Quantification of deformable image registration uncertainties for dose accumulation on head and neck cancer proton treatments.

PURPOSE: Head and neck cancer (HNC) patients in radiotherapy require adaptive treatment plans due to anatomical changes. Deformable image registration (DIR) is used in adaptive radiotherapy, e.g. for deformable dose accumulation (DDA). However, DIR's ill-posedness necessitates addressing uncertainties, often overlooked in clinical implementations. DIR's further clinical implementation is hindered by missing quantitative commissioning and quality assurance tools. This study evaluates one pathway for more quantitative DDA uncertainties. METHODS: For five HNC patients, each with multiple repeated CTs acquired during treatment, a simultaneous-integrated boost (SIB) plan was optimized. Recalculated doses were warped individually using multiple DIRs from repeated to reference CTs, and voxel-by-voxel dose ranges determined an error-bar for DDA. Followed by evaluating, a previously proposed early-stage DDA uncertainty estimation method tested for lung cancer, which combines geometric DIR uncertainties, dose gradients and their directional dependence, in the context of HNC. RESULTS: Applying multiple DIRs show dose differences, pronounced in high dose gradient regions. The patient with largest anatomical changes (-13.1 % in ROI body volume), exhibited 33 % maximum uncertainty in contralateral parotid, with 54 % of voxels presenting an uncertainty >5 %. Accumulation over multiple CTs partially mitigated uncertainties. The estimation approach predicted 92.6 % of voxels within ±5 % to the reference dose uncertainty across all patients. CONCLUSIONS: DIR variations impact accumulated doses, emphasizing DDA uncertainty quantification's importance for HNC patients. Multiple DIR dose warping aids in quantifying DDA uncertainties. An estimation approach previously described for lung cancer was successfully validated for HNC, for SIB plans, presenting different dose gradients, and for accumulated treatments.

A survey of practice patterns for real-time intrafractional motion-management in particle therapy.

Background and purpose: Organ motion compromises accurate particle therapy delivery. This study reports on the practice patterns for real-time intrafractional motion-management in particle therapy to evaluate current clinical practice and wishes and barriers to implementation. Materials and methods: An institutional questionnaire was distributed to particle therapy centres worldwide (7/2020-6/2021) asking which type(s) of real-time respiratory motion management (RRMM) methods were used, for which treatment sites, and what were the wishes and barriers to implementation. This was followed by a three-round DELPHI consensus analysis (10/2022) to define recommendations on required actions and future vision. With 70 responses from 17 countries, response rate was 100% for Europe (23/23 centres), 96% for Japan (22/23) and 53% for USA (20/38). Results: Of the 68 clinically operational centres, 85% used RRMM, with 41% using both rescanning and active methods. Sixty-four percent used active-RRMM for at least one treatment site, mostly with gating guided by an external marker. Forty-eight percent of active-RRMM users wished to expand or change their RRMM technique. The main barriers were technical limitations and limited resources. From the DELPHI analysis, optimisation of rescanning parameters, improvement of motion models, and pre-treatment 4D evaluation were unanimously considered clinically important future focus. 4D dose calculation was identified as the top requirement for future commercial treatment planning software. Conclusion:  A majority of particle therapy centres have implemented RRMM. Still, further development and clinical integration were desired by most centres. Joint industry, clinical and research efforts are needed to translate innovation into efficient workflows for broad-scale implementation.

A survey of practice patterns for adaptive particle therapy for interfractional changes.

Background and purpose: Anatomical changes may compromise the planned target coverage and organs-at-risk dose in particle therapy. This study reports on the practice patterns for adaptive particle therapy (APT) to evaluate current clinical practice and wishes and barriers to further implementation. Materials and methods: An institutional questionnaire was distributed to PT centres worldwide (7/2020-6/2021) asking which type of APT was used, details of the workflow, and what the wishes and barriers to implementation were. Seventy centres from 17 countries participated. A three-round Delphi consensus analysis (10/2022) among the authors followed to define recommendations on required actions and future vision. Results: Out of the 68 clinically operational centres, 84% were users of APT for at least one treatment site with head and neck being most common. APT was mostly performed offline with only two online APT users (plan-library). No centre used online daily re-planning. Daily 3D imaging was used for APT by 19% of users. Sixty-eight percent of users had plans to increase their use or change their technique for APT. The main barrier was "lack of integrated and efficient workflows". Automation and speed, reliable dose deformation for dose accumulation and higher quality of in-room volumetric imaging were identified as the most urgent task for clinical implementation of online daily APT. Conclusion: Offline APT was implemented by the majority of PT centres. Joint efforts between industry research and clinics are needed to translate innovations into efficient and clinically feasible workflows for broad-scale implementation of online APT.

Inter- and intrafractional 4D dose accumulation for evaluating ΔNTCP robustness in lung cancer.

BACKGROUND AND PURPOSE: Model-based selection of proton therapy patients relies on a predefined reduction in normal tissue complication probability (NTCP) with respect to photon therapy. The decision is necessarily made based on the treatment plan, but NTCP can be affected when the delivered treatment deviates from the plan due to delivery inaccuracies. Especially for proton therapy of lung cancer, this can be important because of tissue density changes and, with pencil beam scanning, the interplay effect between the proton beam and breathing motion. MATERIALS AND METHODS: In this work, we verified whether the expected benefit of proton therapy is retained despite delivery inaccuracies by reconstructing the delivered treatment using log-file based dose reconstruction and inter- and intrafractional accumulation. Additionally, the importance of two uncertain parameters for treatment reconstruction, namely deformable image registration (DIR) algorithm and α/ß ratio, was assessed. RESULTS: The expected benefit or proton therapy was confirmed in 97% of all studied cases, despite regular differences up to 2 percent point (p.p.) NTCP between the delivered and planned treatments. The choice of DIR algorithm affected NTCP up to 1.6 p.p., an order of magnitude higher than the effect of α/ß ratio. CONCLUSION: For the patient population and treatment technique employed, the predicted clinical benefit for patients selected for proton therapy was confirmed for 97.0% percent of all cases, although the NTCP based proton selection was subject to 2 p.p. variations due to delivery inaccuracies.

Optically stimulated luminescence dosimeters for simultaneous measurement of point dose and dose-weighted LET in an adaptive proton therapy workflow.

Purpose: To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy. Methods: A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs. Results: The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response. Conclusion: The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.

Experimental validation of daily adaptive proton therapy.

Anatomical changes during proton therapy require rapid treatment plan adaption to mitigate the associated dosimetric impact. This in turn requires a highly efficient workflow that minimizes the time between imaging and delivery. At the Paul Scherrer Institute, we have developed an online adaptive workflow, which is specifically designed for treatments in the skull-base/cranium, with the focus set on simplicity and minimizing changes to the conventional workflow. The dosimetric and timing performance of this daily adaptive proton therapy (DAPT) workflow has been experimentally investigated using an in-house developed DAPT software and specifically developed anthropomorphic phantom. After a standard treatment preparation, which includes the generation of a template plan, the treatment can then be adapted each day, based on daily imaging acquired on an in-room CT. The template structures are then rigidly propagated to this CT and the daily plan is fully re-optimized using the same field arrangement, DVH constraints and optimization settings of the template plan. After a dedicated plan QA, the daily plan is delivered. To minimize the time between imaging and delivery, clinically integrated software for efficient execution of all online adaption steps, as well as tools for comprehensive and automated QA checks, have been developed. Film measurements of an end-to-end validation of a multi-fraction DAPT treatment showed high agreement to the calculated doses. Gamma pass rates with a 3%/3 mm criteria were >92% when comparing the measured dose to the template plan. Additionally, a gamma pass rate >99% was found comparing measurements to the Monte Carlo dose of the daily plans reconstructed from the logfile, accumulated over the delivered fractions. With this, we experimentally demonstrate that the described adaptive workflow can be delivered accurately in a timescale similar to a standard delivery.

An approach for estimating dosimetric uncertainties in deformable dose accumulation in pencil beam scanning proton therapy for lung cancer.

Deformable image registration (DIR) is an important component for dose accumulation and associated clinical outcome evaluation in radiotherapy. However, the resulting deformation vector field (DVF) is subject to unavoidable discrepancies when different algorithms are applied, leading to dosimetric uncertainties of the accumulated dose. We propose here an approach for proton therapy to estimate dosimetric uncertainties as a consequence of modeled or estimated DVF uncertainties. A patient-specific DVF uncertainty model was built on the first treatment fraction, by correlating the magnitude differences of five DIR results at each voxel to the magnitude of any single reference DIR. In the following fractions, only the reference DIR needs to be applied, and DVF geometric uncertainties were estimated by this model. The associated dosimetric uncertainties were then derived by considering the estimated geometric DVF uncertainty, the dose gradient of fractional recalculated dose distribution and the direction factor from the applied reference DIR of this fraction. This estimated dose uncertainty was respectively compared to the reference dose uncertainty when different DIRs were applied individually for each dose warping. This approach was validated on seven NSCLC patients, each with nine repeated CTs. The proposed model-based method is able to achieve dose uncertainty distribution on a conservative voxel-to-voxel comparison within ±5% of the prescribed dose to the 'reference' dosimetric uncertainty, for 77% of the voxels in the body and 66%-98% of voxels in investigated structures. We propose a method to estimate DIR induced uncertainties in dose accumulation for proton therapy of lung tumor treatments.

Dosimetric influence of deformable image registration uncertainties on propagated structures for online daily adaptive proton therapy of lung cancer patients.

PURPOSE: A major burden of introducing an online daily adaptive proton therapy (DAPT) workflow is the time and resources needed to correct the daily propagated contours. In this study, we evaluated the dosimetric impact of neglecting the online correction of the propagated contours in a DAPT workflow. MATERIAL AND METHODS: For five NSCLC patients with nine repeated deep-inspiration breath-hold CTs, proton therapy plans were optimised on the planning CT to deliver 60 Gy-RBE in 30 fractions. All repeated CTs were registered with six different clinically used deformable image registration (DIR) algorithms to the corresponding planning CT. Structures were propagated rigidly and with each DIR algorithm and reference structures were contoured on each repeated CT. DAPT plans were optimised with the uncorrected, propagated structures (propagated DAPT doses) and on the reference structures (ideal DAPT doses), non-adapted doses were recalculated on all repeated CTs. RESULTS: Due to anatomical changes occurring during the therapy, the clinical target volume (CTV) coverage of the non-adapted doses reduces on average by 9.7% (V95) compared to an ideal DAPT doses. For the propagated DAPT doses, the CTV coverage was always restored (average differences in the CTV V95 < 1% compared to the ideal DAPT doses). Hotspots were always reduced with any DAPT approach. CONCLUSION: For the patients presented here, a benefit of online DAPT was shown, even if the daily optimisation is based on propagated structures with some residual uncertainties. However, a careful (offline) structure review is necessary and corrections can be included in an offline adaption.

Extension of the phenotypic spectrum of GLE1-related disorders to a mild congenital form resembling congenital myopathy.

BACKGROUND: GLE1 (GLE1, RNA Export Mediator, OMIM#603371) variants are associated with severe autosomal recessive motor neuron diseases, that are lethal congenital contracture syndrome 1 (LCCS1, OMIM#253310) and congenital arthrogryposis with anterior horn cell disease (CAAHD, OMIM#611890). The clinical spectrum of GLE1-related disorders has been expanding these past years, including with adult-onset amyotrophic lateral sclerosis (ALS) GLE1-related forms, especially through the new molecular diagnosis strategies associated with the emergence of next-generation sequencing (NGS) technologies. However, despite this phenotypic variability, reported congenital or ALS adult-onset forms remain severe, leading to premature death. METHODS: Through multidisciplinary interactions between our Neuropediatric and Medical Genetics departments, we were able to diagnose two siblings presenting with congenital disorder, using an NGS approach accordingly to the novel French national recommendations. RESULTS: Two siblings with very similar clinical features, meaning neuromuscular disorder of neonatal onset with progressive improvement, were examined in our Neuropediatrics department. The clinical presentation evoked initially congenital myopathy with autosomal recessive inheritance. However, additional symptoms such as mild dysmorphic features including high anterior hairline, downslanted palpebral fissures, anteverted nares, smooth philtrum with thin upper-lip, narrow mouth and microretrognathia or delayed expressive language and postnatal growth retardation were suggestive of a more complex clinical presentation and molecular diagnosis. Our NGS approach revealed an unexpected molecular diagnosis for these two siblings, meaning the presence of the homozygous c.1808G>T GLE1 variant. CONCLUSIONS: We here report the mildest phenotype ever described, in two siblings carrying the homozygous c.1808G>T GLE1 variant, further widening the clinical spectrum of GLE1-related diseases. Moreover, by reflecting current medical practice, this case report confirms the importance of establishing regular multidisciplinary meetings, essential for discussing such difficult clinical presentations to finally enable molecular diagnosis, especially when NGS technologies are used.

Deformable image registration uncertainty for inter-fractional dose accumulation of lung cancer proton therapy.

BACKGROUND AND PURPOSE: Non-small cell lung cancer (NSCLC) patients show typically large anatomical changes during treatment, making recalculation or adaption necessary. For report and review, the applied treatment dose can be accumulated on the reference planning CT using deformable image registration (DIR). We investigated the dosimetric impact of using six different clinically available DIR algorithms for dose accumulation in presence of inter-fractional anatomy variations. MATERIALS AND METHODS: For seven NSCLC patients, proton treatment plans with 66 Gy-RBE to the planning target volume (PTV) were optimised. Nine repeated CTs were registered to the planning CT using six DIR algorithms each. All CTs were acquired in visually guided deep-inspiration breath-hold. The plans were recalculated on the repeated CTs and warped back to the planning CT using the corresponding DIRs. Fraction doses warped with the same DIR were summed up to six different accumulated dose distributions per patient, and compared to the initial dose. RESULTS: The PTV-V95 of accumulated doses decreased by 16% on average over all patients, with variations due to DIR selection of 8.7%. A separation of the dose effects caused by anatomical changes and DIR uncertainty showed a good agreement between the dose degradation caused by anatomical changes and the dose predicted from the average of all DIRs (differences of only 1.6%). CONCLUSION: The dose degradation caused by anatomical changes was more pronounced than the uncertainty of employing different DIRs for dose accumulation, with averaged results from several DIRs providing a good representation of dose degradation caused by anatomy. However, accumulated dose variations between DIRs can be substantial, leading to an additional dose uncertainty.

Daily Adaptive Proton Therapy: Is it Appropriate to Use Analytical Dose Calculations for Plan Adaption?

PURPOSE: The accuracy of analytical dose calculations (ADC) and dose uncertainties resulting from anatomical changes are both limiting factors in proton therapy. For the latter, rapid plan adaption is necessary; for the former, Monte Carlo (MC) approaches are increasingly recommended. These, however, are inherently slower than analytical approaches, potentially limiting the ability to rapidly adapt plans. Here, we compare the clinical relevance of uncertainties resulting from both. METHODS AND MATERIALS: Five patients with non-small cell lung cancer with up to 9 computed tomography (CT) scans acquired during treatment and five paranasal (head and neck) patients with 10 simulated anatomical changes (sinus filling) were analyzed. On the initial planning CT scans, treatment plans were optimized and calculated using an ADC and then recalculated with MC. Additionally, all plans were recalculated (non-adapted) and reoptimized (adapted) on each repeated CT using the same ADC as for the initial plan, and the resulting dose distributions were compared. RESULTS: When comparing analytical and MC calculations in the initial treatment plan and averaged over all patients, 94.2% (non-small cell lung cancer) and 98.5% (head and neck) of voxels had differences <±5%, and only minor differences in clinical target volume (CTV) V95 (average <2%) were observed. In contrast, when recalculating nominal plans on the repeat (anatomically changed) CT scans, CTV V95 degraded by up to 34%. Plan adaption, however, restored CTV V95 differences between adapted and nominal plans to <0.5%. Adapted organ-at-risk doses remained the same or improved. CONCLUSIONS: Dose degradations caused by anatomic changes are substantially larger than uncertainties introduced by the use of analytical instead of MC dose calculations. Thus, if the use of analytical calculations can enable more rapid and efficient plan adaption than MC approaches, they can and should be used for plan adaption for these patient groups.

Shortening delivery times for intensity-modulated proton therapy by reducing the number of proton spots: an experimental verification.

Delivery times of intensity-modulated proton therapy (IMPT) can be shortened by reducing the number of spots in the treatment plan, but this may affect clinical plan delivery. Here, we assess the experimental deliverability, accuracy and time reduction of spot-reduced treatment planning for a clinical case, as well as its robustness. For a single head-and-neck cancer patient, a spot-reduced plan was generated and compared with the conventional clinical plan. The number of proton spots was reduced using the iterative 'pencil beam resampling' technique. This involves repeated inverse optimization, while adding in each iteration a small sample of randomly selected spots and subsequently excluding low-weighted spots until plan quality deteriorates. Field setup was identical for both plans and comparable dosimetric quality was a prerequisite. Both IMPT plans were delivered on PSI Gantry 2 and measured in water, while delivery log-files were used to extract delivery times and reconstruct the delivered dose via Monte-Carlo dose calculations. In addition, robustness simulations were performed to assess sensitivity to machine inaccuracies and errors in patient setup and proton range. The number of spots was reduced by 96% (from 33 855 to 1510 in total) without compromising plan quality. The spot-reduced plan was deliverable on our gantry in standard clinical mode and resulted in average delivery times per field being shortened by 46% (from 51.2 to 27.6 s). For both plans, differences between measured and calculated dose were within clinical tolerance for patient-specific verifications and Monte-Carlo dose reconstructions were in accordance with clinical experience. The spot-reduced plan was slightly more sensitive to machine inaccuracies, but more robust against setup and range errors. In conclusion, for an example head-and-neck case, spot-reduced IMPT planning provided a deliverable treatment plan and enabled considerable shortening of the delivery time (∼50%) without compromising plan quality or delivery accuracy, and without substantially affecting robustness.

Radiation-induced optic neuropathy after pencil beam scanning proton therapy for skull-base and head and neck tumours.

OBJECTIVE: To assess the radiation-induced optic neuropathy (RION) prevalence, following high dose pencil beam scanning proton therapy (PBSPT) to skull base and head and neck (H&N) tumours. METHODS: Between 1999 and 2014, 216 adult patients, median age 47 years (range, 18-77), were treated with PBS PT for skull base or H&N malignancies, delivering ≥45 GyRBE to the optic nerve(s) (ON) and/or optic chiasma (OC). The median administered dose to the planning target volume was 74.0 GyRBE (range, 54.0-77.4). The median follow-up was 5.3 years (range, 0.8-15.9). RESULTS: RION was observed in 14 (6.5%) patients at a median time of 13.2 months (range, 4.8-42.6) following PBSPT. Most (92.9%) of RION were symptomatic. Most affected patients (11/14; 79%) developed unilateral toxicity. Grade 4, 3, 2 and 1 toxicity was observed in 10, 2, 1 and 1 patients, respectively. On univariate analyses, age (<70 vs ≥70 years; p < 0.0001), hypertension (p = 0.0007) and tumour abutting the optic apparatus (p = 0.012) were associated with RION. OC's V60 GyRBE was of border line significance (p = 0.06). None of the other evaluated OC-ON dose/volume metrics (Dmax, Dmean, V40-60) were significantly associated with this complication. CONCLUSION: These data suggest that high-dose PBS PT for skull base and H&N tumours is associated with a low prevalence of RION. Caution should be however exercised when treating elderly/hypertensive patients with tumours abutting the optic apparatus. ADVANCES IN KNOWLEDGE: This is the first study reporting the risk of developing RION following proton therapy with PBS technique, demonstrating the safety of this treatment.

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.

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.

Intensity modulated proton therapy plan generation in under ten seconds.

Background: Treatment planning for intensity modulated proton therapy (IMPT) can be significantly improved by reducing the time for plan calculation, facilitating efficient sampling of the large solution space characteristic of IMPT treatments. Additionally, fast plan generation is a key for online adaptive treatments, where the adapted plan needs to be ideally available in a few seconds. However, plan generation is a computationally demanding task and, although dose restoration methods for adaptive therapy have been proposed, computation times remain problematic. Material and methods: IMPT plan generation times were reduced by the development of dedicated graphical processing unit (GPU) kernels for our in-house, clinically validated, dose and optimization algorithms. The kernels were implemented into a coherent system, which performed all steps required for a complete treatment plan generation. Results: Using a single GPU, our fast implementation was able to generate a complete new treatment plan in 5-10 sec for typical IMPT cases, and in under 25 sec for plans to very large volumes such as for cranio-spinal axis irradiations. Although these times did not include the manual input of optimization parameters or a final clinical dose calculation, they included all required computational steps, including reading of CT and beam data. In addition, no compromise was made on plan quality. Target coverage and homogeneity for four patient plans improved (by up to 6%) or remained the same (changes <1%). No worsening of dose-volume parameters of the relevant organs at risk by more than 0.5% was observed. Conclusions: Fast plan generation with a clinically validated dose calculation and optimizer is a promising approach for daily adaptive proton therapy, as well as for automated or highly interactive planning.

Long term outcome of skull-base chondrosarcoma patients treated with high-dose proton therapy with or without conventional radiation therapy.

BACKGROUND AND PURPOSE: Skull-base chondrosarcoma (ChSa) is a rare bone tumor and the outcome of patients with this malignancy has been documented only in a limited number of series with a restricted number of patients. OBJECTIVE: This study was conducted to assess the outcome and prognostic factors of a large cohort of ChSa patients treated with radiotherapy in two proton therapy centers. MATERIALS AND METHODS: From 1996 to 2015, 251 (male, 43.4%) patients (mean age, 42.0 ±â€¯16.2 years) were treated with protons with (n = 135; 53.8%) or without photons (n = 116; 46.2%). Median delivered dose was 70.2 GyRBE. Failure-free survival (FFS), overall survival (OS) and CTCAE grade ≥3 toxicity free survival (TFS) were calculated using the Kaplan-Meier method. RESULTS: After a median follow-up of 88.0 months for surviving patients, local and distant failures were observed in 12 (4.8%) and 4 (1.6%) patients, respectively. Late failures >6 years were observed in 4 (33.3%) patients. The estimated 7-year FFS was 93.1%. Twenty-five (10%) patients died. The estimated 7-year OS was 93.6%. Tumor volume (p = 0.006) and optic pathway compression (p = 0.027) were significantly associated with the risk of treatment failure on univariate analysis. Treatment failure was significantly associated with a higher risk of death (hazard ratio = 126). The estimated 7-year TFS was 84.2%. CONCLUSIONS: The outcome of skull-base ChSa patients treated with high-dose protons with or without photons is excellent, particularly for patients with small tumors with no optic pathway compression. Treatment failure was however associated with a significantly increased risk of death.

Long-Term Outcomes and Prognostic Factors After Pencil-Beam Scanning Proton Radiation Therapy for Spinal Chordomas: A Large, Single-Institution Cohort.

PURPOSE: To evaluate the efficacy and safety of high-dose pencil-beam scanning proton therapy (PBS-PT) in the adjuvant treatment of spinal chordomas. METHODS AND MATERIALS: Between 1997 and 2015, 100 patients with spinal chordomas (median age, 56 years; range, 25-81 years) were treated with adjuvant PBS-PT at the Paul Scherrer Institute: cervical (n = 46), thoracic (n = 4), lumbar (n = 12), and sacral (n = 38). The majority (88%) received PBS-PT alone rather than combined photon-proton therapy. The median radiation therapy dose prescribed was 74 Gy (relative biological effectiveness [RBE]) (range, 59.4-77 Gy [RBE]). Thirty-nine patients (39%) had undergone surgical stabilization, primarily with titanium hardware, before radiation therapy. RESULTS: With a median follow-up of 65 months (range, 13-175 months), 5-year local control, disease control, and overall survival rates were 63% (95% confidence interval [CI] 57.7-68.7%; median, 103 months), 57% (95% CI 50.9-62.1%; median, 82 months), and 81% (95% CI 76.8-85.6%; median, 157 months), respectively. On univariate and multivariate analyses, the presence of surgical stabilization was highly prognostic for worsened outcomes. Multivariate analysis also revealed the extent of treatment volumes and presence of gross residual disease to be important in predicting outcomes. High-grade (grade ≥3) toxicities were rare in both the acute (8%) and late (6%) settings. CONCLUSION: For spinal chordomas, PBS-PT remains a highly effective and safe method for delivery of dose-escalated adjuvant radiation therapy. The presence of metallic surgical stabilization prognosticates for worsened outcomes. Further investigation is warranted to characterize ideal treatment volumes and effect of surgical stabilization on therapy for these challenging tumors.

Anatomical robust optimization to account for nasal cavity filling variation during intensity-modulated proton therapy: a comparison with conventional and adaptive planning strategies.

The aim of this study is to develop an anatomical robust optimization method for intensity-modulated proton therapy (IMPT) that accounts for interfraction variations in nasal cavity filling, and to compare it with conventional single-field uniform dose (SFUD) optimization and online plan adaptation. We included CT data of five patients with tumors in the sinonasal region. Using the planning CT, we generated for each patient 25 'synthetic' CTs with varying nasal cavity filling. The robust optimization method available in our treatment planning system 'Erasmus-iCycle' was extended to also account for anatomical uncertainties by including (synthetic) CTs with varying patient anatomy as error scenarios in the inverse optimization. For each patient, we generated treatment plans using anatomical robust optimization and, for benchmarking, using SFUD optimization and online plan adaptation. Clinical target volume (CTV) and organ-at-risk (OAR) doses were assessed by recalculating the treatment plans on the synthetic CTs, evaluating dose distributions individually and accumulated over an entire fractionated 50 GyRBE treatment, assuming each synthetic CT to correspond to a 2 GyRBE fraction. Treatment plans were also evaluated using actual repeat CTs. Anatomical robust optimization resulted in adequate CTV doses (V95% ⩾ 98% and V107% ⩽ 2%) if at least three synthetic CTs were included in addition to the planning CT. These CTV requirements were also fulfilled for online plan adaptation, but not for the SFUD approach, even when applying a margin of 5 mm. Compared with anatomical robust optimization, OAR dose parameters for the accumulated dose distributions were on average 5.9 GyRBE (20%) higher when using SFUD optimization and on average 3.6 GyRBE (18%) lower for online plan adaptation. In conclusion, anatomical robust optimization effectively accounted for changes in nasal cavity filling during IMPT, providing substantially improved CTV and OAR doses compared with conventional SFUD optimization. OAR doses can be further reduced by using online plan adaptation.

A robust optimisation approach accounting for the effect of fractionation on setup uncertainties.

Proton plans are subject to a number of uncertainties which must be accounted for to ensure that they are delivered safely. Misalignment resulting from residual errors in daily patient positioning can result in both a displacement and distortion of dose distributions. This can be particularly important for intensity modulated proton therapy treatments where the accurate alignment of highly modulated fields may be required to deliver the intended treatment. A number of methods to generate plans that are robust to these uncertainties exist. These include robust optimisation approaches which account for the effect of uncertainties on the dose distribution within the optimisation process. However, robustness to uncertainty comes at the cost of plan quality. For this reason, it is important that the uncertainties considered are realistic. Existing approaches to robust optimisation have neglected the role of fractionated treatment deliveries in reducing the uncertainties that result from random setup errors. Here, a method of robust optimisation which accounts for this effect is presented and is evaluated using a 2D planning environment. The optimisation algorithm considers the dose in the estimated upper and lower bounds of the dose distribution under the effect of setup and range errors. A comparison with plans robustly optimised without consideration of the effect of fractionation and conventionally optimised plans is presented. Fractionation incorporated robust optimisation demonstrates a reduced sensitivity to uncertainty compared to conventionally optimised plans and a reduced integral dose compared to robustly optimised plans.