Dosimetric impact of bone marrow sparing for robustly optimized IMPT for locally advanced cervical cancer.

BACKGROUND AND PURPOSE: To investigate the trade-off between bone marrow sparing (BMS) and dose to organs at risk (OARs) for intensity modulated proton therapy (IMPT) for women with locally advanced cervical cancer (LACC). MATERIALS AND METHODS: Twenty LACC patients were retrospectively included. IMPT plans were created for each patient using automated treatment planning. These plans progressively reduced bone marrow mean doses by steps of 1 GyRBE, while constraining target coverage and conformality. The relation between bone marrow dose and bladder, small bowel, rectum, and sigmoid doses was evaluated. RESULTS: A total of 140 IMPT plans were created. Plans without BMS had an average [range] bone marrow mean dose of 17.3 [14.7-21.6] GyRBE , which reduced to 12.0 [10.0-14.0] GyRBE with maximum BMS. The mean OAR dose [range] increased modestly for 1 GyRBE BMS: 0.2 [0.0 - 0.6] GyRBE for bladder, 0.3 [-0.2 - 0.7] GyRBE for rectum, 0.4 [0.1 - 0.8] GyRBE for small bowel, and 0.2 [-0.2 - 0.4] GyRBE for sigmoid. Moreover, for maximum BMS, mean OAR doses [range] escalated by 3.3 [0.1 - 6.7] GyRBE for bladder, 5.8 [1.8 - 12.4] GyRBE for rectum, 3.9 [1.6 - 5.9] GyRBE for small bowel, and 2.7 [0.6 - 5.9] GyRBE for sigmoid. CONCLUSION: Achieving 1 GyRBE BMS for IMPT is feasible for LACC patients with limited dosimetric impact on other OARs. While further bone marrow dose reduction is possible for some patients, it may increase OAR doses substantially for others. Hence, we recommend a personalized approach when introducing BMS into clinical IMPT treatment planning to carefully assess individual patient benefits and risks.

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

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

TBS-BAO: fully automated beam angle optimization for IMRT guided by a total-beam-space reference plan.

Properly selected beam angles contribute to the quality of radiotherapy treatment plans. However, the beam angle optimization (BAO) problem is difficult to solve to optimality due to its non-convex discrete nature with many local minima. In this study, we propose TBS-BAO, a novel approach for solving the BAO problem, and test it for non-coplanar robotic CyberKnife radiotherapy for prostate cancer. First, an ideal Pareto-optimal reference dose distribution is automatically generated usinga priorimulti-criterial fluence map optimization (FMO) to generate a plan that includes all candidate beams (total-beam-space, TBS). Then, this ideal dose distribution is reproduced as closely as possible in a subsequent segmentation/beam angle optimization step (SEG/BAO), while limiting the number of allowed beams to a user-selectable preset value. SEG/BAO aims at a close reproduction of the ideal dose distribution. For each of 33 prostate SBRT patients, 18 treatment plans with different pre-set numbers of allowed beams were automatically generated with the proposed TBS-BAO. For each patient, the TBS-BAO plans were then compared to a plan that was automatically generated with an alternative BAO method (Erasmus-iCycle) and to a high-quality manually generated plan. TBS-BAO was able to automatically generate plans with clinically feasible numbers of beams (∼25), with a quality highly similar to corresponding 91-beam ideal reference plans. Compared to the alternative Erasmus-iCycle BAO approach, similar plan quality was obtained for 25-beam segmented plans, while computation times were reduced from 10.7 hours to 4.8/1.5 hours, depending on the applied pencil-beam resolution in TBS-BAO. 25-beam TBS-BAO plans had similar quality as manually generated plans with on average 48 beams, while delivery times reduced from 22.3 to 18.4/18.1 min. TBS reference plans could effectively steer the discrete non-convex BAO.

Accurate 3D-dose-based generation of MLC segments for robotic radiotherapy.

Radiotherapy treatment planning requires accurate modeling of the delivered patient dose, including radiation scatter effects, multi-leaf collimator (MLC) leaf transmission, interleaf-leakage, etc. In fluence map optimization (FMO), a simple dose model is used to first generate an intermediate plan based on pencil-beams. In a second step (segmentation phase), this intermediate plan is then converted into a deliverable treatment plan with MLC segments. In this paper, we investigate novel approaches for the use of a clinical dose engine (CDE) for segmentation of FMO plans in robotic radiotherapy. Segments are sequentially added to the plan. Generation of each next segment is based on the total 3D dose distribution, resulting from already selected segments and the desired FMO dose, considering all treatment beams as candidates for delivery of the new segment. Three versions of the segmentation algorithm were investigated with differences in the integration of the CDE. The combined use of pencil-beams and segments in a segmentation method is non-trivial. Therefore, new methods were developed for the use of segment doses calculated with the CDE in combination with pencil-beams, used for the selection of new segments. For 20 patients with prostate cancer and 12 with liver cancer, segmented plans were compared with FMO plans. All three versions of the proposed segmentation algorithm could well mimic FMO dose distributions. Segmentation with a fully integrated CDE provided the best plan quality and lowest numbers of monitor units and segments at the cost of increased calculation time.

Fast and exact Hessian computation for a class of nonlinear functions used in radiation therapy treatment planning.

In nonlinear optimisation, using exact Hessian computations (full-Newton) hold superior convergence properties over quasi-Newton methods or gradient-based methods. However, for medium-scale problems, computing the Hessian can be computationally expensive and thus time-consuming. For solvers dedicated to a specific problem type, it can be advantageous to hard-code optimised implementations to keep the computation time to a minimum. In this paper we derive a computationally efficient canonical form for a class of additively and multiplicatively separable functions. The major computational cost is reduced to a single multiplication of the data matrix with itself, allowing simple parallellisation on modern-day multi-core processors. We present the approach in the practical application of radiation therapy treatment planning, where this form appears for many common functions. In this case, the data matrices are the dose-influence matrices. The method is compared against automatic differentiation.

Automated prioritised 3D dose-based MLC segment generation for step-and-shoot IMRT.

Segmentation can degrade a high-quality dose distribution obtained by fluence map optimisation (FMO). A novel algorithm is proposed for generation of MLC segments to deliver an FMO plan with step-and-shoot IMRT while minimising quality loss. All beams are considered simultaneously while generating MLC segments for reproducing the 3D FMO dose distribution. Segment generation is only steered by the 3D FMO dose distribution, i.e. underlying FMO fluence profiles are not considered. The algorithm features prioritised generation of segments, focusing on accurate reproduction of clinical objectives with the highest priorities. The performance of the segmentation algorithm was evaluated for 20 prostate patients, 15 head-and-neck patients, and 12 liver patients. FMO dose distributions were generated by automated multi-criteria treatment planning (Pareto-optimal plans) and subsequently segmented using the proposed method. Various segmentation strategies were investigated regarding prioritisation of objectives and limitation of the number of segments. Segmented plans were dosimetrically similar to FMO plans and for all patients a clinically acceptable segmented plan could be generated. Substantial differences between FMO and segmented fluence profiles were observed. Avoidance of the usual reconstruction of 2D FMO fluence profiles for segment generation, and instead simultaneously generating segments for all beams to directly reproduce the 3D FMO dose distribution is a likely explanation for the obtained results. For the strategies of limiting the number of segments large reductions in number of segments were observed with minimal impact on plan quality.

Computation of mean and variance of the radiotherapy dose for PCA-modeled random shape and position variations of the target.

Radiotherapy dose delivery in the tumor and surrounding healthy tissues is affected by movements and deformations of the corresponding organs between fractions. The random variations may be characterized by non-rigid, anisotropic principal component analysis (PCA) modes. In this article new dynamic dose deposition matrices, based on established PCA modes, are introduced as a tool to evaluate the mean and the variance of the dose at each target point resulting from any given set of fluence profiles. The method is tested for a simple cubic geometry and for a prostate case. The movements spread out the distributions of the mean dose and cause the variance of the dose to be highest near the edges of the beams. The non-rigidity and anisotropy of the movements are reflected in both quantities. The dynamic dose deposition matrices facilitate the inclusion of the mean and the variance of the dose in the existing fluence-profile optimizer for radiotherapy planning, to ensure robust plans with respect to the movements.

Improved efficiency of multi-criteria IMPT treatment planning using iterative resampling of randomly placed pencil beams.

This study investigates whether 'pencil beam resampling', i.e. iterative selection and weight optimization of randomly placed pencil beams (PBs), reduces optimization time and improves plan quality for multi-criteria optimization in intensity-modulated proton therapy, compared with traditional modes in which PBs are distributed over a regular grid. Resampling consisted of repeatedly performing: (1) random selection of candidate PBs from a very fine grid, (2) inverse multi-criteria optimization, and (3) exclusion of low-weight PBs. The newly selected candidate PBs were added to the PBs in the existing solution, causing the solution to improve with each iteration. Resampling and traditional regular grid planning were implemented into our in-house developed multi-criteria treatment planning system 'Erasmus iCycle'. The system optimizes objectives successively according to their priorities as defined in the so-called 'wish-list'. For five head-and-neck cancer patients and two PB widths (3 and 6 mm sigma at 230 MeV), treatment plans were generated using: (1) resampling, (2) anisotropic regular grids and (3) isotropic regular grids, while using varying sample sizes (resampling) or grid spacings (regular grid). We assessed differences in optimization time (for comparable plan quality) and in plan quality parameters (for comparable optimization time). Resampling reduced optimization time by a factor of 2.8 and 5.6 on average (7.8 and 17.0 at maximum) compared with the use of anisotropic and isotropic grids, respectively. Doses to organs-at-risk were generally reduced when using resampling, with median dose reductions ranging from 0.0 to 3.0 Gy (maximum: 14.3 Gy, relative: 0%-42%) compared with anisotropic grids and from -0.3 to 2.6 Gy (maximum: 11.4 Gy, relative: -4%-19%) compared with isotropic grids. Resampling was especially effective when using thin PBs (3 mm sigma). Resampling plans contained on average fewer PBs, energy layers and protons than anisotropic grid plans and more energy layers and protons than isotropic grid plans. In conclusion, resampling resulted in improved plan quality and in considerable optimization time reduction compared with traditional regular grid planning.

SU-E-T-617: Towards Fully Automated Multi-Criterial Plan Generation: A Prospective Clinical Study.

PURPOSE: To prospectively compare plans generated with iCycle, an in-house developed algorithm for fully automated multi-criterial IMRT beam profile and beam orientation optimization (Breedveld, Med. Phys. 2012), and plans manually generated by dosimetrists with the clinical treatment planning system. METHODS: For 20 randomly selected head-and-neck cancer patients with various tumour locations (of whom 13 received sequential boost treatments) we offered the treating physician the choice between an automatically generated iCycle plan and a manually optimized plan following standard clinical procedures. While iCycle used a fixed'wish-list' with hard constraints and prioritised objectives, the dosimetrists manually selected the beam configuration and fine-tuned the constraints and objectives for each IMRT plan. Dosimetrists and treating physicians were not informed in advance whether a competing iCycle plan was made or not. The two plans were simultaneously presented to the physician who then selected the plan to be used for treatment. For the patient group, we quantified differences in PTV coverage and sparing of critical tissues. RESULTS: In 32/33 plan comparisons the physician selected the iCycle plan for treatment. This highly consistent preference for automatically generated plans was mainly caused by improved sparing for the large majority of critical structures. With iCycle, the NTCPs for parotid and submandibular glands were reduced by 2.4% ± 4.9% (maximum: 18.5%, p=0.001) and 6.5% ± 8.3% (maximum: 27%, p=0.005), respectively. The reduction in mean oral cavity dose was 2.8 Gy ± 2.8 Gy (maximum: 8.1 Gy, p=0.005). For swallowing muscles, esophagus and larynx, the mean dose reduction was 3.3 Gy ± 1.1Gy (maximum: 9.2 Gy, p<0.001). Moreover, for 15 patients, the target coverage was improved as well. CONCLUSIONS: In 97% of cases, the automatically generated plan was selected for treatment because of superior quality. Apart from improved plan quality, automatic plan generation is economically attractive because of reduced workload.

SU-E-T-647: Plan Quality in Computerized Non-Coplanar IMRT Beam Angle Optimization is Highly Dependent on the Extent of the Beam direction Search Space.

PURPOSE: To investigate the relationship between plan quality and the extent of the beam direction search space in computerized beam angle selection for generating optimal (non-coplanar) IMRT plans for prostate SBRT with dose distributions simulating HDR brachytherapy. METHODS: iCycle (1) was used to investigate the relationship between plan quality and the extent of the set of beam directions available for plan generation. For a group of 10 prostate patients, optimal plans were generated for 5 direction search spaces. For coplanar treatments (CP set), 72 orientations were available for selection (separation 5°). The fully non-coplanar set (F-NCP) included the CP directions plus 430 directions spread over the sphere. The CK set contained the directions available at the robotic Cyberknife unit. CK+ and CK++ were extensions of CK to investigate some of its characteristics. Generated plans were in accordance with our clinical SBRT protocol for Cyberknife treatment, delivering 4 fractions of 9.5 Gy. Adequate PTV coverage had the highest priority. Reduction of rectum dose was the highest OAR priority. RESULTS: The mean PTV coverage (V95) of all SBRT plans was 99% ï,± 0.9% (1 SD). F-NCP plans had most favorable OAR dose parameters, while for coplanar plans OAR doses were highest. Compared to coplanar treatment, rectum Dmean/V60 were 25% / 37% and 19% / 21% lower in F-NCP and CK plans. Higher rectum dose for the Cyberknife set compared to F-NCP was not caused by a lack of posterior beams for Cyberknife. For all search spaces, reduction in OAR dose only leveled off with > 20 beams in the plans (for CP, rectum V60 in 25 beam plans was reduced by 64% compared to 11 beams). In the non-coplanar set-ups, there was a preference for beams with a (large) lateral component. CONCLUSIONS: Plan quality clearly improved with the extent of the beam direction search space (coplanar worst), and the number of beam directions in the plan (25 clearly better than 11).(1) Breedveld S, Storchi P, Voet P, Heijmen B, Med Phys 2012; DOI: 10.1118/1.3676689.