Improving knowledge-based treatment planning for lung cancer radiotherapy with automatic multi-criteria optimized training plans.

BACKGROUND: Knowledge-based planning (KBP) is a method for automated radiotherapy treatment planning where appropriate optimization objectives for new patients are predicted based on a library of training plans. KBP can save time and improve organ at-risk sparing and inter-patient consistency compared to manual planning, but its performance depends on the quality of the training plans. We used another system for automated planning, which generates multi-criteria optimized (MCO) plans based on a wish list, to create training plans for the KBP model, to allow seamless integration of knowledge from a new system into clinical routine. Model performance was compared for KBP models trained with manually created and automatic MCO treatment plans. MATERIAL AND METHODS: Two RapidPlan models with the same 30 locally advanced non-small cell lung cancer patients included were created, one containing manually created clinical plans (RP_CLIN) and one containing fully automatic multi-criteria optimized plans (RP_MCO). For 15 validation patients, model performance was compared in terms of dose-volume parameters and normal tissue complication probabilities, and an oncologist performed a blind comparison of the clinical (CLIN), RP_CLIN, and RP_MCO plans. RESULTS: The heart and esophagus doses were lower for RP_MCO compared to RP_CLIN, resulting in an average reduction in the risk of 2-year mortality by 0.9 percentage points and the risk of acute esophageal toxicity by 1.6 percentage points with RP_MCO. The oncologist preferred the RP_MCO plan for 8 patients and the CLIN plan for 7 patients, while the RP_CLIN plan was not preferred for any patients. CONCLUSION: RP_MCO improved OAR sparing compared to RP_CLIN and was selected for implementation in the clinic. Training a KBP model with clinical plans may lead to suboptimal output plans, and making an extra effort to optimize the library plans in the KBP model creation phase can improve the plan quality for many future patients.

First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer.

Background and purpose: In this study we developed a workflow for fully-automated generation of deliverable IMRT plans for a 1.5 T MR-Linac (MRL) based on contoured CT scans, and we evaluated automated MRL planning for rectal cancer.Methods: The Monte Carlo dose calculation engine used in the clinical MRL TPS (Monaco, Elekta AB, Stockholm, Sweden), suited for high accuracy dose calculations in a 1.5 T magnetic field, was coupled to our in-house developed Erasmus-iCycle optimizer. Clinically deliverable plans for 23 rectal cancer patients were automatically generated in a two-step process, i.e., multi-criterial fluence map optimization with Erasmus-iCycle followed by a conversion into a deliverable IMRT plan in the clinical TPS. Automatically generated plans (AUTOplans) were compared to plans that were manually generated with the clinical TPS (MANplans).Results: With AUTOplanning large reductions in planning time and workload were obtained; 4-6 h mainly hands-on planning for MANplans vs ∼1 h of mainly computer computation time for AUTOplans. For equal target coverage, the bladder and bowel bag Dmean was reduced in the AUTOplans by 1.3 Gy (6.9%) on average with a maximum reduction of 4.5 Gy (23.8%). Dosimetric measurements at the MRL demonstrated clinically acceptable delivery accuracy for the AUTOplans.Conclusions: A system for fully automated multi-criterial planning for a 1.5 T MR-Linac was developed and tested for rectal cancer patients. Automated planning resulted in major reductions in planning workload and time, while plan quality improved. Negative impact of the high magnetic field on the dose distributions could be avoided.

Plan-library supported automated replanning for online-adaptive intensity-modulated proton therapy of cervical cancer.

Background: Intensity-modulated proton therapy is sensitive to inter-fraction variations, including density changes along the pencil-beam paths and variations in organ-shape and location. Large day-to-day variations are seen for cervical cancer patients. The purpose of this study was to develop and evaluate a novel method for online selection of a plan from a patient-specific library of prior plans for different anatomies, and adapt it for the daily anatomy. Material and methods: The patient-specific library of prior plans accounting for altered target geometries was generated using a pretreatment established target motion model. Each fraction, the best fitting prior plan was selected. This prior plan was adapted using (1) a restoration of spot-positions (Bragg peaks) by adapting the energies to the new water equivalent path lengths; and (2) a spot addition to fully cover the target of the day, followed by a fast optimization of the spot-weights with the reference point method (RPM) to obtain a Pareto-optimal plan for the daily anatomy. Spot addition and spot-weight optimization could be repeated iteratively. The patient cohort consisted of six patients with in total 23 repeat-CT scans, with a prescribed dose of 45 Gy(RBE) to the primary tumor and the nodal CTV. Using a 1-plan-library (one prior plan based on all motion in the motion model) was compared to choosing from a 2-plan-library (two prior plans based on part of the motion). Results: Applying the prior-plan adaptation method with one iteration of adding spots resulted in clinically acceptable target coverage ( V95%≥95% and V107%≤2% ) for 37/46 plans using the 1-plan-library and 41/46 plans for the 2-plan-library. When adding spots twice, the 2-plan-library approach could obtain acceptable coverage for all scans, while the 1-plan-library approach showed V107%>2% for 3/46 plans. Similar OAR results were obtained. Conclusion: The automated prior-plan adaptation method can successfully adapt for the large day-to-day variations observed in cervical cancer patients.

Automated volumetric modulated arc therapy planning for whole pelvic prostate radiotherapy.

BACKGROUND: For several tumor entities, automated treatment planning has improved plan quality and planning efficiency, and may enable adaptive treatment approaches. Whole-pelvic prostate radiotherapy (WPRT) involves large concave target volumes, which present a challenge for volumetric arc therapy (VMAT) optimization. This study evaluates automated VMAT planning for WPRT-VMAT and compares the results with manual expert planning. METHODS: A system for fully automated multi-criterial plan generation was configured for each step of sequential-boost WPRT-VMAT, with final "autoVMAT" plans being automatically calculated by the Monaco treatment planning system (TPS; Elekta AB, Stockholm, Sweden). Configuration was based on manually generated VMAT plans (manualVMAT) of 5 test patients, the planning protocol, and discussions with the treating physician on wishes for plan improvements. AutoVMAT plans were then generated for another 30 evaluation patients and compared to manualVMAT plans. For all 35 patients, manualVMAT plans were optimized by expert planners using the Monaco TPS. RESULTS: AutoVMAT plans exhibited strongly improved organ sparing and higher conformity compared to manualVMAT. On average, mean doses (Dmean) of bladder and rectum were reduced by 10.7 and 4.5 Gy, respectively, by autoVMAT. Prostate target coverage (V95%) was slightly higher (+0.6%) with manualVMAT. In a blinded scoring session, the radiation oncologist preferred autoVMAT plans to manualVMAT plans for 27/30 patients. All treatment plans were considered clinically acceptable. The workload per patient was reduced by > 70 min. CONCLUSION: Automated VMAT planning for complex WPRT dose distributions is feasible and creates treatment plans that are generally dosimetrically superior to manually optimized plans.

First fully automated planning solution for robotic radiosurgery - comparison with automatically planned volumetric arc therapy for prostate cancer.

BACKGROUND: For conventional radiotherapy treatment units, automated planning can significantly improve plan quality. For robotic radiosurgery, systems for automatic generation of clinically deliverable plans do not yet exist. For prostate stereotactic body radiation therapy (SBRT), few studies have systematically compared VMAT with robotic treatment. MATERIAL AND METHODS: The multi-criteria autoplanning optimizer, developed at our institute, was coupled to the commercial treatment planning system of our robotic treatment unit, for fully automated generation of clinically deliverable plans (autoROBOT). The system was then validated by comparing autoROBOT plans with manually generated plans. Next, the autoROBOT system was used for systematic comparisons between autoROBOT plans and VMAT plans, that were also automatically generated (autoVMAT). CTV-PTV margins of 3 mm were used for autoROBOT (clinical routine) and autoVMAT plan generation. For autoVMAT, an extra plan was generated with 5 mm margin (often applied for VMAT). Plans were generated for a 4 × 9.5 Gy fractionation scheme. RESULTS: Compared to manual planning, autoROBOT improved rectum D[Formula: see text] (16%), V[Formula: see text] (75%) and D[Formula: see text] (41%), and bladder D[Formula: see text] (37%) (all p [Formula: see text] .002), with equal PTV coverage. In the autoROBOT and autoVMAT comparison, both with 3 mm margin, rectum doses were lower for autoROBOT by 5% for rectum D[Formula: see text] (p=.002), 33% for V[Formula: see text] (p=.001) and 4% for D[Formula: see text] (p=.05), with comparable PTV coverage and other OAR sparing. With 5 mm margin for VMAT, 18/20 plans had a PTV coverage lower than requested (<95%) and all plans had higher rectum doses than autoROBOT (mean percentage differences of 13% for D[Formula: see text], 69% for V[Formula: see text] and 32% for D[Formula: see text] (all p<.001)). CONCLUSIONS: The first system for fully automated generation of clinically deliverable robotic plans was built. Autoplanning did largely enhance robotic plan quality, compared to manual planning. Using autoplanning for both the robotic system and VMAT, superiority of non-coplanar robotic treatment compared to coplanar VMAT for prostate SBRT was demonstrated.

Impact of model and dose uncertainty on model-based selection of oropharyngeal cancer patients for proton therapy.

BACKGROUND: Proton therapy is becoming increasingly available, so it is important to apply objective and individualized patient selection to identify those who are expected to benefit most from proton therapy compared to conventional intensity modulated radiation therapy (IMRT). Comparative treatment planning using normal tissue complication probability (NTCP) evaluation has recently been proposed. This work investigates the impact of NTCP model and dose uncertainties on model-based patient selection. MATERIAL AND METHODS: We used IMRT and intensity modulated proton therapy (IMPT) treatment plans of 78 oropharyngeal cancer patients, which were generated based on automated treatment planning and evaluated based on three published NTCP models. A reduction in NTCP of more than a certain threshold (e.g. 10% lower NTCP) leads to patient selection for IMPT, referred to as 'nominal' selection. To simulate the effect of uncertainties in NTCP-model coefficients (based on reported confidence intervals) and planned doses on the accuracy of model-based patient selection, the Monte Carlo method was used to sample NTCP-model coefficients and doses from a probability distribution centered at their nominal values. Patient selection accuracy within a certain sample was defined as the fraction of patients which had similar selection in both the 'nominal' and 'sampled' scenario. RESULTS: For all three NTCP models, the median patient selection accuracy was found to be above 70% when only NTCP-model uncertainty was considered. Selection accuracy decreased with increasing uncertainty resulting from differences between planned and delivered dose. In case of excessive dose uncertainty, selection accuracy decreased to 60%. CONCLUSION: Model and dose uncertainty highly influence the accuracy of model-based patient selection for proton therapy. A reduction of NTCP-model uncertainty is necessary to reach more accurate model-based patient selection.

Validation of Fully Automated Robust Multicriterial Treatment Planning for Head and Neck Cancer IMPT.

PURPOSE: Our purpose was to compare robust intensity modulated proton therapy (IMPT) plans, automatically generated with wish-list-based multicriterial optimization as implemented in Erasmus-iCycle, with manually created robust clinical IMPT plans for patients with head and neck cancer. METHODS AND MATERIALS: Thirty-three patients with head and neck cancer were retrospectively included. All patients were previously treated with a manually created IMPT plan with 7000 cGy dose prescription to the primary tumor (clinical target volume [CTV]7000) and 5425 cGy dose prescription to the bilateral elective volumes (CTV5425). Plans had a 4-beam field configuration and were generated with scenario-based robust optimization (21 scenarios, 3-mm setup error, and ±3% density uncertainty for the CTVs). Three clinical plans were used to configure the Erasmus-iCycle wish-list for automated generation of robust IMPT plans for the other 30 included patients, in line with clinical planning requirements. Automatically and manually generated IMPT plans were compared for (robust) target coverage, organ-at-risk (OAR) doses, and normal tissue complication probabilities (NTCP). No manual fine-tuning of automatically generated plans was performed. RESULTS: For all automatically generated plans, voxel-wise minimum D98% values for the CTVs were within clinical constraints and similar to manual plans. All investigated OAR parameters were favorable in the automatically generated plans (all P < .001). Median reductions in mean dose to OARs went up to 667 cGy for the inferior pharyngeal constrictor muscle, and median reductions in D0.03cm3 in serial OARs ranged up to 1795 cGy for the spinal cord surface. The observed lower mean dose in parallel OARs resulted in statistically significant lower NTCP for xerostomia (grade ≥2: 34.4% vs 38.0%; grade ≥3: 9.0% vs 10.2%) and dysphagia (grade ≥2: 11.8% vs 15.0%; grade ≥3: 1.8% vs 2.8%). CONCLUSIONS: Erasmus-iCycle was able to produce IMPT dose distributions fully automatically with similar (robust) target coverage and improved OAR doses and NTCPs compared with clinical manual planning, with negligible hands-on planning workload.

Comparison of deep inspiration breath hold and free breathing intensity modulated proton therapy of locally advanced lung cancer.

Background and purpose: For locally advanced non-small cell lung cancer (LA-NSCLC), intensity-modulated proton therapy (IMPT) can reduce organ at risk (OAR) doses compared to intensity-modulated radiotherapy (IMRT). Deep inspiration breath hold (DIBH) reduces OAR doses compared to free breathing (FB) in IMRT. In IMPT, differences in dose distributions and robustness between DIBH and FB are unclear. In this study, we compare DIBH to FB in IMPT, and IMPT to IMRT. Materials and methods: Fortyone LA-NSCLC patients were prospectively included. 4D computed tomography images (4DCTs) and DIBH CTs were acquired for treatment planning and during weeks 1 and 3 of treatment. A new system for automated robust planning was developed and used to generate a FB and a DIBH IMPT plan for each patient. Plans were compared in terms of dose-volume parameters and normal tissue complication probabilities (NTCPs). Dose recalculations on repeat CTs were used to compare inter-fraction plan robustness. Results: In IMPT, DIBH reduced median lungs Dmean from 9.3 Gy(RBE) to 8.0 Gy(RBE) compared to FB, and radiation pneumonitis NTCP from 10.9 % to 9.4 % (p < 0.001). Inter-fraction plan robustness for DIBH and FB was similar. Median NTCPs for radiation pneumonitis and mortality were around 9 percentage points lower with IMPT than IMRT (p < 0.001). These differences were much larger than between FB and DIBH within each modality. Conclusion: DIBH IMPT resulted in reduced lung dose and radiation pneumonitis NTCP compared to FB IMPT. Inter-fraction robustness was comparable. OAR doses were far lower in IMPT than IMRT.

A fast and robust constraint-based online re-optimization approach for automated online adaptive intensity modulated proton therapy in head and neck cancer.

Objective. In head-and-neck cancer intensity modulated proton therapy, adaptive radiotherapy is currently restricted to offline re-planning, mitigating the effect of slow changes in patient anatomies. Daily online adaptations can potentially improve dosimetry. Here, a new, fully automated online re-optimization strategy is presented. In a retrospective study, this online re-optimization approach was compared to our trigger-based offline re-planning (offlineTBre-planning) schedule, including extensive robustness analyses.Approach. The online re-optimization method employs automated multi-criterial re-optimization, using robust optimization with 1 mm setup-robustness settings (in contrast to 3 mm for offlineTBre-planning). Hard planning constraints and spot addition are used to enforce adequate target coverage, avoid prohibitively large maximum doses and minimize organ-at-risk doses. For 67 repeat-CTs from 15 patients, fraction doses of the two strategies were compared for the CTVs and organs-at-risk. Per repeat-CT, 10.000 fractions with different setup and range robustness settings were simulated using polynomial chaos expansion for fast and accurate dose calculations.Main results. For 14/67 repeat-CTs, offlineTBre-planning resulted in <50% probability ofD98%≥ 95% of the prescribed dose (Dpres) in one or both CTVs, which never happened with online re-optimization. With offlineTBre-planning, eight repeat-CTs had zero probability of obtainingD98%≥ 95%Dpresfor CTV7000, while the minimum probability with online re-optimization was 81%. Risks of xerostomia and dysphagia grade ≥ II were reduced by 3.5 ± 1.7 and 3.9 ± 2.8 percentage point [mean ± SD] (p< 10-5for both). In online re-optimization, adjustment of spot configuration followed by spot-intensity re-optimization took 3.4 min on average.Significance. The fast online re-optimization strategy always prevented substantial losses of target coverage caused by day-to-day anatomical variations, as opposed to the clinical trigger-based offline re-planning schedule. On top of this, online re-optimization could be performed with smaller setup robustness settings, contributing to improved organs-at-risk sparing.

Clinical acceptance and dosimetric impact of automatically delineated elective target and organs at risk for head and neck MR-Linac patients.

Background: MR-Linac allows for daily online treatment adaptation to the observed geometry of tumor targets and organs at risk (OARs). Manual delineation for head and neck cancer (HNC) patients takes 45-75 minutes, making it unsuitable for online adaptive radiotherapy. This study aims to clinically and dosimetrically validate an in-house developed algorithm which automatically delineates the elective target volume and OARs for HNC patients in under a minute. Methods: Auto-contours were generated by an in-house model with 2D U-Net architecture trained and tested on 52 MRI scans via leave-one-out cross-validation. A randomized selection of 684 automated and manual contours (split half-and-half) was presented to an oncologist to perform a blind test and determine the clinical acceptability. The dosimetric impact was investigated for 13 patients evaluating the differences in dosage for all structures. Results: Automated contours were generated in 8 seconds per MRI scan. The blind test concluded that 114 (33%) of auto-contours required adjustments with 85 only minor and 15 (4.4%) of manual contours required adjustments with 12 only minor. Dosimetric analysis showed negligible dosimetric differences between clinically acceptable structures and structures requiring minor changes. The Dice Similarity coefficients for the auto-contours ranged from 0.66 ± 0.11 to 0.88 ± 0.06 across all structures. Conclusion: Majority of auto-contours were clinically acceptable and could be used without any adjustments. Majority of structures requiring minor adjustments did not lead to significant dosimetric differences, hence manual adjustments were needed only for structures requiring major changes, which takes no longer than 10 minutes per patient.

Per-fraction planning to enhance optimization degrees of freedom compared to the conventional single-plan approach.

Objective. In conventional radiotherapy, a single treatment plan is generated pre-treatment, and delivered in daily fractions. In this study, we propose to generate different treatment plans for all fractions ('Per-fraction' planning) to reduce cumulative organs at risk (OAR) doses. Per-fraction planning was compared to the 'Conventional' single-plan approach for non-coplanar 4 × 9.5 Gy prostate stereotactic body radiation therapy (SBRT).Approach. An in-house application for fully automated, non-coplanar multi-criterial treatment planning with integrated beam angle and fluence optimization was used for plan generations. For the Conventional approach, a single 12-beam non-coplanar IMRT plan with individualized beam angles was generated for each of the 20 included patients. In Per-fraction planning, four fraction plans were generated for each patient. For each fraction, a different set of patient-specific 12-beam configurations could be automatically selected. Per-fraction plans were sequentially generated by adding dose to already generated fraction plan(s). For each fraction, the cumulative- and fraction dose were simultaneously optimized, allowing some minor constraint violations in fraction doses, but not in cumulative.Main results. In the Per-fraction approach, on average 32.9 ± 3.1 [29;39] unique beams per patient were used. PTV doses in the separate Per-fraction plans were acceptable and highly similar to those in Conventional plans, while also fulfilling all OAR hard constraints. When comparing total cumulative doses, Per-fraction planning showed improved bladder sparing for all patients with reductions in Dmean of 22.6% (p= 0.0001) and in D1cc of 2.0% (p= 0.0001), reductions in patient volumes receiving 30% and 50% of the prescribed dose of 54.7% and 6.3%, respectively, and a 3.1% lower rectum Dmean (p= 0.007). Rectum D1cc was 4.1% higher (p= 0.0001) and Urethra dose was similar.Significance. In this proof-of-concept paper, Per-fraction planning resulted in several dose improvements in healthy tissues compared to the Conventional single-plan approach, for similar PTV dose. By keeping the number of beams per fraction the same as in Conventional planning, reported dosimetric improvements could be obtained without increase in fraction durations. Further research is needed to explore the full potential of the Per-fraction planning approach.

Pencil-beam Delivery Pattern Optimization Increases Dose Rate for Stereotactic FLASH Proton Therapy.

PURPOSE: FLASH dose rates >40 Gy/s are readily available in proton therapy (PT) with cyclotron-accelerated beams and pencil-beam scanning (PBS). The PBS delivery pattern will affect the local dose rate, as quantified by the PBS dose rate (PBS-DR), and therefore needs to be accounted for in FLASH-PT with PBS, but it is not yet clear how. Our aim was to optimize patient-specific scan patterns for stereotactic FLASH-PT of early-stage lung cancer and lung metastases, maximizing the volume irradiated with PBS-DR >40 Gy/s of the organs at risk voxels irradiated to >8 Gy (FLASH coverage). METHODS AND MATERIALS: Plans to 54 Gy/3 fractions with 3 equiangular coplanar 244 MeV proton shoot-through transmission beams for 20 patients were optimized with in-house developed software. Planning target volume-based planning with a 5 mm margin was used. Planning target volume ranged from 4.4 to 84 cc. Scan-pattern optimization was performed with a Genetic Algorithm, run in parallel for 20 independent populations (islands). Mapped crossover, inversion, swap, and shift operators were applied to achieve (local) optimality on each island, with migration between them for global optimality. The cost function was chosen to maximize the FLASH coverage per beam at >8 Gy, >40 Gy/s, and 40 nA beam current. The optimized patterns were evaluated on FLASH coverage, PBS-DR distribution, and population PBS-DR-volume histograms, compared with standard line-by-line scanning. Robustness against beam current variation was investigated. RESULTS: The optimized patterns have a snowflake-like structure, combined with outward swirling for larger targets. A population median FLASH coverage of 29.0% was obtained for optimized patterns compared with 6.9% for standard patterns, illustrating a significant increase in FLASH coverage for optimized patterns. For beam current variations of 5 nA, FLASH coverage varied between -6.1%-point and 2.2%-point for optimized patterns. CONCLUSIONS: Significant improvements on the PBS-DR and, hence, on FLASH coverage and potential healthy-tissue sparing are obtained by sequential scan-pattern optimization. The optimizer is flexible and may be further fine-tuned, based on the exact conditions for FLASH.

Dosimetric impact of adaptive proton therapy in head and neck cancer - A review.

Background: Intensity Modulated Proton Therapy (IMPT) in head and neck cancer (HNC) is susceptible to anatomical changes and patient set-up inaccuracies during the radiotherapy course, which can cause discrepancies between planned and delivered dose. The discrepancies can be counteracted by adaptive replanning strategies. This article reviews the observed dosimetric impact of adaptive proton therapy (APT) and the timing to perform a plan adaptation in IMPT in HNC. Methods: A literature search of articles published in PubMed/MEDLINE, EMBASE and Web of Science from January 2010 to March 2022 was performed. Among a total of 59 records assessed for possible eligibility, ten articles were included in this review. Results: Included studies reported on target coverage deterioration in IMPT plans during the RT course, which was recovered with the application of an APT approach. All APT plans showed an average improved target coverage for the high- and low-dose targets as compared to the accumulated dose on the planned plans. Dose improvements up to 2.5 Gy (3.5 %) and up to 4.0 Gy (7.1 %) in the D98 of the high- and low dose targets were observed with APT. Doses to the organs at risk (OARs) remained equal or decreased slightly after APT was applied. In the included studies, APT was largely performed once, which resulted in the largest target coverage improvement, but eventual additional APT improved the target coverage further. There is no data showing what is the most appropriate timing for APT. Conclusion: APT during IMPT for HNC patients improves target coverage. The largest improvement in target coverage was found with a single adaptive intervention, and an eventual second or more frequent APT application improved the target coverage further. Doses to the OARs remained equal or decreased slightly after applying APT. The most optimal timing for APT is yet to be determined.

The impact of bone marrow sparing on organs at risk dose for cervical cancer: a Pareto front analysis.

Background and purpose: To quantify the increase in bladder and rectum dose of a bone marrow sparing (BMS) VMAT strategy for primary treatment of locally advanced cervical cancer (LACC). Materials and methods: Twenty patients with stage IB-IVA cervical cancer were selected for this study. The whole Pelvic Bones (PB) was taken as substitute for bone marrow. For every patient, Pareto-optimal plans were generated to explore the trade-off between rectum, bladder, and PB mean dose. The PB mean dose was decreased in steps of 1 Gy. For each step, the increase in rectum and bladder mean dose was quantified. The increase in mean dose of other OAR compared to no BMS was constrained to 1 Gy. Results: In total, 931 plans of 19 evaluable patients were analyzed. The average [range] mean dose of PB without BMS was 22.8 [20.7-26.2] Gy. When maximum BMS was applied, the average reduction in mean PB dose was 5.4 [3.0-6.8] Gy resulting in an average mean PB dose of 17.5 [15.8-19.8] Gy. For <1 Gy increase in both the bladder and the rectum mean dose, the PB mean dose could be decreased by >2 Gy, >3 Gy, >4 Gy, and >5 Gy for 19/19, 13/19, 5/19, and 1/19 patients, respectively. Conclusion: Based on the comprehensive three-dimensional Pareto front analysis, we conclude that 2-5 Gy BMS can be implemented without a clinically relevant increase in mean dose to other OAR. If BMS is too dominant, it results in a large increase in mean dose to other OAR. Therefore, we recommend implementing moderate BMS for the treatment of LACC patients with VMAT.

iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans.

PURPOSE: To introduce iCycle, a novel algorithm for integrated, multicriterial optimization of beam angles, and intensity modulated radiotherapy (IMRT) profiles. METHODS: A multicriterial plan optimization with iCycle is based on a prescription called wish-list, containing hard constraints and objectives with ascribed priorities. Priorities are ordinal parameters used for relative importance ranking of the objectives. The higher an objective priority is, the higher the probability that the corresponding objective will be met. Beam directions are selected from an input set of candidate directions. Input sets can be restricted, e.g., to allow only generation of coplanar plans, or to avoid collisions between patient/couch and the gantry in a noncoplanar setup. Obtaining clinically feasible calculation times was an important design criterium for development of iCycle. This could be realized by sequentially adding beams to the treatment plan in an iterative procedure. Each iteration loop starts with selection of the optimal direction to be added. Then, a Pareto-optimal IMRT plan is generated for the (fixed) beam setup that includes all so far selected directions, using a previously published algorithm for multicriterial optimization of fluence profiles for a fixed beam arrangement Breedveld et al. [Phys. Med. Biol. 54, 7199-7209 (2009)]. To select the next direction, each not yet selected candidate direction is temporarily added to the plan and an optimization problem, derived from the Lagrangian obtained from the just performed optimization for establishing the Pareto-optimal plan, is solved. For each patient, a single one-beam, two-beam, three-beam, etc. Pareto-optimal plan is generated until addition of beams does no longer result in significant plan quality improvement. Plan generation with iCycle is fully automated. RESULTS: Performance and characteristics of iCycle are demonstrated by generating plans for a maxillary sinus case, a cervical cancer patient, and a liver patient treated with SBRT. Plans generated with beam angle optimization did better meet the clinical goals than equiangular or manually selected configurations. For the maxillary sinus and liver cases, significant improvements for noncoplanar setups were seen. The cervix case showed that also in IMRT with coplanar setups, beam angle optimization with iCycle may improve plan quality. Computation times for coplanar plans were around 1-2 h and for noncoplanar plans 4-7 h, depending on the number of beams and the complexity of the site. CONCLUSIONS: Integrated beam angle and profile optimization with iCycle may result in significant improvements in treatment plan quality. Due to automation, the plan generation workload is minimal. Clinical application has started.

Integrated multicriterial optimization of beam angles and intensity profiles for coplanar and noncoplanar head and neck IMRT and implications for VMAT.

PURPOSE: To quantify improved salivary gland sparing for head and neck cancer patients using intensity-modulated radiotherapy (IMRT) plans based on integrated computerized optimization of beam orientations and intensity profiles. To assess if optimized nonzero couch angles also improve VMAT plans. METHODS: Our in-house developed algorithm iCycle was used for automated generation of multicriterial optimized plans with optimized beam orientations and intensity profiles, and plans with optimized profiles for preselected beam arrangements. For 20 patients, five IMRT plans, based on one "wish-list," were compared: (i) and (ii) seven- and nine-beam equiangular coplanar plans (iCycle(7equi), iCycle(9equi)), (iii) and (iv) nine-beam plans with optimized coplanar and noncoplanar beam orientations (iCycle(copl), iCycle(noncopl)), and (v) a nine-beam coplanar plan with optimized gantry angles and one optimized couch rotation (iCycle(couch)). VMAT plans without and with this optimized couch rotation were evaluated. RESULTS: iCycle(noncopl) resulted in the best salivary gland sparing, while iCycle(couch) yielded similar results for 18 patients. For iCycle(7equi), submandibular gland NTCP values were on average 5% higher. iCycle(9equi) performed better than iCycle(7equi). iCycle(copl) showed further improvement. Application of the optimized couch angle from iCycle(couch) also improved NTCP values in VMAT plans. CONCLUSIONS: iCycle allows objective comparison of competing planning strategies. Integrated optimization of beam profiles and angles can significantly improve normal tissue sparing, yielding optimal results for iCycle(noncopl).

Trade-off in healthy tissue sparing of FLASH and fractionation in stereotactic proton therapy of lung lesions with transmission beams.

PURPOSE AND OBJECTIVE: Besides a dose-rate threshold of 40-100 Gy/s, the FLASH effect may require a dose > 3.5-7 Gy. Even in hypofractioned treatments, with all beams delivered in each fraction (ABEF), most healthy tissue is irradiated to a lower fraction dose. This can be circumvented by single-beam-per-fraction (SBPF) delivery, with a loss of healthy tissue sparing by fractionation. We investigated the trade-off between FLASH and loss of fractionation in SBPF stereotactic proton therapy of lung cancer and determined break-even FLASH-enhancement ratios (FERs). MATERIALS AND METHODS: Treatment plans for 12 patients were generated. GTV delineations were available and a 5 mm GTV-PTV margin was applied. Equiangular arrangements of 3, 5, 7, and 9 244 MeV proton transmission beams were used. To facilitate SBPF, the number of fractions was equal to the number of beams. Iso-effective fractionation schedules with a single field uniform dose prescription were used: D95%,PTV = 100%Dpres per beam. All plans were evaluated in terms of dose to lung and conformity of dose to target of FLASH-enhanced biologically equivalent dose (EQD2). RESULTS: Compared to ABEF, SBPF resulted in a median increase of EQD2mean to healthy lung of 56%, 58%, 55% and 54% in plans with 3, 5, 7 and 9 fractions respectively and of 236%, 78%, 50% and 41% in V100% EQD2, quantifying conformity. This can be compensated for by FERs of at least 1.28, 1.32, 1.30 and 1.23 respectively for EQD2mean and 1.29, 1.18, 1.28 and 1.15 for V100%,EQD2. CONCLUSION: A FLASH effect outweighing the loss of fractionation in SBPF may be achieved in stereotactic lung treatments. The trade-off with fractionation depends on the conditions under which the FLASH effect occurs. Better understanding of the underlying biology and the impact of delivery conditions is needed.

Automated multi-criterial planning with beam angle optimization to establish non-coplanar VMAT class solutions for nasopharyngeal carcinoma.

PURPOSE: Complexity in selecting optimal non-coplanar beam setups and prolonged delivery times may hamper the use of non-coplanar treatments for nasopharyngeal carcinoma (NPC). Automated multi-criterial planning with integrated beam angle optimization was used to define non-coplanar VMAT class solutions (CSs), each consisting of a coplanar arc and additional 1 or 2 fixed, non-coplanar partial arcs. METHODS: Automated planning was used to generate a coplanar VMAT plan with 5 complementary computer-optimized non-coplanar IMRT beams (VMAT+5) for each of the 20 included patients. Subsequently, the frequency distribution of the 100 patient-specific non-coplanar IMRT beam directions was used to select non-coplanar arcs for supplementing coplanar VMAT. A second investigated CS with only one non-coplanar arc consisted of coplanar VMAT plus a partial arc at 90° couch angle (VMATCS90). Plans generated with the two VMATCSs were compared to coplanar VMAT. RESULTS: VMAT+5 analysis resulted in VMATCS60: two partial non-coplanar arcs at couch angles 60° and -60° to complement coplanar VMAT. Compared to coplanar VMAT, the non-coplanar VMATCS60 and VMATCS90 yielded substantial average dose reductions in OARs associated with xerostomia and dysphagia, i.e., parotids, submandibular glands, oral cavity and swallowing muscles (p < 0.05) for the same PTV coverage and without violating hard constraints. Impact of non-coplanar treatment and superiority of either VMACS60 and VMATCS90 was highly patient dependent. CONCLUSIONS: Compared to coplanar VMAT, dose to OARs was substantially reduced with a CS with one or two non-coplanar arcs. Preferences for coplanar or one or two additional arcs are highly patient-specific, balancing plan quality and treatment time.

Patient selection, inter-fraction plan robustness and reduction of toxicity risk with deep inspiration breath hold in intensity-modulated radiotherapy of locally advanced non-small cell lung cancer.

Background: State-of-the-art radiotherapy of locally advanced non-small cell lung cancer (LA-NSCLC) is performed with intensity-modulation during free breathing (FB). Previous studies have found encouraging geometric reproducibility and patient compliance of deep inspiration breath hold (DIBH) radiotherapy for LA-NSCLC patients. However, dosimetric comparisons of DIBH with FB are sparse, and DIBH is not routinely used for this patient group. The objective of this simulation study was therefore to compare DIBH and FB in a prospective cohort of LA-NSCLC patients treated with intensity-modulated radiotherapy (IMRT). Methods: For 38 LA-NSCLC patients, 4DCTs and DIBH CTs were acquired for treatment planning and during the first and third week of radiotherapy treatment. Using automated planning, one FB and one DIBH IMRT plan were generated for each patient. FB and DIBH was compared in terms of dosimetric parameters and NTCP. The treatment plans were recalculated on the repeat CTs to evaluate robustness. Correlations between ΔNTCPs and patient characteristics that could potentially predict the benefit of DIBH were explored. Results: DIBH reduced the median Dmean to the lungs and heart by 1.4 Gy and 1.1 Gy, respectively. This translated into reductions in NTCP for radiation pneumonitis grade ≥2 from 20.3% to 18.3%, and for 2-year mortality from 51.4% to 50.3%. The organ at risk sparing with DIBH remained significant in week 1 and week 3 of treatment, and the robustness of the target coverage was similar for FB and DIBH. While the risk of radiation pneumonitis was consistently reduced with DIBH regardless of patient characteristics, the ability to reduce the risk of 2-year mortality was evident among patients with upper and left lower lobe tumors but not right lower lobe tumors. Conclusion: Compared to FB, DIBH allowed for smaller target volumes and similar target coverage. DIBH reduced the lung and heart dose, as well as the risk of radiation pneumonitis and 2-year mortality, for 92% and 74% of LA-NSCLC patients, respectively. However, the advantages varied considerably between patients, and the ability to reduce the risk of 2-year mortality was dependent on tumor location. Evaluation of repeat CTs showed similar robustness of the dose distributions with each technique.

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.