Elimination of importance factors for clinically accurate selection of beam orientations, beam weights and wedge angles in conformal radiation therapy

Direct incorporation of patient-specific efficacy and toxicity estimates in radiation therapy plan optimization

PURPOSE

Current radiation therapy (RT) treatment planning relies mainly on pre-defined dose-based objectives and constraints to develop plans that aim to control disease while limiting damage to normal tissues during treatment. These objectives and constraints are generally population-based, in that they are developed from the aggregate response of a broad patient population to radiation. However, correlations of new biologic markers and patient-specific factors to treatment efficacy and toxicity provide the opportunity to further stratify patient populations and develop a more individualized approach to RT planning. We introduce a novel intensity-modulated radiation therapy (IMRT) optimization strategy that directly incorporates patient-specific dose response models into the planning process. In this strategy, we integrate the concept of utility-based planning where the optimization objective is to maximize the predicted value of overall treatment utility, defined by the probability of efficacy (e.g., local control) minus the weighted sum of toxicity probabilities. To demonstrate the feasibility of the approach, we apply the strategy to treatment planning for non-small cell lung cancer (NSCLC) patients.

METHODS AND MATERIALS

We developed a prioritized approach to patient-specific IMRT planning. Using a commercial treatment planning system (TPS), we calculate dose based on an influence matrix of beamlet-dose contributions to regions-of-interest. Then, outside of the TPS, we hierarchically solve two optimization problems to generate optimal beamlet weights that can then be imported back to the TPS. The first optimization problem maximizes a patient's overall plan utility subject to typical clinical dose constraints. In this process, we facilitate direct optimization of efficacy and toxicity trade-off based on individualized dose-response models. After optimal utility is determined, we solve a secondary optimization problem that minimizes a conventional dose-based objective subject to the same clinical dose constraints as the first stage but with the addition of a constraint to maintain the optimal utility from the first optimization solution. We tested this method by retrospectively generating plans for five previously treated NSCLC patients and comparing the prioritized utility plans to conventional plans optimized with only dose metric objectives. To define a plan utility function for each patient, we utilized previously published correlations of dose to local control and grade 3-5 toxicities that include patient age, stage, microRNA levels, and cytokine levels, among other clinical factors.

RESULTS

The proposed optimization approach successfully generated RT plans for five NSCLC patients that improve overall plan utility based on personalized efficacy and toxicity models while accounting for clinical dose constraints. Prioritized utility plans demonstrated the largest average improvement in local control (16.6%) when compared to plans generated with conventional planning objectives. However, for some patients, the utility-based plans resulted in similar local control estimates with decreased estimated toxicity.

CONCLUSION

The proposed optimization approach, where the maximization of a patient's RT plan utility is prioritized over the minimization of standardized dose metrics, has the potential to improve treatment outcomes by directly accounting for variability within a patient population. The implementation of the utility-based objective function offers an intuitive, humanized approach to biological optimization in which planning trade-offs are explicitly optimized.

Prior-knowledge treatment planning for volumetric arc therapy using feature-based database mining

Treatment planning for volumetric arc therapy (VMAT) is a lengthy process that requires many rounds of optimizations to obtain the best treatment settings and optimization constraints for a given patient's geometry. We propose a feature‐selection search engine that explores previously treated cases of similar anatomy, returning the optimal plan configurations and attainable DVH constraints. Using an institutional database of 83 previously treated cases of prostate carcinoma treated with volumetric‐modulated arc therapy, the search procedure first finds the optimal isocenter position with an optimization procedure, then ranks the anatomical similarity as the mean distance between targets. For the best matching plan, the planning information is reformatted to the DICOM format and imported into the treatment planning system to suggest isocenter, arc directions, MLC patterns, and optimization constraints that can be used as starting points in the optimization process. The approach was tested to create prospective treatment plans based on anatomical features that match previously treated cases from the institution database. By starting from a near‐optimal solution and using previous optimization constraints, the best matching test only required simple optimization steps to further decrease target inhomogeneity, ultimately reducing time spend by the therapist in planning arcs' directions and lengths.

PACS number: 87.55.D‐, 87.55.de

Optimising stereotactic body radiotherapy for non-small cell lung cancer with volumetric intensity-modulated arc therapy--a planning study

AIMS

The potential advantages of stereotactic body radiotherapy (SBRT) for early stage non-small cell lung cancer (NSCLC) over conventional fractionated radiotherapy include a higher biological effective dose, a reduction in accelerated repopulation, greater patient convenience and reduced demand on radiotherapy resources. Before introducing SBRT in our department, a review of planning and delivery was undertaken, starting with an assessment of optimum beam number and arrangement.

MATERIALS AND METHODS

Radiotherapy planning computed tomography scans for five patients previously treated for T1 peripheral NSCLC were selected. In each the contoured tumour had planning target volume (PTV) margins of 1cm in all directions. Forward-planned three-field coplanar and non-coplanar plans and a seven-field coplanar plan were produced and optimised. In-house inverse-planning software (AutoBeam) was used to generate three-, five-, seven- and nine-field coplanar and non-coplanar plans and two volumetric intensity-modulated arc therapy (VMAT) plans. The resulting V(20), V(11), PTV(90), PTV(95) and mean lung dose were compared.

RESULTS

Analysis of variance showed non-coplanar plans to have lower V(11) and higher PTV(90) and PTV(95) than coplanar plans. VMAT showed equivalent V(20) and target coverage when compared with the best non-coplanar plans, but with a faster delivery time (2min 8s versus 12min 40s).

CONCLUSIONS

Inverse-planned five-field non-coplanar plans and VMAT improve target coverage while minimising the higher dose to normal lung tissue for SBRT of NSCLC compared with coplanar beam arrangements. VMAT is preferable because of significantly shorter treatment delivery times.

Helical volumetric modulated arc therapy for treatment of craniospinal axis

PURPOSE

Volumetric modulated arc therapy (VMAT) can be used with multiple isocenters to provide an effective treatment of the craniospinal axis. Additional efficiency can be achieved by simultaneously applying linear couch motion to generate a helical arc trajectory. This study investigated the treatment planning and delivery of helical VMAT for treatment of the craniospinal axis.

METHODS AND MATERIALS

VMAT plans were retrospectively created for 5 patients. The first plan consisted of multiple separate arcs. A second plan consisted of a single helical arc with a pitch of 10 cm. Three additional plans consisted of multiple helical arcs with the beam rotating alternately clockwise and counterclockwise to avoid the need for the gantry to pass through 180°. The three plans had a pitch of 5, 10, and 15 cm. For 1 of the patients, three possible plans with alternate gantry motion and a pitch of 10 cm were delivered helically, and the dose was verified.

RESULTS

Relative to the plan with separate arcs, the continuous helical plan produced a mean objective value of 104.0% ± 14.8% (standard deviation), and the alternating helical plans produced an objective value of 118.9% ± 9.8%, 102.3% ± 13.5%, and 101.5% ± 15.8% for a pitch of 5 cm, 10 cm, and 15 cm, respectively (with lower values representing better plans). For the delivered plans, taking a mean of 17 min 51 s to deliver, a mean of 97.1% of the measurements were within 4% and 4 mm of the planned dose.

CONCLUSIONS

A continuous helical VMAT plan provides comparable dose quality to a plan with separate VMAT arcs. Comparable quality is also produced by an alternating helical plan, provided the pitch is chosen appropriately. Alternating helical plans have been delivered and verified successfully. Alternating helical delivery offers the ultimate delivery efficiency for intensity-modulated radiotherapy for the craniospinal axis.

Reduced order constrained optimization (ROCO): clinical application to lung IMRT

PURPOSE

The authors use reduced-order constrained optimization (ROCO) to create clinically acceptable IMRT plans quickly and automatically for advanced lung cancer patients. Their new ROCO implementation works with the treatment planning system and full dose calculation used at Memorial Sloan-Kettering Cancer Center (MSKCC). The authors have implemented mean dose hard constraints, along with the point-dose and dose-volume constraints that the authors used for our previous work on the prostate.

METHODS

ROCO consists of three major steps. First, the space of treatment plans is sampled by solving a series of optimization problems using penalty-based quadratic objective functions. Next, an efficient basis for this space is found via principal component analysis (PCA); this reduces the dimensionality of the problem. Finally, a constrained optimization problem is solved over this basis to find a clinically acceptable IMRT plan. Dimensionality reduction makes constrained optimization computationally efficient.

RESULTS

The authors apply ROCO to 12 stage III non-small-cell lung cancer (NSCLC) cases, generating IMRT plans that meet all clinical constraints and are clinically acceptable, and demonstrate that they are competitive with the clinical treatment plans. The authors also test how many samples and PCA modes are necessary to achieve an adequate lung plan, demonstrate the importance of long-range dose calculation for ROCO, and evaluate the performance of nonspecific normal tissue ("rind") constraints in ROCO treatment planning for the lung. Finally, authors show that ROCO can save time for planners, and they estimate that in the clinic, planning using their approach would save a median of 105 min for the patients in the study.

CONCLUSIONS

New challenges arise when applying ROCO to the lung site, which include the lack of a class solution, a larger treatment site, an increased number of parameters and beamlets, a variable number of beams and beam arrangement, and the customary use of rinds in clinical plans to avoid high-dose areas outside the PTV. In the authors previous work, use of an approximate dose calculation in the hard constraint optimization sometimes meant that clinical constraints were not met when evaluated with the full dose calculation. This difficulty has been removed in the current work by using the full dose calculation in the hard constraint optimization. The authors have demonstrated that ROCO offers a fast and automatic way to create IMRT plans for advanced NSCLC, which extends their previous application of ROCO to prostate cancer IMRT planning.

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.

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‐

Reduced-order constrained optimization in IMRT planning

This paper presents a new algorithm for constrained intensity-modulated radiotherapy (IMRT) planning, made tractable by a dimensionality reduction using a set of plans obtained by fast, unconstrained optimizations. The main result is to reduce planning time by an order of magnitude, producing viable five field prostate IMRT plans in about 5 min. Broadly, the algorithm has three steps. First, we solve a series of independent unconstrained minimization problems based on standard penalty-based objective functions, 'probing' the space of reasonable beamlet intensities. Next, we apply principal component analysis (PCA) to this set of plans, revealing that the high-dimensional intensity space can be spanned by only a few basis vectors. Finally, we parameterize an IMRT plan as a linear combination of these few basis vectors, enabling the fast solution of a constrained optimization problem for the desired intensities. We describe a simple iterative process for handling the dose-volume constraints that are typically required for clinical evaluation, and demonstrate that the resulting plans meet all clinical constraints based on an approximate dose calculation algorithm.

A potential to reduce pulmonary toxicity: The use of perfusion SPECT with IMRT for functional lung avoidance in radiotherapy of non-small cell lung cancer

BACKGROUND AND PURPOSE

The study aimed to examine specific avoidance of functional lung (FL) defined by a single photon emission computerized tomography (SPECT) lung perfusion scan, using intensity modulated radiotherapy (IMRT) and three-dimensional conformal radiotherapy (3-DCRT) in patients with non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

Patients with NSCLC underwent planning computerized tomography (CT) and lung perfusion SPECT scan in the treatment position using fiducial markers to allow co-registration in the treatment planning system. Radiotherapy (RT) volumes were delineated on the CT scan. FL was defined using co-registered SPECT images. Two inverse coplanar RT plans were generated for each patient: 4-field 3-DCRT and 5-field step-and-shoot IMRT. 3-DCRT plans were created using automated AutoPlan optimisation software, and IMRT plans were generated employing Pinnacle(3) treatment planning system (Philips Radiation Oncology Systems). All plans were prescribed to 64 Gy in 32 fractions using data for the 6 MV beam from an Elekta linear accelerator. The objectives for both plans were to minimize the volume of FL irradiated to 20 Gy (fV(20)) and dose variation within the planning target volume (PTV). A spinal cord dose was constrained to 46 Gy. Volume of PTV receiving 90% of the prescribed dose (PTV(90)), fV(20), and functional mean lung dose (fMLD) were recorded. The PTV(90)/fV(20) ratio was used to account for variations in both measures, where a higher value represented a better plan.

RESULTS

Thirty-four RT plans of 17 patients with stage I-IIIB NSCLC suitable for radical RT were analysed. In 6 patients with stage I-II disease there was no improvement in PTV(90), fV(20), PTV/fV(20) ratio and fMLD using IMRT compared to 3-DCRT. In 11 patients with stage IIIA-B disease, the PTV was equally well covered with IMRT and 3-DCRT plans, with IMRT producing better PTV(90)/fV(20) ratio (mean ratio - 7.2 vs. 5.3, respectively, p=0.001) and reduced fMLD figures compared to 3-DCRT (mean value - 11.5 vs. 14.3 Gy, p=0.001). This was due to reduction in fV(20) while maintaining PTV coverage.

CONCLUSION

The use of IMRT compared to 3-DCRT improves the avoidance of FL defined by perfusion SPECT scan in selected patients with locally advanced NSCLC. If the dose to FL is shown to be the primary determinant of lung toxicity, IMRT would allow for effective dose escalation by specific avoidance of FL.

Comparison of inverse-planned three-dimensional conformal radiotherapy and intensity-modulated radiotherapy for non–small-cell lung cancer

PURPOSE

Lungs are the major dose-limiting organ during radiotherapy (RT) for non-small-cell lung cancer owing to the development of pneumonitis. This study compared intensity-modulated RT (IMRT) with three-dimensional conformal RT (3D-CRT) in reducing the dose to the lungs.

METHODS

Ten patients with localized non-small-cell lung cancer underwent computed tomography (CT). The planning target volume (PTV) was defined and the organs at risk were outlined. An inverse-planning program, AutoPlan, was used to design the beam angle-optimized six-field noncoplanar 3D-CRT plans. Each 3D-CRT plan was compared with a series of five IMRT plans per patient. The IMRT plans were created using a commercial algorithm and consisted of a series of three, five, seven, and nine equidistant coplanar field arrangements and one six-field noncoplanar plan. The planning objectives were to minimize the lung dose while maintaining the dose to the PTV. The percentage of lung volume receiving >20 Gy (V20) and the percentage of the PTV covered by the 90% isodose (PTV90) were the primary endpoints. The PTV90/V20 ratio was used as the parameter accounting for both the reduction in lung volume treated and the PTV coverage.

RESULTS

All IMRT plans, except for the three-field coplanar plans, improved the PTV90/V20 ratio significantly compared with the optimized 3D-CRT plan. Nine coplanar IMRT beams were significantly better than five or seven coplanar IMRT beams, with an improved PTV90/V20 ratio.

CONCLUSION

The results of our study have shown that IMRT can reduce the dose to the lungs compared with 3D-CRT by improving the conformity of the plan.

IMRT treatment planning based on prioritizing prescription goals

Determining the 'best' optimization parameters in IMRT planning is typically a time-consuming trial-and-error process with no unambiguous termination point. Recently we and others proposed a goal-programming approach which better captures the desired prioritization of dosimetric goals. Here, individual prescription goals are addressed stepwise in their order of priority. In the first step, only the highest order goals are considered (target coverage and dose-limiting normal structures). In subsequent steps, the achievements of the previous steps are turned into hard constraints and lower priority goals are optimized, in turn, subject to higher priority constraints. So-called 'slip' factors were introduced to allow for slight, clinically acceptable violations of the constraints. Focusing on head and neck cases, we present several examples for this planning technique. The main advantages of the new optimization method are (i) its ability to generate plans that meet the clinical goals, as well as possible, without tuning any weighting factors or dose-volume constraints, and (ii) the ability to conveniently include more terms such as fluence map smoothness. Lower level goals can be optimized to the achievable limit without compromising higher order goals. The prioritized prescription-goal planning method allows for a more intuitive and human-time-efficient way of dealing with conflicting goals compared to the conventional trial-and-error method of varying weighting factors and dose-volume constraints.

Reduced-order parameter optimization for simplifying prostate IMRT planning

Intensity-modulated radiotherapy (IMRT) has become an effective tool for cancer treatment with radiation. However, even expert radiation planners still need to spend a substantial amount of time manually adjusting IMRT optimization parameters such as dose limits and costlet weights in order to obtain a clinically acceptable plan. In this paper, we describe two main advances that simplify the parameter adjustment process for five-field prostate IMRT planning. First, we report the results of a sensitivity analysis that quantifies the effect of each hand-tunable parameter of the IMRT cost function on each clinical objective and the overall quality of the resulting plan. Second, we show that a recursive random search over the six most sensitive parameters as an outer loop in IMRT planning can quickly and automatically determine parameters for the cost function that lead to a plan meeting the clinical requirements. Our experiments on a ten-patient dataset show that for 70% of the cases, we can automatically determine a plan in 10 min (on the average) that is either clinically acceptable or requires only minor adjustment by the planner. The outer-loop optimization can be easily integrated into a traditional IMRT planning system.

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.

Constrained segment shapes in direct-aperture optimization for step-and-shoot IMRT

Previous studies have shown that, by optimizing segment shapes and weights directly, without explicitly optimizing fluence profiles, effective IMRT plans can be generated with fewer segments. This study proposes a method of direct-aperture optimization with aperture shape constraints, which is designed to provide segmental IMRT plans using a minimum of simple, regular segments. The method uses a cubic function to create smoothly curving multileaf collimator shapes. Constraints on segment dimension and equivalent square are applied, and each segment can be constrained to lie within the previous one, for easy generation of fluence profiles with a single maximum. To simply optimize the segment shapes and reject any shapes which violate the constraints is too inefficient, so an innovative method of feedback optimization is used to ensure in advance that viable aperture shapes are generated. The algorithm is demonstrated using a simple cylindrical phantom consisting of a hemi-annular planning target volume and a central cylindrical organ-at-risk. A simple IMRT rectum case is presented, where segments are used to replace a wedge. More complex cases of prostate and seminal vesicles and prostate and pelvic nodes are also shown. The algorithm produces effective plans in each case with three to five segments per beam. For the simple plans, the constraint that each segment should be contained within the previous one adds additional simplicity to the plan, for a small reduction in plan quality. This study confirms that direct-aperture optimization gives efficient solutions to the segmental IMRT inverse problem and provides a method for generating simple apertures. By using such a method, the workload of IMRT verification may be reduced and simplified, as verification of fluence profiles from individual beams may be eliminated.

Comparison of forward planning with automated inverse planning for three-dimensional conformal radiotherapy of non-small cell lung cancer without IMRT

The forward and inverse treatment plans of 10 patients with lung cancer were compared in terms of PTV coverage, sparing of normal lung and time required to generate a plan. The inverse planning produced as good treatment plans as an experienced dosimetrist with considerable reduction in staff time. When translated to other complex sites, inverse non-IMRT planning may have considerable impact on manpower requirements.

The incorporation of SPECT functional lung imaging into inverse radiotherapy planning for non-small cell lung cancer

BACKGROUND AND PURPOSE

Patients with non-small cell lung cancer (NSCLC) often have inhomogeneous lung perfusion. Radiotherapy planning computed tomography (CT) scans have been accurately co-registered with lung perfusion single photon emission computed tomography (SPECT) scans to design radiotherapy treatments which limit dose to healthy 'perfused' lung.

PATIENTS AND METHODS

Patients with localised NSCLC had CT and SPECT scans accurately co-registered in the planning system. The SPECT images were used to define a volume of perfused 'functioning' lung (FL). Inverse planning software was used to create 3D-conformal plans, the planning objective being either to minimise the dose to whole lungs (WL) or to minimise the dose to FL.

RESULTS

Four plans were created for each of six patients. The mean difference in volume between WL and FL was 1011.7 cm(3) (range 596.2-1581.1cm(3)). One patient with bilateral upper lobe perfusion deficits had a 16% reduction in FLV(20) (the percentage volume of functioning lung receiving >or=20 Gy). The remaining patients had inhomogeneous perfusion deficits such that inverse planning was not able to sufficiently optimise beam angles to avoid functioning lung.

CONCLUSION

SPECT perfusion images can be accurately co-registered with radiotherapy planning CT scans and may be helpful in creating treatment plans for patients with large perfusion deficits.

Treatment planning evaluation of non-coplanar techniques for conformal radiotherapy of the prostate

BACKGROUND AND PURPOSE

To evaluate the benefit of using non-coplanar treatment plans for irradiation of two different clinical treatment volumes: prostate only (PO) and the prostate plus seminal vesicles (PSV).

MATERIAL AND METHODS

An inverse planning algorithm was used to produce three-field, four-field, five-field and six-field non-coplanar treatment plans without intensity-modulation in ten patients. These were compared against a three-field coplanar plan. A dose of 74 Gy was prescribed to the isocentre. Plans were compared using the minimum dose to the planning target volume (PTV), maximum dose to the small bowel, and irradiated volumes of rectum, bladder and femoral head. Biological indices were also evaluated.

RESULTS

For the PO group, volume of rectum irradiated to 60 Gy (V(60)) was 22.5+/-3.7% for the coplanar plan, and 21.5+/-5.3% for the five-field non-coplanar plan, which was the most beneficial (p=0.3). For the PSV group, the five-field non-coplanar plan was again the most beneficial. Rectal V(60) was in this case reduced from 41.5+/-10.4% for the coplanar plan to 35.2+/-9.3% for the non-coplanar plan (p=0.02).

CONCLUSIONS

The use of non-coplanar beams in conformal prostate radiotherapy provides a small increase in rectal sparing, more significantly with PSV volumes than for PO volumes.

Feasibility of using ultrasound for real-time tracking during radiotherapy

This study was designed to examine the feasibility of utilizing transabdominal ultrasound for real-time monitoring of target motion during a radiotherapy fraction. A clinical Acuson 128/XP ultrasound scanner was used to image various stationary and moving phantoms while an Elekta SL25 linear accelerator radiotherapy treatment machine was operating. The ultrasound transducer was positioned to image from the outer edge of the treatment field at all times. Images were acquired to videotape and analyzed using in-house motion tracking algorithms to determine the effect of the SL25 on the quality of the displacement measurements. To determine the effect on the dosimetry of the presence of the transducer, dose distributions were examined using thermoluminescent dosimeters loaded into an Alderson Rando phantom and exposed to a 10 x 10 cm2 treatment field with and without the ultrasound transducer mounted 2.5 cm outside the field edge. The ultrasound images acquired a periodic noise that was shown to occur at the pulsing frequency of the treatment machine. Images of moving tissue were analyzed and the standard deviation on the displacement estimates within the tissue was identical with the SL25 on and off. This implies that the periodic noise did not significantly degrade the precision of the tracking algorithm (which was better than 0.01 mm). The presence of the transducer at the surface of the phantom presented only a 2.6% change to the dose distribution to the volume of the phantom. The feasibility of ultrasonic motion tracking during radiotherapy treatment is demonstrated. This presents the possibility of developing a noninvasive, real-time and low-cost method of tracking target motion during a treatment fraction.

Interactively exploring optimized treatment plans

PURPOSE

A new paradigm for treatment planning is proposed that embodies the concept of interactively exploring the space of optimized plans. In this approach, treatment planning ignores the details of individual plans and instead presents the physician with clinical summaries of sets of solutions to well-defined clinical goals in which every solution has been optimized in advance by computer algorithms.

METHODS AND MATERIALS

Before interactive planning, sets of optimized plans are created for a variety of treatment delivery options and critical structure dose-volume constraints. Then, the dose-volume parameters of the optimized plans are fit to linear functions. These linear functions are used to show in real time how the target dose-volume histogram (DVH) changes as the DVHs of the critical structures are changed interactively. A bitmap of the space of optimized plans is used to restrict the feasible solutions. The physician selects the critical structure dose-volume constraints that give the desired dose to the planning target volume (PTV) and then those constraints are used to create the corresponding optimized plan.

RESULTS

The method is demonstrated using prototype software, Treatment Plan Explorer (TPEx), and a clinical example of a patient with a tumor in the right lung. For this example, the delivery options included 4 open beams, 12 open beams, 4 wedged beams, and 12 wedged beams. Beam directions and relative weights were optimized for a range of critical structure dose-volume constraints for the lungs and esophagus. Cord dose was restricted to 45 Gy. Using the interactive interface, the physician explored how the tumor dose changed as critical structure dose-volume constraints were tightened or relaxed and selected the best compromise for each delivery option. The corresponding treatment plans were calculated and compared with the linear parameterization presented to the physician in TPEx. The linear fits were best for the maximum PTV dose and worst for the minimum PTV dose. Based on the root-mean-square error between the fit values and their corresponding data values, the linear fit appears to be adequate, although higher order polynomials could give better results. Some of the variance in fit is due to the stochastic nature of the simulated annealing optimization algorithm, which does not reproduce the exact same results in repetitions of the same calculation. Using a directed search algorithm for plan optimization should produce better parameter fits and, therefore, better predictions of plan characteristics by TPEx.

CONCLUSIONS

Using TPEx, the physician can easily select the optimum plan for a patient, with no imposed arbitrary definition of the "best" plan. More importantly, the physician can readily see what can be achieved for the patient with a given delivery technique. There is no more uncertainty about whether or not a better plan exists. By comparing the "best" plans for different delivery options (e.g., three-dimensional conformal radiotherapy versus intensity-modulated radiation therapy), the physician can gauge the clinical benefits of greater technical complexity. However, before the TPEx process can be clinical useful, faster computers and/or algorithms are needed and more studies are needed to better model the spaces of optimized solutions.

Prediction of radiation-induced normal tissue complications in radiotherapy using functional image data

The aim of this study has been to explicitly include the functional heterogeneity of an organ as a factor that contributes to the probability of complication of normal tissues following radiotherapy. Situations for which the inclusion of this information can be advantageous to the design of treatment plans are then investigated. A Java program has been implemented for this purpose. This makes use of a voxelated model of a patient, which is based on registered anatomical and functional data in order to enable functional voxel weighting. Using this model, the functional dose-volume histogram (fDVH) and the functional normal tissue complication probability (fNTCP) are then introduced as extensions to the conventional dose-volume histogram (DVH) and normal tissue complication probability (NTCP). In the presence of functional heterogeneity, these tools are physically more meaningful for plan evaluation than the traditional indices, as they incorporate additional information and are anticipated to show a better correlation with outcome. New parameters m(f), n(f) and TD(50f) are required to replace the m, n and TD(50) parameters. A range of plausible values was investigated, awaiting fitting of these new parameters to patient outcomes where functional data have been measured. As an example, the model is applied to two lung datasets utilizing accurately registered computed tomography (CT) and single photon emission computed tomography (SPECT) perfusion scans. Assuming a linear perfusion-function relationship, the biological index mean perfusion weighted lung dose (MPWLD) has been extracted from integration over outlined regions of interest. In agreement with the MPWLD ranking, the fNTCP predictions reveal that incorporation of functional imaging in radiotherapy treatment planning is most beneficial for organs with a large volume effect and large focal areas of dysfunction. There is, however, no additional advantage in cases presenting with homogeneous function. Although presented for lung radiotherapy, this model is general. It can also be applied to positron emission tomography (PET)-CT or functional magnetic resonance imaging (fMRI)-CT registered data and extended to the functional description of tumour control probability.

Feasibility study of beam orientation class-solutions for prostate IMRT

IMRT is being increasingly used for treatment of prostate cancer. In practice, however, the beam orientations used for the treatments are still selected empirically, without any guideline. The purpose of this work was to investigate interpatient variation of the optimal beam configuration and to facilitate intensity modulated radiation therapy (IMRT) prostate treatment planning by proposing a set of beam orientation class-solutions for a range of numbers of incident beams. We used fifteen prostate cases to generate the beam orientation class-solutions. For each patient and a given number of incident beams, a multiobjective optimization engine was employed to provide optimal beam directions. For the fifteen cases considered, the gantry angle of any of the optimized plans were all distributed within a certain range The angular distributions of the optimal beams were analyzed and the most selected directions are identified as optimal directions. The optimal directions for all patients are averaged to obtain the class-solution. The class-solution gantry angles for prostate IMRT were found to be: three beams (0 degrees, 120 degrees, 240 degrees), five beams (35 degrees, 110 degrees, 180 degrees, 250 degrees, 325 degrees), six beams (0 degrees, 60 degrees, 120 degrees, 180 degrees, 240 degrees, 300 degrees), seven beams (25 degrees, 75 degrees, 130 degrees, 180 degrees, 230 degrees, 285 degrees, 335 degrees), eight beams (20 degrees, 70 degrees, 110 degrees, 150 degrees, 200 degrees, 250 degrees, 290 degrees, 340 degrees), and nine beams (20 degrees, 60 degrees, 100 degrees, 140 degrees, 180 degrees, 220 degrees, 260 degrees, 300 degrees, 340 degrees). The level of validity of the class-solutions was tested using an additional clinical prostate case by comparing with the individually optimized beam configurations. The difference between the plans obtained with class-solutions and patient-specific optimizations was found to be clinically insignificant.

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

As an alternative between manual planning and beamlet-based IMRT, we have developed an optimization system for inverse planning with anatomy-based MLC fields. In this system, named Ballista, the orientation (table and gantry), the wedge filter and the field weights are simultaneously optimized for every beam. An interesting feature is that the system is coupled to Pinnacle3 by means of the PinnComm interface, and uses its convolution dose calculation engine. A fully automatic MLC segmentation algorithm is also included. The plan evaluation is based on a quasi-random sampling and on a quadratic objective function with penalty-like constraints. For efficiency, optimal wedge angles and wedge orientations are determined using the concept of the super-omni wedge. A bound-constrained quasi-Newton algorithm performs field weight optimization, while a fast simulated annealing algorithm selects the optimal beam orientations. Moreover, in order to generate directly deliverable plans, the following practical considerations have been incorporated in the system: collision between the gantry and the table as well as avoidance of the radio-opaque elements of a table top. We illustrate the performance of the new system on two patients. In a rhabdomyosarcoma case, the system generated plans improving both the target coverage and the sparing of the parotide, as compared to a manually designed plan. In the second case presented, the system successfully produced an adequate plan for the treatment of the prostate while avoiding both hip prostheses. For the many cases where full IMRT may not be necessary, the system efficiently generates satisfactory plans meeting the clinical objectives, while keeping the treatment verification much simpler.

Application of influence diagrams to prostate intensity-modulated radiation therapy plan selection

The purpose is to incorporate clinically relevant factors such as patient-specific and dosimetric information as well as data from clinical trials in the decision-making process for the selection of prostate intensity-modulated radiation therapy (IMRT) plans. The approach is to incorporate the decision theoretic concept of an influence diagram into the solution of the multiobjective optimization inverse planning problem. A set of candidate IMRT plans was obtained by varying the importance factors for the planning target volume (PTV) and the organ-at-risk (OAR) in combination with simulated annealing to explore a large part of the solution space. The Pareto set for the PTV and OAR was analysed to demonstrate how the selection of the weighting factors influenced which part of the solution space was explored. An influence diagram based on a Bayesian network with 18 nodes was designed to model the decision process for plan selection. The model possessed nodes for clinical laboratory results, tumour grading, staging information, patient-specific information, dosimetric information, complications and survival statistics from clinical studies. A utility node was utilized for the decision-making process. The influence diagram successfully ranked the plans based on the available information. Sensitivity analyses were used to judge the reasonableness of the diagram and the results. In conclusion, influence diagrams lend themselves well to modelling the decision processes for IMRT plan selection. They provide an excellent means to incorporate the probabilistic nature of data and beliefs into one model. They also provide a means for introducing evidence-based medicine, in the form of results of clinical trials, into the decision-making process.

Verification of inverse planning and treatment delivery for segmental IMRT

With intensity‐modulated radiotherapy (IMRT), it is important that the inverse planning process yields the most appropriate dose distribution for the patient and that the delivered dose then corresponds to the planned dose. This paper presents methods by which the inverse planning and delivery of segmental (step‐and‐shoot) IMRT can be verified, and gives results for a typical treatment planning system (Pinnacle³ v6.2b, Philips Radiation Oncology Systems, Milpitas, CA). Inverse planning was assessed by observing the reduction in objective function as fields were successively added to three‐field prostate, esophagus, and thyroid plans. The ability of the treatment planning system to calculate dose for a segmented field was examined by creating a stepped field with five successively narrowing segments. The complete planning process was then investigated by using two orthogonal IMRT fields to create a homogeneous dose distribution in a cubic water phantom. Finally, a clinical situation was simulated by creating a five‐field segmental IMRT plan for a lung target in an anthropomorphic phantom. A conformal plan was also compared for context. Addition of fields to inverse plans generally resulted in a reduction of objective function, indicating consistency of inverse planning solutions. Planned dose for fields with stepped intensity agreed with ionization chamber measurements to within 5%. For orthogonal fields, planned dose distributions agreed well with dose measured using film and agreed with ionization chamber measurements to within 3%. For the anthropomorphic phantom, the standard deviation of difference between planned and measured dose was 4%. Although no consensus has yet been reached on what constitutes an acceptable IMRT plan, these results indicate that step‐and‐shoot IMRT can be planned and delivered using the system described with comparable accuracy to a standard conformal treatment.

PACS numbers: 87.53.Dq, 87.53.Kn, 87.53.Mr, 87.53.Tf, 87.53.Xd

Segmentation of IMRT plans for radical lung radiotherapy delivery with the step-and-shoot technique

The purpose of this work was to determine a segmentation protocol for the treatment of localized non-small-cell lung cancer (NSCLC) with intensity-modulated radiotherapy (IMRT) that is as effective as possible while practically simple and hence robust to known practical inaccuracies. This study focused on the stratification of continuous profiles into a discrete number of intensity levels. The selection of the segmentation parameters for the delivery of the fluence profiles using multiple static fields has been considered. Five-field equispaced IMRT treatment plans of five patients with NSCLC were selected. The study comprised nine treatment plans for each patient, starting from a conformal plan, optimizing it for IMRT and then segmenting it utilizing different numbers of segments in each case and optimizing for segment weights separately. A conformal plan, optimized for beam directions, collimator and wedge angles, was also used for comparison with the IMRT plans, so as to consider the best coplanar conformal case. A dose objective for the PTV and the organs-at-risk plus a constraint for the spinal cord were set for all inverse plans. All stages were compared with the aid of dose-volume histograms, dose distributions at the plane of the isocenter, intensity maps for key beams and plots of PTV homogeneity and overall conformality versus complexity. The unsegmented IMRT plans gave the best results but cannot be realized in practice with an MLC. They were best approximated by plans that needed 106-167 segments to deliver, but did not deteriorate significantly when approximated by plans which required 26-40 segments in total. All segmented IMRT plans gave a better lung sparing than the conformal plans, indicating that the deterioration of IMRT plans following segmentation is not equivalent to that of unmodulated, conformal plans. However, optimized conformal plans have the potential to approach the lung sparing achieved by segmented IMRT plans. Among the IMRT situations examined, five-field treatment plans for the lung, utilizing a maximum of 40 segments in total, have proven to give a good approximation of the IMRT plans with continuous modulation.

Multiobjective evolutionary optimization of the number of beams, their orientations and weights for intensity-modulated radiation therapy

We propose a hybrid multiobjective (MO) evolutionary optimization algorithm (MOEA) for intensity-modulated radiotherapy inverse planning and apply it to optimize the number of incident beams, their orientations and intensity profiles. The algorithm produces a set of efficient solutions, which represent different clinical trade-offs and contains information such as variety of dose distributions and dose-volume histograms. No importance factors are required and solutions can be obtained in regions not accessible by conventional weighted sum approaches. The application of the algorithm using a test case, a prostate and a head and neck tumour case is shown. The results are compared with MO inverse planning using a gradient-based optimization algorithm.