Incorporating multi-leaf collimator leaf sequencing into iterative IMRT optimization

Multi-level multi-leaf collimators: optimization of layer thicknesses and a feasibility study

PURPOSE

The function of multi-leaf collimators (MLC) is to modulate and shape the intensity of a radiotherapy beam by either blocking or unblocking beamlets. A variation on this functionality is tested in this work wherein the MLC is split into layers, with each layer attenuating the beam by a different amount. In this design, full blocking of a beamlet occurs only if all layers are blocked. This work suggests that such a device, a multi-layer MLC (MLMLC), can deliver dose distributions like a single layer MLC can deliver while requiring less time and monitor units (MU) .

METHODS

Optimal fluences were made for prostate plans using the Eclipse v13.6. An algorithm was developed to create step-and-shoot MLMLC patterns to match these optimal fluences when using up to six layers of MLC. Twelve MLMLC plans were made in total. These patterns were imported back into Eclipse as equivalent tungsten compensators and doses were calculated. Dose volume histogram (DVH) values, total monitor units (MU), and total time to deliver were compared between arc-style MLMLC plans and nine-field step and shoot IMRT plans created completely in Eclipse using a single layer MLC .

RESULTS

When using three or more layers, specified DVH values between the two sets agreed to within 5% while requiring roughly half as much time to deliver and about 20% fewer MU .

CONCLUSIONS

Demonstrated that having multi-layer MLC can deliver dose distributions like a single layer MLC with less time and monitor units. This article is protected by copyright. All rights reserved.

An atlas-guided automatic planning approach for rectal cancer intensity-modulated radiotherapy

We try to develop an atlas-guided automatic planning (AGAP) approach and evaluate its feasibility and performance in rectal cancer intensity-modulated radiotherapy. The developed AGAP approach consisted of four independent modules: patient atlas, similar patient retrieval, beam morphing (BM), and plan fine-tuning (PFT) modules. The atlas was setup using anatomy and plan data from Pinnacle auto-planning (P-auto) plans. Given a new patient, the retrieval function searched the top similar patient by a generic Fourier descriptor algorithm and retrieved its plan information. The BM function generated an initial plan for the new patient by morphing the beam aperture from the top similar patient plan. The beam aperture and calculated dose of the initial plan were used to guide the new plan optimization in the PFT function. The AGAP approach was tested on 96 patients by the leave-one-out validation and plan quality was compared with the P-auto plans. The AGAP and P-auto plans had no statistical difference for target coverage and dose homogeneity in terms ofV_100%(p = 0.76) and homogeneity index (p = 0.073), respectively. The CI index showed they had a statistically significant difference. But the ΔCI was both 0.02 compared to the perfect CI index of 1. The AGAP approach reduced the bladder mean dose by 152.1 cGy (p < 0.05) andV₅₀by 0.9% (p < 0.05), and slightly increased the left and right femoral head mean dose by 70.1 cGy (p < 0.05) and 69.7 cGy (p < 0.05), respectively. This work developed an efficient and automatic approach that could fully automate the IMRT planning process in rectal cancer radiotherapy. It reduced the plan quality dependence on the planner experience and maintained the comparable plan quality with P-auto plans.

Define dose field to assess the modulation complexity of intensity-modulated radiation therapy

PURPOSE

Introduce a new concept of dose field to assess the modulation complexity (MC) of intensity-modulated radiation therapy (IMRT).

METHODS

A total of 91 IMRT plans for different diseases were retrospectively retrieved randomly from treatment database. The dose field of plans were calculated and feature values such as force magnitude and diversity were defined and extracted. Correlation analysis between these feature values and execution cost, delivery accuracy of plans was performed, to verify the validity of dose field in characterizing the MC.

RESULTS

The feature values of dose field in different disease own significant differences (p < 0.001). For correlation analysis, number of control point (CP) and cumulative perimeter of CP have the highest correlation with angle entropy (0.815 and 0.848 respectively), while the correlation between number of monitor units(MU), cumulative area of CP and force, force entropy is higher than others (0.797-0.909). However, complexity of CP shape is almost irrelevant to all the dose field features. The gamma passing rate and the dose field features shows a weak negative correlation trend.

CONCLUSIONS

Dose field can be used as a tool to assess the MC of IMRT.

Estimation of monitor unit through analytical method for dynamic IMRT using control points as an effective parameter

Introduction:

The control points (CP) play a significant role in the delivery of segmented based Intensity-Modulated Radiation Therapy (IMRT) delivery, particularly in dynamic mode. The number of segments is determined by control points and these segments will transfer from one to the other either during beam ON called dynamic delivery or during beam OFF called static delivery or step and shoot. This study was aimed at indirect estimation of the total monitor units (MU) to be delivered per field by exploiting the control points and also to find the MUs at any nth segment.

Materials and methods:

This study was performed in the Eclipse treatment planning software version 13.8.0. The details of control points, metre set weight per segment, leaf positions for each segment, field size, etc. were taken into consideration.

Results:

TPS calculated MU value and analytically estimated MU value were compared and the percentage of difference was estimated. The overall mean percentage of deviation was 1·03% between the TPS calculated method and the analytical method. The paired sample t-test was performed and, p-value <0·05, no significant difference was found. The analytical relationship determined to estimate the total number of MU delivered for any nth control point was also evaluated.

Conclusion:

The control points are a potential parameter in the conventional IMRT delivery. Through this study, we have addressed the indirect method to estimate the monitor units delivered per segment.

Rapid direct aperture optimization via dose influence matrix based piecewise aperture dose model

In the traditional two-step procedure used in intensity-modulated radiation therapy, fluence map optimization (FMO) is performed first, followed by use of a leaf sequencing algorithm (LSA). By contrast, direct aperture optimization (DAO) directly optimizes aperture leaf positions and weights. However, dose calculation using the Monte Carlo (MC) method for DAO is often time-consuming. Therefore, a rapid DAO (RDAO) algorithm is proposed that uses a dose influence matrix based piecewise aperture dose model (DIM-PADM). In the proposed RDAO algorithm, dose calculation is based on the dose influence matrix instead of MC. The dose dependence of aperture leafs is modeled as a piecewise function using the DIM. The corresponding DIM-PADM-based DAO problem is solved using a simulated annealing algorithm.The proposed algorithm was validated through application to TG119, prostate, liver, and head and neck (H&N) cases from the common optimization for radiation therapy dataset. Compared with the two-step FMO–LSA procedure, the proposed algorithm resulted in more precise dose conformality in all four cases. Specifically, for the H&N dataset, the cost value for the planned target volume (PTV) was decreased by 32%, whereas the cost value for the two organs at risk (OARs) was decreased by 60% and 92%. Our study of the proposed novel DIM-PADM-based RDAO algorithm makes two main contributions: First, we validate the use of the proposed algorithm, in contrast to the FMO–LSA framework, for direct optimization of aperture leaf positions and show that this method results in more precise dose conformality. Second, we demonstrate that compared to MC, the DIM-PADM-based method significantly reduces the computational time required for DAO.

Integral Dose-Based Inverse Optimization May Reduce Side Effects in Radiotherapy of Prostate Carcinoma

PURPOSE

The purpose of this work is to apply a novel inverse optimization approach, based on utilization of quantitative imaging information in the optimization function, to prostate carcinoma.

MATERIALS AND METHODS

This new inverse optimization algorithm relies upon quantitative information derived from computed tomography (CT) imaging studies. The Hounsfield numbers of the CT voxels are converted to physical density, which in turn is used to calculate voxel mass and the corresponding integral dose, by summation over the product of dose and mass in each dose voxel. This integral dose is used for plan optimization through its global minimization. The optimization results are compared to the optimization results derived from most commonly used dose-volume-based inverse optimization, where objective functions are formed as summation over all dose voxels of the squared differences between voxel doses and user specified doses. The data from 25 prostate plans were optimized with dose-volume histogram (DVH) and integral dose (energy) minimization objective functions. The results obtained with the energy- and DVH-based optimization schemes were studied through commonly used dosimetric indices (DIs). Statistical equivalence tests were further performed to establish population-based significance results.

RESULTS

Both DVH- and energy-based plans for each case were normalized so that 95% of the planning target volume receives the prescription dose. The average differences for the rectum and bladder DIs ranged from 1.6 to 25%, where the energy-based quantities were lower. For both femoral heads, the energy-based optimization-derived doses were lower on average by 32%. The statistical tests demonstrated that the significant differences in the tallied dose indices range from 2.7% to more than 50% for rectum, bladder, and femoral heads.

CONCLUSION

For majority of the clinically relevant dosimetric quantities, energy-based inverse optimization performs better than the standard of care DVH-based optimization in prostate carcinoma. The population averaged statistically significant differences range from ~3 to ~50%. Therefore, this newly proposed optimization approach, incorporating explicitly quantitative imaging information in the inverse optimization function, holds potential for further reduction of complication rates in prostate cancer.

An empirical method for automatic determination of maximum number of segments in DMPO-based IMRT for Head and Neck cases

AIM

An empirical scheme called "anatomy-guided segment counting (AGSC)" is proposed for automatic selection of maximum number of segments (NOS) for direct machine parameter optimization (DMPO).

BACKGROUND

Direct machine parameter optimization (DMPO) requires the user to define the maximum number of segments (NOS) in order to proceed with an optimization process. Till date there is no established approach to arrive at an optimal and case-specific maximum NOS in DMPO, and this step is largely left to the planner's experience.

MATERIALS AND METHODS

The AGSC scheme basically uses the Beam's-eye views (BEVs) and other planning parameters to decide on appropriate number of segments for the beam. The proposed algorithm was tested in eight H&N cases. We used Auto Plan feature available in Pinnacle3 (version 9.10.0) for driving the DMPO optimization.

RESULTS

There is about 13% reduction in the composite objective value in AGSC plans as compared to the plans employing 6 NOS per beam and 10% increase in the composite objective value in AGSC plans as compared to the plans employing 8 NOS per beam. On the delivery efficiency front, there is about 10% increase in NOS in AGSC plans as compared to the plans employing 6 NOS per beam specification. Similarly, there is about 19% reduction in NOS in AGSC plans as compared to the plans employing 8 NOS per beam specification.

CONCLUSION

The study demonstrates that the AGSC method allows specifying appropriate number of segments into the DMPO module accounting for the complexity of a given case.

New approach in lung cancer radiotherapy offers better normal tissue sparing

PURPOSE

Medical images are more than pictures. They contain additional quantitative information which can be interrogated, quantified, and utilized. Besides anatomical information computed tomography (CT) imaging data provide electron density information. Radiotherapy use of this density information is limited to its application only in dose calculations. The direct product of dose, density, and volume forms a quantity called integral dose. The integral dose delivered to a volume of interest is the total energy deposited in that volume. Here it is hypothesized that minimization of the integral dose is advantageous in radiotherapy planning. The purpose of this work is to study the incorporation of quantitative imaging information in radiotherapy inverse optimization through total energy minimization (Energy hereafter).

DESIGN

Twenty lung patient plans were studied. For each patient density was quantified on voxel-by-voxel basis through image gray value-to-density conversion curves. Energy-based objective function was used for inverse radiotherapy plan optimization. The obtained plans were evaluated in the light of current standard of care, based on dose-volume (DVH) optimization approach.

RESULTS

The statistical significance analyses of the results indicated that the doses to normal tissue were between 14% and 45% lower, when Energy-based optimization was used instead of DVH-based optimization.

CONCLUSION

Incorporation of quantitative imaging information, through CT derived density, in the optimization cost function allows reduction of dose to normal tissue for NSCLC cases. Energy-based radiotherapy plans result in lower normal tissue dose and potentially lower complication rates compared to standard of care.

Dose domain regularization of MLC leaf patterns for highly complex IMRT plans

PURPOSE

The advent of automated beam orientation and fluence optimization enables more complex intensity modulated radiation therapy (IMRT) planning using an increasing number of fields to exploit the expanded solution space. This has created a challenge in converting complex fluences to robust multileaf collimator (MLC) segments for delivery. A novel method to regularize the fluence map and simplify MLC segments is introduced to maximize delivery efficiency, accuracy, and plan quality.

METHODS

In this work, we implemented a novel approach to regularize optimized fluences in the dose domain. The treatment planning problem was formulated in an optimization framework to minimize the segmentation-induced dose distribution degradation subject to a total variation regularization to encourage piecewise smoothness in fluence maps. The optimization problem was solved using a first-order primal-dual algorithm known as the Chambolle-Pock algorithm. Plans for 2 GBM, 2 head and neck, and 2 lung patients were created using 20 automatically selected and optimized noncoplanar beams. The fluence was first regularized using Chambolle-Pock and then stratified into equal steps, and the MLC segments were calculated using a previously described level reducing method. Isolated apertures with sizes smaller than preset thresholds of 1-3 bixels, which are square units of an IMRT fluence map from MLC discretization, were removed from the MLC segments. Performance of the dose domain regularized (DDR) fluences was compared to direct stratification and direct MLC segmentation (DMS) of the fluences using level reduction without dose domain fluence regularization.

RESULTS

For all six cases, the DDR method increased the average planning target volume dose homogeneity (D95/D5) from 0.814 to 0.878 while maintaining equivalent dose to organs at risk (OARs). Regularized fluences were more robust to MLC sequencing, particularly to the stratification and small aperture removal. The maximum and mean aperture sizes using the DDR were consistently larger than those from DMS for all tested number of segments.

CONCLUSIONS

The fluence map to MLC segmentation conversion problem was formulated as a secondary optimization problem in the dose domain to minimize the smoothness-regularized dose discrepancy. The large scale optimization problem was solved using a primal-dual algorithm that transformed complicated fluences into maps that were more robust to the MLC segmentation and sequencing, affording fewer and larger segments with minimal degradation to dose distribution.

Dose-mass inverse optimization for minimally moving thoracic lesions

In the past decade, several different radiotherapy treatment plan evaluation and optimization schemes have been proposed as viable approaches, aiming for dose escalation or an increase of healthy tissue sparing. In particular, it has been argued that dose-mass plan evaluation and treatment plan optimization might be viable alternatives to the standard of care, which is realized through dose-volume evaluation and optimization. The purpose of this investigation is to apply dose-mass optimization to a cohort of lung cancer patients and compare the achievable healthy tissue sparing to that one achievable through dose-volume optimization. Fourteen non-small cell lung cancer (NSCLC) patient plans were studied retrospectively. The range of tumor motion was less than 0.5 cm and motion management in the treatment planning process was not considered. For each case, dose-volume (DV)-based and dose-mass (DM)-based optimization was performed. Nine-field step-and-shoot IMRT was used, with all of the optimization parameters kept the same between DV and DM optimizations. Commonly used dosimetric indices (DIs) such as dose to 1% the spinal cord volume, dose to 50% of the esophageal volume, and doses to 20 and 30% of healthy lung volumes were used for cross-comparison. Similarly, mass-based indices (MIs), such as doses to 20 and 30% of healthy lung masses, 1% of spinal cord mass, and 33% of heart mass, were also tallied. Statistical equivalence tests were performed to quantify the findings for the entire patient cohort. Both DV and DM plans for each case were normalized such that 95% of the planning target volume received the prescribed dose. DM optimization resulted in more organs at risk (OAR) sparing than DV optimization. The average sparing of cord, heart, and esophagus was 23, 4, and 6%, respectively. For the majority of the DIs, DM optimization resulted in lower lung doses. On average, the doses to 20 and 30% of healthy lung were lower by approximately 3 and 4%, whereas lung volumes receiving 2000 and 3000 cGy were lower by 3 and 2%, respectively. The behavior of MIs was very similar. The statistical analyses of the results again indicated better healthy anatomical structure sparing with DM optimization. The presented findings indicate that dose-mass-based optimization results in statistically significant OAR sparing as compared to dose-volume-based optimization for NSCLC. However, the sparing is case-dependent and it is not observed for all tallied dosimetric endpoints.

Beam geometry selection using sequential beam addition

PURPOSE

The selection of optimal beam geometry has been of interest since the inception of conformal radiotherapy. The authors report on sequential beam addition, a simple beam geometry selection method, for intensity modulated radiation therapy.

METHODS

The sequential beam addition algorithm (SBA) requires definition of an objective function (score) and a set of candidate beam geometries (pool). In the first iteration, the optimal score is determined for each beam in the pool and the beam with the best score selected. In the next iteration, the optimal score is calculated for each beam remaining in the pool combined with the beam selected in the first iteration, and the best scoring beam is selected. The process is repeated until the desired number of beams is reached. The authors selected three treatment sites, breast, lung, and brain, and determined beam arrangements for up to 11 beams from a pool comprised of 25 equiangular transverse beams. For the brain, arrangements were additionally selected from a pool of 22 noncoplanar beams. Scores were determined for geometries comprised equiangular transverse beams (EQA), as well as two tangential beams for the breast case.

RESULTS

In all cases, SBA resulted in scores superior to EQA. The breast case had the strongest dependence on beam geometry, for which only the 7-beam EQA geometry had a score better than the two tangential beams, whereas all SBA geometries with more than two beams were superior. In the lung case, EQA and SBA scores monotonically improved with increasing number of beams; however, SBA required fewer beams to achieve scores equivalent to EQA. For the brain case, SBA with a coplanar pool was equivalent to EQA, while the noncoplanar pool resulted in slightly better scores; however, the dose-volume histograms demonstrated that the differences were not clinically significant.

CONCLUSIONS

For situations in which beam geometry has a significant effect on the objective function, SBA can identify arrangements equivalent to equiangular geometries but using fewer beams. Furthermore, SBA provides the value of the objective function as the number of beams is increased, allowing the planner to select the minimal beam number that achieves the clinical goals. The method is simple to implement and could readily be incorporated into an existing optimization system.

Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity-modulated proton therapy treatment planning

The purpose of this study is to investigate the feasibility and impact of incorporating deliverable monitor unit (MU) constraints into spot intensity optimization (SIO) in intensity-modulated proton therapy (IMPT) treatment planning. The current treatment planning system (TPS) for IMPT disregards deliverable MU constraints in the SIO routine. It performs a post-processing procedure on an optimized plan to enforce deliverable MU values that are required by the spot scanning proton delivery system. This procedure can create a significant dose distribution deviation between the optimized and post-processed deliverable plans, especially when small spot spacings are used. In this study, we introduce a two-stage linear programming approach to optimize spot intensities and constrain deliverable MU values simultaneously, i.e., a deliverable SIO (DSIO) model. Thus, the post-processing procedure is eliminated and the associated optimized plan deterioration can be avoided. Four prostate cancer cases at our institution were selected for study and two parallel opposed beam angles were planned for all cases. A quadratic programming based model without MU constraints, i.e., a conventional SIO (CSIO) model, was also implemented to emulate commercial TPS. Plans optimized by both the DSIO and CSIO models were evaluated for five different settings of spot spacing from 3 to 7 mm. For all spot spacings, the DSIO-optimized plans yielded better uniformity for the target dose coverage and critical structure sparing than did the CSIO-optimized plans. With reduced spot spacings, more significant improvements in target dose uniformity and critical structure sparing were observed in the DSIO than in the CSIO-optimized plans. Additionally, better sparing of the rectum and bladder was achieved when reduced spacings were used for the DSIO-optimized plans. The proposed DSIO approach ensures the deliverability of optimized IMPT plans that take into account MU constraints. This eliminates the post-processing procedure required by the TPS as well as the resultant deteriorating effect on ultimate dose distributions. This approach therefore allows IMPT plans to adopt all possible spot spacings optimally. Moreover, dosimetric benefits can be achieved using smaller spot spacings.

Independent calculation-based verification of IMRT plans using a 3D dose-calculation engine

Independent monitor unit verification of intensity-modulated radiation therapy (IMRT) plans requires detailed 3-dimensional (3D) dose verification. The aim of this study was to investigate using a 3D dose engine in a second commercial treatment planning system (TPS) for this task, facilitated by in-house software. Our department has XiO and Pinnacle TPSs, both with IMRT planning capability and modeled for an Elekta-Synergy 6MV photon beam. These systems allow the transfer of computed tomography (CT) data and RT structures between them but do not allow IMRT plans to be transferred. To provide this connectivity, an in-house computer programme was developed to convert radiation therapy prescription (RTP) files as generated by many planning systems into either XiO or Pinnacle IMRT file formats. Utilization of the technique and software was assessed by transferring 14 IMRT plans from XiO and Pinnacle onto the other system and performing 3D dose verification. The accuracy of the conversion process was checked by comparing the 3D dose matrices and dose volume histograms (DVHs) of structures for the recalculated plan on the same system. The developed software successfully transferred IMRT plans generated by 1 planning system into the other. Comparison of planning target volume (TV) DVHs for the original and recalculated plans showed good agreement; a maximum difference of 2% in mean dose, - 2.5% in D95, and 2.9% in V95 was observed. Similarly, a DVH comparison of organs at risk showed a maximum difference of +7.7% between the original and recalculated plans for structures in both high- and medium-dose regions. However, for structures in low-dose regions (less than 15% of prescription dose) a difference in mean dose up to +21.1% was observed between XiO and Pinnacle calculations. A dose matrix comparison of original and recalculated plans in XiO and Pinnacle TPSs was performed using gamma analysis with 3%/3mm criteria. The mean and standard deviation of pixels passing gamma tolerance for XiO-generated IMRT plans was 96.1 ± 1.3, 96.6 ± 1.2, and 96.0 ± 1.5 in axial, coronal, and sagittal planes respectively. Corresponding results for Pinnacle-generated IMRT plans were 97.1 ± 1.5, 96.4 ± 1.2, and 96.5 ± 1.3 in axial, coronal, and sagittal planes respectively.

Relationship of segment area and monitor unit efficiency in aperture-based IMRT optimization

In step‐and‐shoot IMRT plans, aperture‐based optimization (or one‐step optimization) has been considered as a means of improving monitor unit (MU) efficiency compared to fluence‐based optimization (or two‐step optimization). However, the extent of improvement on MU efficiency varies, depending on the implementation and design of one‐step optimization. In this paper, we attempted to investigate MU efficiency issue in two methods of one‐step optimization implemented in two commercial treatment planning systems (TPSs). Five patients with nasopharyngeal cancer and five patients with advanced prostate cancer were selected for this study. For these patients, clinically used IMRT plans were generated using the Direct Machine Parameter Optimization (DMPO) in the Pinnacle TPS. New IMRT plans were created using the Direct Aperture Optimization (DAO) method in the Panther TPS. For the purpose of this study, we used the similar planning dose objectives and beam configurations with a similar total number of segments in each pair of DMPO and DAO plans. With similar plan quality, DMPO plans required more MUs than DAO plans. The average number of MUs (expressed in mean ±1 SD) for the DMPO and DAO plans was 1,169±186 and 671±135 for the nasopharynx cases, and 711±48 and 400±65 for the prostate cases, respectively. The average segment areas (expressed in mean ±1 SD) for the DMPO plans were smaller than those for the DAO plans: 46.0±7.6 cm2 vs. 100.9±32.3 cm2 for the nasopharynx cases, and 58.3±17.2 cm2 vs. 97.4±35.0 cm2 for the prostate cases, respectively. In conclusion, two one‐step optimization algorithms, DMPO and DAO, resulted in much different MU efficiency with the similar number of segments and optimization parameters. This MU difference is largely attributed to the fact that large area segments are used more often in DAO plans than in DMPO plans.

PACS number: 87.55.de

Helical tomotherapy setup variations in canine nasal tumor patients immobilized with a bite block

The purpose of our study was to compare setup variation in four degrees of freedom (vertical, longitudinal, lateral, and roll) between canine nasal tumor patients immobilized with a mattress and bite block, versus a mattress alone. Our secondary aim was to define a clinical target volume (CTV) to planning target volume (PTV) expansion margin based on our mean systematic error values associated with nasal tumor patients immobilized by a mattress and bite block. We evaluated six parameters for setup corrections: systematic error, random error, patient-patient variation in systematic errors, the magnitude of patient-specific random errors (root mean square [RMS]), distance error, and the variation of setup corrections from zero shift. The variations in all parameters were statistically smaller in the group immobilized by a mattress and bite block. The mean setup corrections in the mattress and bite block group ranged from 0.91 mm to 1.59 mm for the translational errors and 0.5°. Although most veterinary radiation facilities do not have access to Image-guided radiotherapy (IGRT), we identified a need for more rigid fixation, established the value of adding IGRT to veterinary radiation therapy, and define the CTV-PTV setup error margin for canine nasal tumor patients immobilized in a mattress and bite block.

The effect of gantry spacing resolution on plan quality in a single modulated arc optimization

Volumetric‐modulated arc technique (VMAT) is an efficient form of IMRT delivery. It is advantageous over conventional IMRT in terms of treatment delivery time. This study investigates the relation between the number of segments and plan quality in VMAT optimization for a single modulated arc. Five prostate, five lung, and five head‐and‐neck (HN) patient plans were studied retrospectively. For each case, four VMAT plans were generated. The plans differed only in the number of control points used in the optimization process. The control points were spaced 2°, 3°, 4°, and 6° apart, respectively. All of the optimization parameters were the same among the four schemes. The 2° spacing plan was used as a reference to which the other three plans were compared. The plan quality was assessed by comparison of dose indices (DIs) and generalized equivalent uniform doses (gEUDs) for targets and critical structures. All optimization schemes generated clinically acceptable plans. The differences between the majority of reference and compared DIs and gEUDs were within 3%. DIs and gEUDs which differed in excess of 3% corresponded to dose levels well below the organ tolerances. The DI and the gEUD differences increased with an increase in plan complexity from prostates to HNs. Optimization with gantry spacing resolution of 4° seems to be a very balanced alternative between plan quality and plan complexity.

PACS number: 87.55.de

Impact of four-dimensional computed tomography pulmonary ventilation imaging-based functional avoidance for lung cancer radiotherapy

PURPOSE

To quantify the dosimetric impact of four-dimensional computed tomography (4D-CT) pulmonary ventilation imaging-based functional treatment planning that avoids high-functional lung regions.

METHODS AND MATERIALS

4D-CT ventilation images were created from 15 non-small-cell lung cancer patients using deformable image registration and quantitative analysis of the resultant displacement vector field. For each patient, anatomic and functional plans were created for intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). Consistent beam angles and dose-volume constraints were used for all cases. The plans with Radiation Therapy Oncology Group (RTOG) 0617-defined major deviations were modified until clinically acceptable. Functional planning spared the high-functional lung, and anatomic planning treated the lungs as uniformly functional. We quantified the impact of functional planning compared with anatomic planning using the two- or one-tailed t test.

RESULTS

Functional planning led to significant reductions in the high-functional lung dose, without significantly increasing other critical organ doses, but at the expense of significantly degraded the planning target volume (PTV) conformity and homogeneity. The average reduction in the high-functional lung mean dose was 1.8 Gy for IMRT (p < .001) and 2.0 Gy for VMAT (p < .001). Significantly larger changes occurred in the metrics for patients with a larger amount of high-functional lung adjacent to the PTV.

CONCLUSION

The results of the present study have demonstrated the impact of 4D-CT ventilation imaging-based functional planning for IMRT and VMAT for the first time. Our findings indicate the potential of functional planning in lung functional avoidance for both IMRT and VMAT, particularly for patients who have high-functional lung adjacent to the PTV.

Lung dose for minimally moving thoracic lesions treated with respiration gating

PURPOSE

To evaluate incidental doses to benign lung tissue for patients with minimally moving lung lesions treated with respiratory gating.

METHODS AND MATERIALS

Seventeen lung patient plans were studied retrospectively. Tumor motion was less than 5 mm in all cases. For each patient, mid-ventilation (MidVen) and mid-inhalation (MidInh) breathing phases were reconstructed. The MidInh phase was centered on the end-of-inhale (EOI) phase within a 30% gating window. Planning target volumes, heart, and spinal cord were delineated on the MidVen phase and transferred to the MidInh phase. Lungs were contoured separately on each phase. Intensity-modulated radiotherapy plans were generated on the MidVen phases. The plans were transferred to the MidInh phase, and doses were recomputed. The evaluation metric was based on dose indices, volume indices, generalized equivalent uniform doses, and mass indices for targets and critical structures. Statistical tests were used to establish the significance of the differences between the reference (MidVen) and compared (MidInh) dose distributions.

RESULTS

Statistical tests demonstrated that the indices evaluated for targets, cord, and heart differed by within 2.3%. The index differences in the lungs, however, are in excess of 6%, indicating the potentially achievable lung sparing and/or dose escalation.

CONCLUSIONS

Respiratory gating is a clinical option for patients with minimally moving lung lesions treated at EOI. Gating will be more beneficial for larger tumors, since dose escalation in those cases will result in a larger increase in the tumor control probability.

Calculated organ doses from selected prostate treatment plans using Monte Carlo simulations and an anatomically realistic computational phantom

There is growing concern about radiation-induced second cancers associated with radiation treatments. Particular attention has been focused on the risk to patients treated with intensity-modulated radiation therapy (IMRT) due primarily to increased monitor units. To address this concern we have combined a detailed medical linear accelerator model of the Varian Clinac 2100 C with anatomically realistic computational phantoms to calculate organ doses from selected treatment plans. This paper describes the application to calculate organ-averaged equivalent doses using a computational phantom for three different treatments of prostate cancer: a 4-field box treatment, the same box treatment plus a 6-field 3D-CRT boost treatment and a 7-field IMRT treatment. The equivalent doses per MU to those organs that have shown a predilection for second cancers were compared between the different treatment techniques. In addition, the dependence of photon and neutron equivalent doses on gantry angle and energy was investigated. The results indicate that the box treatment plus 6-field boost delivered the highest intermediate- and low-level photon doses per treatment MU to the patient primarily due to the elevated patient scatter contribution as a result of an increase in integral dose delivered by this treatment. In most organs the contribution of neutron dose to the total equivalent dose for the 3D-CRT treatments was less than the contribution of photon dose, except for the lung, esophagus, thyroid and brain. The total equivalent dose per MU to each organ was calculated by summing the photon and neutron dose contributions. For all organs non-adjacent to the primary beam, the equivalent doses per MU from the IMRT treatment were less than the doses from the 3D-CRT treatments. This is due to the increase in the integral dose and the added neutron dose to these organs from the 18 MV treatments. However, depending on the application technique and optimization used, the required MU values for IMRT treatments can be two to three times greater than 3D CRT. Therefore, the total equivalent dose in most organs would be higher from the IMRT treatment compared to the box treatment and comparable to the organ doses from the box treatment plus the 6-field boost. This is the first time when organ dose data for an adult male patient of the ICRP reference anatomy have been calculated and documented. The tools presented in this paper can be used to estimate the second cancer risk to patients undergoing radiation treatment.

Direct machine parameter optimization for intensity modulated radiation therapy (IMRT) of oropharyngeal cancer--a planning study

The purpose of the study was to investigate the potential of direct machine parameter optimization (DMPO) to achieve parotid sparing without compromising target coverage in IMRT of oropharyngeal cancer as compared to fluence modulation with subsequent leaf sequencing (IM) and forward planned two‐step arc therapy (IMAT). IMRT plans were generated for 10 oropharyngeal cancer patients using DMPO and IM. The resulting dose volume histograms (DVH) were evaluated with regard to compliance with the dose volume objectives (DVO) and plan quality. DMPO met the DVO for the targets better than IM, but violated the DVO to the parotids in some cases. DMPO provided better target coverage and dose homogeneity than IM and was comparable to IMAT. Dose to the parotids (23Gy) was significantly lower than for IMAT (48Gy), but somewhat higher than for IM (20Gy). Parotid sparing with IM was, however, only achieved at the cost of target coverage and homogeneity. DMPO allows achieving parotid sparing in the treatment of oropharyngeal cancer without compromising target coverage and dose homogeneity in the target as compared to two‐step IMAT. Better overall plan quality can be delivered with less monitor units than with IM.

PACS number: 87.50.Gi

Coverage-based treatment planning: optimizing the IMRT PTV to meet a CTV coverage criterion

This work demonstrates an iterative approach-referred to as coverage-based treatment planning-designed to produce treatment plans that ensure target coverage for a specified percentage of setup errors. In this approach the clinical target volume to planning target volume (CTV-to-PTV) margin is iteratively adjusted until the specified CTV coverage is achieved. The advantage of this approach is that it automatically compensates for the dosimetric margin around the CTV, i.e., the extra margin that is created when the dose distribution extends beyond the PTV. When applied to 27 prostate plans, this approach reduced the average CTV-to-PTV margin from 5 to 2.8 mm. This reduction in PTV size produced a corresponding decrease in the volume of normal tissue receiving high dose. The total volume of tissue receiving > or =65 Gy was reduced on average by 19.3% or about 48 cc. Individual reductions varied from 8.7% to 28.6%. The volume of bladder receiving > or =60 Gy was reduced on average by 5.6% (reductions for individuals varied from 1.7% to 10.6%), and the volume of periprostatic rectum receiving > or =65 Gy was reduced on average by 4.9% (reductions for individuals varied from 0.9% to 12.3%). The iterative method proposed here represents a step toward a probabilistic treatment planning algorithm which can generate dose distributions (i.e., treated volumes) that closely approximate a specified level of coverage in the presence of geometric uncertainties. The general principles of coverage-based treatment planning are applicable to arbitrary treatment sites and delivery techniques. Importantly, observed deviations between coverage implied by specified CTV-to-PTV margins and coverage achieved by a given treatment plan imply a generic need to perform coverage probability analysis on a per-plan basis to ensure that the desired level of coverage is achieved.

Parameter optimization in HN-IMRT for Elekta linacs

Planning and delivery in HN‐IMRT has been challenging for the Elekta linac because of numerous machine limitations. Direct aperture optimization (DAO) algorithms have had success in simplifying the planning process and improving plan quality. Commercial adaptations of DAO allow for widespread use in many clinics; however clinical validation of these methods is still needed. In this work we evaluated Pinnacle³ commercial software for HN‐IMRT on the Elekta linac. The purpose was to find a set of planning parameters that are applicable to most patients and optimal in terms of plan quality, delivery efficiency, and dosimetric accuracy. Four types of plans were created for each of 12 patients: ideal fluence optimization (FO), conventional two‐step optimization (TS), segment weight optimization (SW), and direct machine parameter optimization (DMPO). Maximum number of segments (NS) and minimum segment area (MSA) were varied in DMPO. Results showed DMPO plans have the best optimization scores and dosimetric indices, and the most consistent IMRT output among patients. At larger NS (≥80), plan quality decreases with increasing MSA as expected, except for MSA<8 cm2, suggesting presence of local minima in DMPO. Segment area and MUs can vary significantly between optimization methods and parameter settings; however, the quantity ‘integral MU’ remains constant. Irradiation time is linearly proportional to total plan segments, weakly dependent on MUs and independent of MSA. Dosimetric accuracy is independent of DMPO parameters. The superior quality of DMPO makes it the choice for HN‐IMRT on Elekta linacs and its consistency allows development of ‘class solutions’. However, planners should be aware of the local minima issue when pushing parameters to the limit such as NS<80 and MSA<8 cm2. The optimal set of parameters should be chosen to balance plan quality and delivery efficiency based on a systematic evaluation of the planning technique and system constraints.

PACS number: PACS: 87.55.D, 87.55.de

Pre-segmented 2-Step IMRT with subsequent direct machine parameter optimisation - a planning study

BACKGROUND

Modern intensity modulated radiotherapy (IMRT) mostly uses iterative optimisation methods. The integration of machine parameters into the optimisation process of step and shoot leaf positions has been shown to be successful. For IMRT segmentation algorithms based on the analysis of the geometrical structure of the planning target volumes (PTV) and the organs at risk (OAR), the potential of such procedures has not yet been fully explored. In this work, 2-Step IMRT was combined with subsequent direct machine parameter optimisation (DMPO-Raysearch Laboratories, Sweden) to investigate this potential.

METHODS

In a planning study DMPO on a commercial planning system was compared with manual primary 2-Step IMRT segment generation followed by DMPO optimisation. 15 clinical cases and the ESTRO Quasimodo phantom were employed. Both the same number of optimisation steps and the same set of objective values were used. The plans were compared with a clinical DMPO reference plan and a traditional IMRT plan based on fluence optimisation and consequent segmentation. The composite objective value (the weighted sum of quadratic deviations of the objective values and the related points in the dose volume histogram) was used as a measure for the plan quality. Additionally, a more extended set of parameters was used for the breast cases to compare the plans.

RESULTS

The plans with segments pre-defined with 2-Step IMRT were slightly superior to DMPO alone in the majority of cases. The composite objective value tended to be even lower for a smaller number of segments. The total number of monitor units was slightly higher than for the DMPO-plans. Traditional IMRT fluence optimisation with subsequent segmentation could not compete.

CONCLUSION

2-Step IMRT segmentation is suitable as starting point for further DMPO optimisation and, in general, results in less complex plans which are equal or superior to plans generated by DMPO alone.

Evaluation of dose prediction errors and optimization convergence errors of deliverable-based head-and-neck IMRT plans computed with a superposition/convolution dose algorithm

The purpose of this study is to evaluate dose prediction errors (DPEs) and optimization convergence errors (OCEs) resulting from use of a superposition/convolution dose calculation algorithm in deliverable intensity-modulated radiation therapy (IMRT) optimization for head-and-neck (HN) patients. Thirteen HN IMRT patient plans were retrospectively reoptimized. The IMRT optimization was performed in three sequential steps: (1) fast optimization in which an initial nondeliverable IMRT solution was achieved and then converted to multileaf collimator (MLC) leaf sequences; (2) mixed deliverable optimization that used a Monte Carlo (MC) algorithm to account for the incident photon fluence modulation by the MLC, whereas a superposition/convolution (SC) dose calculation algorithm was utilized for the patient dose calculations; and (3) MC deliverable-based optimization in which both fluence and patient dose calculations were performed with a MC algorithm. DPEs of the mixed method were quantified by evaluating the differences between the mixed optimization SC dose result and a MC dose recalculation of the mixed optimization solution. OCEs of the mixed method were quantified by evaluating the differences between the MC recalculation of the mixed optimization solution and the final MC optimization solution. The results were analyzed through dose volume indices derived from the cumulative dose-volume histograms for selected anatomic structures. Statistical equivalence tests were used to determine the significance of the DPEs and the OCEs. Furthermore, a correlation analysis between DPEs and OCEs was performed. The evaluated DPEs were within +/- 2.8% while the OCEs were within 5.5%, indicating that OCEs can be clinically significant even when DPEs are clinically insignificant. The full MC-dose-based optimization reduced normal tissue dose by as much as 8.5% compared with the mixed-method optimization results. The DPEs and the OCEs in the targets had correlation coefficients greater than 0.71, and there was no correlation for the organs at risk. Because full MC-based optimization results in lower normal tissue doses, this method proves advantageous for HN IMRT optimization.

The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans

Monte Carlo (MC) is rarely used for IMRT plan optimization outside of research centres due to the extensive computational resources or long computation times required to complete the process. Time can be reduced by degrading the statistical precision of the MC dose calculation used within the optimization loop. However, this eventually introduces optimization convergence errors (OCEs). This study determines the statistical noise levels tolerated during MC-IMRT optimization under the condition that the optimized plan has OCEs <100 cGy (1.5% of the prescription dose) for MC-optimized IMRT treatment plans.Seven-field prostate IMRT treatment plans for 10 prostate patients are used in this study. Pre-optimization is performed for deliverable beams with a pencil-beam (PB) dose algorithm. Further deliverable-based optimization proceeds using: (1) MC-based optimization, where dose is recomputed with MC after each intensity update or (2) a once-corrected (OC) MC-hybrid optimization, where a MC dose computation defines beam-by-beam dose correction matrices that are used during a PB-based optimization. Optimizations are performed with nominal per beam MC statistical precisions of 2, 5, 8, 10, 15, and 20%. Following optimizer convergence, beams are re-computed with MC using 2% per beam nominal statistical precision and the 2 PTV and 10 OAR dose indices used in the optimization objective function are tallied. For both the MC-optimization and OC-optimization methods, statistical equivalence tests found that OCEs are less than 1.5% of the prescription dose for plans optimized with nominal statistical uncertainties of up to 10% per beam. The achieved statistical uncertainty in the patient for the 10% per beam simulations from the combination of the 7 beams is ~3% with respect to maximum dose for voxels with D>0.5D(max). The MC dose computation time for the OC-optimization is only 6.2 minutes on a single 3 Ghz processor with results clinically equivalent to high precision MC computations.

What is an acceptably smoothed fluence? Dosimetric and delivery considerations for dynamic sliding window IMRT

Background

The study summarised in this report aimed to investigate the interplay between fluence complexity, dose calculation algorithms, dose calculation spatial resolution and delivery characteristics (monitor units, effective field width and dose delivery against dose prediction agreement) was investigated. A sample set of complex planning cases was selected and tested using a commercial treatment planning system capable of inverse optimisation and equipped with tools to tune fluence smoothness.

Methods

A set of increasingly smoothed fluence patterns was correlated to a generalised expression of the Modulation Index (MI) concept, in nature independent from the specific planning system used that could therefore be recommended as a predictor to score fluence "quality" at a very early stage of the IMRT QA process. Fluence complexity was also correlated to delivery accuracy and characteristics in terms of number of MU, dynamic window width and agreement between calculation and measurement (expressed as percentage of field area with a γ > 1 (%FA)) when comparing calculated vs. delivered modulated dose maps. Different resolutions of the calculation grid and different photon dose algorithms (pencil beam and anisotropic analytical algorithm) were used for the investigations.

Results and Conclusion

i) MI can be used as a reliable parameter to test different approaches/algorithms to smooth fluences implemented in a TPS, and to identify the preferable default values for the smoothing parameters if appropriate tools are implemented; ii) a MI threshold set at MI < 19 could ensure that the planned beams are safely and accurately delivered within stringent quality criteria; iii) a reduction in fluence complexity is strictly correlated to a corresponding reduction in MUs, as well as to a decrease of the average sliding window width (for dynamic IMRT delivery); iv) a smoother fluence results in a reduction of dose in the healthy tissue with a potentially relevant clinical benefit; v) increasing the smoothing parameter s, MI decreases with %FA: fluence complexity has a significant impact on the accuracy of delivery and the agreement between calculation and measurements improves with the advanced algorithms.

Optimal starting gantry angles using equiangular-spaced beams with intensity modulated radiation therapy for prostate cancer on RTOG 0126: A clinical study of 5 and 7 fields

BACKGROUND AND PURPOSE

To investigate the effects of starting gantry angle and number of equiangular-spaced beams for prostate cancer radiotherapy on the Radiation Therapy Oncology Group (RTOG) 0126 protocol using intensity-modulated radiation therapy (IMRT).

MATERIALS AND METHODS

Ten localized prostate cancer patients were prescribed to 79.2Gy in 44 fractions. Static IMRT plans using five and seven equiangular-spaced beams were generated. The starting gantry angles were incremented by 5 degrees resulting in 15 (5 beams) and 11 (7 beams) plans per patient. Constant target coverage was ensured for all plans in order to isolate the variation in the rectal and bladder metrics as a function of starting gantry angle.

RESULTS

The variation with starting gantry angle in rectal metrics using 5 beams was statistically significant (p<0.001) with dosimetric importance. The 5-beam rectal V 75Gy and V 70Gy demonstrated a class solution with a characteristic 'W' pattern and two optimal starting gantry angles near 20 degrees and 50 degrees . Statistically insignificant differences were observed for the bladder metrics using 5 beams. There was little dosimetric variation in the rectal and bladder metrics with 7 beams. Nearly equivalent rectal V 75Gy was achieved between 5 optimal equiangular-spaced beams starting at 20 degrees (class solution) and 7 equiangular-spaced beams starting at 0 degrees for most patients.

CONCLUSIONS

The use of an optimal starting gantry angle for 5 equiangular-spaced beams, as indicated by a class solution in this study, will facilitate rectal sparing and can produce plans that are equivalent to those employing 7 equiangular-spaced beams.

Computational Challenges for Image-Guided Radiation Therapy: Framework and Current Research

It is arguable that the imaging and delivery hardware necessary for delivering real-time adaptive image-guided radiotherapy is available on high-end linear accelerators. Robust and computationally efficient software is the limiting factor in achieving highly accurate and precise radiotherapy to the constantly changing anatomy of a cancer patient. The limitations are not caused by the availability of algorithms but rather issues of reliability, integration, and calculation time. However, each of the software components is an active area of research and development at academic and commercial centers. This article describes the software solutions in 4 broad areas: deformable image registration, adaptive replanning, real-time image guidance, and dose calculation and accumulation. Given the pace of technological advancement, the integration of these software solutions to develop real-time adaptive image-guided radiotherapy and the associated challenges they bring will be implemented to varying degrees by all major manufacturers over the coming years.

Improved stratification algorithms for step-and-shoot MLC delivery in intensity-modulated radiation therapy

In inverse planning for intensity-modulated radiotherapy (IMRT), the fluence distribution of each treatment beam is usually calculated in an optimization process. The delivery of the resulting treatment plan using multileaf collimators (MLCs) is performed either in the step-and-shoot or sliding window technique. For step-and-shoot delivery, the arbitrary beam fluence distributions have to be transformed into an applicable sequence of subsegments. In a stratification step the complexity of the fluence maps is reduced by assigning each beamlet to discrete intensity values, followed by the sequencing step that generates the subsegments. In this work, we concentrate on the stratification for step-and-shoot delivery. Different concepts of stratification are formally introduced. In addition to already used strategies that minimize the difference between original and stratified beam intensities, we propose an original stratification principle that minimizes the error of the resulting dose distribution. It could be shown that for a comparable total number of subsegments the dose-oriented stratification results in a better approximation of the original, unsequenced plan. The presented algorithm can replace the stratification routine in existing sequencer programs and can also be applied to interpolated plans that are generated in an interactive decision making process of multicriteria inverse planning programs.

Performance of a hybrid MC dose algorithm for IMRT optimization dose evaluation

This paper presents a hybrid intensity modulated radiation therapy (IMRT) optimization strategy which combines the speed of pencil beam (PB) and the accuracy of Monte Carlo (MC) dose calculations. After an initial deliverable-based optimization using a PB algorithm, doses are recomputed using the VMC++ MC code to determine dose correction factors, which are then utilized during further PB-based optimization. The hybrid method is benchmarked with respect to full MC deliverable-based optimization for ten prostate and ten head-and-neck IMRT plans. Final optimized plans are compared in terms of dose-volume indices used for the plan optimization. Dose prediction errors (DPEs) and optimization convergence errors (OCEs) at intermediate steps of the hybrid sequence are evaluated. The hybrid method is found to produce optimized plans that are clinically equivalent to full MC-based optimization, yet requires only 40% of the number of MC dose calculations. With the hybrid strategy presented here, MC-based optimization results are achieved in 35 min or less on a modest computing cluster. While the initial PB-deliverable-based optimization is found to have DPEs and OCEs of up to 3 Gy relative to the 65-73 Gy prescription doses, application of the first MC correction reduces the average DPEs to less than 0.3 Gy for the prostate plans and less than 0.06 Gy for the head and neck plans. The maximum observed DPE or OCE is 0.7 Gy after 1 MC dose correction, indicating that a single MC dose calculation correction might be sufficient for IMRT optimization.

Evaluation of clinical margins via simulation of patient setup errors in prostate IMRT treatment plans

This work evaluates: (i) the size of random and systematic setup errors that can be absorbed by 5 mm clinical target volume (CTV) to planning target volume (PTV) margins in prostate intensity modulated radiation therapy (IMRT); (ii) agreement between simulation results and published margin recipes; and (iii) whether shifting contours with respect to a static dose distribution accurately predicts dose coverage due to setup errors. In 27 IMRT treatment plans created with 5 mm CTV-to-PTV margins, random setup errors with standard deviations (SDs) of 1.5, 3, 5 and 10 mm were simulated by fluence convolution. Systematic errors with identical SDs were simulated using two methods: (a) shifting the isocenter and recomputing dose (isocenter shift), and (b) shifting patient contours with respect to the static dose distribution (contour shift). Maximum tolerated setup errors were evaluated such that 90% of plans had target coverage equal to the planned PTV coverage. For coverage criteria consistent with published margin formulas, plans with 5 mm margins were found to absorb combined random and systematic SDs = 3 mm. Published recipes require margins of 8-10 mm for 3 mm SDs. For the prostate IMRT cases presented here a 5 mm margin would suffice, indicating that published recipes may be pessimistic. We found significant errors in individual plan doses given by the contour shift method. However, dose population plots (DPPs) given by the contour shift method agreed with the isocenter shift method for all structures except the nodal CTV and small bowel. For the nodal CTV, contour shift DPP differences were due to the structure moving outside the patient. Small bowel DPP errors were an artifact of large relative differences at low doses. Estimating individual plan doses by shifting contours with respect to a static dose distribution is not recommended. However, approximating DPPs is acceptable, provided care is taken with structures such as the nodal CTV which lie close to the surface.

Application of an inverse kernel concept to Monte Carlo based IMRT

Inverse treatment planning by means of pencil beam algorithms can lead to errors in the calculation of dose in areas without secondary electron equilibrium. Monte Carlo (MC) simulations give accurate results in such areas but result in increased computation times. We present a new, so-called inverse kernel concept that offers MC precision in inverse treatment planning with acceptable computation times and memory consumption. Inverse kernels are matrices that describe the dose contribution from all bixels of a beam to a distinct voxel of the patient phantom. The concept is similar to other generalized pencil-beam concepts, except that inverse kernel elements are precalculated using a single MC simulation and stored as binary trees. In this procedure a modified MC code (XVMC) is applied to trace the photon history for each dose deposition. Iterative optimization is then applied in a second step. The inverse process is separated into (i) a slower MC simulation and (ii) a faster iterative optimization, followed by (iii) the segmentation procedure, and (iv) a final MC dose calculation step including a segment weight reoptimization. Inverse kernel optimization, or IKO, with segmentation and reoptimization steps is demonstrated by means of a lung cancer case. To demonstrate the superiority of an inverse MC system over pencil-beam or collapsed-cone based systems, the final result of the IKO is compared to plans where all segments have been calculated by pencil beam or collapsed cone, respectively. Dose-volume histograms and dose-difference histograms show remarkable differences, which can be attributed to systematic errors in both algorithms. IKO is a precise, nonhybrid, inverse MC treatment planning system which suits current clinical needs, as several optimization steps can follow one single MC-simulation step for a distinct beam setup.

Improving IMRT dose accuracy via deliverable Monte Carlo optimization for the treatment of head and neck cancer patients

The purpose of this work is to investigate the effect of dose-calculation accuracy on head and neck (H&N) intensity modulated radiation therapy (IMRT) plans by determining the systematic dose-prediction and optimization-convergence errors (DPEs and OCEs), using a superposition/convolution (SC) algorithm. Ten patients with locally advanced H&N squamous cell carcinoma who were treated with simultaneous integrated boost IMRT were selected for this study. The targets consisted of gross target volume (GTV), clinical target volume (CTV), and nodal target volumes (CTV nodes). The critical structures included spinal cord, parotid glands, and brainstem. For all patients, three IMRT plans were created: A: an SC optimized plan (SCopt), B: an SCopt plan recalculated with Monte Carlo [MC(SCopt)], and C: an MC optimized plan (MCopt). For each structure, DPEs and OCEs were estimated as DPE(SC)=D(B)-D(A) and OCE(SC)=D(C)-D(B) where A, B, and C stand for the three different optimized plans as defined above. Deliverable optimization was used for all plans, that is, a leaf-sequencing step was incorporated into the optimization loop at each iteration. The range of DPE(SC) in the GTV D98 varied from -1.9% to -4.9%, while the OCE(SC) ranged from 0.9% to 7.0%. The DPE(SC) in the contralateral parotid D50 reached 8.2%, while the OCE(SC) in the contralateral parotid D50 varied from 0.91% to 6.99%. The DPE(SC) in cord D2 reached -3.0%, while the OCE(SC) reached to -7.0%. The magnitude of the DPE(SC) and OCE(SC) differences demonstrate the importance of using the most accurate available algorithm in the deliverable IMRT optimization process, especially for the estimation of normal structure doses.

Intensity-modulated radiotherapy of breast cancer using direct aperture optimization

BACKGROUND AND PURPOSE

To design a clinically reliable and efficient step-and-shoot IMRT delivery technique for the treatment of breast cancer using direct aperture optimization (DAO). Using DAO, segments are created and optimized within the same optimization process.

PATIENTS AND METHODS

The DAO technique implemented in the Pinnacle treatment planning system, which is called direct machine parameter optimization (DMPO), was used to generate IMRT plans for twelve breast cancer patients. The prescribed dose was 50 Gy. Two DMPO plans were generated. The first approach uses DMPO only; the second technique combines DMPO with two predefined segments (DMPO(segm)), having shapes identical to the conventional tangential fields. The weight of these predefined segments is optimized simultaneously with DMPO. The DMPO plans were compared with normal two-step (TS) IMRT, creating segments after optimizing the intensity.

RESULTS

Dose homogeneity within the target volume was 4.8+/-0.6, 4.3+/-0.5 and 3.8+/-0.5 Gy for the TS, DMPO and DMPO(segm) plans, respectively. Comparing the IMRT plans with an idealized dose distribution obtained using only beamlet optimization, the degradation of the dose distribution was less for the DMPO plans compared with the two-step IMRT approach. Furthermore, this degradation was similar for all patients, while for the two-step IMRT approach it was patient specific.

CONCLUSIONS

An efficient step-and-shoot IMRT solution was developed for the treatment of breast cancer using DMPO combined with two predefined segments.

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.

Continuous intensity map optimization (CIMO): A novel approach to leaf sequencing in step and shoot IMRT

A new leaf-sequencing approach has been developed that is designed to reduce the number of required beam segments for step-and-shoot intensity modulated radiation therapy (IMRT). This approach to leaf sequencing is called continuous-intensity-map-optimization (CIMO). Using a simulated annealing algorithm, CIMO seeks to minimize differences between the optimized and sequenced intensity maps. Two distinguishing features of the CIMO algorithm are (1) CIMO does not require that each optimized intensity map be clustered into discrete levels and (2) CIMO is not rule-based but rather simultaneously optimizes both the aperture shapes and weights. To test the CIMO algorithm, ten IMRT patient cases were selected (four head-and-neck, two pancreas, two prostate, one brain, and one pelvis). For each case, the optimized intensity maps were extracted from the Pinnacle3 treatment planning system. The CIMO algorithm was applied, and the optimized aperture shapes and weights were loaded back into Pinnacle. A final dose calculation was performed using Pinnacle's convolution/superposition based dose calculation. On average, the CIMO algorithm provided a 54% reduction in the number of beam segments as compared with Pinnacle's leaf sequencer. The plans sequenced using the CIMO algorithm also provided improved target dose uniformity and a reduced discrepancy between the optimized and sequenced intensity maps. For ten clinical intensity maps, comparisons were performed between the CIMO algorithm and the power-of-two reduction algorithm of Xia and Verhey [Med. Phys. 25(8), 1424-1434 (1998)]. When the constraints of a Varian Millennium multileaf collimator were applied, the CIMO algorithm resulted in a 26% reduction in the number of segments. For an Elekta multileaf collimator, the CIMO algorithm resulted in a 67% reduction in the number of segments. An average leaf sequencing time of less than one minute per beam was observed.

Monte Carlo–based dosimetry of head-and-neck patients treated with SIB-IMRT

PURPOSE

To evaluate the accuracy of previously reported superposition/convolution (SC) dosimetric results by comparing with Monte Carlo (MC) dose calculations for head-and-neck intensity-modulated radiation therapy (IMRT) patients treated with the simultaneous integrated boost technique.

METHODS AND MATERIALS

Thirty-one plans from 24 patients previously treated on a phase I/II head-and-neck squamous cell carcinoma simultaneous integrated boost IMRT protocol were used. Clinical dose distributions, computed with an SC algorithm, were recomputed using an EGS4-based MC algorithm. Phantom-based dosimetry quantified the fluence prediction accuracy of each algorithm. Dose-volume indices were used to compare patient dose distributions.

RESULTS AND DISCUSSION

The MC algorithm predicts flat-phantom measurements better than the SC algorithm. Average patient dose indices agreed within 2.5% of the local dose for targets; 5.0% for parotids; and 1.9% for cord and brainstem. However, only 1 of 31 plans agreed within 3% for all indices; 4 of 31 agreed within 5%. In terms of the prescription dose, 4 of 31 plans agreed within 3% for all indices, whereas 28 of 31 agreed within 5%.

CONCLUSIONS

Average SC-computed doses agreed with MC results in the patient geometry; however deviations >5% were common. The fluence modulation prediction is likely the major source of the dose discrepancy. The observed dose deviations can impact dose escalation protocols, because they would result in shifting patients to higher dose levels.

Iterative regularization in intensity-modulated radiation therapy optimization

A common way to solve intensity-modulated radiation therapy (IMRT) optimization problems is to use a beamlet-based approach. The approach is usually employed in a three-step manner: first a beamlet-weight optimization problem is solved, then the fluence profiles are converted into step-and-shoot segments, and finally postoptimization of the segment weights is performed. A drawback of beamlet-based approaches is that beamlet-weight optimization problems are ill-conditioned and have to be regularized in order to produce smooth fluence profiles that are suitable for conversion. The purpose of this paper is twofold: first, to explain the suitability of solving beamlet-based IMRT problems by a BFGS quasi-Newton sequential quadratic programming method with diagonal initial Hessian estimate, and second, to empirically show that beamlet-weight optimization problems should be solved in relatively few iterations when using this optimization method. The explanation of the suitability is based on viewing the optimization method as an iterative regularization method. In iterative regularization, the optimization problem is solved approximately by iterating long enough to obtain a solution close to the optimal one, but terminating before too much noise occurs. Iterative regularization requires an optimization method that initially proceeds in smooth directions and makes rapid initial progress. Solving ten beamlet-based IMRT problems with dose-volume objectives and bounds on the beamlet-weights, we find that the considered optimization method fulfills the requirements for performing iterative regularization. After segment-weight optimization, the treatments obtained using 35 beamlet-weight iterations outperform the treatments obtained using 100 beamlet-weight iterations, both in terms of objective value and of target uniformity. We conclude that iterating too long may in fact deteriorate the quality of the deliverable plan.

Elongated beamlets: a simple technique for segment and MU reduction for sMLC IMRT delivery on accelerators utilizing 5 mm leaf widths

The focus of this work is to demonstrate the effects of using an elongated beamlet to achieve similar dose conformity as achieved with a square beamlet while reducing the number of segments and subsequent MU required. A series of 10 patients were planned for IMRT delivery to the prostate using minimum beamlet sizes of 5x5 mm2 (default scheme), 10x5 mm2 with the short axis parallel to the prostate-rectum interface (scheme 1), and 10x5 mm2 with the short axis perpendicular to the prostate-rectum interface (scheme 2). All other parameters between plans were left unchanged. Plans were appropriately normalized and evaluated for R65, R40, conformity index, total number of segments and MU. All plans were generated using the Corvus inverse planning system. The average number of segments in this study decreased by approximately 49% for both schemes 1 and 2. The subsequent number of MU required decreased by approximately 34.6%. The resultant modified modulation scaling factor (MSFmod) decreased by approximately 34.3%. Additionally, we found that each isodose distribution using scheme 2 would still meet our clinical acceptance criteria with no visible degradation in the dose distribution as compared with the default scheme. In conclusion, we have demonstrated that it is possible to achieve similar results as those obtained using a 5x5 mm2 beamlet with respect to target coverage and critical structure sparing by using strategically oriented elongated beamlets. This technique directly translates to a decreased MSF(mod) allowing for decreased leakage dose to the patient, a decreased risk of exceeding secondary shielding limits in pre-existing vaults, and shorter treatment times.