Purpose This study evaluates the use of the mCycle automated planning system integrated into the Monaco Treatment Planning System (TPS) for step-and-shoot intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) in whole breast irradiation (WBI). The aim is to assess whether automation can standardize plan quality across a diverse patient cohort and compare dosimetric outcomes and robustness of the two techniques against setup errors and anatomical variations. Materials and Methods A total of 65 breast cancer patients who underwent postoperative WBI were selected for the study. Treatment plans were generated using mCycle, which employs multicriteria optimization (MCO) with no manual intervention. Two automated planning techniques—IMRT and VMAT—were implemented and evaluated based on dosimetric outcomes, physician review, planning time, and plan robustness. The plan deliverability was verified through γ index and point dose measurements. Results The mCycle system produced clinically acceptable plans for both IMRT and VMAT across all patient cohorts. VMAT showed superior target coverage (V95%= 97.9%) and better sparing of ipsilateral organs at risk (OARs), while IMRT demonstrated enhanced sparing of contralateral OARs and greater robustness to anatomical changes such as breast swelling. Planning times were reduced with VMAT due to complete automation. Plan deliverability was confirmed with high γ passing rates and acceptable point dose deviations. Conclusions The use of mCycle in WBI planning successfully standardized plan quality and improved workflow efficiency. VMAT provided superior target coverage and ipsilateral OAR sparing but was more sensitive to anatomical changes. IMRT showed better contralateral OAR sparing and robustness. Both techniques are viable, with advantages depending on clinical scenarios.

Purpose: This study evaluates the use of the mCycle automated planning system integrated into the Monaco Treatment Planning System for step-and-shoot intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) in whole breast irradiation (WBI). The aim was to assess whether automation can standardize plan quality across a diverse patient cohort and compare dosimetric outcomes and robustness of the 2 techniques against setup errors and anatomical variations. Methods and Materials: A total of 65 patients with breast cancer who underwent postoperative WBI were selected for the study. Treatment plans were generated using mCycle, which employs multicriteria optimization with no manual intervention. Two automated planning techniques—IMRT and VMAT—were implemented and evaluated based on dosimetric outcomes, physician review, planning time, and plan robustness. The plan deliverability was verified through γ index and point dose measurements. Results: The mCycle system produced clinically acceptable plans for both IMRT and VMAT across all patient cohorts. VMAT showed superior target coverage (V95% = 97.9%) and better sparing of ipsilateral organs at risks (OARs), whereas IMRT demonstrated enhanced sparing of contralateral OARs and greater robustness to anatomical changes such as breast swelling. Planning times were reduced with VMAT because of complete automation. Plan deliverability was confirmed with high γ passing rates and acceptable point dose deviations. Conclusions: The use of mCycle in WBI planning successfully standardized plan quality and improved workflow efficiency. VMAT provided superior target coverage and ipsilateral OAR sparing but was more sensitive to anatomical changes. IMRT showed better contralateral OAR sparing and robustness. Both techniques are viable, with advantages depending on clinical scenarios.

Background and Purpose: Application of different deformable dose accumulation (DDA) solutions makes institutional comparisons after online-adaptive magnetic resonance-guided radiotherapy (OA-MRgRT) challenging. The aim of this multi-institutional study was to analyze accuracy and agreement of DDA-implementations in OA-MRgRT. Material and Methods: One gold standard (GS) case deformed with a biomechanical-model and five clinical cases consisting of prostate (2x), cervix, liver, and lymph node cancer, treated with OA-MRgRT, were analyzed. Six centers conducted DDA using institutional implementations. Deformable image registration (DIR) and DDA results were compared using the contour metrics Dice Similarity Coefficient (DSC), surface-DSC, Hausdorff-distance (HD95%), and accumulated dose-volume histograms (DVHs) analyzed via intraclass correlation coefficient (ICC) and clinical dosimetric criteria (CDC). Results: For the GS, median DDA errors ranged from 0.0 to 2.8 Gy across contours and implementations. DIR of clinical cases resulted in DSC > 0.8 for up to 81.3% of contours and a variability of surface-DSC values depending on the implementation. Maximum HD95%=73.3 mm was found for duodenum in the liver case. Although DVH ICC > 0.90 was found after DDA for all but two contours, relevant absolute CDC differences were observed in clinical cases: Prostate I/II showed maximum differences in bladder V28Gy (10.2/7.6%), while for cervix, liver, and lymph node the highest differences were found for rectum D2cm3 (2.8 Gy), duodenum Dmax (7.1 Gy), and rectum D0.5cm3 (4.6 Gy). Conclusion: Overall, high agreement was found between the different DIR and DDA implementations. Case- and algorithm-dependent differences were observed, leading to potentially clinically relevant results. Larger studies are needed to define future DDA-guidelines.

Background This study aimed to evaluate an a-priori multicriteria plan optimization algorithm (mCycle) for locally advanced breast cancer radiation therapy (RT) by comparing automatically generated VMAT (Volumetric Modulated Arc Therapy) plans (AP-VMAT) with manual clinical Helical Tomotherapy (HT) plans. Methods The study included 25 patients who received postoperative RT using HT. The patient cohort had diverse target selections, including both left and right breast/chest wall (CW) and III-IV node, with or without internal mammary node (IMN) and Simultaneous Integrated Boost (SIB). The Planning Target Volume (PTV) was obtained by applying a 5 mm isotropic expansion to the CTV (Clinical Target Volume), with a 5 mm clip from the skin. Comparisons of dosimetric parameters and delivery/planning times were conducted. Dosimetric verification of the AP-VMAT plans was performed. Results The study showed statistically significant improvements in AP-VMAT plans compared to HT for OARs (Organs At Risk) mean dose, except for the heart and ipsilateral lung. No significant differences in V 95% were observed for PTV breast/CW and PTV III-IV, while increased coverage (higher V 95% ) was seen for PTV IMN in AP-VMAT plans. HT plans exhibited smaller values of PTV V 105% for breast/CW and III-IV, with no differences in PTV IMN and boost. HT had an average (± standard deviation) delivery time of (17 ± 8) minutes, while AP-VMAT took (3 ± 1) minutes. The average γ passing rate for AP-VMAT plans was 97%±1%. Planning times reduced from an average of 6 h for HT to about 2 min for AP-VMAT. Conclusions Comparing AP-VMAT plans with clinical HT plans showed similar or improved quality. The implementation of mCycle demonstrated successful automation of the planning process for VMAT treatment of locally advanced breast cancer, significantly reducing workload.

BACKGROUND:To investigate the capability of a not-yet commercially available fully automated lexicographic optimization (LO) planning algorithm, called mCycle (Elekta AB, Stockholm, Sweden), to further improve the plan quality of an already-validated Wish List (WL) pushing on the organs-at-risk (OAR) sparing without compromising target coverage and plan delivery accuracy.MATERIAL AND METHODS:Twenty-four mono-institutional consecutive cervical cancer Volumetric-Modulated Arc Therapy (VMAT) plans delivered between November 2019 and April 2022 (50 Gy/25 fractions) have been retrospectively selected. In mCycle the LO planning algorithm was combined with the a-priori multi-criterial optimization (MCO). Two versions of WL have been defined to reproduce manual plans (WL01), and to improve the OAR sparing without affecting minimum target coverage and plan delivery accuracy (WL02). Robust WLs have been tuned using a subset of 4 randomly selected patients. The remaining plans have been automatically re-planned by using the designed WLs. Manual plans (MP) and mCycle plans (mCP01 and mCP02) were compared in terms of dose distributions, complexity, delivery accuracy, and clinical acceptability. Two senior physicians independently performed a blind clinical evaluation, ranking the three competing plans. Furthermore, a previous defined global quality index has been used to gather into a single score the plan quality evaluation.RESULTS:The WL tweaking requests 5 and 3 working days for the WL01 and the WL02, respectively. The re-planning took in both cases 3 working days. mCP01 best performed in terms of target coverage (PTV V95% (%): MP 98.0 [95.6-99.3], mCP01 99.2 [89.7-99.9], mCP02 96.9 [89.4-99.5]), while mCP02 showed a large OAR sparing improvement, especially in the rectum parameters (e.g., Rectum D50% (Gy): MP 41.7 [30.2-47.0], mCP01 40.3 [31.4-45.8], mCP02 32.6 [26.9-42.6]). An increase in plan complexity has been registered in mCPs without affecting plan delivery accuracy. In the blind comparisons, all automated plans were considered clinically acceptable, and mCPs were preferred over MP in 90% of cases. Globally, automated plans registered a plan quality score at least comparable to MP.CONCLUSIONS:This study showed the flexibility of the Lexicographic approach in creating more demanding Wish Lists able to potentially minimize toxicities in RT plans.

Purpose: Adaptive stereotactic body radiation therapy (SBRT) for prostate cancer (PC) by the 1.5 T MR-linac currently requires online planning by an expert user. A fully automated and user-independent solution to adaptive planning (mCycle) of PC-SBRT was compared with user's plans for the 1.5 T MR-linac. Methods and Materials: Fifty adapted plans on daily magnetic resonance imaging scans for 10 patients with PC treated by 35 Gy (prescription dose [D-p]) in 5 fractions were reoptimized offline from scratch, both by an expert planner (manual) and by mCycle. Manual plans consisted of multicriterial optimization (MCO) of the fluence map plus manual tweaking in segmentation, whereas in mCycle plans, the objectives were sequentially optimized by MCO according to an a-priori assigned priority list. The main criteria for planning approval were a dose >= 95% of the D-p to at least 95% of the planning target volume (PTV), V-33.2 (PTV) >= 95%, a dose less than the D-p to the hottest cubic centimeter (V-35 <= 1 cm(3)) of rectum, bladder, penile bulb, and urethral planning risk volume (ie, urethra plus 3 mm isotropically), and V-32 <= 5%, V-28 <= 10%, and V-18 <= 35% to the rectum. Such dose-volume metrics, plus some efficiency and deliverability metrics, were used for the comparison of mCycle versus manual plans. Results: mCycle plans improved target dose coverage, with V-33.2 (PTV) passing on average (+/- 1 SD) from 95.7% (+/- 1.0%) for manual plans to 97.5% (+/- 1.3%) for mCycle plans (P < .001), and rectal dose sparing, with significantly reduced V32, V28, and V18 (P <= .004). Although at an equivalent number of segments, mCycle plans consumed moderately more monitor units (+17%) and delivery time (+9%) (P < .001), whereas they were generally faster (-19%) in terms of optimization times (P <.019). No significant differences were found for the passing rates of locally normalized gamma (3 mm, 3%) (P = .059) and gamma (2 mm, 2%) (P = .432) deliverability metrics. Conclusions: In the offline setting, mCycle proved to be a trustable solution for automated planning of PC-SBRT on the 1.5 T MR-linac. mCycle integration in the online workflow will free the user from the challenging online-optimization task. (c) 2021 The Author(s). Published by Elsevier Inc. on behalf of American Society for Radiation Oncology.

Objective. To develop and evaluate a deep learning based fast volumetric modulated arc therapy (VMAT) plan generation method for prostate radiotherapy.Approach. A customized 3D U-Net was trained and validated to predict initial segments at 90 evenly distributed control points of an arc, linked to our research treatment planning system (TPS) for segment shape optimization (SSO) and segment weight optimization (SWO). For 27 test patients, the VMAT plans generated based on the deep learning prediction (VMATDL) were compared with VMAT plans generated with a previously validated automated treatment planning method (VMATref). For all test cases, the deep learning prediction accuracy, plan dosimetric quality, and the planning efficiency were quantified and analyzed.Main results. For all 27 test cases, the resulting plans were clinically acceptable. TheV95%for the PTV2 was greater than 99%, and theV107%was below 0.2%. Statistically significant difference in target coverage was not observed between the VMATrefand VMATDLplans (P = 0.3243 > 0.05). The dose sparing effect to the OARs between the two groups of plans was similar. Small differences were only observed for the Dmean of rectum and anus. Compared to the VMATref, the VMATDLreduced 29.3% of the optimization time on average.Significance. A fully automated VMAT plan generation method may result in significant improvement in prostate treatment planning efficiency. Due to the clinically acceptable dosimetric quality and high efficiency, it could potentially be used for clinical planning application and real-time adaptive therapy application after further validation.

PURPOSE:Automated planning techniques aim to reduce manual planning time and inter-operator variability without compromising the plan quality which is particularly challenging for head-and-neck (HN) cancer radiotherapy. The objective of this study was to evaluate the performance of an a priori-multicriteria plan optimization algorithm on a cohort of HN patients.METHODS:A total of 14 nasopharyngeal carcinoma (upper-HN) and 14 "middle-lower indications" (lower-HN) previously treated in our institution were enrolled in this study. Automatically generated plans (autoVMAT) were compared to manual VMAT or Helical Tomotherapy planning (manVMAT-HT) by assessing differences in dose delivered to targets and organs at risk (OARs), calculating plan quality indexes (PQIs) and performing blinded comparisons by clinicians. Quality control of the plans and measurements of the delivery times were also performed.RESULTS:For the 14 lower-HN patients, with equivalent planning target volume (PTV) dosimetric criteria and dose homogeneity, significant decrease in the mean doses to the oral cavity, esophagus, trachea and larynx were observed for autoVMAT compared to manVMAT-HT. Regarding the 14 upper-HN cases, the PTV coverage was generally significantly superior for autoVMAT which was also confirmed with higher calculated PQIs on PTVs for 13 out of 14 patients, whereas PQIs calculated on OARs were generally equivalent. Number of MUs and total delivery time were significantly higher for autoVMAT compared to manVMAT. All plans were considered clinically acceptable by clinicians.CONCLUSIONS:Overall superiority of autoVMAT compared to manVMAT-HT plans was demonstrated for HN cancer. The obtained plans were operator-independent and required no post-optimization or manual intervention.

Abstract Purpose For the 1.5 T Elekta MR‐Linac it is essential that the optimisation of a treatment plan accounts for the electron return effect on the planned dose distribution. The ability of two algorithms for the first stage fluence optimisation, pencil beam (PB) and Monte Carlo (MC), to produce acceptable plan quality was investigated. Optimisation time for each algorithm was also compared. Methods Ten head and neck patients, ten lung patients and five prostate patients were selected from the clinical archive. These were retrospectively planned using a research version of Monaco with both the PB and MC algorithms for the fluence optimisation stage. After full optimisation DVH parameters, optimisation time and the number of Monitor Units (MU) as a measure of plan complexity were extracted. Results There were no clinically significant differences between any of the DVH parameters studied or the total number of MUs between using PB or MC for stage 1 optimisation across the three patient groups. However, planning time increased by a factor of ten using MC algorithms for stage 1. Conclusion The use of MC calculations compared to PB, for stage 1 fluence optimisation, results in increased planning time without clinical improvement in plan quality or reduction in complexity and is therefore not necessary.

BACKGROUND AND PURPOSE:Reported plan quality improvements with autoplanning of radiotherapy of the prostate and seminal vesicles are poor. A system for automated multi-criterial planning has been validated for this treatment in a large international multi-center study. The system is configured with training plans using a mechanism that strives for quality improvements relative to those plans. MATERIAL AND METHODS:Each of the four participating centers included thirty manually generated clinical Volumetric Modulated Arc Therapy prostate plans (manVMAT). Ten plans were used for autoplanning training. The other twenty were compared with an automatically generated plan (autoVMAT). Plan evaluations considered dosimetric plan parameters and blinded side-by-side plan comparisons by clinicians. RESULTS:With equivalent Planning Target Volume (PTV) V95%, D2%, D98%, and dose homogeneity autoVMAT was overall superior for rectum with median differences of 3.4 Gy (p < 0.001) in Dmean, 4.0% (p < 0.001) in V60Gy, and 1.5% (p = 0.001) in V75Gy, and for bladder Dmean (0.9 Gy, p < 0.001). Also the clinicians' plan comparisons pointed at an overall preference for autoVMAT. Advantages of autoVMAT were highly treatment center- and patient-specific with overall ranges for differences in rectum Dmean and V60Gy of [-4,12] Gy and [-2,15]%, respectively. CONCLUSION:Observed advantages of autoplanning were clinically relevant and larger than reported in the literature. The latter is likely related to the multi-criterial nature of the applied autoplanning algorithm, with for each center a dedicated configuration that aims at plan improvements relative to its (clinical) training plans. Large variations among patients in differences between manVMAT and autoVMAT point at inconsistencies in manual planning.

Background: Planning for Volumetric Modulated Arc Therapy (VMAT) may be time consuming and its use is limited by available staff resources. Automated multicriterial treatment planning can eliminate this bottleneck. We compared automatically created (auto) VMAT plans generated by Erasmus-iCycle to manually created VMAT plans for treatment of spinal metastases.Methods: Forty-two targets in 32 patients were analyzed. Lungs and kidneys were defined as organs at risk (OARs). Twenty-two patients received radiotherapy on kidney levels, 17 on lung levels, and 3 on both levels.Results: All Erasmus-iCycle plans were clinically acceptable. When compared to manual plans, planning target volume (PTV) coverage of auto plans was significantly better. The Homogeneity Index did not differ significantly between the groups. Mean dose to OARs was lower in auto plans concerning both kidneys and the left lung. One hotspot (> 110% of D-50%) occurred in the spinal cord of one auto plan (33.2 Gy, D-50%: 30 Gy). Treatment time was 7% longer in auto plans.Conclusions: Erasmus-iCycle plans showed better target coverage and sparing of OARs at the expense of minimally longer treatment times (for which no constraint was set).

. In radiation therapy treatment planning, generating a treatment plan is a multi-objective optimisation problem. The decision-making strategy is uniform for each group of cancer patients, e.g. prostate cancer, and can thus be automated. Predefined priorities and aspiration levels are assigned to each objective, and the strategy is to attain these levels in order of priority. Therefore, a straightforward lexicographic approach is sequential epsilon-constraint programming where objectives are sequentially optimised and constrained according to predefined rules, mimicking human decision-making. The clinically applied 2-phase epsilon-constraint (2p epsilon c) method captures this approach and generates clinically acceptable treatment plans.However, the number of optimisation problems to be solved for the 2p epsilon c method, and hence the computation time, scales linearly with the number of objectives. To improve the daily planning workload and to further enhance radiation therapy, it is extremely important to reduce this time. Therefore, we developed the lexicographic reference point method (LRPM), a lexicographic extension of the reference point method, for generating a treatment plan by solving a single optimisation problem. The LRPM processes multiple a priori defined reference points into modified partial achievement functions. In addition, a priori bounds on a subset of the partial trade-offs can be imposed using a weighted sum component.The LRPM was validated for 30 randomly selected prostate cancer patients. While the treatment plans generated using the LRPM were of similar clinical quality to those generated using the 2p epsilon c method, the LRPM decreased the average computation time from 12.4 to 1.2 minutes, a speed-up factor of 10. (C) 2017 Elsevier B.V. All rights reserved.

PURPOSE:To develop and validate fully automated generation of VMAT plan-libraries for plan-of-the-day adaptive radiotherapy in locally-advanced cervical cancer.MATERIAL AND METHODS:Our framework for fully automated treatment plan generation (Erasmus-iCycle) was adapted to create dual-arc VMAT treatment plan libraries for cervical cancer patients. For each of 34 patients, automatically generated VMAT plans (autoVMAT) were compared to manually generated, clinically delivered 9-beam IMRT plans (CLINICAL), and to dual-arc VMAT plans generated manually by an expert planner (manVMAT). Furthermore, all plans were benchmarked against 20-beam equi-angular IMRT plans (autoIMRT). For all plans, a PTV coverage of 99.5% by at least 95% of the prescribed dose (46 Gy) had the highest planning priority, followed by minimization of V45Gy for small bowel (SB). Other OARs considered were bladder, rectum, and sigmoid.RESULTS:All plans had a highly similar PTV coverage, within the clinical constraints (above). After plan normalizations for exactly equal median PTV doses in corresponding plans, all evaluated OAR parameters in autoVMAT plans were on average lower than in the CLINICAL plans with an average reduction in SB V45Gy of 34.6% (p<0.001). For 41/44 autoVMAT plans, SB V45Gy was lower than for manVMAT (p<0.001, average reduction 30.3%), while SB V15Gy increased by 2.3% (p = 0.011). AutoIMRT reduced SB V45Gy by another 2.7% compared to autoVMAT, while also resulting in a 9.0% reduction in SB V15Gy (p<0.001), but with a prolonged delivery time. Differences between manVMAT and autoVMAT in bladder, rectal and sigmoid doses were ≤ 1%. Improvements in SB dose delivery with autoVMAT instead of manVMAT were higher for empty bladder PTVs compared to full bladder PTVs, due to differences in concavity of the PTVs.CONCLUSIONS:Quality of automatically generated VMAT plans was superior to manually generated plans. Automatic VMAT plan generation for cervical cancer has been implemented in our clinical routine. Due to the achieved workload reduction, extension of plan libraries has become feasible.

Background and purpose In a published study on cervical cancer, 5-beam IMRT was inferior to single arc VMAT. Here we compare 9, 12, and 20 beam IMRT with single and dual arc VMAT. Material and methods For each of 10 patients, automated plan generation with the in-house Erasmus-iCycle optimizer was used to assist an expert planner in generating the five plans with the clinical TPS. Results For each patient, all plans were clinically acceptable with a high and similar PTV coverage. OAR sparing increased when going from 9 to 12 to 20 IMRT beams, and from single to dual arc VMAT. For all patients, 12 and 20 beam IMRT were superior to single and dual arc VMAT, with substantial variations in gain among the study patients. As expected, delivery of VMAT plans was significantly faster than delivery of IMRT plans. Conclusions Often reported increased plan quality for VMAT compared to IMRT has not been observed for cervical cancer. Twenty and 12 beam IMRT plans had a higher quality than single and dual arc VMAT. For individual patients, the optimal delivery technique depends on a complex trade-off between plan quality and treatment time that may change with introduction of faster delivery systems.

Purpose: To develop and evaluate fully automated volumetric modulated arc therapy (VMAT) treatment planning for prostate cancer patients, avoiding manual trial-and-error tweaking of plan parameters by dosimetrists.Methods and Materials: A system was developed for fully automated generation of VMAT plans with our commercial clinical treatment planning system (TPS), linked to the in-house developed Erasmus-iCycle multicriterial optimizer for preoptimization. For 30 randomly selected patients, automatically generated VMAT plans (VMAT(auto)) were compared with VMAT plans generated manually by 1 expert dosimetrist in the absence of time pressure (VMAT(man)). For all treatment plans, planning target volume (PTV) coverage and sparing of organs-at-risk were quantified.Results: All generated plans were clinically acceptable and had similar PTV coverage (V-95% > 99%). For VMAT(auto) and VMAT(man) plans, the organ-at-risk sparing was similar as well, although only the former plans were generated without any planning workload.Conclusions: Fully automated generation of high-quality VMAT plans for prostate cancer patients is feasible and has recently been implemented in our clinic. (C) 2014 Elsevier Inc.

markdownabstractThis thesis focuses on automated contouring of planning CT-scans and automated treatment plan generation in radiotherapy to improve treatment quality and / or efficiency compared to current manual procedures. For automated contouring we have evaluated a commercially available atlas-based autosegmentation tool. With this tool, the CT-scan of a new patient can be segmented based on segmented scans of previously treated patients, called atlases, thereby significantly reducing the manual contouring time. For automated plan generation we have investigated Erasmus-iCycle, an in-house developed algorithm for multicriterial beam angle and profile optimization. For individual patients, Erasmus-iCycle can fully automatically generate Pareto-optimal plans, based on a wish-list with constraints and prioritized objectives specified for the corresponding disease / tumor site. Compared to manually generated plans, Erasmus-iCycle plans are superior or equal in quality. Moreover, cost savings are possible, as time consuming manual planning by dosimetrists can be avoided. Feasibility of high quality automated contouring and planning has been demonstrated, which is also highly relevant for the rapidly evolving field of adaptive daily re-planning.

PURPOSE:To compare IMRT planning strategies for prostate cancer patients with metal hip prostheses.METHODS:All plans were generated fully automatically (i.e., no human trial-and-error interactions) using iCycle, the authors' in-house developed algorithm for multicriterial selection of beam angles and optimization of fluence profiles, allowing objective comparison of planning strategies. For 18 prostate cancer patients (eight with bilateral hip prostheses, ten with a right-sided unilateral prosthesis), two planning strategies were evaluated: (i) full exclusion of beams containing beamlets that would deliver dose to the target after passing a prosthesis (IMRT remove) and (ii) exclusion of those beamlets only (IMRT cut). Plans with optimized coplanar and noncoplanar beam arrangements were generated. Differences in PTV coverage and sparing of organs at risk (OARs) were quantified. The impact of beam number on plan quality was evaluated.RESULTS:Especially for patients with bilateral hip prostheses, IMRT cut significantly improved rectum and bladder sparing compared to IMRT remove. For 9-beam coplanar plans, rectum V60 Gy reduced by 17.5% ± 15.0% (maximum 37.4%, p = 0.036) and rectum D mean by 9.4% ± 7.8% (maximum 19.8%, p = 0.036). Further improvements in OAR sparing were achievable by using noncoplanar beam setups, reducing rectum V 60Gy by another 4.6% ± 4.9% (p = 0.012) for noncoplanar 9-beam IMRT cut plans. Large reductions in rectum dose delivery were also observed when increasing the number of beam directions in the plans. For bilateral implants, the rectum V 60Gy was 37.3% ± 12.1% for coplanar 7-beam plans and reduced on average by 13.5% (maximum 30.1%, p = 0.012) for 15 directions.CONCLUSIONS:iCycle was able to automatically generate high quality plans for prostate cancer patients with prostheses. Excluding only beamlets that passed through the prostheses (IMRTcut strategy) significantly improved OAR sparing. Noncoplanar beam arrangements and, to a larger extent, increasing the number of treatment beams further improved plan quality.

PURPOSE:To dosimetrically evaluate a margin-of-the-day (MoD) online adaptive intensity-modulated radiotherapy (IMRT) strategy for cervical cancer patients. The strategy is based on a single planning computed tomography (CT) scan and a pretreatment constructed IMRT plan library with incremental clinical target volumes (CTV)-to-planning target volumes (PTV) margins.MATERIAL AND METHODS:For 14 patients, 9-10 variable bladder filling CT scans acquired at pretreatment and after 40 Gy were available. Bladder volume variability during the treatment course was recorded by twice-weekly US bladder-volume measurements. A MoD strategy that selects the best IMRT plan of the day from a library of plans with incremental margins in steps of 5 mm was compared with a clinically recommended population-based margin (15 mm). To compare the strategies, for each fraction that had a recorded US bladder-volume measurement, the CT scan with the nearest bladder volume was selected from the pretreatment CT series and from the CT series acquired after 40 Gy. A frequency-weighted average of the dose-volume histograms (DVH) parameters calculated for the two selected CT scans was used to estimate the DVH parameters of the fraction of interest.RESULTS:The 15-mm recommended margin resulted in cervix-uterus underdosage in six of 14 patients. Compared with the 15-mm margin, the MoD strategy resulted in significantly better cervix-uterus coverage (p = 0.008) without a significant difference in the sparing of rectum, bladder, and small bowel. For each patient, 3-8 (median 5) plans were needed in the library of plans for the MoD strategy. The required range of the MoD was 5-45 mm (median 15 mm). Twenty-five percent of all fractions could be treated with a MoD of 5 mm and 81% of all fractions could be treated with a MoD up to 25 mm.CONCLUSIONS:Compared with a clinically recommended margin, a simple online adaptive strategy resulted in better cervix-uterus coverage without compromising organs at risk sparing.

PURPOSETo introduce iCycle, a novel algorithm for integrated, multicriterial optimization of beam angles, and intensity modulated radiotherapy (IMRT) profiles.METHODSA 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.RESULTSPerformance 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.CONCLUSIONSIntegrated 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.

In a recent paper, we have published a new algorithm, designated 'iCycle', for fully automated multi-criterial optimization of beam angles and intensity profiles. In this study, we have used this algorithm to investigate the relationship between plan quality and the extent of the beam direction search space, i.e. the set of candidate beam directions that may be selected for generating an optimal plan. For a group of ten prostate cancer patients, optimal IMRT plans were made for stereotactic body radiation therapy (SBRT), mimicking high dose rate brachytherapy dosimetry. Plans were generated for five different beam direction input sets: a coplanar (CP) set and four non-coplanar (NCP) sets. For CP treatments, the search space consisted of 72 orientations (5° separations). The NCP CyberKnife (CK) space contained all directions available in the robotic CK treatment unit. The fully non-coplanar (F-NCP) set facilitated the highest possible degree of freedom in selecting optimal directions. CK+ and CK++ were subsets of F-NCP to investigate some aspects of the CK space. For each input set, plans were generated with up to 30 selected beam directions. Generated plans were clinically acceptable, according to an assessment of our clinicians. Convergence in plan quality occurred only after around 20 included beams. For individual patients, variations in PTV dose delivery between the five generated plans were minimal, as aimed for (average spread in V95: 0.4%). This allowed plan comparisons based on organ at risk (OAR) doses, with the rectum considered most important. Plans generated with the NCP search spaces had improved OAR sparing compared to the CP search space, especially for the rectum. OAR sparing was best with the F-NCP, with reductions in rectum DMean, V40Gy, V60Gy and D2% compared to CP of 25%, 35%, 37% and 8%, respectively. Reduced rectum sparing with the CK search space compared to F-NCP could be largely compensated by expanding CK with beams with relatively large direction components along the superior–inferior axis (CK++). Addition of posterior beams (CK++ → F-NCP) did not lead to further improvements in OAR sparing. Plans with 25 beams clearly performed better than 11-beam plans. For CP plans, an increase from 11 to 25 involved beams resulted in reductions in rectum DMean, V40Gy, V60Gy and D2% of 39%, 57%, 64% and 13%, respectively.