S. Breedveld

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.

A novel approach to multi-criteria inverse planning for IMRT

Treatment plan optimization is a multi-criteria process. Optimizing solely on one objective or on a sum of a priori weighted objectives may result in inferior treatment plans. Manually adjusting weights or constraints in a trial and error procedure is time consuming. In this paper we introduce a novel multi-criteria optimization approach to automatically optimize treatment constraints (dose-volume and maximum-dose). The algorithm tries to meet these constraints as well as possible, but in the case of conflicts it relaxes lower priority constraints so that higher priority constraints can be met. Afterwards, all constraints are tightened, starting with the highest priority constraints. Applied constraint priority lists can be used as class solutions for patients with similar tumour types. The presented algorithm does iteratively apply an underlying algorithm for beam profile optimization, based on a quadratic objective function with voxel-dependent importance factors. These voxel-dependent importance factors are automatically adjusted to reduce dose-volume and maximum-dose constraint violations.

Fully automated volumetric modulated arc therapy plan generation for prostate cancer patients

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 (VMATauto) were compared with VMAT plans generated manually by 1 expert dosimetrist in the absence of time pressure (VMATman). 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 (V95% > 99%). For VMATauto and VMATman 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.

The equivalence of multi-criteria methods for radiotherapy plan optimization

Several methods can be used to achieve multi-criteria optimization of radiation therapy treatment planning, which strive for Pareto-optimality. The property of the solution being Pareto optimal is desired, because it guarantees that no criteria can be improved without deteriorating another criteria. The most widely used methods are the weighted-sum method, in which the different treatment objectives are weighted, and constrained optimization methods, in which treatment goals are set and the algorithm has to find the best plan fulfilling these goals. The constrained method used in this paper, the 2p element of c (2-phase element-constraint) method is based on the element-constraint method, which generates Pareto-optimal solutions. Both approaches are uniquely related to each other. In this paper, we will show that it is possible to switch from the constrained method to the weighted-sum method by using the Lagrange multipliers from the constrained optimization problem, and vice versa by setting the appropriate constraints. In general, the theory presented in this paper can be useful in cases where a new situation is slightly different from the original situation, e.g. in online treatment planning, with deformations of the volumes of interest, or in automated treatment planning, where changes to the automated plan have to be made. An example of the latter is given where the planner is not satisfied with the result from the constrained method and wishes to decrease the dose in a structure. By using the Lagrange multipliers, a weighted-sum optimization problem is constructed, which generates a Pareto-optimal solution in the neighbourhood of the original plan, but fulfills the new treatment objectives.

Comparison of VMAT and IMRT strategies for cervical cancer patients using automated planning

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.

Fast, multiple optimizations of quadratic dose objective functions in IMRT

Inverse treatment planning for intensity-modulated radiotherapy may include time consuming, multiple minimizations of an objective function. In this paper, methods are presented to speed up the process of (repeated) minimization of the well-known quadratic dose objective function, extended with a smoothing term that ensures generation of clinically acceptable beam profiles. In between two subsequent optimizations, the voxel-dependent importance factors of the quadratic terms will generally be adjusted, based on an intermediate plan evaluation. The objective function has been written in matrix-vector format, facilitating the use of a recently published, fast quadratic minimization algorithm, instead of commonly applied gradient-based methods. This format also reduces the calculation time in between subsequent minimizations, related to adjustment of the voxel-dependent importance factors. Sparse matrices are used to limit the required amount of computer memory. For three patients, comparisons have been made with a gradient method. Mean speed improvements of up to a factor of 37 have been achieved.

IMRT for image-guided single vocal cord irradiation

PURPOSE We have been developing an image-guided single vocal cord irradiation technique to treat patients with stage T1a glottic carcinoma. In the present study, we compared the dose coverage to the affected vocal cord and the dose delivered to the organs at risk using conventional, intensity-modulated radiotherapy (IMRT) coplanar, and IMRT non-coplanar techniques. METHODS AND MATERIALS For 10 patients, conventional treatment plans using two laterally opposed wedged 6-MV photon beams were calculated in XiO (Elekta-CMS treatment planning system). An in-house IMRT/beam angle optimization algorithm was used to obtain the coplanar and non-coplanar optimized beam angles. Using these angles, the IMRT plans were generated in Monaco (IMRT treatment planning system, Elekta-CMS) with the implemented Monte Carlo dose calculation algorithm. The organs at risk included the contralateral vocal cord, arytenoids, swallowing muscles, carotid arteries, and spinal cord. The prescription dose was 66 Gy in 33 fractions. RESULTS For the conventional plans and coplanar and non-coplanar IMRT plans, the population-averaged mean dose ± standard deviation to the planning target volume was 67 ± 1 Gy. The contralateral vocal cord dose was reduced from 66 ± 1 Gy in the conventional plans to 39 ± 8 Gy and 36 ± 6 Gy in the coplanar and non-coplanar IMRT plans, respectively. IMRT consistently reduced the doses to the other organs at risk. CONCLUSIONS Single vocal cord irradiation with IMRT resulted in good target coverage and provided significant sparing of the critical structures. This has the potential to improve the quality-of-life outcomes after RT and maintain the same local control rates.

Validation of fully automated VMAT plan generation for library-based plan-of-the-day cervical cancer radiotherapy

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.

Adaptive Liver Stereotactic Body Radiation Therapy: Automated Daily Plan Reoptimization Prevents Dose Delivery Degradation Caused by Anatomy Deformations

PURPOSE To investigate how dose distributions for liver stereotactic body radiation therapy (SBRT) can be improved by using automated, daily plan reoptimization to account for anatomy deformations, compared with setup corrections only. METHODS AND MATERIALS For 12 tumors, 3 strategies for dose delivery were simulated. In the first strategy, computed tomography scans made before each treatment fraction were used only for patient repositioning before dose delivery for correction of detected tumor setup errors. In adaptive second and third strategies, in addition to the isocenter shift, intensity modulated radiation therapy beam profiles were reoptimized or both intensity profiles and beam orientations were reoptimized, respectively. All optimizations were performed with a recently published algorithm for automated, multicriteria optimization of both beam profiles and beam angles. RESULTS In 6 of 12 cases, violations of organs at risk (ie, heart, stomach, kidney) constraints of 1 to 6 Gy in single fractions occurred in cases of tumor repositioning only. By using the adaptive strategies, these could be avoided (<1 Gy). For 1 case, this needed adaptation by slightly underdosing the planning target volume. For 2 cases with restricted tumor dose in the planning phase to avoid organ-at-risk constraint violations, fraction doses could be increased by 1 and 2 Gy because of more favorable anatomy. Daily reoptimization of both beam profiles and beam angles (third strategy) performed slightly better than reoptimization of profiles only, but the latter required only a few minutes of computation time, whereas full reoptimization took several hours. CONCLUSIONS This simulation study demonstrated that replanning based on daily acquired computed tomography scans can improve liver stereotactic body radiation therapy dose delivery.

Shortening treatment time in robotic radiosurgery using a novel node reduction technique

PURPOSE The fraction duration of robotic radiosurgery treatments can be reduced by generating more time-efficient treatment plans with a reduced number of node positions, beams, and monitor units (MUs). Node positions are preprogramed locations where the robot can position the focal spot of the x-ray beam. As the time needed for the robot to travel between node positions takes up a large part of the treatment time, the aim of this study was to develop and evaluate a node reduction technique in order to reduce the treatment time per fraction for robotic radiosurgery. METHODS Node reduction was integrated into the inverse planning algorithm, developed in-house for the robotic radiosurgery modality. It involved repeated inverse optimization, each iteration excluding low-contribution node positions from the planning and resampling new candidate beams from the remaining node positions. Node reduction was performed until the exclusion of a single node position caused a constraint violation, after which the shortest treatment plan was selected retrospectively. Treatment plans were generated with and without node reduction for two lung cases of different complexity, one oropharyngeal case and one prostate case. Plan quality was assessed using the number of node positions, beams and MUs, and the estimated treatment time per fraction. All treatment plans had to fulfill all clinical dose constraints. Extra constraints were added to maintain the low-dose conformality and restrict skin doses during node reduction. RESULTS Node reduction resulted in 12 residual node positions, on average (reduction by 77%), at the cost of an increase in the number of beams and total MUs of 28% and 9%, respectively. Overall fraction durations (excluding patient setup) were shortened by 25% (range of 18%-40%), on average. Dose distributions changed only little and dose in low-dose regions was effectively restricted by the additional constraints. CONCLUSIONS The fraction duration of robotic radiosurgery treatments can be reduced considerably by node reduction with minimal changes in dosimetrical plan quality. Additional constraints are required to guarantee low-dose conformality and to avoid unacceptable skin dose.