Transitioning from conventional photon therapy to proton therapy for primary brain tumors.

INTRODUCTION: Proton radiation therapy (PT) has become a treatment option alongside photon therapy (XRT) for lower-grade gliomas (LGG). In this single-institution retrospective study, we investigate the patient characteristics and treatment outcomes, including pseudo-progression (PsP), for LGG patients selected for PT. METHOD: Adult patients with grade 2-3 glioma consecutively treated with radiotherapy (RT) from May 2012 to December 2019 were retrospectively included in this cohort study. Tumor characteristics and treatment data were collected. The groups treated with PT and XRT were compared regarding treatment characteristics, side effects, occurrence of PsP, and survival outcomes. PsP was defined as new or growing lesions followed by either decrease or stabilization during a 12 month-period with no treatment. RESULTS: Out of 143 patients meeting the inclusion criteria, 44 were treated with PT, 98 with XRT and one with mixed PT + XRT. The patients receiving PT were younger, had a lower tumor grade, more oligodendrogliomas and received a lower mean brain and brainstem dose. PsP was observed in 21 out of 126 patients, with no difference between XRT and PT (p = .38). The rate of fatigue in immediate connection to RT (zero to three months after) was higher for XRT than for PT (p = .016). The PT patients had a significantly better PFS and OS than the XRT patients (p = .025 and .035), but in multivariate analysis radiation modality was non-significant. Higher average dose to both brain and brainstem was associated with inferior PFS and OS (p < .001). Median follow-up time were 69 months and 26 months for XRT and PT patients, respectively. CONCLUSION: Contrary to previous studies, there was no difference in risk of PsP for XRT and PT. PT was associated with lower rates of fatigue <3 months after RT. The superior survival outcomes for PT indicates that the patients with the best prognosis were referred to PT.

Volumetric modulated arc therapy dose prediction and deliverable treatment plan generation for prostate cancer patients using a densely connected deep learning model.

BACKGROUND AND PURPOSE: Radiation therapy treatment planning is a manual, time-consuming task that might be accelerated using machine learning algorithms. In this study, we aimed to evaluate if a triplet-based deep learning model can predict volumetric modulated arc therapy (VMAT) dose distributions for prostate cancer patients. MATERIALS AND METHODS: A modified U-Net was trained on triplets, a combination of three consecutive image slices and corresponding segmentations, from 160 patients, and compared to a baseline U-Net. Dose predictions from 17 test patients were transformed into deliverable treatment plans using a novel planning workflow. RESULTS: The model achieved a mean absolute dose error of 1.3%, 1.9%, 1.0% and ≤ 2.6% for clinical target volume (CTV) CTV_D100%, planning target volume (PTV) PTV_D98%, PTV_D95% and organs at risk (OAR) respectively, when compared to the clinical ground truth (GT) dose distributions. All predicted distributions were successfully transformed into deliverable treatment plans and tested on a phantom, resulting in a passing rate of 100% (global gamma, 3%, 2 mm, 15% cutoff). The dose difference between deliverable treatment plans and GT dose distributions was within 4.4%. The difference between the baseline model and our improved model was statistically significant (p < 0.05) for CVT_D100%, PTV_D98% and PTV_D95%. CONCLUSION: Triplet-based training improved VMAT dose distribution predictions when compared to 2D. Dose predictions were successfully transformed into deliverable treatment plans using our proposed treatment planning procedure. Our method may automate parts of the workflow for external beam prostate radiation therapy and improve the overall treatment speed and plan quality.

The effect of prostate motion during hypofractionated radiotherapy can be reduced by using flattening filter free beams.

BACKGROUND AND PURPOSE: Hypofractionated radiotherapy of prostate cancer reduces the overall treatment time but increases the per-fraction beam-on time due to the higher fraction doses. This increased fraction treatment time results in a larger uncertainty of the prostate position. The purpose of this study was to investigate the effect of prostate motion during flattening filter free (FFF) Volumetric Modulated Arc Therapy (VMAT) in ultrahypofractionation of prostate cancer radiotherapy with preserved plan quality compared to conventional flattened beams. MATERIALS AND METHODS: Nine prostate patients from the Scandinavian HYPO-RT-PC trial were re-planned using VMAT technique with both conventional and flattening filter free beams. Two fractionation schedules were used, one hypofractionated (42.7 Gy in 7 fractions), and one conventional (78.0 Gy in 39 fractions). Pre-treatment verification measurements were performed on all plans and the treatment time was recorded. Measurements with simulated prostate motion were performed for the plans with the longest treatment times. RESULTS: All the 10FFF plans fulfilled the clinical gamma pass rate, 90% (3%, 2 mm), during all simulated prostate motion trajectories. The 10MV plans only fulfilled the clinical pass rate for three of the trajectories. The mean beam-on-time for the hypofractionated plans were reduced from 2.3 min to 1.0 min when using 10FFF compared to 10MV. No clinically relevant differences in dose distribution were identified when comparing the plans with different beam qualities. CONCLUSION: Flattening-filter free VMAT reduces treatment times, limiting the dosimetric effect of organ motion for ultrahypofractionated prostate cancer with preserved plan quality.

Introducing multiple treatment plan-based comparison to investigate the performance of gantry angle optimisation (GAO) in IMRT for head and neck cancer.

BACKGROUND AND PURPOSE: The purpose of this study was to evaluate the performance of gantry angle optimisation (GAO) compared to equidistant beam geometry for two inverse treatment planning systems (TPSs) by utilising the information obtained from a range of treatment plans. MATERIAL AND METHODS: The comparison was based on treatment plans generated for four different head and neck (H&N) cancer cases using two inverse treatment planning systems (TPSs); Varian Eclipse™ representing dynamic MLC intensity modulated radiotherapy (IMRT) and Oncentra® Masterplan representing segmented MLC-based IMRT. The patient cases were selected on the criterion of representing different degrees of overlap between the planning target volume (PTV) and the investigated organ at risk, the ipsilateral parotid gland. For each case, a number of 'Pareto optimal' plans were generated in order to investigate the trade-off between the under-dosage to the PTV (V(PTV,D < 95%)) or the decrease in dose homogeneity (D(5)-D(95)) to the PTV as a function of the mean absorbed dose to the ipsilateral parotid gland ((parotid gland)). RESULTS: For the Eclipse system, GAO had a clear advantage for the cases with smallest overlap (Cases 1 and 2). The set of data points, representing the underlying trade-offs, generated with and without using GAO were, however, not as clearly separated for the cases with larger overlap (Cases 3 and 4). With the OMP system, the difference was less pronounced for all cases. The Eclipse GAO displays the most favourable trade-off for all H&N cases. CONCLUSIONS: We have found differences in the effectiveness of GAO as compared to equidistant beam geometry, in terms of handling conflicting trade-offs for two commercial inverse TPSs. A comparison, based on a range of treatment plans, as developed in this study, is likely to improve the understanding of conflicting trade-offs and might apply to other thorough comparison techniques.

Conversion of helical tomotherapy plans to step-and-shoot IMRT plans--Pareto front evaluation of plans from a new treatment planning system.

PURPOSE: The resulting plans from a new type of treatment planning system called SharePlan have been studied. This software allows for the conversion of treatment plans generated in a TomoTherapy system for helical delivery, into plans deliverable on C-arm linear accelerators (linacs), which is of particular interest for clinics with a single TomoTherapy unit. The purpose of this work was to evaluate and compare the plans generated in the SharePlan system with the original TomoTherapy plans and with plans produced in our clinical treatment planning system for intensity-modulated radiation therapy (IMRT) on C-arm linacs. In addition, we have analyzed how the agreement between SharePlan and TomoTherapy plans depends on the number of beams and the total number of segments used in the optimization. METHODS: Optimized plans were generated for three prostate and three head-and-neck (H&N) cases in the TomoTherapy system, and in our clinical treatment planning systems (TPS) used for IMRT planning with step-and-shoot delivery. The TomoTherapy plans were converted into step-and-shoot IMRT plans in SharePlan. For each case, a large number of Pareto optimal plans were created to compare plans generated in SharePlan with plans generated in the Tomotherapy system and in the clinical TPS. In addition, plans were generated in SharePlan for the three head-and-neck cases to evaluate how the plan quality varied with the number of beams used. Plans were also generated with different number of beams and segments for other patient cases. This allowed for an evaluation of how to minimize the number of required segments in the converted IMRT plans without compromising the agreement between them and the original TomoTherapy plans. RESULTS: The plans made in SharePlan were as good as or better than plans from our clinical system, but they were not as good as the original TomoTherapy plans. This was true for both the head-and-neck and the prostate cases, although the differences between the plans for the latter were small. The evaluation of the head-and-neck cases also showed that the plans generated in SharePlan were improved when more beams were used. The SharePlan Pareto front came close to the front for the TomoTherapy system when a sufficient number of beams were added. The results for plans generated with varied number of beams and segments demonstrated that the number of segments could be minimized with maintained agreement between SharePlan and TomoTherapy plans when 10-19 beams were used. CONCLUSIONS: This study showed (using Pareto front evaluation) that the plans generated in Share-Plan are comparable to plans generated in other TPSs. The evaluation also showed that the plans generated in SharePlan could be improved with the use of more beams. To minimize the number of segments needed in a plan with maintained agreement between the converted IMRT plans and the original TomoTherapy plans, 10-19 beams should be used, depending on target complexity. SharePlan has proved to be useful and should thereby be a time-saving complement as a backup system for clinics with a single TomoTherapy system installed alongside conventional C-arm linacs.