Dose uncertainties in IMPT for oropharyngeal cancer in the presence of anatomical, range, and setup errors

Quantifying dose uncertainties resulting from cardiorespiratory motion in intensity-modulated proton therapy for cardiac stereotactic body radiotherapy

Background

Cardiac stereotactic body radiotherapy (CSBRT) with photons efficaciously and safely treats cardiovascular arrhythmias. Proton therapy, with its unique physical and radiobiological properties, can offer advantages over traditional photon-based therapies in certain clinical scenarios, particularly pediatric tumors and those in anatomically challenging areas. However, dose uncertainties induced by cardiorespiratory motion are unknown.

Objective

This study investigated the effect of cardiorespiratory motion on intensity-modulated proton therapy (IMPT) and the effectiveness of motion-encompassing methods.

Methods

We retrospectively included 12 patients with refractory arrhythmia who underwent CSBRT with four-dimensional computed tomography (4DCT) and 4D cardiac CT (4DcCT). Proton plans were simulated using an IBA accelerator based on the 4D average CT. The prescription was 25 Gy in a single fraction, with all plans normalized to ensure that 95% of the target volume received the prescribed dose. 4D dose reconstruction was performed to generate 4D accumulated and dynamic doses. Furthermore, dose uncertainties due to the interplay effect of the substrate target and organs at risk (OARs) were assessed. The differences between internal organs at risk volume (IRV) and OARreal (manually contoured on average CT) were compared. In 4D dynamic dose, meeting prescription requirements entails V25 and D95 reaching 95% and 25 Gy, respectively.

Results

The 4D dynamic dose significantly differed from the 3D static dose. The mean V25 and D95 were 89.23% and 24.69 Gy, respectively, in 4DCT and 94.35% and 24.99 Gy, respectively, in 4DcCT. Eleven patients in 4DCT and six in 4DcCT failed to meet the prescription requirements. Critical organs showed varying dose increases. All metrics, except for Dmean and D50, significantly changed in 4DCT; in 4DcCT, only D50 remained unchanged with regards to the target dose uncertainties induced by the interplay effect. The interplay effect was only significant for the Dmax values of several OARs. Generally, respiratory motion caused a more pronounced interplay effect than cardiac pulsation. Neither IRV nor OARreal effectively evaluated the dose discrepancies of the OARs.

Conclusions

Complex cardiorespiratory motion can introduce dose uncertainties during IMPT. Motion-encompassing techniques may mitigate but cannot entirely compensate for the dose discrepancies. Individualized 4D dose assessments are recommended to verify the effectiveness and safety of CSBRT.

Using the gamma-index analysis for inter-fractional comparison of in-beam PET images for head-and-neck treatment monitoring in proton therapy: A Monte Carlo simulation study

GOAL

In-beam Positron Emission Tomography (PET) is a technique for in-vivo non-invasive treatment monitoring for proton therapy. To detect anatomical changes in patients with PET, various analysis methods exist, but their clinical interpretation is problematic. The goal of this work is to investigate whether the gamma-index analysis, widely used for dose comparisons, is an appropriate tool for comparing in-beam PET distributions. Focusing on a head-and-neck patient, we investigate whether the gamma-index map and the passing rate are sensitive to progressive anatomical changes.

METHODS/MATERIALS

We simulated a treatment course of a proton therapy patient using FLUKA Monte Carlo simulations. Gradual emptying of the sinonasal cavity was modeled through a series of artificially modified CT scans. The in-beam PET activity distributions from three fields were evaluated, simulating a planar dual head geometry. We applied the 3D-gamma evaluation method to compare the PET images with a reference image without changes. Various tolerance criteria and parameters were tested, and results were compared to the CT-scans.

RESULTS

Based on 210 MC simulations we identified appropriate parameters for the gamma-index analysis. Tolerance values of 3 mm/3% and 2 mm/2% were suited for comparison of simulated in-beam PET distributions. The gamma passing rate decreased with increasing volume change for all fields.

CONCLUSION

The gamma-index analysis was found to be a useful tool for comparing simulated in-beam PET images, sensitive to sinonasal cavity emptying. Monitoring the gamma passing rate behavior over the treatment course is useful to detect anatomical changes occurring during the treatment course.

Synthetic CT imaging for PET monitoring in proton therapy: a simulation study

Objective.This study addresses a fundamental limitation of in-beam positron emission tomography (IB-PET) in proton therapy: the lack of direct anatomical representation in the images it produces. We aim to overcome this shortcoming by pioneering the application of deep learning techniques to create synthetic control CT images (sCT) from combining IB-PET and planning CT scan data.Approach.We conducted simulations involving six patients who underwent irradiation with proton beams. Leveraging the architecture of a visual transformer (ViT) neural network, we developed a model to generate sCT images of these patients using the planning CT scans and the inter-fractional simulated PET activity maps during irradiation. To evaluate the model's performance, a comparison was conducted between the sCT images produced by the ViT model and the authentic control CT images-serving as the benchmark.Main results.The structural similarity index was computed at a mean value across all patients of 0.91, while the mean absolute error measured 22 Hounsfield Units (HU). Root mean squared error and peak signal-to-noise ratio values were 56 HU and 30 dB, respectively. The Dice similarity coefficient exhibited a value of 0.98. These values are comparable to or exceed those found in the literature. More than 70% of the synthetic morphological changes were found to be geometrically compatible with the ones reported in the real control CT scan.Significance.Our study presents an innovative approach to surface the hidden anatomical information of IB-PET in proton therapy. Our ViT-based model successfully generates sCT images from inter-fractional PET data and planning CT scans. Our model's performance stands on par with existing models relying on input from cone beam CT or magnetic resonance imaging, which contain more anatomical information than activity maps.

SISS-MCO: large scale sparsity-induced spot selection for fast and fully-automated robust multi-criteria optimisation of proton plans

Objective.Intensity modulated proton therapy (IMPT) is an emerging treatment modality for cancer. However, treatment planning for IMPT is labour-intensive and time-consuming. We have developed a novel approach for multi-criteria optimisation (MCO) of robust IMPT plans (SISS-MCO) that is fully automated and fast, and we compare it for head and neck, cervix, and prostate tumours to a previously published method for automated robust MCO (IPBR-MCO, van de Water 2013).Approach.In both auto-planning approaches, the applied automated MCO of spot weights was performed with wish-list driven prioritised optimisation (Breedveld 2012). In SISS-MCO, spot weight MCO was applied once for every patient after sparsity-induced spot selection (SISS) for pre-selection of the most relevant spots from a large input set of candidate spots. IPBR-MCO had several iterations of spot re-sampling, each followed by MCO of the weights of the current spots.Main results.Compared to the published IPBR-MCO, the novel SISS-MCO resulted in similar or slightly superior plan quality. Optimisation times were reduced by a factor of 6 i.e. from 287 to 47 min. Numbers of spots and energy layers in the final plans were similar.Significance.The novel SISS-MCO automatically generated high-quality robust IMPT plans. Compared to a published algorithm for automated robust IMPT planning, optimisation times were reduced on average by a factor of 6. Moreover, SISS-MCO is a large scale approach; this enables optimisation of more complex wish-lists, and novel research opportunities in proton therapy.

Considerations for study design in the DAHANCA 35 trial of protons versus photons for head and neck cancer

Proton radiotherapy offers a dosimetric advantage compared to photon therapy in sparing normal tissue, but the clinical evidence for toxicity reductions in the treatment of head and neck cancer is limited. The Danish Head and Neck Cancer Group (DAHANCA) has initiated the DAHANCA 35 randomised trial to clarify the value of proton therapy (NCT04607694). The DAHANCA 35 trial is performed in an enriched population of patients selected by an anticipated benefit of proton therapy to reduce the risk of late dysphagia or xerostomia based on normal tissue complication probability (NTCP) modelling. We present our considerations on the trial design and a test of the selection procedure conducted before initiating the randomised study.

Assessment of residual geometrical errors of clinical target volumes and their impact on dose accumulation for head and neck radiotherapy

PURPOSE

To assess the residual geometrical errors (dr) and their impact on the clinical target volumes (CTV) dose coverage for head and neck cancer (HNC) proton therapy patients.

METHODS

We analysed 28 HNC patients treated with 70 Gy (RBE) and 54.25 Gy (RBE) to the therapeutic CTV70 and prophylactic CTV54.25, respectively. Daily cone beam CTs were converted to high quality synthetic CTs (sCTs). The CTVs from the nominal CT were propagated to the corresponding sCTs using a hybrid deformable image registration (propagated CTVs) in RayStation 11B. For 11 patients, all propagated CTVs were reviewed by our HNC radiation oncologist (physician corrected CTVs). The residual geometrical error dr was quantified as a function of the daily CTVs volume overlap with the nominal plan CTV. The errors dr(propagated CTVs) and dr(physician corrected CTVs) and the difference in dice similarity coefficients (ΔDSC) were determined. Using clinical plans, dose coverage and the tumor control probability (TCP) for the nominal, accumulated and voxel-wise minimum scenarios were determined.

RESULTS

The difference in the residual geometrical error dr (propagated CTVs - physician corrected CTVs) and mean DSC (|ΔDSC|mean) were minor: Δdr(CTV70) = 0.16 mm, Δdr(CTV54.25) = 0.26 mm, |ΔDSC|mean < 0.9%. For all 28 patients, dr(CTV70) = 1.91 mm and dr(CTV54.25) = 1.90 mm. However, CTV54.25 above and below the cricoid cartilage differed substantially (1.00 mm c.f. 3.93 mm). The CTV54.25 coverage below the cricoid was then almost always lower, although the TCP of the accumulated dose was higher than the TCP of the voxel-wise minimum dose.

CONCLUSIONS

Setup uncertainty setting of 2 mm is possible. The feasibility of using propagated CTVs for error determination is demonstrated.

Advancing knowledge-based intensity modulated proton planning for adaptive treatment of high-risk prostate cancer

To assess the performance of a knowledge-based planning (KBP) model for generating intensity-modulated proton therapy (IMPT) treatment plans as part of an adaptive radiotherapy (ART) strategy for patients with high-risk prostate cancer. A knowledge-based planning (KBP) model for proton adaptive treatment plan generation was developed based on thirty patient treatment plans utilizing RapidPlanTM PT (Varian Medical Systems, Palo Alto, CA). The model was subsequently validated using an additional eleven patient cases. All patients in the study were administered a prescribed dose of 70.2 Gy to the prostate and seminal vesicle (CTV70.2), along with 46.8 Gy to the pelvic lymph nodes (CTV46.8) through simultaneous integrated boost (SIB) technique. To assess the quality of the validation knowledge-based proton plans (KBPPs), target coverage and organ-at-risk (OAR) dose-volume constraints were compared against those of clinically used expert plans using paired t-tests. The KBP model training statistics (R2) (mean ± SD, 0.763 ± 0.167, range, 0.406 to 0.907) and χ² values (1.162 ± 0.0867, 1.039-1.253) indicate acceptable model training quality. Moreover, the average total treatment planning optimization and calculation time for adaptive plan generation is approximately 10 minutes. The CTV70.2 D98% for the KBPPs (mean ± SD, 69.1 ± 0.08 Gy) and expert plans (69.9 ± 0.04 Gy) shows a significant difference (p < 0.05) but are both within 1.1 Gy of the prescribed dose which is clinically acceptable. While the maximum dose for some organs-at-risk (OARs) such as the bladder and rectum is generally higher in the KBPPs, the doses still fall within clinical constraints. Among all the OARs, most of them received comparable results to the expert plan, except the cauda equina Dmax, which shows statistical significance and was lower in the KBPPs than in expert plans (48.5 ± 0.06 Gy vs 49.3 ± 0.05 Gy). The generated KBPPs were clinically comparable to manually crafted plans by expert treatment planners. The adaptive plan generation process was completed within an acceptable timeframe, offering a quick same-day adaptive treatment option. Our study supports the integration of KBP as a crucial component of an ART strategy, including maintaining plan consistency, improving quality, and enhancing efficiency. This advancement in speed and adaptability promises more precise treatment in proton ART.

Daily Head and Neck Treatment Assessment for Optimal Proton Therapy Planning Robustness

Robust optimization in proton therapy ensures adequate target coverage; however, validation of fractional plan quality and setup uncertainty in patients has not been performed. We aimed to assess plan robustness on delivered head and neck proton plans classified into two categories: (1) primary only (PO) and (2) primary and neck nodal (PNN) coverage. Registration at the machine was utilized for daily CBCT to generate a synthetic CT. The dose for the clinical target volume (CTV) and organs at risk (OAR) was compared to the expected robustness bands using 3.5% range uncertainty and 3 mm vs. 5 mm setup uncertainty. The fractional deviation was defined as D95% and V100% outside of uncertainty constraints. About 203 daily fractions from 6 patients were included for analysis. The percentage of fractions that exceeded robustness calculations was greater in 3 mm as compared to 5 mm setup uncertainty for both CTV and OAR volumes. PO plans had clinically insignificant average fractional deviation, less than 1%, in delivered D95% and V100%. In comparison, PNN plans had up to 2.2% average fractional deviation in delivered V100% using 3 mm robustness. Given the need to balance dose accuracy with OAR sparing, we recommend the utilization of 3 mm setup uncertainty as an acceptable simulation of the dose delivered.

An uncertainty-incorporated method for fast beam angle selection in intensity-modulated proton therapy

Aim

We propose a novel metric called ψ - score to rank the Intensity Modulated Proton Therapy (IMPT) beams in the order of their optimality and robustness. The beams ranked based on this metric were accordingly chosen for IMPT optimization. The objective of this work is to study the effectiveness of the proposed method in various clinical cases.

Methods and Materials

We have used Pinnacle TPS (Philips Medical System V 16.2) for performing the optimization. To validate our approach, we have applied it in four clinical cases: Lung, Pancreas, Prostate+Node and Prostate. Basically, for all clinical cases, four set of plans were created using Multi field optimization (MFO) and Robust Optimization (RO) with same clinical objectives, namely (1) Conventional angle plan without Robust Optimization (CA Plan), (2) Suitable angle Plan without Robust Optimization (SA Plan), (3) Conventional angle plan with Robust Optimization (CA-RO Plan), (4) Suitable angle Plan with Robust Optimization (SA-RO Plan). Initial plan was generated with 20 equiangular beams starting from the gantry angle of 0°. In the corresponding SA Plan and SA-RO Plan, the beam angles were obtained using the guidance provided by ψ - score.

Results

All CA plans were compared against the SA plans in terms of Dose distribution, Dose volume histogram (DVH) and percentage of dose difference. The results obtained from the clinical cases indicate that the plan quality is considerably improved without significantly compromising the robustness when the beam angles are optimized using the proposed method. It takes approximately 10-15 min to find the suitable beam angles without Robust Optimization (RO), while it takes approximately 20-30 min to find the suitable beam angles with RO. However, the inclusion of RO in BAO did not result in a change in the final beam angles for anatomies other than lung.

Conclusion

The results obtained in different anatomic sites demonstrate the usefulness of our approach in improving the plan quality by determining optimal beam angles in IMPT.

Pre-treatment analysis of non-rigid variations can assist robust intensity-modulated proton therapy plan selection for head and neck patients

PURPOSE

To incorporate small non-rigid variations of head and neck patients into the robust evaluation of intensity-modulated proton therapy (IMPT) for the selection of robust treatment plans.

METHODS

A cohort of 20 nasopharynx cancer patients with weekly kilovoltage CT (kVCT) and 15 oropharynx cancer patients with weekly cone-beam CT (CBCT) were retrospectively included. Anatomical variations between week 0/week 1 of treatment were acquired using deformable image registration (DIR) for all 35 patients and then applied to the planning CT of four patients who have kVCT scanned each week to simulate potential small non-rigid variations (sNRVs). The robust evaluations were conducted on IMPT plans with: (1) different number of beam fields from 3-field to 5-field; (2) different beam angles. The robust evaluation before treatment, including the sNRVs and setup uncertainty, referred to as sNRV+R evaluation was compared with the conventional evaluation (without sNRVs) in terms of robustness consistency with the gold standard evaluation based on weekly CT.

RESULTS

Among four patients (490 scenarios), we observed a maximum difference in the sNRV+R evaluation to the nominal dose of: 9.37% dose degradation on D₉₅ of clinical target volumes (CTVs), increase in mean dose (D mean $_{\text{mean}}$ ) of parotid 11.87 Gy, increase in max dose (D max $_{\text{max}}$ ) of brainstem 20.82 Gy. In contrast, in conventional evaluation, we observed a maximum difference to the nominal dose of: 7.58% dose degradation on D₉₅ of the CTVs, increase in parotid D mean $_{\text{mean}}$ by 4.88 Gy, increase in brainstem D max $_{\text{max}}$ by 13.5 Gy. In the measurement of the robustness ranking consistency with the gold standard evaluation, the sNRV+R evaluation was better or equal to the conventional evaluation in 77% of cases, particularly, better on spinal cord, parotid glands, and low-risk CTV.

CONCLUSION

This study demonstrated the additional dose discrepancy that sNRVs can make. The inclusion of sNRVs can be beneficial to robust evaluation, providing information on clinical uncertainties additional to the conventional rigid isocenter shift.

An online adaptive plan library approach for intensity modulated proton therapy for head and neck cancer

BACKGROUND AND PURPOSE

In intensity modulated proton therapy (IMPT), the impact of setup errors and anatomical changes is commonly mitigated by robust optimization with population-based setup robustness (SR) settings and offline replanning. In this study we propose and evaluate an alternative approach based on daily plan selection from patient-specific pre-treatment established plan libraries (PLs). Clinical implementation of the PL strategy would be rather straightforward compared to daily online re-planning.

MATERIALS AND METHODS

For 15 head-and-neck cancer patients, the planning CT was used to generate a PL with 5 plans, robustly optimized for increasing SR: 0, 1, 2, 3, 5 mm, and 3% range robustness. Repeat CTs (rCTs) and realistic setup and range uncertainty distributions were used for simulation of treatment courses for the PL approach, treatments with fixed SR (fSR₃) and a trigger-based offline adaptive schedule for 3 mm SR (fSR₃OfA). Daily plan selection in the PL approach was based only on recomputed dose to the CTV on the rCT.

RESULTS

Compared to using fSR₃ and fSR₃OfA, the risk of xerostomia grade ≥ II & III and dysphagia ≥ grade III were significantly reduced with the PL. For 6/15 patients the risk of xerostomia and/or dysphagia ≥ grade II could be reduced by > 2% by using PL. For the other patients, adherence to target coverage constraints was often improved. fSR₃OfA resulted in significantly improved coverage compared to PL for selected patients.

CONCLUSION

The proposed PL approach resulted in overall reduced NTCPs compared to fSR₃ and fSR₃OfA at limited cost in target coverage.

Use of CBCT plus plan robustness for reducing QACT frequency in intensity-modulated proton therapy: Head-and-neck cases

PURPOSE

Anatomic variation has a significant dosimetric impact in intensity-modulated proton therapy. Weekly or biweekly computed tomography (CT) scans, called quality assurance CTs (QACTs), are used to monitor anatomic and resultant dose changes to determine whether adaptive plans are needed. Frequent CT scans result in unwanted QACT dose and increased clinical workloads. This study proposed utilizing patient setup cone-beam CTs (CBCTs) and treatment plan robustness to reduce the frequency of QACTs.

METHODS

We retrospectively analyzed data from 27 patients with head-and-neck cancer, including 594 CBCTs, 136 QACTs, and 19 adaptive plans. For each CBCT, water-equivalent thickness (WET) along the pencil-beam path was calculated. For each treatment plan, the WET of the first-day CBCT was used as the reference, and the mean WET changes (ΔWET) in each following CBCT was used as the surrogate of proton range change. Using CBCTs acquired prior to a QACT, we predicted the ΔWET on the QACT day by a linear regression model. The impact of range change on target dose was calculated as the predicted ΔWET weighted by the monitor units of each field. In addition, plan robustness was estimated from the robust dose-volume histograms (DVHs) and combined with ΔWET to reduce QACT frequency. Robustness was estimated from the distance between the DVH curves of the nominal and worst scenarios.

RESULTS

When the estimated mean ΔWET was <6.5 mm (or <7.5 mm if the robustness was >95%), the QACT could be skipped without missing any adaptive planning; otherwise a QACT was required. Overall, 41% of QACTs could be eliminated when ΔWET was <6.5 mm and 56% when ΔWET was <7.5 mm, and robustness was >95%. At least one QACT could have been omitted in 25 of the 27 cases under skipping thresholds at ΔWETs <7.5 mm and R > 95%.

CONCLUSION

This study suggests that the number of QACTs can be greatly reduced by calculating range change in patient setup CBCTs and can be further reduced by combining this information with analyses of plan robustness.

Evaluation of intrafraction couch shifts for proton treatment delivery in head-and-neck cancer patients: Toward optimal imaging frequency

PURPOSE

Treatment planning for head-and-neck (H&N) cancer, in particular oropharynx, nasopharynx, and paranasal sinus cases, at our center requires noncoplanar proton beams due to the complexity of the anatomy and target location. Targeting accuracy for all beams is carefully evaluated by using image guidance before delivering proton beam therapy (PBT). In this study, we analyzed couch shifts to evaluate whether imaging is required before delivering each field with different couch angles.

METHODS

After the Institutional Review Board approval, a retrospective analysis was performed on data from 28 H&N patients treated with PBT. Each plan was made with two-to-three noncoplanar and two-to-three coplanar fields. Cone-beam computed tomography and orthogonal kilovoltage (kV) images were acquired for setup and before delivering each field, respectively. The Cartesian (longitudinal, vertical, and lateral) and angular (pitch and roll) shifts for each field were recorded from the treatment summary on the first two fractions and every subsequent fifth fraction. A net magnitude of the three-dimensional (3D) shift in Cartesian coordinates was calculated, and a 3D vector was created from the 6 degrees of freedom coordinates for transforming couch shifts in the system coordinate to the beam's-eye view.

RESULTS

A total of 3219 Cartesian and 2146 angular shift values were recorded for 28 patients. Of the Cartesian shifts, 2069 were zero (64.3%), and 1150 (35.7%) were nonzero (range, -7 to 11 mm). Of the angular shifts, 1034 (48.2%) were zero, and 1112 (51.8%) were nonzero (range, -3.0° to 3.2°). For 17 patients, the couch shifts increased toward the end of the treatment course. We also found that patients with higher body mass index (BMI) presented increased net couch shifts (p < 0.001). With BMI < 27, all overall net shift averages were <2 mm, and overall maximum net shifts were <6 mm.

CONCLUSIONS

These results confirm the need for orthogonal kV imaging before delivering each field of H&N PBT at our center, where a couch rotation is involved.

In-vivo range verification analysis with in-beam PET data for patients treated with proton therapy at CNAO

Morphological changes that may arise through a treatment course are probably one of the most significant sources of range uncertainty in proton therapy. Non-invasive in-vivo treatment monitoring is useful to increase treatment quality. The INSIDE in-beam Positron Emission Tomography (PET) scanner performs in-vivo range monitoring in proton and carbon therapy treatments at the National Center of Oncological Hadrontherapy (CNAO). It is currently in a clinical trial (ID: NCT03662373) and has acquired in-beam PET data during the treatment of various patients. In this work we analyze the in-beam PET (IB-PET) data of eight patients treated with proton therapy at CNAO. The goal of the analysis is twofold. First, we assess the level of experimental fluctuations in inter-fractional range differences (sensitivity) of the INSIDE PET system by studying patients without morphological changes. Second, we use the obtained results to see whether we can observe anomalously large range variations in patients where morphological changes have occurred. The sensitivity of the INSIDE IB-PET scanner was quantified as the standard deviation of the range difference distributions observed for six patients that did not show morphological changes. Inter-fractional range variations with respect to a reference distribution were estimated using the Most-Likely-Shift (MLS) method. To establish the efficacy of this method, we made a comparison with the Beam’s Eye View (BEV) method. For patients showing no morphological changes in the control CT the average range variation standard deviation was found to be 2.5 mm with the MLS method and 2.3 mm with the BEV method. On the other hand, for patients where some small anatomical changes occurred, we found larger standard deviation values. In these patients we evaluated where anomalous range differences were found and compared them with the CT. We found that the identified regions were mostly in agreement with the morphological changes seen in the CT scan.

Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning

Knowledge-based planning solutions have brought significant improvements in treatment planning. However, the performance of a proton-specific knowledge-based planning model in creating knowledge-based plans (KBPs) with beam angles differing from those used to train the model remains unexplored. We used a previously validated RapidPlanPT model and scripting to create nine KBPs, one with default and eight with altered beam angles, for 10 recent oropharynx cancer patients. The altered-angle plans were compared against the default-angle ones in terms of grade 2 dysphagia and xerostomia normal tissue complication probability (NTCP), mean doses of several organs at risk, and dose homogeneity index (HI). As KBP could be suboptimal, a proof of principle automatic iterative optimizer (AIO) was added with the aim of reducing the plan NTCP. There were no statistically significant differences in NTCP or HI between default- and altered-angle KBPs, and the altered-angle plans showed a <1% reduction in NTCP. AIO was able to reduce the sum of grade 2 NTCPs in 66/90 cases with mean a reduction of 3.5 ± 1.8%. While the altered-angle plans saw greater benefit from AIO, both default- and altered-angle plans could be improved, indicating that the KBP model alone was not completely optimal to achieve the lowest NTCP. Overall, the data showed that the model was robust to the various beam arrangements within the range described in this analysis.

Proton Therapy for Squamous Cell Carcinoma of the Head and Neck: Early Clinical Experience and Current Challenges

Simple Summary

Proton therapy is a promising type of radiation therapy used to destroy tumor cells. It has the potential to further improve the outcomes for patients with head and neck cancer since it allows to minimize the radiation dose to vital structures around the tumor, leading to less toxicity. This paper describes the current experience worldwide with proton therapy in head and neck cancer.

Abstract

Proton therapy (PT) is a promising development in radiation oncology, with the potential to further improve outcomes for patients with squamous cell carcinoma of the head and neck (HNSCC). By utilizing the finite range of protons, healthy tissue can be spared from beam exit doses that would otherwise be irradiated with photon-based treatments. Current evidence on PT for HNSCC is limited to comparative dosimetric analyses and retrospective single-institution series. As a consequence, the recognized indications for the reimbursement of PT remain scarce in most countries. Nevertheless, approximately 100 PT centers are in operation worldwide, and initial experiences for HNSCC are being reported. This review aims to summarize the results of the early clinical experience with PT for HNSCC and the challenges that are currently faced.

DIR-based models to predict weekly anatomical changes in head and neck cancer proton therapy

Objective. We proposed two anatomical models for head and neck patients to predict anatomical changes during the course of radiotherapy.Approach. Deformable image registration was used to build two anatomical models: (1) the average model (AM) simulated systematic progressive changes across the patient cohort; (2) the refined individual model (RIM) used a patient's CT images acquired during treatment to update the prediction for each individual patient. Planning CTs and weekly CTs were used from 20 nasopharynx patients. This dataset included 15 training patients and 5 test patients. For each test patient, a spot scanning proton plan was created. Models were evaluated using CT number differences, contours, proton spot location deviations and dose distributions.Main results. If no model was used, the CT number difference between the planning CT and the repeat CT at week 6 of treatment was on average 128.9 Hounsfield Units (HU) over the test population. This can be reduced to 115.5 HU using the AM, and to 110.5 HU using the RIM3(RIM, updated at week (3). When the predicted contours from the models were used, the average mean surface distance of parotid glands can be reduced from 1.98 (no model) to 1.16 mm (AM) and 1.19 mm (RIM3) at week 6. Using the proton spot range, the average anatomical uncertainty over the test population reduced from 4.47 ± 1.23 (no model) to 2.41 ± 1.12 mm (AM), and 1.89 ± 0.96 mm (RIM3). Based on the gamma analysis, the average gamma index over the test patients was improved from 93.87 ± 2.48 % (no model) to 96.16 ± 1.84% (RIM3) at week 6.Significance. The AM and the RIM both demonstrated the ability to predict anatomical changes during the treatment. The RIM can gradually refine the prediction of anatomical changes based on the AM. The proton beam spots provided an accurate and effective way for uncertainty evaluation.

Evaluation of the clinical value of automatic online dose restoration for adaptive proton therapy of head and neck cancer

INTRODUCTION

Intensity modulated proton therapy (IMPT) is highly sensitive to anatomical variations which can cause inadequate target coverage during treatment. This study compares not-adapted (NA) robust plans to two adaptive IMPT methods - a fully-offline adaptive (FOA) and a simplified automatic online adaptive strategy (dose restoration (DR)) to determine the benefit of DR, in head and neck cancer (HNC).

MATERIAL/METHODS

Robustly optimized clinical IMPT doses in planning-CTs (pCTs) were available for a cohort of 10 HNC patients. During robust re-optimization, DR used isodose contours, generated from the clinical dose on pCTs, and patient specific objectives to reproduce the clinical dose in every repeated-CT(rCT). For each rCT(n=50), NA, DR and FOA plans were robustly evaluated.

RESULTS

An improvement in DVH-metrics and robustness was seen for DR and FOA plans compared to NA plans. For NA plans, 74%(37/50) of rCTs did not fulfill the CTV coverage criteria (D98%>95%Dprescription). DR improved target coverage, target homogeneity and variability on critical risk organs such as the spinal cord. After DR, 52%(26/50) of rCTs met all clinical goals. Because of large anatomical changes and/or inaccurate patient repositioning, 48%(24/50) of rCTs still needed full offline adaptation to ensure an optimal treatment since dose restoration was not able to re-establish the initial plan quality.

CONCLUSION

Robust optimization together with fully-automatized DR avoided offline adaptation in 52% of the cases. Implementation of dose restoration in clinical routine could ensure treatment plan optimality while saving valuable human and material resources to radiotherapy departments.

Single-institution clinical experience using robust intensity modulated proton therapy in chordoma and chondrosarcoma of the mobile spine and sacrum: Feasibility and need for plan adaptation

BACKGROUND

Due to its specific physical characteristics, proton irradiation is especially suited for irradiation of chordomas and chondrosarcoma in the axial skeleton. Robust plan optimization renders the proton beam therapy more predictable upon individual setup errors. Reported experience with the planning and delivery of robustly optimized plans in chordoma and chondrosarcoma of the mobile spine and sacrum, is limited. In this study, we report on the clinical use of robustly optimized, intensity modulated proton beam therapy in these patients.

METHODS

We retrospectively reviewed patient, treatment and acute toxicity data of all patients with chordoma and chondrosarcoma of the mobile spine and sacrum, treated between 1 April 2019 and 1 April 2020 at our institute. Anatomy changes during treatment were evaluated by weekly cone-beam CTs (CBCT), supplemented by scheduled control-CTs or ad-hoc control-CTs. Acute toxicity was scored weekly during treatment and at 3 months after therapy according to CTCAE 4.0.

RESULTS

17 chordoma and 3 chondrosarcoma patients were included. Coverage of the high dose clinical target volume was 99.8% (range 56.1-100%) in the nominal and 80.9% (range 14.3-99.6%) in the voxel-wise minimum dose distribution. Treatment plan adaptation was needed in 5 out of 22 (22.7%) plans. Reasons for plan adaptation were either reduced tumor coverage or increased dose to the OAR.

CONCLUSIONS

Robustly optimized intensity modulated proton beam therapy for chordoma and chondrosarcoma of the mobile spine is feasible. Plan adaptations due to anatomical changes were required in approximately 23 percent of treatment courses.

Localization of anatomical changes in patients during proton therapy with in-beam PET monitoring: A voxel-based morphometry approach exploiting Monte Carlo simulations

Purpose

In‐beam positron emission tomography (PET) is one of the modalities that can be used for in vivo noninvasive treatment monitoring in proton therapy. Although PET monitoring has been frequently applied for this purpose, there is still no straightforward method to translate the information obtained from the PET images into easy‐to‐interpret information for clinical personnel. The purpose of this work is to propose a statistical method for analyzing in‐beam PET monitoring images that can be used to locate, quantify, and visualize regions with possible morphological changes occurring over the course of treatment.

Methods

We selected a patient treated for squamous cell carcinoma (SCC) with proton therapy, to perform multiple Monte Carlo (MC) simulations of the expected PET signal at the start of treatment, and to study how the PET signal may change along the treatment course due to morphological changes. We performed voxel‐wise two‐tailed statistical tests of the simulated PET images, resembling the voxel‐based morphometry (VBM) method commonly used in neuroimaging data analysis, to locate regions with significant morphological changes and to quantify the change.

Results

The VBM resembling method has been successfully applied to the simulated in‐beam PET images, despite the fact that such images suffer from image artifacts and limited statistics. Three dimensional probability maps were obtained, that allowed to identify interfractional morphological changes and to visualize them superimposed on the computed tomography (CT) scan. In particular, the characteristic color patterns resulting from the two‐tailed statistical tests lend themselves to trigger alarms in case of morphological changes along the course of treatment.

Conclusions

The statistical method presented in this work is a promising method to apply to PET monitoring data to reveal interfractional morphological changes in patients, occurring over the course of treatment. Based on simulated in‐beam PET treatment monitoring images, we showed that with our method it was possible to correctly identify the regions that changed. Moreover we could quantify the changes, and visualize them superimposed on the CT scan. The proposed method can possibly help clinical personnel in the replanning procedure in adaptive proton therapy treatments.

Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting

Objective. To present an efficient uncertainty quantification method for range and set-up errors in Monte Carlo (MC) dose calculations. Further, we show that uncertainty induced by interplay and other dynamic influences may be approximated using suitable error correlation models.Approach. We introduce an importance (re-)weighting method in MC history scoring to concurrently construct estimates for error scenarios, the expected dose and its variance from a single set of MC simulated particle histories. The approach relies on a multivariate Gaussian input and uncertainty model, which assigns probabilities to the initial phase space sample, enabling the use of different correlation models. Through modification of the phase space parameterization, accuracy can be traded between that of the uncertainty or the nominal dose estimate.Main results. The method was implemented using the MC code TOPAS and validated for proton intensity-modulated particle therapy (IMPT) with reference scenario estimates. We achieve accurate results for set-up uncertainties (γ_{2 mm/2%}≥ 99.01% (E[d]),γ_{2 mm/2%}≥ 98.04% (σ(d))) and expectedly lower but still sufficient agreement for range uncertainties, which are approximated with uncertainty over the energy distribution. Here pass rates of 99.39% (E[d])/ 93.70% (σ(d)) (range errors) and 99.86% (E[d])/ 96.64% (σ(d)) (range and set-up errors) can be achieved. Initial evaluations on a water phantom, a prostate and a liver case from the public CORT dataset show that the CPU time decreases by more than an order of magnitude.Significance. The high precision and conformity of IMPT comes at the cost of susceptibility to treatment uncertainties in particle range and patient set-up. Yet, dose uncertainty quantification and mitigation, which is usually based on sampled error scenarios, becomes challenging when computing the dose with computationally expensive but accurate MC simulations. As the results indicate, the proposed method could reduce computational effort while also facilitating the use of high-dimensional uncertainty models.

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.

Work Outcomes after Intensity-Modulated Proton Therapy (IMPT) versus Intensity-Modulated Photon Therapy (IMRT) for Oropharyngeal Cancer

Purpose

We compared work outcomes in patients with oropharyngeal cancer (OPC), randomized to intensity-modulated proton (IMPT) versus intensity-modulated photon therapy (IMRT) for chemoradiation therapy (CRT).

Patients and Methods

In 147 patients with stage II-IVB squamous cell OPC participating in patient-reported outcomes assessments, a prespecified secondary aim of a randomized phase II/III trial of IMPT (n = 69) versus IMRT (n = 78), we compared absenteeism, presenteeism (i.e., the extent to which an employee is not fully functional at work), and work productivity losses. We used the work productivity and activity impairment questionnaire at baseline (pre-CRT), at the end of CRT, and at 6 months, 1 year, and 2 years. A one-sided Cochran-Armitage test was used to analyze within-arm temporal trends, and a χ² test was used to compare between-arm differences. Among working patients, at each follow-up point, a 1-sided Wilcoxon rank-sum test was used to compare work-productivity scores.

Results

Patient characteristics in IMPT versus IMRT arms were similar. In the IMPT arm, within-arm analysis demonstrated that an increasing proportion of patients resumed working after IMPT, from 60% (40 of 67) pre-CRT and 71% (30 of 42) at 1 year to 78% (18 of 23) at 2 years (P = 0.025). In the IMRT arm, the proportion remained stable, with 57% (43 of 76) pre-CRT, 54% (21 of 39) at 1 year, and 52% (13 of 25) working at 2 years (P = 0.47). By 2 years after CRT, the between-arm difference between patients who had IMPT and those who had IMRT trended toward significance (P = 0.06). Regardless of treatment arm, among working patients, the most severe work impairments occurred from treatment initiation to the end of CRT, with significant recovery from absenteeism, presenteeism, and productivity impairments by the 2-year follow-up (P < 0.001 for all). Higher magnitudes of recovery from absenteeism (at 1 year, P = 0.05; and at 2 years, P = 0.04) and composite work impairment scores (at 1 year, P = 0.04; and at 2 years, P = 0.04) were seen in patients treated with IMPT versus those treated with IMRT.

Conclusion

In patients with OPC receiving curative CRT, patients randomized to IMPT demonstrated increasing work and productivity recovery trends. Studies are needed to identify mechanisms underlying head and neck CRT treatment causing work disability and impairment.

CBCT-Based Adaptive Assessment Workflow for Intensity Modulated Proton Therapy for Head and Neck Cancer

Purpose

Anatomical changes and patient setup uncertainties during intensity modulated proton therapy (IMPT) of head and neck (HN) cancers demand frequent evaluation of delivered dose. This work investigated a cone-beam computed tomography (CBCT) and deformable image registration based therapy workflow to demonstrate the feasibility of proton dose calculation on synthetic computed tomography (sCT) for adaptive IMPT treatment of HN cancer.

Materials and Methods

Twenty-one patients with HN cancer were enrolled in this study, a retrospective institutional review board protocol. They had previously been treated with volumetric modulated arc therapy and had daily iterative CBCT. For each patient, robust optimization (RO) IMPT plans were generated using ±3 mm patient setup and ±3% proton range uncertainties. The sCTs were created and the weekly delivered dose was recalculated using an adaptive dose accumulation workflow in which the planning computed tomography (CT) was deformably registered to CBCTs and Hounsfield units transferred from the planning CT. Accumulated doses from ±3 mm/±3% RO-IMPT plans were evaluated using clinical dose-volume constraints for targets (clinical target volume, or CTV) and organs at risk.

Results

Evaluation of weekly recalculated dose on sCTs showed that most of the patient plans maintained target dose coverage. The primary CTV remained covered by the V95 > 95% (95% of the volume receiving more than 95% of the prescription dose) worst-case scenario for 84.5% of the weekly fractions. The oral cavity accumulated mean dose remained lower than the worst-case scenario for all patients. Parotid accumulated mean dose remained within the uncertainty bands for 18 of the 21 patients, and all were kept lower than RO-IMPT worst-case scenario for 88.7% and 84.5% for left and right parotids, respectively.

Conclusion

This study demonstrated that RO-IMPT plans account for most setup and anatomical uncertainties, except for large weight-loss changes that need to be tracked throughout the treatment course. We showed that sCTs could be a powerful decision tool for adaptation of these cases in order to reduce workload when using repeat CTs.

Long short-term memory networks for proton dose calculation in highly heterogeneous tissues

PURPOSE

To investigate the feasibility and accuracy of proton dose calculations with artificial neural networks (ANNs) in challenging three-dimensional (3D) anatomies.

METHODS

A novel proton dose calculation approach was designed based on the application of a long short-term memory (LSTM) network. It processes the 3D geometry as a sequence of two-dimensional (2D) computed tomography slices and outputs a corresponding sequence of 2D slices that forms the 3D dose distribution. The general accuracy of the approach is investigated in comparison to Monte Carlo reference simulations and pencil beam dose calculations. We consider both artificial phantom geometries and clinically realistic lung cases for three different pencil beam energies.

RESULTS

For artificial phantom cases, the trained LSTM model achieved a 98.57% γ-index pass rate ([1%, 3 mm]) in comparison to MC simulations for a pencil beam with initial energy 104.25 MeV. For a lung patient case, we observe pass rates of 98.56%, 97.74%, and 94.51% for an initial energy of 67.85, 104.25, and 134.68 MeV, respectively. Applying the LSTM dose calculation on patient cases that were fully excluded from the training process yields an average γ-index pass rate of 97.85%.

CONCLUSIONS

LSTM networks are well suited for proton dose calculation tasks. Further research, especially regarding model generalization and computational performance in comparison to established dose calculation methods, is warranted.

Accounting for prompt gamma emission and detection for range verification in proton therapy treatment planning

Prompt gamma (PG) imaging is widely investigated as one of the most promising methods for proton range verification in proton therapy. The performance of this technique is affected by several factors like tissue heterogeneity, number of protons in the considered pencil beam and the detection device. Our previous work proposed a new treatment planning concept which boosts the number of protons of a few PG monitoring-friendly pencil beams (PBs), selected on the basis of two proposed indicators quantifying the conformity between the dose and PG at the emission level, above the desired detectability threshold. To further explore this method at the detection level, in this work we investigated the response of a knife-edge slit PG camera which was deployed in the first clinical application of PG to proton therapy monitoring. The REGistration Graphical User Interface (REGGUI) is employed to simulate the PG emission, PG detection as well as the corresponding dose distribution. As the PG signal detected by this kind of PG camera is sensitive to the relative position of the camera and PG signal falloff, we optimized our PB selection method for this camera by introducing a new camera position indicator identifying whether the expected falloff of the PG signal is centered in the field of view of the camera or not. Our camera-adapted PB selection method is investigated using computed tomography (CT) scans at two different treatment time points of a head and neck, and a prostate cancer patient under scenarios considering different statistics level. The results show that a precision of 0.8 mm for PG falloff identification can be achieved when a PB has more than 2 × 10⁸ primary protons. Except for one case due to unpredictable and comparably large anatomical changes, the PG signals of most of the PBs recommended by all our indicators are observed to be reliable for proton range verification with deviations between the inter-fractional shift of proton range (as deduced from the PB dose distribution) and the detected PG signal within 2.0 mm. In contrast, a shift difference up to 9.6 mm has been observed for the rejected PBs. The magnitude of the proton range shift due to the inter-fractional anatomical changes is observed to be up to 23 mm. The proposed indicators are shown to be valuable for identifying and recommending reliable PBs to create new PG monitoring-friendly TPs. Comparison between our PB boosting method and the alternative PB aggregation, which combines the signal of nearby PBs to reach the desired counting statistics, is also discussed.

Validation of a new open-source method for automatic delineation and dose assessment of the heart and LADCA in breast radiotherapy with simultaneous uncertainty estimation

Radiotherapy has been shown to increase risks of cardiotoxicities for breast cancer patients. Automated delineation approaches are necessary for consistent and efficient assessment of cardiac doses in large, retrospective datasets, while patient-specific estimation of the uncertainty in these doses provides valuable additional data for modelling and understanding risks. In this work, we aim to validate the consistency of our previously described open-source software model for automatic cardiac delineation in the context of dose assessment, relative to manual contouring. We also extend our software to introduce a novel method to automatically quantify the uncertainty in cardiac doses based on expected inter-observer variability (IOV) in contouring. This method was applied to a cohort of 15 left-sided breast cancer patients treated in Denmark using modern tangential radiotherapy techniques. On each image set, the whole heart and left anterior descending coronary artery (LADCA) were contoured by nine independent experts; the range of doses to these nine volumes provided a reference for the dose uncertainties generated from the automatic method. Local and external atlas sets were used to test the method. Results give confidence in the consistency of automatic segmentations, with mean whole heart dose differences for local and external atlas sets of -0.20 ± 0.17 and -0.10 ± 0.14 Gy, respectively. Automatic estimates of uncertainties in doses are similar to those from IOV for both the whole heart and LADCA. Overall, this study confirms that our automated approach can be used to accurately assess cardiac doses, and the proposed method can provide a useful tool in estimating dose uncertainties.

Past, present and future of proton therapy for head and neck cancer

Proton therapy has recently gained substantial momentum worldwide due to improved accessibility to the technology and sustained interests in its advantage of better tissue sparing compared to traditional photon radiation. Proton therapy in head and neck cancer has a unique advantage given the complex anatomy and proximity of targets to vital organs. As head and neck cancer patients are living longer due to epidemiological shifts and advances in treatment options, long-term toxicity from radiation treatment has become a major concern that may be better mitigated by proton therapy. With increased utilization of proton therapy, new proton centers breaking ground, and as excitement about the technology continue to increase, we aim to comprehensively review the evidence of proton therapy in major subsites within the head and neck, hoping to facilitate a greater understanding of the full risks and benefits of proton therapy for head and neck cancer.

The Importance of Verification CT-QA Scans in Patients Treated with IMPT for Head and Neck Cancers

Purpose

To understand how verification computed tomography-quality assurance (CT-QA) scans influenced clinical decision-making to replan patients with head and neck cancer and identify predictors for replanning to guide intensity-modulated proton therapy (IMPT) clinical practice.

Patients and Methods

We performed a quality-improvement study by prospectively collecting data on 160 consecutive patients with head and neck cancer treated using spot-scanning IMPT who underwent weekly verification CT-QA scans. Kaplan-Meier estimates were used to determine the cumulative probability of a replan by week. Predictors for replanning were determined with univariate (UVA) and multivariate (MVA) Cox model hazard ratios (HRs). Logistic regression was used to determine odds ratios (ORs). P < .05 was considered statistically significant.

Results

Of the 160 patients, 79 (49.4%) had verification CT-QA scans, which prompted a replan. The cumulative probability of a replan by week 1 was 13.7% (95% confidence interval [CI], 8.82-18.9), week 2, 25.0% (95% CI, 18.0-31.4), week 3, 33.1% (95% CI, 25.4-40.0), week 4, 45.6% (95% CI, 37.3-52.8), and week 5 and 6, 49.4% (95% CI, 41.0-56.6). Predictors for replanning were sinonasal disease site (UVA: HR, 1.82, P = .04; MVA: HR, 3.64, P = .03), advanced stage disease (UVA: HR, 4.68, P < .01; MVA: HR, 3.10, P < .05), dose > 60 Gy equivalent (GyE; relative biologic effectiveness, 1.1) (UVA: HR, 1.99, P < .01; MVA: HR, 2.20, P < .01), primary disease (UVA: HR, 2.00 versus recurrent, P = .01; MVA: HR, 2.46, P = .01), concurrent chemotherapy (UVA: HR, 2.05, P < .01; MVA: not statistically significant [NS]), definitive intent treatment (UVA: HR, 1.70 versus adjuvant, P < .02; MVA: NS), bilateral neck treatment (UVA: HR, 2.07, P = .03; MVA: NS), and greater number of beams (5 beam UVA: HR, 5.55 versus 1 or 2 beams, P < .02; MVA: NS). Maximal weight change from baseline was associated with higher odds of a replan (≥3 kg: OR, 1.97, P = .04; ≥ 5 kg: OR, 2.13, P = .02).

Conclusions

Weekly verification CT-QA scans frequently influenced clinical decision-making to replan. Additional studies that evaluate the practice of monitoring IMPT-treated patients with weekly CT-QA scans and whether that improves clinical outcomes are warranted.

Analytical probabilistic modeling of dose-volume histograms

PURPOSE

Radiotherapy, especially with charged particles, is sensitive to executional and preparational uncertainties that propagate to uncertainty in dose and plan quality indicators, for example, dose-volume histograms (DVHs). Current approaches to quantify and mitigate such uncertainties rely on explicitly computed error scenarios and are thus subject to statistical uncertainty and limitations regarding the underlying uncertainty model. Here we present an alternative, analytical method to approximate moments, in particular expectation value and (co)variance, of the probability distribution of DVH-points, and evaluate its accuracy on patient data.

METHODS

We use Analytical Probabilistic Modeling (APM) to derive moments of the probability distribution over individual DVH-points based on the probability distribution over dose. By using the computed moments to parameterize distinct probability distributions over DVH-points (here normal or beta distributions), not only the moments but also percentiles, that is, α - DVHs, are computed. The model is subsequently evaluated on three patient cases (intracranial, paraspinal, prostate) in 30- and single-fraction scenarios by assuming the dose to follow a multivariate normal distribution, whose moments are computed in closed-form with APM. The results are compared to a benchmark based on discrete random sampling.

RESULTS

The evaluation of the new probabilistic model on the three patient cases against a sampling benchmark proves its correctness under perfect assumptions as well as good agreement in realistic conditions. More precisely, ca. 90% of all computed expected DVH-points and their standard deviations agree within 1% volume with their empirical counterpart from sampling computations, for both fractionated and single fraction treatments. When computing α - DVH, the assumption of a beta distribution achieved better agreement with empirical percentiles than the assumption of a normal distribution: While in both cases probabilities locally showed large deviations (up to ±0.2), the respective - DVHs for α={0.05,0.5,0.95} only showed small deviations in respective volume (up to ±5% volume for a normal distribution, and up to 2% for a beta distribution). A previously published model from literature, which was included for comparison, exhibited substantially larger deviations.

CONCLUSIONS

With APM we could derive a mathematically exact description of moments of probability distributions over DVH-points given a probability distribution over dose. The model generalizes previous attempts and performs well for both choices of probability distributions, that is, normal or beta distributions, over DVH-points.

Proton therapy for head and neck squamous cell carcinomas: A review of the physical and clinical challenges

The quality of radiation therapy has been shown to significantly influence the outcomes for head and neck squamous cell carcinoma (HNSCC) patients. The results of dosimetric studies suggest that intensity-modulated proton therapy (IMPT) could be of added value for HNSCC by being more effective than intensity-modulated (photon) radiation therapy (IMRT) for reducing side effects of radiation therapy. However, the physical properties of protons make IMPT more sensitive than photons to planning uncertainties. This could potentially have a negative effect on the quality of IMPT planning and delivery. For this review, the three French proton therapy centers collaborated to evaluate the differences between IMRT and IMPT. The review explored the effects of these uncertainties and their management for developing a robust and optimized IMPT treatment delivery plan to achieve clinical outcomes that are superior to those for IMRT. We also provide practical suggestions for the management of HNSCC carcinoma with IMPT. Because metallic dental implants can increase range uncertainties (3-10%), patient preparation for IMPT may require more systematic removal of in-field alien material than is done for IMRT. Multi-energy CT may be an alternative to calculate more accurately the dose distribution. The practical aspects that we describe are essential to guarantee optimal quality in radiation therapy in both model-based and randomized clinical trials.

Automated proton treatment planning with robust optimization using constrained hierarchical optimization

PURPOSE

We present a method for fully automated generation of high quality robust proton treatment plans using hierarchical optimization. To fill the gap between the two common extreme robust optimization approaches, that is, stochastic and worst-case, a robust optimization approach based on the p-norm function is used whereby a single parameter, p , can be used to control the level of robustness in an intuitive way.

METHODS

A fully automated approach to treatment planning using Expedited Constrained Hierarchical Optimization (ECHO) is implemented in our clinic for photon treatments. ECHO strictly enforces critical (inviolable) clinical criteria as hard constraints and improves the desirable clinical criteria sequentially, as much as is feasible. We extend our in-house developed ECHO codes for proton therapy and integrate it with a new approach for robust optimization. Multiple scenarios accounting for both setup and range uncertainties are included (13scenarios), and the maximum/mean/dose-volume constraints on organs-at-risk (OARs) and target are fulfilled in all scenarios. We combine the objective functions of the individual scenarios using the p-norm function. The p-norm with a parameter p = 1 or p = ∞ result in the stochastic or the worst-case approach, respectively; an intermediate robustness level is obtained by employing p -values in-between. While the worst-case approach only focuses on the worst-case scenario(s), the p-norm approach with a large p value ( p ≈ 20 ) resembles the worst-case approach without completely neglecting other scenarios. The proposed approach is evaluated on three head-and-neck (HN) patients and one water phantom with different parameters, p ∈ 1 , 2 , 5 , 10 , 20 . The results are compared against the stochastic approach (p-norm approach with p = 1 ) and the worst-case approach, as well as the nonrobust approach (optimized solely on the nominal scenario).

RESULTS

The proposed algorithm successfully generates automated robust proton plans on all cases. As opposed to the nonrobust plans, the robust plans have narrower dose volume histogram (DVH) bands across all 13 scenarios, and meet all hard constraints (i.e., maximum/mean/dose-volume constraints) on OARs and the target for all scenarios. The spread in the objective function values is largest for the stochastic approach ( p = 1 ) and decreases with increasing p toward the worst-case approach. Compared to the worst-case approach, the p-norm approach results in DVH bands for clinical target volume (CTV) which are closer to the prescription dose at a negligible cost in the DVH for the worst scenario, thereby improving the overall plan quality. On average, going from the worst-case approach to the p-norm approach with p = 20 , the median objective function value across all the scenarios is improved by 15% while the objective function value for the worst scenario is only degraded by 3%.

CONCLUSION

An automated treatment planning approach for proton therapy is developed, including robustness, dose-volume constraints, and the ability to control the robustness level using the p-norm parameter p , to fit the priorities deemed most important.

Improve the dosimetric outcome in bilateral head and neck cancer (HNC) treatment using spot-scanning proton arc (SPArc) therapy: a feasibility study

BACKGROUND

To explore the dosimetric improvement, delivery efficiency, and plan robustness for bilateral head and neck cancer (HNC) treatment utilizing a novel proton therapy technique - the spot-scanning proton arc (SPArc) therapy.

METHODS

We evaluated fourteen bilateral HNC patients retrospectively. Both SPArc and 3-field Intensity Modulated Proton Therapy (IMPT) plans were generated for each patient using the same robust optimization parameters. The prescription doses were 70Gy (relative biological effectiveness (RBE) for CTV_high and 60Gy[RBE] for CTV_low. Clinically significant dosimetric parameters were extracted and compared. Root-mean-square deviation dose (RMSDs) Volume Histogram(RVH) was used to evaluate the plan robustness. Total treatment delivery time was estimated based on the machine parameters.

RESULTS

The SPArc plan was able to provide equivalent or better robust target coverage while showed significant dosimetric improvements over IMPT in most of the organs at risk (OARs). More specifically, it reduced the mean dose of the ipsilateral parotid, contralateral parotid, and oral cavity by 25.8%(p = 0.001), 20.8%(p = 0.001) and 20.3%(p = 0.001) respectively compared to IMPT. This technique reduced D1 (the maximum dose covering 1% volume of a structure) of cord and brain stem by 20.8% (p = 0.009) and 10.7% (p = 0.048), respectively. SPArc also reduced the average integral dose by 17.2%(p = 0.001) and external V3Gy (the volume received 3Gy[RBE]) by 8.3%(p = 0.008) as well. RVH analysis showed that the SPArc plans reduced the dose uncertainties in most OARs compared to IMPT, such as cord: 1.1 ± 0.4Gy[RBE] vs 0.7 ± 0.3Gy[RBE](p = 0.001), brain stem: 0.9 ± 0.7Gy[RBE] vs 0.7 ± 0.7Gy[RBE](p = 0.019), contralateral parotid: 2.5 ± 0.5Gy[RBE] vs 2.2 ± 0.6Gy[RBE](p = 0.022) and ipsilateral parotid: 3.1 ± 0.7Gy[RBE] vs 2.8 ± 0.6Gy[RBE](p = 0.004) respectively. The average total estimated treatment delivery time were 283.4 ± 56.2 s, 469.2 ± 62.0 s and 1294.9 ± 106.7 s based on energy-layer-switching-time (ELST) of 0.1 s, 1 s, and 5 s respectively for SPArc plans, compared to the respective values of 328.0 ± 47.6 s(p = 0.002), 434.1 ± 52.0 s(p = 0.002), and 901.7 ± 74.8 s(p = 0.001) for 3-field IMPT plans. The potential clinical benefit of utilizing SPArc will lead to a decrease in the mean probability of salivary flow dysfunction by 31.3%(p = 0.001) compared with IMPT.

CONCLUSIONS

SPArc could significantly spare OARs while providing a similar or better robust target coverage compared with IMPT in the treatment of bilateral HNC. In the modern proton system with ELST less than 0.5 s, SPArc could potentially be implemented in the routine clinic with a practical, achievable treatment delivery efficiency.

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.

Beam angle optimization using angular dependency of range variation assessed via water equivalent path length (WEPL) calculation for head and neck proton therapy

PURPOSE

To investigate angular sensitivity of proton range variation due to anatomic change in patients and patient setup error via water equivalent path length (WEPL) calculations.

METHODS

Proton range was estimated by calculating WEPL to the distal edge of target volume using planning CT (pCT) and weekly scatter-corrected cone-beam CT (CBCT) images of 11 head and neck patients. Range variation was estimated as the difference between the distal WEPLs calculated on pCT and scatter-corrected CBCT (cCBCT). This WEPL analysis was performed every five degrees ipsilaterally to the target. Statistics of the distal WEPL difference were calculated over the distal area to compare between different beam angles. Physician-defined contours were used for the WEPL calculation on both pCT and cCBCT, not considering local deformation of target volume. It was also tested if a couch kick (10°) can mitigate the range variation due to anatomic change and patient setup error.

RESULTS

For most of the patients considered, median, 75% quantile, and 95% quantile of the distal WEPL difference were largest for posterior oblique angles, indicating a higher chance of overdosing normal tissues at distal edge with these angles. Using a couch kick resulted in decrease in the WEPL difference for some posterior oblique angles.

CONCLUSIONS

It was demonstrated that the WEPL change has angular dependency for the cohort of head and neck cancer patients. Selecting beam configuration robust to anatomic change in patient and patient setup error may improve the treatment outcome of head and neck proton therapy.

Practical robustness evaluation in radiotherapy - A photon and proton-proof alternative to PTV-based plan evaluation

BACKGROUND AND PURPOSE

A planning target volume (PTV) in photon treatments aims to ensure that the clinical target volume (CTV) receives adequate dose despite treatment uncertainties. The underlying static dose cloud approximation (the assumption that the dose distribution is invariant to errors) is problematic in intensity modulated proton treatments where range errors should be taken into account as well. The purpose of this work is to introduce a robustness evaluation method that is applicable to photon and proton treatments and is consistent with (historic) PTV-based treatment plan evaluations.

MATERIALS AND METHODS

The limitation of the static dose cloud approximation was solved in a multi-scenario simulation by explicitly calculating doses for various treatment scenarios that describe possible errors in the treatment course. Setup errors were the same as the CTV-PTV margin and the underlying theory of 3D probability density distributions was extended to 4D to include range errors, maintaining a 90% confidence level. Scenario dose distributions were reduced to voxel-wise minimum and maximum dose distributions; the first to evaluate CTV coverage and the second for hot spots. Acceptance criteria for CTV D98 and D2 were calibrated against PTV-based criteria from historic photon treatment plans.

RESULTS

CTV D98 in worst case scenario dose and voxel-wise minimum dose showed a very strong correlation with scenario average D98 (R² > 0.99). The voxel-wise minimum dose visualised CTV dose conformity and coverage in 3D in agreement with PTV-based evaluation in photon therapy. Criteria for CTV D98 and D2 of the voxel-wise minimum and maximum dose showed very strong correlations to PTV D98 and D2 (R² > 0.99) and on average needed corrections of -0.9% and +2.3%, respectively.

CONCLUSIONS

A practical approach to robustness evaluation was provided and clinically implemented for PTV-less photon and proton treatment planning, consistent with PTV evaluations but without its static dose cloud approximation.

[Proton therapy for head and neck squamous cell carcinomas: From physics to clinic]

Intensity-modulated radiation therapy (IMRT) is presently the recommended technique for the treatment of locally advanced head and neck carcinomas. Proton therapy would allow to reduce the volume of irradiated normal tissue and, thus, to decrease the risk of late dysphagia, xerostomia, dysgeusia and hypothyroidism. An exhaustive research was performed with the search engine PubMed by focusing on the papers about the physical difficulties that slow down use of proton therapy for head and neck carcinomas. Range uncertainties in proton therapy (±3 %) paradoxically limit the use of the steep dose gradient in distality. Calibration uncertainties can be important in the treatment of head and neck cancer in the presence of materials of uncertain stoichiometric composition (such as with metal implants, dental filling, etc.) and complex heterogeneities. Dental management for example may be different with IMRT or proton therapy. Some uncertainties can be somewhat minimized at the time of optimization. Inter- and intrafractional variations and uncertainties in Hounsfield units/stopping power can be integrated in a robust optimization process. Additional changes in patient's anatomy (tumour shrinkage, changes in skin folds in the beam patch, large weight loss or gain) require rescanning. Dosimetric and small clinical studies comparing photon and proton therapy have well shown the interest of proton therapy for head and neck cancers. Intensity-modulated proton therapy is a promising treatment as it can reduce the substantial toxicity burden of patients with head and neck squamous cell carcinoma compared to IMRT. Robust optimization will allow to perform an optimal treatment and to use proton therapy in current clinical practice.

Intensity-modulated proton therapy decreases dose to organs at risk in low-grade glioma patients: results of a multicentric in silico ROCOCO trial

BACKGROUND AND PURPOSE

Patients with low-grade glioma (LGG) have a prolonged survival expectancy due to better discriminative tumor classification and multimodal treatment. Consequently, long-term treatment toxicity gains importance. Contemporary radiotherapy techniques such as intensity-modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT), tomotherapy (TOMO) and intensity-modulated proton therapy (IMPT) enable high-dose irradiation of the target but they differ regarding delivered dose to organs at risk (OARs). The aim of this comparative in silico study was to determine these dosimetric differences in delivered doses.

MATERIAL AND METHODS

Imaging datasets of 25 LGG patients having undergone postoperative radiotherapy were included. For each of these patients, in silico treatment plans to a total dose of 50.4 Gy to the target volume were generated for the four treatment modalities investigated (i.e., IMRT, VMAT, TOMO, IMPT). Resulting treatment plans were analyzed regarding dose to target and surrounding OARs comparing IMRT, TOMO and IMPT to VMAT.

RESULTS

In total, 100 treatment plans (four per patient) were analyzed. Compared to VMAT, the IMPT mean dose (D_mean) for nine out of 10 (90%) OARs was statistically significantly (p < .02) reduced, for TOMO this was true in 3/10 (30%) patients and for 1/10 (10%) patients for IMRT. IMPT was the prime modality reducing dose to the OARs followed by TOMO.

DISCUSSION

The low dose volume to the majority of OARs was significantly reduced when using IMPT compared to VMAT. Whether this will lead to a significant reduction in neurocognitive decline and improved quality of life is to be determined in carefully designed future clinical trials.

On-line dose-guidance to account for inter-fractional motion during proton therapy

Background and purpose

Proton therapy (PT) of extra-cranial tumour sites is challenged by density changes caused by inter-fractional organ motion. In this study we investigate on-line dose-guided PT (DGPT) to account inter-fractional target motion, exemplified by internal motion in the pelvis.

Materials and methods

On-line DGPT involved re-calculating dose distributions with the isocenter shifted up to 15 mm from the position corresponding to conventional soft-tissue based image-guided PT (IGPT). The method was applied to patient models with simulated prostate/seminal vesicle target motion of ±3, ±5 and ±10 mm along the three cardinal axes. Treatment plans were created using either two lateral (gantry angles of 90°/270°) or two lateral oblique fields (gantry angles of 35°/325°). Target coverage and normal tissue doses from DGPT were compared to both soft-tissue and bony anatomy based IGPT.

Results

DGPT improved the dose distributions relative to soft-tissue based IGPT for 39 of 90 simulation scenarios using lateral fields and for 50 of 90 scenarios using lateral oblique fields. The greatest benefits of DGPT were seen for large motion, e.g. a median target coverage improvement of 13% was found for 10 mm anterior motion with lateral fields. DGPT also improved the dose distribution in comparison to bony anatomy IGPT in all cases. The best strategy was often to move the fields back towards the original target position prior to the simulated target motion.

Conclusion

DGPT has the potential to better account for large inter-fractional organ motion in the pelvis than IGPT.

Proton beam therapy for cancer in the era of precision medicine

Precision radiotherapy, which accurately delivers the dose on a tumor and confers little or no irradiation to the surrounding normal tissue and organs, results in maximum tumor control and decreases the toxicity to the utmost extent. Proton beam therapy (PBT) provides superior dose distributions and has a dosimetric advantage over photon beam therapy. Initially, the clinical practice and study of proton beam therapy focused on ocular tumor, skull base, paraspinal tumors (chondrosarcoma and chordoma), and unresectable sarcomas, which responded poorly when treated with photon radiotherapy. Then, it is widely regarded as an ideal mode for reirradiation and pediatrics due to reducing unwanted side effects by lessening the dose to normal tissue. During the past decade, the application of PBT has been rapidly increasing worldwide and gradually expanding for the treatment of various malignancies. However, to date, the role of PBT in clinical settings is still controversial, and there are considerable challenges in its application. We systematically review the latest advances of PBT and the challenges for patient treatment in the era of precision medicine.

The Practicality of ICRU and Considerations for Future ICRU Definitions

The International Commission on Radiation Units and Measurements (ICRU) volumes are standardized volume definitions used in radiation oncology practice that have evolved over time to account for advancements in technology and radiation planning. The current definitions have strengths but also practical limitations. The main limitation is related to the process of accounting for tumor motion during treatment. As radiotherapeutic techniques become more precise, motion interplay effects and anatomical changes during treatment must be taken into account to ensure accurate and safe delivery of treatment. Adaptive replanning can help to mitigate the effect of these uncertainties and widen the therapeutic ratio by maximizing dose to the tumor and protecting critical normal structures. As adaptive replanning becomes more common, standardization of how adaptive therapy is implemented and reported will become necessary.

Intensity modulated proton therapy (IMPT) - The future of IMRT for head and neck cancer

Radiation therapy plays an integral role in the management of head and neck cancers (HNCs). While most HNC patients have historically been treated with photon-based radiation techniques such as intensity modulated radiation therapy (IMRT), there is a growing awareness of the potential clinical benefits of proton therapy over IMRT in the definitive, postoperative and reirradiation settings given the unique physical properties of protons. Intensity modulated proton therapy (IMPT), also known as "pencil beam proton therapy," is a sophisticated mode of proton therapy that is analogous to IMRT and an active area of investigation in cancer care. Multifield optimization IMPT allows for high quality plans that can target superficially located HNCs as well as large neck volumes while significantly reducing integral doses. Several dosimetric studies have demonstrated the superiority of IMPT over IMRT to improve dose sparing of nearby organs such as the larynx, salivary glands, and esophagus. Evidence of the clinical translation of these dosimetric advantages has been demonstrated with documented toxicity reductions (such as decreased feeding tube dependency) after IMPT for patients with HNCs. While there are relative challenges to IMPT planning that exist today such as particle range uncertainties and high sensitivity to anatomical changes, ongoing investigations in image-guidance techniques and robust optimization methods are promising. A systematic approach towards utilizing IMPT and additional prospective studies are necessary in order to more accurately estimate the clinical benefit of IMPT over IMRT and passive proton therapy on a case-by-case basis for patients with sub-site specific HNCs.