 different setup and range uncertainty scenario combinations) were calculated for each plan. The dose‐volume histograms (DVHs) band method was used to assess plan robustness. Benchmarking the tool as an application’s example, we compared plan robustness under both three‐dimensional (3D) and 4D robustly optimized IMPT plans for 10 nonrandomly selected patients with non‐small cell lung cancer.
Results
The developed comprehensive plan robustness tool had been successfully applied to compare the plan robustness between 3D and 4D robustly optimized IMPT plans for 10 lung cancer patients. In the presence of interplay effect with uncertainties considered simultaneously, 4D robustly optimized plans provided significantly better CTV coverage (D95%, P = 0.002), CTV homogeneity (D5%‐D95%, P = 0.002) with less target hot spots (D5%, P = 0.002), and target coverage robustness (CTV D95% bandwidth, P = 0.004) compared to 3D robustly optimized plans. Superior dose sparing of normal lung (lung Dmean, P = 0.020) favoring 4D plans and comparable normal tissue sparing including esophagus, heart, and spinal cord for both 3D and 4D plans were observed. The calculation time for all patients included in this study was 11.4 ± 2.6 min.
Conclusion
A comprehensive plan robustness evaluation tool was successfully developed and benchmarked for plan robustness evaluation in the presence of interplay effect, setup and range uncertainties. The very high efficiency of this tool marks its clinical adaptation, highly practical and versatile nature, including possible real‐time intra‐fractional interplay effect evaluation as a potential application for future use.
“…The Particle Therapy Co-Operative Group (PTCOG) has recently recommended 4D robust optimization (4D RO) to mitigate the IMPT interplay effects in treatment planning for thoracic tumors (74). Owing to similar motion robustness and management considerations, the same recommendations are also highly relevant in GI cancers (75). 4D RO includes dosimetric objectives defined on the individual phases of the 4D-CT dataset in the cost function.…”
Section: D Robust Optimizationmentioning
confidence: 99%
“…4D RO includes dosimetric objectives defined on the individual phases of the 4D-CT dataset in the cost function. Based on reported 4D optimization methods, the CTV defined on the individual phases of the 4D-CT deliberately receives non-uniform doses, i.e., 4D RO creates hot and cold regions along the target motion direction on these 4D-CT phases (39,46,75). But, also by design, the cumulative dose to the CTV over all 4D-CT phases can result in uniform coverage.…”
Section: D Robust Optimizationmentioning
confidence: 99%
“…But, also by design, the cumulative dose to the CTV over all 4D-CT phases can result in uniform coverage. It has been reported that compared to 3D RO, 4D RO produces significantly more robust and interplay-resistant plans for targets with comparable dose distributions for normal tissues in thoracic and distal esophageal malignancies (39,46), or generates plans with better sparing of normal tissues in hepatocellular carcinoma (75). A detailed review article recently compared 3D and 4D robust optimization (76).…”
In recent years, there has been rapid adaption of proton beam radiotherapy (RT) for treatment of various malignancies in the gastrointestinal (GI) tract, with increasing number of institutions implementing intensity modulated proton therapy (IMPT). We review the progress and existing literature regarding the technical aspects of RT planning for IMPT, and the existing tools that can help with the management of uncertainties which may impact the daily delivery of proton therapy. We provide an in-depth discussion regarding range uncertainties, dose calculations, image guidance requirements, organ and body cavity filling consideration, implanted devices and hardware, use of fiducials, breathing motion evaluations and both active and passive motion management methods, interplay effect, general IMPT treatment planning considerations including robustness plan evaluation and optimization, and finally plan monitoring and adaptation. These advances have improved confidence in delivery of IMPT for patients with GI malignancies under various scenarios.
“…Tumors in the thorax and abdomen are strongly affected by respiratory motion and its variability [6,7]. Therefore, treatment methods have been developed in attempt to handle tumor motion during radiotherapy including gating, ITVs, rescanning, tumor tracking [3,8] and 4D optimization [9], as well as robust optimization [10][11][12].…”
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