Multiple-CT optimization of intensity-modulated proton therapy - Is it possible to eliminate adaptive planning?

Robustness evaluation of pencil beam scanning proton therapy treatment planning: A systematic review

Compared to conventional radiotherapy using X-rays, proton therapy, in principle, allows better conformity of the dose distribution to target volumes, at the cost of greater sensitivity to physical, anatomical, and positioning uncertainties. Robust planning, both in terms of plan optimization and evaluation, has gained high visibility in publications on the subject and is part of clinical practice in many centers. However, there is currently no consensus on the methods and parameters to be used for robust optimization or robustness evaluation. We propose to overcome this deficiency by following the modified Delphi consensus method. This method first requires a systematic review of the literature. We performed this review using the PubMed and Web Of Science databases, via two different experts. Potential conflicts were resolved by a third expert. We then explored the different methods before focusing on clinical studies that evaluate robustness on a significant number of patients. Many robustness assessment methods are proposed in the literature. Some are more successful than others and their implementation varies between centers. Moreover, they are not all statistically or mathematically equivalent. The most sophisticated and rigorous methods have seen more limited application due to the difficulty of their implementation and their lack of widespread availability.

Effectiveness of robust optimization against geometric uncertainties in TomoHelical planning for prostate cancer

BACKGROUND

Geometrical uncertainties in patients can severely affect the quality of radiotherapy.

PURPOSE

We evaluated the dosimetric efficacy of robust optimization for helical intensity-modulated radiotherapy (IMRT) planning in the presence of patient setup uncertainty and anatomical changes.

METHODS

Two helical IMRT plans for 10 patients with localized prostate cancer were created using either minimax robust optimization (robust plan) or a conventional planning target volume (PTV) margin approach (PTV plan). Plan robustness was evaluated by creating perturbed dose plans with setup uncertainty from isocenter shifts and anatomical changes due to organ variation. The magnitudes of the geometrical uncertainties were based on the patient setup uncertainty considered during robust optimization, which was identical to the PTV margin. The homogeneity index, and target coverage (TC, defined as the V100% of the clinical target volume), and organs at risk (OAR; rectum and bladder) doses were analyzed for all nominal and perturbed plans. A statistical t-test was performed to evaluate the differences between the robust and PTV plans.

RESULTS

Comparison of the nominal plans showed that the robust plans had lower OAR doses and a worse homogeneity index and TC than the PTV plans. The evaluations of robustness that considered setup errors more than the PTV margin demonstrated that the worst-case perturbed scenarios for robust plans had significantly higher TC while maintaining lower OAR doses. However, when anatomical changes were considered, improvement in TC from robust optimization was not observed in the worst-case perturbed plans.

CONCLUSIONS

For helical IMRT planning in localized prostate cancer, robust optimization provides benefits over PTV margin-based planning, including better OAR sparing, and increased robustness against systematic patient-setup errors.

SWFT-Net: a deep learning framework for efficient fine-tuning spot weights towards adaptive proton therapy

Objective. One critical task for adaptive proton therapy is how to perform spot weight re-tuning and reoptimize plan, both of which are time-consuming and labor intensive. We proposed a deep learning framework (SWFT-Net) to speed up such a task, a starting point for us to move towards online adaptive proton therapy.Approach. For a H&N patient case, a reference intensity modulated proton therapy plan was generated. For data augmentation, spot weights were modified to generate three datasets (DS10, DS30, DS50), corresponding to different levels of weight adjustment. For each dataset, the samples were split into the training and testing groups at a ratio of 8:2 (6400 for training, 1706 for testing). To ease the difficulty of machine learning, the residuals of dose maps and spot weights (i.e. difference relative to a reference) were used as inputs and outputs, respectively. Quantitative analyses were performed in terms of normalized root mean square error (NRMSE) of spot weights, Gamma passing rate and dose difference within the PTV.Main results. The SWFT-Net is able to generate an adapted plan in less than a second with a NVIDIA GeForce RTX 3090 GPU. For the 1706 samples in the testing dataset, the NRMSE is 0.41% (DS10), 1.05% (DS30) and 2.04% (DS50), respectively. Cold/hot spots in the dose maps after adaptation are observed. The mean relative dose difference is 0.64% (DS10), 0.92% (DS30) and 0.88% (DS50), respectively. For all three datasets, the mean Gamma passing rate is consistently over 95% for both 1 mm/1% and 3 mm/3% settings.Significance. The proposed SWFT-Net is a promising tool to help realize adaptive proton therapy. It can be used as an alternative tool to other spot fine-tuning optimization algorithms, likely demonstrating superior performance in terms of speed, accuracy, robustness and minimum human interaction. This study lays down a foundation for us to move further incorporating other factors such as daily anatomical changes and propagated PTVs, and develop a truly online adaptive workflow in proton therapy.

Evaluating Proton Dose and Associated Range Uncertainty Using Daily Cone-Beam CT

Purpose

This study aimed to quantitatively evaluate the range uncertainties that arise from daily cone-beam CT (CBCT) images for proton dose calculation compared to CT using a measurement-based technique.

Methods

For head and thorax phantoms, wedge-shaped intensity-modulated proton therapy (IMPT) treatment plans were created such that the gradient of the wedge intersected and was measured with a 2D ion chamber array. The measured 2D dose distributions were compared with 2D dose planes extracted from the dose distributions using the IMPT plan calculated on CT and CBCT. Treatment plans of a thymoma cancer patient treated with breath-hold (BH) IMPT were recalculated on 28 CBCTs and 9 CTs, and the resulting dose distributions were compared.

Results

The range uncertainties for the head phantom were determined to be 1.2% with CBCT, compared to 0.5% for CT, whereas the range uncertainties for the thorax phantom were 2.1% with CBCT, compared to 0.8% for CT. The doses calculated on CBCT and CT were similar with similar anatomy changes. For the thymoma patient, the primary source of anatomy change was the BH uncertainty, which could be up to 8 mm in the superior-inferior (SI) direction.

Conclusion

We developed a measurement-based range uncertainty evaluation method with high sensitivity and used it to validate the accuracy of CBCT-based range and dose calculation. Our study demonstrated that the CBCT-based dose calculation could be used for daily dose validation in selected proton patients.

Report of AAPM Task Group 290: Respiratory motion management for particle therapy

Dose uncertainty induced by respiratory motion remains a major concern for treating thoracic and abdominal lesions using particle beams. This Task Group report reviews the impact of tumor motion and dosimetric considerations in particle radiotherapy, current motion‐management techniques, and limitations for different particle‐beam delivery modes (i.e., passive scattering, uniform scanning, and pencil‐beam scanning). Furthermore, the report provides guidance and risk analysis for quality assurance of the motion‐management procedures to ensure consistency and accuracy, and discusses future development and emerging motion‐management strategies. This report supplements previously published AAPM report TG76, and considers aspects of motion management that are crucial to the accurate and safe delivery of particle‐beam therapy. To that end, this report produces general recommendations for commissioning and facility‐specific dosimetric characterization, motion assessment, treatment planning, active and passive motion‐management techniques, image guidance and related decision‐making, monitoring throughout therapy, and recommendations for vendors. Key among these recommendations are that: (1) facilities should perform thorough planning studies (using retrospective data) and develop standard operating procedures that address all aspects of therapy for any treatment site involving respiratory motion; (2) a risk‐based methodology should be adopted for quality management and ongoing process improvement.

Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field

Lung cancer treatment is constantly evolving due to technological advances in the delivery of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment plan with the goal of improving the dose distribution to the patient due to anatomic or physiologic deviations from the initial simulation. The implementation of ART for lung cancer is widely varied with limited consensus on who to adapt, when to adapt, how to adapt, and what the actual benefits of adaptation are. ART for lung cancer presents significant challenges due to the nature of the moving target, tumor shrinkage, and complex dose accumulation because of plan adaptation. This article presents an overview of the current state of the field in ART for lung cancer, specifically, probing topics of: patient selection for the greatest benefit from adaptation, models which predict who and when to adapt plans, best timing for plan adaptation, optimized workflows for implementing ART including alternatives to re-simulation, the best radiation techniques for ART including magnetic resonance guided treatment, algorithms and quality assurance, and challenges and techniques for dose reconstruction. To date, the clinical workflow burden of ART is one of the major reasons limiting its widespread acceptance. However, the growing body of evidence demonstrates overwhelming support for reduced toxicity while improving tumor dose coverage by adapting plans mid-treatment, but this is offset by the limited knowledge about tumor control. Progress made in predictive modeling of on-treatment tumor shrinkage and toxicity, optimizing the timing of adaptation of the plan during the course of treatment, creating optimal workflows to minimize staffing burden, and utilizing deformable image registration represent ways the field is moving toward a more uniform implementation of ART.

Executive Summary of Clinical and Technical Guidelines for Esophageal Cancer Proton Beam Therapy From the Particle Therapy Co-Operative Group Thoracic and Gastrointestinal Subcommittees

Radiation therapy (RT) is an integral component of potentially curative management of esophageal cancer (EC). However, RT can cause significant acute and late morbidity due to excess radiation exposure to nearby critical organs, especially the heart and lungs. Sparing these organs from both low and high radiation dose has been demonstrated to achieve clinically meaningful reductions in toxicity and may improve long-term survival. Accruing dosimetry and clinical evidence support the consideration of proton beam therapy (PBT) for the management of EC. There are critical treatment planning and delivery uncertainties that should be considered when treating EC with PBT, especially as there may be substantial motion-related interplay effects. The Particle Therapy Co-operative Group Thoracic and Gastrointestinal Subcommittees jointly developed guidelines regarding patient selection, treatment planning, clinical trials, and future directions of PBT for EC.

A Review of the Robust Optimization Process and Advances with Monte Carlo in the Proton Therapy Management of Head and Neck Tumors

In intensity-modulated proton therapy, robust optimization processes have been developed to manage uncertainties associated with (1) range, (2) setup, (3) anatomic changes, (4) dose calculation, and (5) biological effects. Here we review our experience using a robust optimization technique that directly incorporates range and setup uncertainties into the optimization process to manage those sources of uncertainty. We also review procedures for implementing adaptive planning to manage the anatomic uncertainties. Finally, we share some early experiences regarding the impact of uncertainties in dose calculation and biological effects, along with techniques to manage and potentially reduce these uncertainties.

Anatomic changes in head and neck intensity-modulated proton therapy: Comparison between robust optimization and online adaptation

BACKGROUND/PURPOSE

Setup variations and anatomical changes can severely affect the quality of head and neck intensity-modulated proton therapy (IMPT) treatments. The impact of these changes can be alleviated by increasing the plan's robustness a priori, or by adapting the plan online. This work compares these approaches in the context of head and neck IMPT.

MATERIALS/METHODS

A representative cohort of 10 head and neck squamous cell carcinoma (HNSCC) patients with daily cone-beam computed tomography (CBCT) was evaluated. For each patient, three IMPT plans were created: 1- a classical robust optimization (cRO) plan optimized on the planning CT, 2- an anatomical robust optimization (aRO) plan additionally including the two first daily CBCTs and 3- a plan optimized without robustness constraints, but online-adapted (OA) daily, using a constrained spot intensity re-optimization technique only.

RESULTS

The cumulative dose following OA fulfilled the clinical objective of both the high-risk and low-risk clinical target volumes (CTV) coverage in all 10 patients, compared to 8 for aRO and 4 for cRO. aRO did not significantly increase the dose to most organs at risk compared to cRO, although the integral dose was higher. OA significantly reduced the integral dose to healthy tissues compared to both robust methods, while providing equivalent or superior target coverage.

CONCLUSION

Using a simple spot intensity re-optimization, daily OA can achieve superior target coverage and lower dose to organs at risk than robust optimization methods.

Anatomically robust proton therapy using multiple planning computed tomography scans for locally advanced prostate cancer

BACKGROUND

Proton therapy (PT) is sensitive towards anatomical changes that may occur during a treatment course. The aim of this study was to investigate if anatomically robust PT (ARPT) plans incorporating patient-specific target motion improved target coverage while still sparing normal tissues, when applied on locally advanced prostate cancer patients where pelvic irradiation is indicated.

MATERIAL AND METHODS

A planning computed tomography (CT) scan used for dose calculation and two additional CTs (acquired on different days) were used to make patient-specific targets for the ARPT plans on the eight included patients. The plans were compared to a conventional robust PT plan and a volumetric modulated arc therapy (VMAT) photon plan, which were derived from the planning CT (pCT). Worst-case robust optimisation was used for all proton plans with a setup uncertainty of 5 mm and a range uncertainty of 3.5%. Target coverage (V95% and D95%) and normal tissue doses (V5-75 Gy) were evaluated on 6-8 rCTs per patient.

RESULTS

The ARPT plans improved the prostate target coverage for the most challenging patient compared to conventional robust PT plans (20% point increase for V95% and 31 Gy increase for D95%). Across the whole cohort the estimated mean value for V95% was 97% for the ARPT plans and 95% for the conventional robust PT plans. The ARPT plans had a slight, statistically insignificant increase in normal tissue doses compared to the conventional robust proton plans. Compared to VMAT, the ARPT plans significantly reduced the normal tissue doses in the low-to-intermediate dose range.

CONCLUSIONS

While both proton plans reduced the low-to-intermediate normal tissue doses compared to VMAT, ARPT plans improved the target coverage for the most challenging patient without significantly increasing the normal tissue doses compared to conventional robust PT plans.

Impact of bowel and rectum air on target dose with robustly optimized intensity-modulated proton therapy plans

PURPOSE

Pelvic target dose from intensity-modulated proton therapy (IMPT) is sensitive to patient bowel motion. Robustly optimized plans in regard to bowel filling may improve the dose coverage in the treatment course. Our purpose is to investigate the effect of air volume in large and small bowel and rectum on target dose from IMPT plans.

METHODS AND MATERIAL

Data from 17 cancer patients (11 prostate, 3 gynecologic, 2 colon, and 1 embryonal rhabdomyosarcoma) with planning CT (pCT) and weekly or biweekly scanned quality assurance CTs (QACTs; 82 QACT scans total) were studied. Air in bowels and rectum traversed by proton pencil beams was contoured. The robust treatment plan was made by using 3 CT sets: the pCT set and 2 virtual CT sets that were copies of pCT but in which the fillings of bowels and rectum were overridden to be either air or muscle. Each plan had 2-5 beams with a mean of 3 beams. Targets in the pCT were mapped to the QACTs by deformable image registration, and the dose in QACTs was calculated. Dose coverage (D99 and D95) and correlations between dose coverage and changes in air volume were analyzed. The significance of the correlation was analyzed by t test.

RESULTS

Mean changes of D99 in QACTs were within 3% of those in the pCT for all prostate and colon cases but >3% in 2 of the 3 gynecologic cases and in the embryonal rhabdomyosarcoma case. Of these three cases with mean change of D99 > 3%, air volume may be the main cause in 2. For the prostate cases, correlation coefficients were <0.7 between change in air volume and change in D99 and D95, because other anatomy changes also contributed to dose deviation. Correlation coefficients in the non-prostate cases were >0.9 between D99 change and rectum and between D95 change and small bowel, indicating a greater effect of the air volume on target dose.

CONCLUSION

The air volume may still have an important effect on target dose coverage in treatment plans using 3 CT sets, particularly when the air is traversed by multiple beams.

Multiple Computed Tomography Robust Optimization to Account for Random Anatomic Density Variations During Intensity Modulated Proton Therapy

Purpose

To propose a method of optimizing intensity modulated proton therapy (IMPT) plans robust against dosimetric degradation caused by random anatomic variations during treatment.

Methods and Materials

Fifteen patients with prostate cancer treated with IMPT to the pelvic targets were nonrandomly selected. On the repeated quality assurance computed tomography (QACTs) for some patients, bowel density changes were observed and caused dose degradation because the treated plans were not robustly optimized (non-RO). To mitigate this effect, we developed a robust planning method based on 3 CT images, including the native planning CT and its 2 copies, with the bowel structures being assigned to air and tissue, respectively. The RO settings included 5 mm setup uncertainty and 3.5% range uncertainty on 3 CTs. This method is called pseudomultiple-CT RO (pMCT-RO). Plans were also generated using RO on the native CT only, with the same setup and range uncertainties. This method is referred to as single-CT RO (SCT-RO). Doses on the QACTs and the nominal planning CT were compared for the 3 planning methods.

Results

All 3 plan methods provided sufficient clinical target volumes D95% and V95% on the QACTs. For pMCT-RO plans, the normal tissue D_max on QACTs of all patients was at maximum 109.1%, compared with 144.4% and 116.9% for non-RO and SCT-RO plans, respectively. On the nominal plans, the rectum and bladder doses were similar among all 3 plans; however, the volume of normal tissue (excluding the rectum and bladder) receiving the prescription dose or higher is substantially reduced in either pMCT-RO plans or SCT-RO plans, compared with the non-RO plans.

Conclusions

We developed a robust optimization method to further mitigate undesired dose heterogeneity caused by random anatomic changes in pelvic IMPT treatment. This method does not require additional patient CT scans. The pMCT-RO planning method has been implemented clinically since 2017 in our center.

Anatomic change over the course of treatment for non-small cell lung cancer patients and its impact on intensity-modulated radiation therapy and passive-scattering proton therapy deliveries

Purpose

To quantify tumor anatomic change of non-small cell lung cancer (NSCLC) patients given passive-scattering proton therapy (PSPT) and intensity-modulated radiation therapy (IMRT) through 6–7 weeks of treatment, and analyze the correlation between anatomic change and the need to adopt adaptive radiotherapy (ART).

Materials and methods

Weekly 4D CT sets of 32 patients (8/8 IMRT with/without ART, 8/8 PSPT with/without ART) acquired during treatment, were registered to the planning CT using an in-house developed deformable registration algorithm. The anatomic change was quantified as the mean variation of the region of interest (ROI) relative to the planning CT by averaging the magnitude of deformation vectors of all voxels within the ROI contour. Mean variations of GTV and CTV were compared between subgroups classified by ART status and treatment modality using the independent t-test. Logistic regression analysis was performed to clarify the effect of anatomic change on the probability of ART adoption.

Results

There was no significant difference (p = 0.679) for the time-averaged mean CTV variations from the planning CT between IMRT (7.61 ± 2.80 mm) and PSPT (7.21 ± 2.67 mm) patients. However, a significant difference (p = 0.001) was observed between ART (8.93 ± 2.19 mm) and non-ART (5.90 ± 2.33 mm) patients, when treatment modality was not considered. Mean CTV variation from the planning CT in all patients increases significantly (p < 0.001), with a changing rate of 1.77 mm per week. Findings for the GTV change was similar. The logistic regression model correctly predicted 71.9% of cases in ART adoption. The correlation is stronger in the PSPT group with a pseudo R² value of 0.782, compared to that in the IMRT group (pseudo R² = 0.182).

Conclusion

The magnitude of target volume variation over time could be greater than the usual treatment margin. Mean target volume variation from the planning position can be used to identify lung cancer patients that may need ART.

Online daily adaptive proton therapy

It is recognized that the use of a single plan calculated on an image acquired some time before the treatment is generally insufficient to accurately represent the daily dose to the target and to the organs at risk. This is particularly true for protons, due to the physical finite range. Although this characteristic enables the generation of steep dose gradients, which is essential for highly conformal radiotherapy, it also tightens the dependency of the delivered dose to the range accuracy. In particular, the use of an outdated patient anatomy is one of the most significant sources of range inaccuracy, thus affecting the quality of the planned dose distribution. A plan should be ideally adapted as soon as anatomical variations occur, ideally online. In this review, we describe in detail the different steps of the adaptive workflow and discuss the challenges and corresponding state-of-the art developments in particular for an online adaptive strategy.

Quantification of plan robustness against different uncertainty sources for classical and anatomical robust optimized treatment plans in head and neck cancer proton therapy

OBJECTIVE

Classical robust optimization (cRO) in intensity-modulated proton therapy (IMPT) considers isocenter position and particle range uncertainties; anatomical robust optimization (aRO) aims to consider additional non-rigid positioning variations. This work compares the influence of different uncertainty sources on the robustness of cRO and aRO IMPT plans for head and neck squamous cell carcinoma (HNSCC).

METHODS

Two IMPT plans were optimized for 20 HNSCC patients who received weekly control CTs (cCT): cRO, using solely the planning CT, and aRO, including 2 additional cCTs. The robustness of the plans in terms of clinical target volume (CTV) coverage and organ at risk (OAR) sparing was analyzed considering stepwise the influence of (1) non-rigid anatomical variations given by the weekly cCT, (2) with fraction-wise added rigid random setup errors and (3) additional systematic proton range uncertainties.

RESULTS

cRO plans presented significantly higher nominal CTV coverage but are outperformed by aRO plans when considering non-rigid anatomical variations only, as cRO and aRO plans presented a median target coverage (D98%) decrease for the low-risk/high-risk CTV of 1.8/1.1 percentage points (pp) and -0.2 pp/-0.3 pp, respectively. Setup and range uncertainties had larger influence on cRO CTV coverage, but led to similar OAR dose changes in both plans. Considering all error sources, 10/2 cRO/aRO patients missed the CTV coverage and a limited number exceeded some OAR constraints in both plans.

CONCLUSION

Non-rigid anatomical variations are mainly responsible for critical target coverage loss of cRO plans, whereas the aRO approach was robust against such variations. Both plans provide similar robustness of OAR parameters.

ADVANCES IN KNOWLEDGE

The influence of different uncertainty sources was quantified for robust IMPT HNSCC plans.

Multiple-CT optimization: An adaptive optimization method to account for anatomical changes in intensity-modulated proton therapy for head and neck cancers

PURPOSE

We aimed to determine whether multiple-CT (MCT) optimization of intensity-modulated proton therapy (IMPT) could improve plan robustness to anatomical changes and therefore reduce the additional need for adaptive planning.

METHODS AND MATERIALS

Ten patients with head and neck cancer who underwent IMPT were included in this retrospective study. Each patient had primary planning CT (PCT), a first adaptive planning CT (ACT1), and a second adaptive planning CT (ACT2). Selective robust IMPT plans were generated using each CT data set (PCT, ACT1, and ACT2). Moreover, a MCT optimized plan was generated using the PCT and ACT1 data sets together. Dose distributions optimized using each of the four plans (PCT, ACT1, ACT2, and MCT plans) were re-calculated on ACT2 data. The doses to the target and to organs at risk were compared between optimization strategies.

RESULTS

MCT plans for all patients met all target dose and organs-at-risk criteria for all three CT data sets. Target dose and organs-at-risk dose for PCT and ACT1 plans re-calculated on ACT2 data set were compromised, indicating the need for adaptive planning on ACT2 if PCT or ACT1 plans were used. The D98% of CTV1 and CTV3 of MCT plan re-calculated on ACT2 were both above the coverage criteria. The CTV2 coverage of the MCT plan re-calculated on ACT2 was worse than ACT2 plan. The MCT plan re-calculated on ACT2 data set had lower chiasm, esophagus, and larynx doses than did PCT, ACT1, or ACT2 plans re-calculated on ACT2 data set.

CONCLUSIONS

MCT optimization can improve plan robustness toward anatomical change and may reduce the number of plan adaptation for head and neck cancers.

Daily adaptive proton therapy - the key to innovative planning approaches for paranasal cancer treatments

Background: For proton therapy of paranasal tumors, field directions avoiding volumes that might change during therapy are typically used. If the plan is optimized on the daily anatomy using daily adapted proton therapy (DAPT) however, field directions crossing the nasal cavities might be feasible. In this study, we investigated the effectiveness of DAPT for enabling narrow-field treatment approaches. Material and methods: For five paranasal tumor patients, representing a wide patient spectrum, anatomically robust 4-field-star and narrow-field plans were calculated and their robustness to anatomical and setup uncertainties was compared with and without DAPT. Based on the nominal planning CTs, per patient up to 125 simulated CTs (simCTs) with different nasal cavity fillings were created and random translations and rotations due to patient setup uncertainties were further simulated. Plans were recalculated or re-optimized on all error scenarios, representing non-adapted and DAPT fractions, respectively. From these, 100 possible treatments (60 GyRBE, 30 fx) were simulated and changes in integral dose, target and organs at risk (OARs) doses evaluated. Results: In comparison to the 4-field-star approach, the use of narrow-fields reduced integral dose between 29% and 56%. If OARs did not overlap with the target, OAR doses were also reduced. Finally, the significantly reduced target coverage in non-adapted treatments (mean V95 reductions of up to 34%) could be almost fully restored with DAPT in all cases (differences <1%). Conclusions: DAPT was found to be not only an effective way to increase plan robustness to anatomical and positional uncertainties, but also opened the possibility to use improved and more conformal field arrangements.

Effect of setup and inter-fraction anatomical changes on the accumulated dose in CT-guided breath-hold intensity modulated proton therapy of liver malignancies

PURPOSE

To evaluate the effect of setup uncertainties including uncertainties between different breath holds (BH) and inter-fractional anatomical changes under CT-guided BH with intensity-modulated proton therapy (IMPT) in patients with liver cancer.

METHODS AND MATERIALS

This retrospective study considered 17 patients with liver tumors who underwent feedback-guided BH (FGBH) IMRT treatment with daily CT-on-rail imaging. Planning CT images were acquired at simulation using FGBH, and FGBH CT-on-rail images were also acquired prior to each treatment. Selective robust IMPT plans were generated using planning CT and re-calculated on each daily CT-on-rail image. Subsequently, the fractional doses were deformed and accumulated onto the planning CT according to the deformable image registration between daily and planning CTs. The doses to the target and organs at risk (OARs) were compared between IMRT, planned IMPT, and accumulated IMPT doses.

RESULTS

For IMPT plans, the mean of D_98% of CTV for all 17 patients was slightly reduced from the planned dose of 68.90 ± 1.61 Gy to 66.48 ± 1.67 Gy for the accumulated dose. The target coverage could be further improved by adjusting planning techniques. The dose-volume histograms of both planned and accumulated IMPT doses showed better sparing of OARs than that of the IMRT.

CONCLUSIONS

IMPT with FGBH and CT-on-rail guidance is a robust treatment approach for liver tumor cases.

Concepts of PTV and Robustness in Passively Scattered and Pencil Beam Scanning Proton Therapy

Concepts of planning target volume and plan robustness in proton therapy are described. Implementation of these concepts into treatment planning is described. Proton plan sensitivity and interfractional and intrafractional anatomical variation are also discussed.

Power-law relationship in the long-tailed sections of proton dose distributions

The halo portion of a proton therapy dose creates a long tail in proton dose distributions, but so far study of this phenomenon has been limited. We used statistical methods and mathematical models to confirm that the long-tailed portion of proton dose distributions exhibits a power-law relationship. By analyzing 299 measured dose profiles, we found that all proton lateral dose distributions had a significant power-law scaling correlation with a high correlation coefficient in the tail. We set up a dual-mechanism model, containing both direct and indirect impact mechanisms. In the direct impact mechanism, the proximal dose deposition is mainly due to the direct impact of a proton on a particle. In the indirect mechanism, the impact of a proton on a given particle is considered in terms of the proton’s impact on a neighboring particle that then impacts the given particle. We found that the indirect impact mechanism led to a tail in the distribution exhibiting a power-law relationship because the probability of the indirect impacts was proportional to the distance; i.e., the longer the distance, the larger the indirect impact probability. Upon analyzing the experimental data, we observed that the power-law exponent increased with proton energy.