Simultaneous optimization of beam orientations, wedge filters and field weights for inverse planning with anatomy-based MLC fields

Functional avoidance of lung in plan optimization with an aperture-based inverse planning system

PURPOSE

To implement SPECT-based optimization in an anatomy-based aperture inverse planning system for the functional avoidance of lung in thoracic irradiation.

MATERIAL AND METHODS

SPECT information has been introduced as a voxel-by-voxel modulation of lung importance factors proportionally to the local perfusion count. Fifteen cases of lung cancer have been retrospectively analyzed by generating angle-optimized non-coplanar plans, comparing a purely anatomical approach and our functional approach. Planning target volume coverage and lung sparing have been compared. Statistical significance was assessed by a Wilcoxon matched pairs test.

RESULTS

For similar target coverage, perfusion-weighted volume receiving 10 Gy was reduced by a median of 2.2% (p=0.022) and mean perfusion-weighted lung dose, by a median of 0.9 Gy (p=0.001). A separate analysis of patients with localized or non-uniform hypoperfusion could not show which would benefit more from SPECT-based treatment planning. Redirection of dose sometimes created overdosage regions in the target volume. Plans consisted of a similar number of segments and monitor units.

CONCLUSIONS

Angle optimization and SPECT-based modulation of importance factors allowed for functional avoidance of the lung while preserving target coverage. The technique could be also applied to implement PET-based modulation inside the target volume, leading to a safer dose escalation.

A unified framework for 3D radiation therapy and IMRT planning: plan optimization in the beamlet domain by constraining or regularizing the fluence map variations

The purpose of this work is to demonstrate that physical constraints on fluence gradients in 3D radiation therapy (RT) planning can be incorporated into beamlet optimization explicitly by direct constraint on the spatial variation of the fluence maps or implicitly by using total-variation regularization (TVR). The former method forces the fluence to vary in accordance with the known form of a wedged field and latter encourages the fluence to take the known form of the wedged field by requiring the derivatives of the fluence maps to be piece-wise constant. The performances of the proposed methods are evaluated by using a brain cancer case and a head and neck case. It is found that both approaches are capable of providing clinically sensible 3D RT solutions with monotonically varying fluence maps. For currently available 3D RT delivery schemes based on the use of customized physical or dynamic wedges, constrained optimization seems to be more useful because the optimized fields are directly deliverable. Working in the beamlet domain provides a natural way to model the spatial variation of the beam fluence. The proposed methods take advantage of the fact that 3D RT is a special form of intensity-modulated radiation therapy (IMRT) and finds the optimal plan by searching for fields with a certain type of spatial variation. The approach provides a unified framework for 3D CRT and IMRT plan optimization.

Performance evaluation of an algorithm for fast optimization of beam weights in anatomy-based intensity modulated radiotherapy

This study aims to evaluate the performance of a new algorithm for optimization of beam weights in anatomy-based intensity modulated radiotherapy (IMRT). The algorithm uses a numerical technique called Gaussian-Elimination that derives the optimum beam weights in an exact or non-iterative way. The distinct feature of the algorithm is that it takes only fraction of a second to optimize the beam weights, irrespective of the complexity of the given case. The algorithm has been implemented using MATLAB with a Graphical User Interface (GUI) option for convenient specification of dose constraints and penalties to different structures. We have tested the numerical and clinical capabilities of the proposed algorithm in several patient cases in comparison with KonRad^® inverse planning system. The comparative analysis shows that the algorithm can generate anatomy-based IMRT plans with about 50% reduction in number of MUs and 60% reduction in number of apertures, while producing dose distribution comparable to that of beamlet-based IMRT plans. Hence, it is clearly evident from the study that the proposed algorithm can be effectively used for clinical applications.

Optimization of photon beam energy in aperture-based inverse planning

Optimal choice of beam energy in radiation therapy is easy in many well‐documented cases, but less obvious in some others. Low‐energy beams may provide better conformity around the target than their high‐energy counterparts due to reduced lateral scatter, but they also contribute to overdosage of peripheral normal tissue. Beam energy was added as an optimization parameter in an automatic aperture‐based inverse planning system. We have investigated a total of six cases for two sites (prostate and lung), representative of deep‐seated and moderately deep‐seated tumors. For one case for each site, different numbers of beam incidences were considered. The other cases for each site were optimized using a fixed number of incidences. Four types of plans were optimized: 6 MV, 23 MV, and mixed energy plans with one or two energies per incidence. Each plan was scored with a dose‐volume cost function. Cost function values, number of segments, monitor units, dose‐volume parameters, and isodose distributions were compared. For the prostate and lung cases, energy mixing improved plans in terms of cost function values, with a more important reduction for a small number of beam incidences. Use of high energy allowed better peripheral tissue sparing, while keeping similar target coverage and sensitive structures avoidance. Low energy contribution to monitor units usually increased with the number of beam incidences. Thus, for deep‐seated and moderately deep‐seated tumors, energy optimization can produce interesting plans with less peripheral dose and monitor units than for low energy alone.

PACS numbers: 87.55.de, 87.55.dk, 87.56.N‐

eIMRT: a web platform for the verification and optimization of radiation treatment plans

The eIMRT platform is a remote distributed computing tool that provides users with Internet access to three different services: Monte Carlo optimization of treatment plans, CRT & IMRT treatment optimization, and a database of relevant radiation treatments/clinical cases. These services are accessible through a user-friendly and platform independent web page. Its flexible and scalable design focuses on providing the final users with services rather than a collection of software pieces. All input and output data (CT, contours, treatment plans and dose distributions) are handled using the DICOM format. The design, implementation, and support of the verification and optimization algorithms are hidden to the user. This allows a unified, robust handling of the software and hardware that enables these computation-intensive services. The eIMRT platform is currently hosted by the Galician Supercomputing Center (CESGA) and may be accessible upon request (there is a demo version at http://eimrt.cesga.es:8080/eIMRT2/demo; request access in http://eimrt.cesga.es/signup.html). This paper describes all aspects of the eIMRT algorithms in depth, its user interface, and its services. Due to the flexible design of the platform, it has numerous applications including the intercenter comparison of treatment planning, the quality assurance of radiation treatments, the design and implementation of new approaches to certain types of treatments, and the sharing of information on radiation treatment techniques. In addition, the web platform and software tools developed for treatment verification and optimization have a modular design that allows the user to extend them with new algorithms. This software is not a commercial product. It is the result of the collaborative effort of different public research institutions and is planned to be distributed as an open source project. In this way, it will be available to any user; new releases will be generated with the new implemented codes or upgrades.

Postoperative Irradiation of Gynecologic Malignancies: Improving Treatment Delivery Using Aperture-Based Intensity-Modulated Radiotherapy

PURPOSE

To evaluate dosimetric and treatment delivery advantages of aperture-based intensity-modulated radiotherapy (AB-IMRT) for the treatment of patients receiving whole pelvic radiotherapy for gynecologic malignancies.

METHODS AND MATERIALS

Nineteen patients undergoing pelvic radiotherapy after resection of endometrial cancers were selected. A 45-Gy dose was prescribed to the target volume delineated on a planning CT scan. An in-house inverse planning system, Ballista, was used to develop a treatment plan using aperture-based multileaf collimator segments. This approach was compared with conventional four-field, enlarged four-field, and static beamlet-based IMRT (BB-IMRT) techniques in terms of target coverage, dose-volume histogram statistics for surrounding normal tissues, and numbers of segments and monitor units (MU).

RESULTS

Three quarters (76.4%) of the planning target volume received the prescription dose with conventional four-field plans. With adequate target coverage, the Ballista plans significantly reduced the volume of bowel and bladder irradiated at the prescribed dose (p < 0.001), whereas the two approaches provided equivalent results for the rectum (p = 0.5). On the other hand, AB-IMRT and BB-IMRT plans showed only small differences in dose-volume histogram statistics of unknown clinical impact, whereas Ballista plan delivery required on average 73% and 59% fewer segments and MU, respectively.

CONCLUSION

With respect to conventional techniques, AB-IMRT for the treatment of gynecologic malignancies provides dosimetric advantages similar to those with BB-IMRT but with clear treatment delivery improvements.

Direct-aperture optimization applied to selection of beam orientations in intensity-modulated radiation therapy

Direct-aperture optimization (DAO) was applied to iterative beam-orientation selection in intensity-modulated radiation therapy (IMRT), so as to ensure a realistic segmental treatment plan at each iteration. Nested optimization engines dealt separately with gantry angles, couch angles, collimator angles, segment shapes, segment weights and wedge angles. Each optimization engine performed a random search with successively narrowing step sizes. For optimization of segment shapes, the filtered backprojection (FBP) method was first used to determine desired fluence, the fluence map was segmented, and then constrained direct-aperture optimization was used thereafter. Segment shapes were fully optimized when a beam angle was perturbed, and minimally re-optimized otherwise. The algorithm was compared with a previously reported method using FBP alone at each orientation iteration. An example case consisting of a cylindrical phantom with a hemi-annular planning target volume (PTV) showed that for three-field plans, the method performed better than when using FBP alone, but for five or more fields, neither method provided much benefit over equally spaced beams. For a prostate case, improved bladder sparing was achieved through the use of the new algorithm. A plan for partial scalp treatment showed slightly improved PTV coverage and lower irradiated volume of brain with the new method compared to FBP alone. It is concluded that, although the method is computationally intensive and not suitable for searching large unconstrained regions of beam space, it can be used effectively in conjunction with prior class solutions to provide individually optimized IMRT treatment plans.

Multiobjective optimization with a modified simulated annealing algorithm for external beam radiotherapy treatment planning

Inverse planning in external beam radiotherapy often requires a scalar objective function that incorporates importance factors to mimic the planner's preferences between conflicting objectives. Defining those importance factors is not straightforward, and frequently leads to an iterative process in which the importance factors become variables of the optimization problem. In order to avoid this drawback of inverse planning, optimization using algorithms more suited to multiobjective optimization, such as evolutionary algorithms, has been suggested. However, much inverse planning software, including one based on simulated annealing developed at our institution, does not include multiobjective-oriented algorithms. This work investigates the performance of a modified simulated annealing algorithm used to drive aperture-based intensity-modulated radiotherapy inverse planning software in a multiobjective optimization framework. For a few test cases involving gastric cancer patients, the use of this new algorithm leads to an increase in optimization speed of a little more than a factor of 2 over a conventional simulated annealing algorithm, while giving a close approximation of the solutions produced by a standard simulated annealing. A simple graphical user interface designed to facilitate the decision-making process that follows an optimization is also presented.

Computer optimization of noncoplanar beam setups improves stereotactic treatment of liver tumors

PURPOSE

To investigate whether computer-optimized fully noncoplanar beam setups may improve treatment plans for the stereotactic treatment of liver tumors.

METHODS

An algorithm for automated beam orientation and weight selection (Cycle) was extended for noncoplanar stereotactic treatments. For 8 liver patients previously treated in our clinic using a prescription isodose of 65%, Cycle was used to generate noncoplanar and coplanar plans with the highest achievable minimum planning target volume (PTV) dose for the clinically delivered isocenter and mean liver doses, while not violating the clinically applied hard planning constraints. The clinical and the optimized coplanar and noncoplanar plans were compared, with respect to D(PTV,99%), the dose received by 99% of the PTV, the PTV generalized equivalent uniform dose (gEUD), and the compliance with the clinical constraints.

RESULTS

For each patient, the ratio between D(PTV,99%) and D(isoc), and the gEUD(-5) and gEUD(-20) values of the optimized noncoplanar plan were higher than for the clinical plan with an average increase of respectively 18.8% (range, 7.8-24.0%), 6.4 Gy (range, 3.4-11.8 Gy), and 10.3 Gy (range, 6.7-12.5). D(PTV,99%)/D(isoc), gEUD(-5), and gEUD(-20) of the optimized noncoplanar plan was always higher than for the optimized coplanar plan with an average increase of, respectively, 4.5% (range, 0.2-9.7%), 2.7 Gy (range, 0.6-9.7 Gy), and 3.4 Gy (range, 0.6-9.9 Gy). All plans were within the imposed hard constraints. On average, the organs at risk were better spared with the optimized noncoplanar plan than with the optimized coplanar plan and the clinical plan.

CONCLUSIONS

The use of automatically generated, fully noncoplanar beam setups results in plans that are favorable compared with coplanar techniques. Because of the automation, we found that the planning workload can be decreased from 1 to 2 days to 1 to 2 h.

Automatic generation of anatomy-based MLC fields in aperture-based IMRT

We have developed an algorithm to automatically generate anatomy-based MLC fields. For each beam, a first field is adjusted to the projection of the target in a beam's eye view, allowing subsequent fields to be derived from this conformal field by removing the overlapping surface of each organ at risk, respectively. The projections are based on a surface sampling of the anatomical structures. On top of the MLC mechanical constraints, verification constraints are imposed on the MLC segments, in order to get reliable dosimetry using a commercial dose calculation engine. Thus, in each direction, the aperture's cross-section must be greater than a specified threshold, in our case 2 cm. Furthermore, junctions are not tolerated in order to avoid underdosage, for instance from the tongue-and-groove effect. The use of such MLC fields simplifies the verification process. The performance of the algorithm is illustrated for head and neck, thorax and prostate cases. Only a fraction of a second of CPU time is required to perform the segmentation for each beam.