Dose sculpting with generalized equivalent uniform dose

Incorporating variable RBE in IMPT optimization for ependymoma

PURPOSE

To study the dosimetric impact of incorporating variable relative biological effectiveness (RBE) of protons in optimizing intensity-modulated proton therapy (IMPT) treatment plans and to compare it with conventional constant RBE optimization and linear energy transfer (LET)-based optimization.

METHODS

This study included 10 pediatric ependymoma patients with challenging anatomical features for treatment planning. Four plans were generated for each patient according to different optimization strategies: (1) constant RBE optimization (ConstRBEopt) considering standard-of-care dose requirements; (2) LET optimization (LETopt) using a composite cost function simultaneously optimizing dose-averaged LET (LETd ) and dose; (3) variable RBE optimization (VarRBEopt) using a recent phenomenological RBE model developed by McNamara et al.; and (4) hybrid RBE optimization (hRBEopt) assuming constant RBE for the target and variable RBE for organs at risk. By normalizing each plan to obtain the same target coverage in either constant or variable RBE, we compared dose, LETd , LET-weighted dose, and equivalent uniform dose between the different optimization approaches.

RESULTS

We found that the LETopt plans consistently achieved increased LET in tumor targets and similar or decreased LET in critical organs compared to other plans. On average, the VarRBEopt plans achieved lower mean and maximum doses with both constant and variable RBE in the brainstem and spinal cord for all 10 patients. To compensate for the underdosing of targets with 1.1 RBE for the VarRBEopt plans, the hRBEopt plans achieved higher physical dose in targets and reduced mean and especially maximum variable RBE doses compared to the ConstRBEopt and LETopt plans.

CONCLUSION

We demonstrated the feasibility of directly incorporating variable RBE models in IMPT optimization. A hybrid RBE optimization strategy showed potential for clinical implementation by maintaining all current dose limits and reducing the incidence of high RBE in critical normal tissues in ependymoma patients.

Accounting for fractionation and heterogeneous dose distributions in the modelling of osteoradionecrosis in oropharyngeal carcinoma treatment

BACKGROUND AND PURPOSE

Osteoradionecrosis (ORN) of the mandible is a severe complication following radiotherapy (RT). With a renewed interest in hypofractionation for head and neck radiotherapy, more information concerning ORN development after high fraction doses is important. The aim of this explorative study was to develop a model for ORN risk prediction applicable across different fractionation schemes using Equivalent Uniform Doses (EUD).

MATERIAL AND METHODS

We performed a retrospective cohort study in 334 oropharyngeal squamous cell carcinoma (OPSCC) patients treated with either a hypofractionated Stereotactic Body Radiation Therapy (HF-SBRT) boost or conventional Intensity Modulated Radiation Therapy (IMRT). ORN was scored with the CTCAE v5.0. HF-SBRT and IMRT dose distributions were converted into equivalent dose in 2 Gy fractions (α/β = 0.85 Gy) and analyzed using EUD. The parameter a that led to an EUD that best discriminated patients with and without grade ≥ 2 ORN was selected. Patient and treatment-related risk factors of ORN were analyzed with uni- and multivariable regression analysis.

RESULTS

A total of 32 patients (9.6%) developed ORN grade ≥ 2. An EUD(a = 8) best discriminated between ORN and non-ORN (AUC = 0.71). In multivariable regression, pre-RT extractions (SHR = 2.34; p = 0.012), mandibular volume (SHR = 1.04; p = 0.003), and the EUD(a = 8) (SHR = 1.14; p < 0.001) were significantly associated with ORN.

CONCLUSION

Risk models for ORN based on conventional DVH parameters cannot be directly applied to HF-SBRT fractionation schemes and dose distributions. However, after correcting for fractionation and non-uniform dose distributions using EUD, a single model can distinguish between ORN and non-ORN after conventionally fractionated radiotherapy and hypofractionated boost treatments.

Radiobiological Comparison of Acuros External Beam and Anisotropic Analytical Algorithm on Esophageal Carcinoma Radiotherapy Treatment Plans

Objective

The present study aimed to investigate the dose differences and radiobiological assessment between Anisotropic Analytical Algorithm (AAA) and Acuros External Beam (AXB) with its 2 calculation models, namely, dose-to-water (AXB-Dw) and dose-to-medium (AXB-Dm), on esophageal carcinoma radiotherapy treatment plans.

Materials and methods

The AXB-Dw and AXB-Dm plans were generated by recalculating the initial 66 AAA plans using the AXB algorithm with the same monitor units and beam parameters as those in the original plan. The dosimetric and radiobiological assessment parameters were calculated for the planning target volume (PTV) and organs at risk (OARs). The gamma agreement for the PTV and the correlation between it and the volume of the air cavity and bone among the different algorithms were compared simultaneously. The dose discrepancy between the theoretical calculation and treatment planning system (TPS) when switching from AXB-Dm to AXB-Dw was analyzed according to the composition of the structures.

Results

The PTV dose of AXB-Dm plans was significantly smaller than that of the AAA and AXB-Dw plans (P < .05), except for D₂. The difference values for AAA vs AXB-Dm (∆D_{x,(AAA-AXB,Dm)}) and AXB-Dw vs AXB-Dm (∆D_{x,(AXB,Dw-AXB,Dm)}) were 1.94% [1.27%, 2.64%] and 1.95% [1.56%, 2.27%], respectively. For the spinal cord and heart, there were obvious differences between the AAA vs AXB-Dm (spinal cord: 1.15%, heart: 2.89%) and AXB-Dw vs AXB-Dm (spinal cord: 1.88%, heart: 3.25%) plans. For the lung, the differences between AAA vs AXB-Dm and AAA vs AXB-Dw were significantly larger than those of AXB-Dm vs AXB-Dw. Compared to the case of AAA and AXB-Dw, the decrease in biologically effective dose (BED¹⁰, αβ=10 ) of AXB-Dm due to dose non-uniformity exceeded 6.5%, even for a small σ. The average values of equivalent uniform dose in the AAA, AXB-Dw, and AXB-Dm plans were 52.03±.39 Gy, 52.24 ± .81 Gy, and 51.13 ± .47 Gy, respectively. The tumor control probability (TCP) results for PTV in the AAA, AXB-Dw, and AXB-Dm plans were 62.29 ± 1.57%, 62.82 ± 1.69%, and 58.68±1.88%, respectively. With the 2%/2 mm and 3%/3 mm acceptance criteria, the mean values of  ΔγAAAAXB−Dw, ΔγAAAAXB−Dm, and  ΔγAXB−DmAXB−Dw were 87.24, 63.3, and 64.81% vs 97.86, 91.77, and 89.25%, respectively. The dose discrepancy between the theoretical calculation and TPS when switching from AXB-Dm to AXB-Dw was approximately 1.63%.

Conclusions

The AAA and AXB-Dw algorithms overestimated the radiobiological parameters when the tumor particularly consisted of nonuniform tissues. A relatively small dose difference could cause a significant reduction in the corresponding TCP. Dose distribution algorithms should be carefully chosen by physicists and oncologists to improve tumor control, as well as to optimize OARs protection.

Influence of Using a Contrast-Enhanced CT Image as the Primary Image on CyberKnife Brain Radiosurgery Treatment Plans

Background and Purpose

This study aimed to quantify the differences between pre- and post-contrast agent (CA) CT for CyberKnife brain SRS plans.

Materials and Methods

Twenty-five patients were retrospectively analyzed. They were divided into two categories, inhomogeneous cases (13 patients) and homogeneous cases (12 patients), according to whether the tumor was close to the cavity and inhomogeneous tissues or not. The pre-CA and post-CA plans were designed and calculated using the same monitor unit and paths as those in the ray-tracing algorithm, respectively.

Results

The CT number difference of tumor between pre- and post-CA was significant (on average, 24.78 ± 18.56 HU, P-value < 0.01). The deviation value of the target was the largest at approximately 37 HU (inhomo-) and 13 HU (homo-) (P < 0.01), and the values of the organs at risk (OARs) were not statistically significant (P-value > 0.05). However, it was not statistically significant for the dose difference between the two groups with the injection of CA (P-value > 0.05). The absolute effective depth difference generally remained at a level of 1 mm, but the dose difference was quitely fluctuated sometimes more than 20%. The absolute effective depth difference of the inhomo-case (0.62 mm) was larger than that of the homo-case (0.37 mm) on median, as well as the variation amplitude (P-value < 0.05). Moreover, the relative dose differences between the two cases were 0.38% (inhomo-) and 0.2% (homo-), respectively (P-value < 0.05). At the criterion of 1 mm/1%, the gamma pass rate of the homo-case (95.89%) was larger than that of the inhomo-case (93.79%). For the OARs, except for the cochlea, the two cases were almost the same (>98.85%). The tumor control probability of the target was over 99.99% before and after injection of a CA, as well as the results for the homo-case and inhomo-case.

Conclusions

Considering the difference of evaluation indexes between pre- and post-CA images, we recommended plain CT to be employed as the primary image for improving the CK treatment accuracy of brain SRS, especially when the target was close to CA-sensitive OARs and cavity.

Application of dose-volume histogram prediction in biologically related models for nasopharyngeal carcinomas treatment planning

PURPOSE

In this study, we employed a gated recurrent unit (GRU)-based recurrent neural network (RNN) using dosimetric information induced by individual beam to predict the dose-volume histogram (DVH) and investigated the feasibility and usefulness of this method in biologically related models for nasopharyngeal carcinomas (NPC) treatment planning.

METHODS AND MATERIALS

One hundred patients with NPC undergoing volumetric modulated arc therapy (VMAT) between 2018 and 2019 were randomly selected for this study. All the VMAT plans were created using the Monaco treatment planning system (Elekta, Sweden) and clinically approved: > 98% of PGTVnx received the prescribed doses of 70 Gy, > 98% of PGTVnd received the prescribed doses of 66 Gy and > 98% of PCTV received 60 Gy. Of these, the data from 80 patients were used to train the GRU-RNN, and the data from the other 20 patients were used for testing. For each NPC patient, the DVHs of different organs at risk were predicted by a trained GRU-based RNN using the information given by individual conformal beams. Based on the predicted DVHs, the equivalent uniform doses (EUD) were calculated and applied as dose constraints during treatment planning optimization. The regenerated VMAT experimental plans (EPs) were evaluated by comparing them with the clinical plans (CPs).

RESULTS

For the 20 test patients, the regenerated EPs guided by the GRU-RNN predictive model achieved good consistency relative to the CPs. The EPs showed better consistency in PTV dose distribution and better dose sparing for many organs at risk, and significant differences were found in the maximum/mean doses to the brainstem, brainstem PRV, spinal cord, lenses, temporal lobes, parotid glands and larynx with P-values < 0.05. On average, compared with the CPs, the maximum/mean doses to these OARs were altered by - 3.44 Gy, - 1.94 Gy, - 1.88 Gy, 0.44 Gy, 1.98 Gy, - 1.82 Gy and 2.27 Gy, respectively. In addition, significant differences were also found in brainstem and spinal cord for the dose received by 1 cc volume with 4.11 and 1.67 Gy dose reduction in EPs on average.

CONCLUSION

The GRU-RNN-based DVH prediction method was capable of accurate DVH prediction. The regenerated plans guided by the predicted EUDs were not inferior to the manual plans, had better consistency in PTVs and better dose sparing in critical OARs, indicating the usefulness and effectiveness of biologically related model in knowledge-based planning.

Correlation of normal lung density changes with dose after stereotactic body radiotherapy (SBRT) for early stage lung cancer

BACKGROUND AND PURPOSE

To investigate the correlation between normal lung CT density changes with dose accuracy and outcome after stereotactic body radiation therapy (SBRT) for patients with early stage non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

Thirty-one patients (with a total of 33 lesions) with non-small cell lung cancer were selected out of 270 patients treated with SBRT at a single institution between 2003 and 2009. Out of these 31 patients, 10 patients had developed radiation pneumonitis (RP). Dose distributions originally planned using a 1-D pencil beam-based dose algorithm were retrospectively recomputed using different algorithms. Prescription dose was 48 Gy in 4 fractions in most patients. Planning CT images were rigidly registered to follow-up CT datasets at 3-9 months after treatment. Corresponding dose distributions were mapped from planning to follow-up CT images. Hounsfield Unit (HU) changes in lung density in individual, 5 Gy, dose bins from 5 to 45 Gy were assessed in the peri-tumoral region. Correlations between HU changes in various normal lung regions, dose indices (V20, MLD, generalized equivalent uniform dose (gEUD)), and RP grade were investigated.

RESULTS

Strong positive correlation was found between HU changes in the peri-tumoral region and RP grade (Spearman's r = 0.760; p < 0.001). Positive correlation was also observed between RP and HU changes in the region covered by V20 for all algorithms (Spearman's r ≥ 0.738; p < 0.001). Additionally, V20, MLD, and gEUD were significantly correlated with RP grade (p < 0.01). MLD in the peri-tumoral region computed with model-based algorithms was 5-7% lower than the PB-based methods.

CONCLUSION

Changes of lung density in the peri-tumoral lung and in the region covered by V20 were strongly associated with RP grade. Relative to model-based methods, PB algorithms over-estimated mean peri-tumoral dose and showed displacement of the high-dose region, which correlated with HU changes on follow-up CT scans.

Automated Field-In-Field (FIF) Plan Framework Combining Scripting Application Programming Interface and User-Executed Program for Breast Forward IMRT

Purpose:

To develop an one-click option on treatment planning system that enables for the automated breast FIF planning by combining the Eclipse Scripting application programming interfaces and user-executed programming in Windows.

Methods:

Scripting application programming interfaces were designed to promote automation in clinical workflow associated with radiation oncology. However, scripting cannot provide all functions that users want to perform. Thus, a new framework proposes to integrate the benefits of the scripting application and user-executed programming for the automated field-in-field technique. We adopted the Eclipse Scripting applications, which provide an interface between treatment planning system server and client and enable for running the executed program to create dose clouds and adjust the planning parameters such as multi-leaf collimator placements and monitor unit values. Importantly, all tasks are designed to perform with one-click option on treatment planning system, including the automated pushback of the proposed plan to the treatment planning system.

Results:

The plans produced from the proposed framework were validated against the manual field-in-field plans with 40 retrospective breast patient cases in planning efficiency and plan quality. The elapsed time for running the framework was less than 1 minute, which significantly reduced the manual multi-leaf collimator/monitor unit adjustment time. It decreased the total planning time by more than 50%, relative to the manual field-in-field planning. In dosimetric aspects, the mean and maximum dose of the heart, lung, and whole breast did not exceed 1% deviation from the manual plans in most patient cases, while maintaining the target dose coverage and homogeneity index inside the target volume. From numerical analysis, the automated plans were demonstrated to be sufficiently close to the manual plans.

Conclusion:

The combination of scripting applications and user-executed programming for automated breast field-in-field planning accomplished a significant enhancement in planning efficiency without degrading the plan quality, relative to the manual field-in-field procedure.

Isodose feature-preserving voxelization (IFPV) for radiation therapy treatment planning

PURPOSE

Inverse planning involves iterative optimization of a large number of parameters and is known to be a labor-intensive procedure. To reduce the scale of computation and improve characterization of isodose plan, this paper presents an isodose feature-preserving voxelization (IFPV) framework for radiation therapy applications and demonstrates an implementation of inverse planning in the IFPV domain.

METHODS

A dose distribution in IFPV scheme is characterized by partitioning the voxels into subgroups according to their geometric and dosimetric values. Computationally, the isodose feature-preserving (IFP) clustering combines the conventional voxels that are spatially and dosimetrically close into physically meaningful clusters. A K-means algorithm and support vector machine (SVM) runs sequentially to group the voxels into IFP clusters. The former generates initial clusters according to the geometric and dosimetric information of the voxels and SVM is invoked to improve the connectivity of the IFP clusters. To illustrate the utility of the formalism, an inverse planning framework in the IFPV domain is implemented, and the resultant plans of three prostate IMRT and one head-and-neck cases are compared quantitatively with that obtained using conventional inverse planning technique.

RESULTS

The IFPV generates models with significant dimensionality reduction without compromising the spatial resolution seen in traditional downsampling schemes. The implementation of inverse planning in IFPV domain is demonstrated. In addition to the improved computational efficiency, it is found that, for the cases studied here, the IFPV-domain inverse planning yields better treatment plans than that of DVH-based planning, primarily because of more effective use of both geometric and dose information of the system during plan optimization.

CONCLUSIONS

The proposed IFPV provides a low parametric representation of isodose plan without compromising the essential characteristics of the plan, thus providing a practically valuable framework for various applications in radiation therapy.

Using measurable dosimetric quantities to characterize the inter-structural tradeoff in inverse planning

Traditional inverse planning relies on the use of weighting factors to balance the conflicting requirements of different structures. Manual trial-and-error determination of weighting factors has long been recognized as a time-consuming part of treatment planning. The purpose of this work is to develop an inverse planning framework that parameterizes the dosimetric tradeoff among the structures with physically meaningful quantities to simplify the search for clinically sensible plans. In this formalism, instead of using weighting factors, the permissible variation range of the prescription dose or dose volume histogram (DVH) of the involved structures are used to characterize the 'importance' of the structures. The inverse planning is then formulated into a convex feasibility problem, called the dosimetric variation-controlled model (DVCM), whose goal is to generate plans with dosimetric or DVH variations of the structures consistent with the pre-specified values. For simplicity, the dosimetric variation range for a structure is extracted from a library of previous cases which possess similar anatomy and prescription. A two-phase procedure (TPP) is designed to solve the model. The first phase identifies a physically feasible plan to satisfy the prescribed dosimetric variation, and the second phase automatically improves the plan in case there is room for further improvement. The proposed technique is applied to plan two prostate cases and two head-and-neck cases and the results are compared with those obtained using a conventional CVaR approach and with a moment-based optimization scheme. Our results show that the strategy is able to generate clinically sensible plans with little trial and error. In all cases, the TPP generates a very competitive plan as compared to those obtained using the alternative approaches. Particularly, in the planning of one of the head-and-neck cases, the TPP leads to a non-trivial improvement in the resultant dose distribution-the fractional volumes receiving a dose above 20 Gy for the spinal cord are reduced by more than 40% when compared to the alternative schemes, while maintaining the same PTV coverage. With physically more meaningful modeling of the inter-structural tradeoff, the reported technique enables us to substantially reduce the need for trial-and-error adjustment of the model parameters. The new formalism also opens new opportunities for incorporating prior knowledge to facilitate the treatment planning process.

Application programming in C# environment with recorded user software interactions and its application in autopilot of VMAT/IMRT treatment planning

An autopilot scheme of volumetric‐modulated arc therapy (VMAT)/intensity‐modulated radiation therapy (IMRT) planning with the guidance of prior knowledge is established with recorded interactions between a planner and a commercial treatment planning system (TPS). Microsoft (MS) Visual Studio Coded UI is applied to record some common planner‐TPS interactions as subroutines. The TPS used in this study is a Windows‐based Eclipse system. The interactions of our application program with Eclipse TPS are realized through a series of subroutines obtained by prerecording the mouse clicks or keyboard strokes of a planner in operating the TPS. A strategy to autopilot Eclipse VMAT/IMRT plan selection process is developed as a specific example of the proposed “scripting” method. The autopiloted planning is navigated by a decision function constructed with a reference plan that has the same prescription and similar anatomy with the case at hand. The calculation proceeds by alternating between the Eclipse optimization and the outer‐loop optimization independent of the Eclipse. In the C# program, the dosimetric characteristics of a reference treatment plan are used to assess and modify the Eclipse planning parameters and to guide the search for a clinically sensible treatment plan. The approach is applied to plan a head and neck (HN) VMAT case and a prostate IMRT case. Our study demonstrated the feasibility of application programming method in C# environment with recorded interactions of planner‐TPS. The process mimics a planner's planning process and automatically provides clinically sensible treatment plans that would otherwise require a large amount of manual trial and error of a planner. The proposed technique enables us to harness a commercial TPS by application programming via the use of recorded human computer interactions and provides an effective tool to greatly facilitate the treatment planning process.

PACS number(s): 87.55.D‐, 87.55.kd, 87.55.de

Radiobiologically optimized couch shift: A new localization paradigm using cone-beam CT for prostate radiotherapy

PURPOSE

To present a novel positioning strategy which optimizes radiation delivery by utilizing radiobiological response knowledge and evaluate its use during prostate external beam radiotherapy.

METHODS

Five patients with low or intermediate risk prostate cancer were evaluated retrospectively in this IRB-approved study. For each patient, a VMAT plan with one 358° arc was generated on the planning CT (PCT) to deliver 78 Gy in 39 fractions. Five representative pretreatment cone beam CTs (CBCT) were selected for each patient. The CBCT images were registered to PCT by a human observer, which consisted of an initial automated registration with three degrees-of-freedom, followed by manual adjustment for agreement at the prostate/rectal wall interface. To determine the optimal treatment position for each CBCT, a search was performed centering on the observer-matched position (OM-position) utilizing a score function based on radiobiological and dosimetric indices (EUDprostate, D99prostate, NTCPrectum, and NTCPbladder) for the prostate, rectum, and bladder. We termed the optimal treatment position the radiobiologically optimized couch shift position (ROCS-position).

RESULTS

The dosimetric indices, averaged over the five patients' treatment plans, were (mean ± SD) 79.5 ± 0.3 Gy (EUDprostate), 78.2 ± 0.4 Gy (D99prostate), 11.1% ± 2.7% (NTCPrectum), and 46.9% ± 7.6% (NTCPbladder). The corresponding values from CBCT at the OM-positions were 79.5 ± 0.6 Gy (EUDprostate), 77.8 ± 0.7 Gy (D99prostate), 12.1% ± 5.6% (NTCPrectum), and 51.6% ± 15.2% (NTCPbladder), respectively. In comparison, from CBCT at the ROCS-positions, the dosimetric indices were 79.5 ± 0.6 Gy (EUDprostate), 77.3 ± 0.6 Gy (D99prostate), 8.0% ± 3.3% (NTCPrectum), and 46.9% ± 15.7% (NTCPbladder). Excessive NTCPrectum was observed on Patient 5 (19.5% ± 6.6%) corresponding to localization at OM-position, compared to the planned value of 11.7%. This was mitigated with radiobiologically optimized localization, resulting in a reduced NTCPrectum value of 11.3% ± 3.5%. Overall, the treatment position optimization resulted in similar target dose coverage with reduced risk to rectum.

CONCLUSIONS

These encouraging results illustrate the potential advantage of applying radiobiologically optimized correction for online image-guided radiotherapy of prostate patients.

Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study

Effective positron emission tomography / computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [(18)F]FDG. The lung lesion insert was driven by six different patient-specific respiratory patterns or kept stationary. PET/CT images were acquired under motionless ground truth, tidal breathing motion-averaged (3D), and respiratory phase-correlated (4D) conditions. Target volumes were estimated by standardized uptake value (SUV) thresholds that accurately defined the ground-truth lesion volume. Non-uniform dose-painting plans using volumetrically modulated arc therapy were optimized for fixed normal lung and spinal cord objectives and variable PET-based target objectives. Resulting plans were delivered to a cylindrical diode array at rest, in motion on a platform driven by the same respiratory patterns (3D), or motion-compensated by a robotic couch with an infrared camera tracking system (4D). Errors were estimated relative to the static ground truth condition for mean target-to-background (T/Bmean) ratios, target volumes, planned equivalent uniform target doses, and 2%-2 mm gamma delivery passing rates. Relative to motionless ground truth conditions, PET/CT imaging errors were on the order of 10-20%, treatment planning errors were 5-10%, and treatment delivery errors were 5-30% without motion compensation. Errors from residual motion following compensation methods were reduced to 5-10% in PET/CT imaging, <5% in treatment planning, and <2% in treatment delivery. We have demonstrated that estimation of respiratory motion uncertainty and its propagation from PET/CT imaging to RT planning, and RT delivery under a dose painting paradigm is feasible within an integrated respiratory motion phantom workflow. For a limited set of cases, the magnitude of errors was comparable during PET/CT imaging and treatment delivery without motion compensation. Errors were moderately mitigated during PET/CT imaging and significantly mitigated during RT delivery with motion compensation. This dynamic motion phantom end-to-end workflow provides a method for quality assurance of 4D PET/CT-guided radiotherapy, including evaluation of respiratory motion compensation methods during imaging and treatment delivery.

Three-dimensional conformal planning with low-segment multicriteria intensity modulated radiation therapy optimization

PURPOSE

The purpose of this study was to evaluate automated multicriteria optimization (MCO), which is designed for intensity modulated radiation therapy (IMRT) but invoked with limited segmentation, to efficiently produce high-quality 3-dimensional (3D) conformal radiation therapy (3D-CRT) plans.

METHODS AND MATERIALS

Treatment for 10 patients previously planned with 3D-CRT to various disease sites (brain, breast, lung, abdomen, pelvis) was replanned with a low-segment inverse MCO technique. The MCO-3D plans used the same beam geometry of the original 3D plans but were limited to an energy of 6 MV. The MCO-3D plans were optimized with fluence-based MCO IMRT and then, after MCO navigation, segmented with a low number of segments. The 3D and MCO-3D plans were compared by evaluating mean dose for all structures, D95 (dose that 95% of the structure receives) and homogeneity indexes for targets, D1 and clinically appropriate dose-volume objectives for individual organs at risk (OARs), monitor units, and physician preference.

RESULTS

The MCO-3D plans reduced the mean doses to OARs (41 of a total of 45 OARs had a mean dose reduction; P << .01) and monitor units (7 of 10 plans had reduced monitor units; the average reduction was 17% [P = .08]) while maintaining clinical standards for coverage and homogeneity of target volumes. All MCO-3D plans were preferred by physicians over their corresponding 3D plans.

CONCLUSIONS

High-quality 3D plans can be produced by use of MCO-IMRT optimization, resulting in automated field-in-field-type plans with good monitor unit efficiency. Adoption of this technology in a clinic could improve plan quality and streamline treatment plan production by using a single system applicable to both IMRT and 3D planning.

Mathematical formulation of energy minimization - based inverse optimization

Purpose: To introduce the concept of energy minimization-based inverse optimization for external beam radiotherapy.

Materials and Methods: Mathematical formulation of energy minimization-based inverse optimization is presented. This mathematical representation is compared to the most commonly used dose–volume based formulation used in inverse optimization. A simple example on digitally created phantom is demonstrated. The phantom consists of three sections: a target surrounded by high and low density regions. The target is irradiated with two beams passing through those regions. Inverse optimization with dose–volume and energy minimization-based objective functions is performed. The dosimetric properties of the two optimization results are evaluated.

Results: Dose–volume histograms for all the volumes of interest used for dose optimization are compared. Energy-based optimization results in higher maximum dose to the volumes that are used as dose-limiting structures. However, the average and the integral doses delivered for the volumes outside of the target are larger with dose–volume optimization.

Conclusion: Mathematical formulation of energy minimization-based inverse optimization is derived. The optimization applied on the digital phantom shows that energy minimization-based approach tends to deliver somewhat higher maximum doses compared to standard of care, realized with dose–volume based optimization. At the same time, however, the energy minimization-based optimization reduces much more significantly the average and the integral doses.

A gEUD-based inverse planning technique for HDR prostate brachytherapy: feasibility study

PURPOSE

The purpose of this work was to study the feasibility of a new inverse planning technique based on the generalized equivalent uniform dose for image-guided high dose rate (HDR) prostate cancer brachytherapy in comparison to conventional dose-volume based optimization.

METHODS

The quality of 12 clinical HDR brachytherapy implants for prostate utilizing HIPO (Hybrid Inverse Planning Optimization) is compared with alternative plans, which were produced through inverse planning using the generalized equivalent uniform dose (gEUD). All the common dose-volume indices for the prostate and the organs at risk were considered together with radiobiological measures. The clinical effectiveness of the different dose distributions was investigated by comparing dose volume histogram and gEUD evaluators.

RESULTS

Our results demonstrate the feasibility of gEUD-based inverse planning in HDR brachytherapy implants for prostate. A statistically significant decrease in D10 or/and final gEUD values for the organs at risk (urethra, bladder, and rectum) was found while improving dose homogeneity or dose conformity of the target volume.

CONCLUSIONS

Following the promising results of gEUD-based optimization in intensity modulated radiation therapy treatment optimization, as reported in the literature, the implementation of a similar model in HDR brachytherapy treatment plan optimization is suggested by this study. The potential of improved sparing of organs at risk was shown for various gEUD-based optimization parameter protocols, which indicates the ability of this method to adapt to the user's preferences.

A quantitative analysis of intensity-modulated radiation therapy plans and comparison of homogeneity indices for the treatment of gynecological cancers

The aim of present study was to evaluate the intensity-modulated radiation therapy (IMRT) plans using different homogeneity and conformity indices in gynecological cancers, as well as to compare and find out the most reliable and accurate measure of the dose homogeneity among the available indices. In this study, a cohort of 12 patients were registered for evaluation, those receiving dynamic IMRT treatment on Clinac-2300C/D linear accelerator with 15-Mega Voltage (MV) photon beam. Dynamic IMRT plans were created on Eclipse treatment planning system with Helios dose volume optimization software. Homogeneity indices (HI) such as H index, modified H index, HI index, modified HI index, and S-index (sigma-index) proposed by M Yoon et al. (2007) were calculated and compared. The values of S-index vary from 1.63 to 2.99. The results indicate that the H and HI indices and their modified versions may not provide the correct dose homogeneity information, but the S-index provides accurate information about the dose homogeneity in the Planning Target Volume (PTV). Each plan was compared with 6-MV photon energy on the basis of S-index and conformity index (CI). Organs at risk (OAR) doses with 6-MV and 15-MV beams were also reported.

Investigation of effective decision criteria for multiobjective optimization in IMRT

PURPOSE

To investigate how using different sets of decision criteria impacts the quality of intensity modulated radiation therapy (IMRT) plans obtained by multiobjective optimization.

METHODS

A multiobjective optimization evolutionary algorithm (MOEA) was used to produce sets of IMRT plans. The MOEA consisted of two interacting algorithms: (i) a deterministic inverse planning optimization of beamlet intensities that minimizes a weighted sum of quadratic penalty objectives to generate IMRT plans and (ii) an evolutionary algorithm that selects the superior IMRT plans using decision criteria and uses those plans to determine the new weights and penalty objectives of each new plan. Plans resulting from the deterministic algorithm were evaluated by the evolutionary algorithm using a set of decision criteria for both targets and organs at risk (OARs). Decision criteria used included variation in the target dose distribution, mean dose, maximum dose, generalized equivalent uniform dose (gEUD), an equivalent uniform dose (EUD(alpha,beta) formula derived from the linear-quadratic survival model, and points on dose volume histograms (DVHs). In order to quantatively compare results from trials using different decision criteria, a neutral set of comparison metrics was used. For each set of decision criteria investigated, IMRT plans were calculated for four different cases: two simple prostate cases, one complex prostate Case, and one complex head and neck Case.

RESULTS

When smaller numbers of decision criteria, more descriptive decision criteria, or less anti-correlated decision criteria were used to characterize plan quality during multiobjective optimization, dose to OARs and target dose variation were reduced in the final population of plans. Mean OAR dose and gEUD (a = 4) decision criteria were comparable. Using maximum dose decision criteria for OARs near targets resulted in inferior populations that focused solely on low target variance at the expense of high OAR dose. Target dose range, (D(max) - D(min)), decision criteria were found to be most effective for keeping targets uniform. Using target gEUD decision criteria resulted in much lower OAR doses but much higher target dose variation. EUD(alpha,beta) based decision criteria focused on a region of plan space that was a compromise between target and OAR objectives. None of these target decision criteria dominated plans using other criteria, but only focused on approaching a different area of the Pareto front.

CONCLUSIONS

The choice of decision criteria implemented in the MOEA had a significant impact on the region explored and the rate of convergence toward the Pareto front. When more decision criteria, anticorrelated decision criteria, or decision criteria with insufficient information were implemented, inferior populations are resulted. When more informative decision criteria were used, such as gEUD, EUD(alpha,beta), target dose range, and mean dose, MOEA optimizations focused on approaching different regions of the Pareto front, but did not dominate each other. Using simple OAR decision criteria and target EUD(alpha,beta) decision criteria demonstrated the potential to generate IMRT plans that significantly reduce dose to OARs while achieving the same or better tumor control when clinical requirements on target dose variance can be met or relaxed.

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.

Equivalence in dose fall-off for isocentric and nonisocentric intracranial treatment modalities and its impact on dose fractionation schemes

PURPOSE

To investigate whether dose fall-off characteristics would be significantly different among intracranial radiosurgery modalities and the influence of these characteristics on fractionation schemes in terms of normal tissue sparing.

METHODS AND MATERIALS

An analytic model was developed to measure dose fall-off characteristics near the target independent of treatment modalities. Variations in the peripheral dose fall-off characteristics were then examined and compared for intracranial tumors treated with Gamma Knife, Cyberknife, or Novalis LINAC-based system. Equivalent uniform biologic effective dose (EUBED) for the normal brain tissue was calculated. Functional dependence of the normal brain EUBED on varying numbers of fractions (1 to 30) was studied for the three modalities.

RESULTS

The derived model fitted remarkably well for all the cases (R(2) > 0.99). No statistically significant differences in the dose fall-off relationships were found between the three modalities. Based on the extent of variations in the dose fall-off curves, normal brain EUBED was found to decrease with increasing number of fractions for the targets, with alpha/beta ranging from 10 to 20. This decrease was most pronounced for hypofractionated treatments with fewer than 10 fractions. Additionally, EUBED was found to increase slightly with increasing number of fractions for targets with alpha/beta ranging from 2 to 5.

CONCLUSION

Nearly identical dose fall-off characteristics were found for the Gamma Knife, Cyberknife, and Novalis systems. Based on EUBED calculations, normal brain sparing was found to favor hypofractionated treatments for fast-growing tumors with alpha/beta ranging from 10 to 20 and single fraction treatment for abnormal tissues with low alpha/beta values such as alpha/beta = 2.

Hypofractionation: what does it mean for prostate cancer treatment?

PURPOSE

Using current radiobiologic models and biologic parameters, we performed an exploratory study of the clinical consequences of hypofractionation in prostate cancer radiotherapy.

METHODS AND MATERIALS

Four hypofractionated treatment regimens were compared with standard fractionation of 2 Gy x 39 for prostate carcinoma using a representative set of anatomical structures. The linear-quadratic model and generalized equivalent uniform dose formalism were used to calculate normalized equivalent uniform dose (gEUD(2)), from which tumor control probability and normal tissue complication probability were calculated, as well as "complication-free tumor control probability" (P+). The robustness of the results was tested for various tumor alpha/beta values and broad interval of biologic parameters such as surviving fraction after a dose of 2 Gy (SF2).

RESULTS

A 2.5% and 5.8% decrease in NTCP for rectum and bladder, respectively, was predicted for the 6.5 Gy/fraction regimen compared with the 2 Gy/fraction. Conversely, TCP for hypofractionated regimens decreased significantly with increasing SF2 and alpha/beta. For tumor cells with SF2 = 0.4-0.5, P+ was superior for nearly all hypofractionated regimens even for alpha/beta values up to 6.5 Gy. For less responsive tumor cells (SF2 = 0.6), hypofractionation regimens were inferior to standard fractionation at much lower alpha/beta.

CONCLUSION

For a sample set of anatomical structures, existing radiobiologic data and models predict improved clinical results from hypofractionation over standard fractionation not only for prostate carcinoma with low alpha/beta but also for high alpha/beta (up to 6.5 Gy) when SF2 < 0.5. Predicted results for specific patients may vary with individual anatomy, and large-scale clinical conclusions can be drawn only after performing similar analysis on an appropriate population of patients.

A theoretical framework for prescribing radiotherapy dose distributions using patient-specific biological information

We present a formalism for using functional imaging both to derive patient-specific radiobiological properties and consequently to prescribe optimal nonuniform radiotherapy dose distributions. The ability to quantitatively assess the response to an initial course of radiotherapy would allow the derivation of radiobiological parameters for individual patients. Both an iterative optimization and an analytical approach to this problem were investigated and illustrated by application to the linear-quadratic model of cell killing using simulated parametric data for a modeled tumor. Potential gains in local control were assessed by comparing uniform dose distributions with optimized dose distributions of equal integral dose. The effect on local prescribed dose of variations in effective radiosensitivity, tumor burden, and proliferation rate was investigated, with results suggesting that dose variations would be significant but clinically achievable. The sensitivity of derived parameters to image noise and the effect of varying the initial fractionation and imaging schedule were assessed. The analytical approach proved remarkably robust, with 10% image noise resulting in dose errors of approximately 1% for a clinically relevant set of parameters. Potential benefits were demonstrated by using this formalism to prescribe nonuniform dose distributions for model tumors using a range of literature-derived parameters. The redistribution of dose improved tumor control probability by factors between 1.03 and 4.27 for a range of model tumors.

Pareto navigation: algorithmic foundation of interactive multi-criteria IMRT planning

Inherently, IMRT treatment planning involves compromising between different planning goals. Multi-criteria IMRT planning directly addresses this compromising and thus makes it more systematic. Usually, several plans are computed from which the planner selects the most promising following a certain procedure. Applying Pareto navigation for this selection step simultaneously increases the variety of planning options and eases the identification of the most promising plan. Pareto navigation is an interactive multi-criteria optimization method that consists of the two navigation mechanisms 'selection' and 'restriction'. The former allows the formulation of wishes whereas the latter allows the exclusion of unwanted plans. They are realized as optimization problems on the so-called plan bundle -- a set constructed from pre-computed plans. They can be approximately reformulated so that their solution time is a small fraction of a second. Thus, the user can be provided with immediate feedback regarding his or her decisions. Pareto navigation was implemented in the MIRA navigator software and allows real-time manipulation of the current plan and the set of considered plans. The changes are triggered by simple mouse operations on the so-called navigation star and lead to real-time updates of the navigation star and the dose visualizations. Since any Pareto-optimal plan in the plan bundle can be found with just a few navigation operations the MIRA navigator allows a fast and directed plan determination. Besides, the concept allows for a refinement of the plan bundle, thus offering a middle course between single plan computation and multi-criteria optimization. Pareto navigation offers so far unmatched real-time interactions, ease of use and plan variety, setting it apart from the multi-criteria IMRT planning methods proposed so far.

An approach for practical multiobjective IMRT treatment planning

PURPOSE

To introduce and demonstrate a practical multiobjective treatment planning procedure for intensity-modulated radiation therapy (IMRT) planning.

METHODS AND MATERIALS

The creation of a database of Pareto optimal treatment plans proceeds in two steps. The first step solves an optimization problem that finds a single treatment plan which is close to a set of clinical aspirations. This plan provides an example of what is feasible, and is then used to determine mutually satisfiable hard constraints for the subsequent generation of the plan database. All optimizations are done using linear programming.

RESULTS

The two-step procedure is applied to a brain, a prostate, and a lung case. The plan databases created allow for the selection of a final treatment plan based on the observed tradeoffs between the various organs involved.

CONCLUSIONS

The proposed method reduces the human iteration time common in IMRT treatment planning. Additionally, the database of plans, when properly viewed, allows the decision maker to make an informed final plan selection.

Towards an objective evaluation of tolerances for beam modeling in a treatment planning system

The performance of a convolution/superposition based treatment planning system depends on the ability of the dose calculation algorithm to accurately account for physical interactions taking place in the tissue, key components of the linac head and on the accuracy of the photon beam model. Generally the user has little or no control over the performance of the dose calculation algorithm but is responsible for the accuracy of the beam model within the constraints imposed by the system. This study explores the dosimetric impact of limitations in photon beam modeling accuracy on complex 3D clinical treatment plans. A total of 70 photon beam models was created in the Pinnacle treatment planning system. Two of the models served as references for 6 MV and 15 MV beams, while the rest were created by perturbing the reference models in order to produce specific deviations in specific regions of the calculated dose profiles (central axis and transverse). The beam models were then used to generate 3D plans on seven CT data sets each for four different treatment sites (breast and conformal prostate, lung and brain). The equivalent uniform doses (EUD) of the targets and the principal organs at risk (OARs) of all plans ( approximately 1000) were calculated and compared to the EUDs delivered by the reference beam models. In general, accurate dosimetry of the target is most greatly compromised by poor modeling of the central axis depth dose and the horns, while the EUDs of the OARs exhibited the greatest sensitivity to beam width accuracy. Based on the results of this analysis we suggest a set of tolerances to be met during commissioning of the beam models in a treatment planning system that are consistent in terms of clinical outcomes as predicted by the EUD.

Self-consistent tumor control probability and normal tissue complication probability models based on generalized EUDa)

Traditional methods to compute the tumor control probability (TCP) or normal tissue complication probability (NTCP) typically require a heterogeneous radiation dose distribution to be converted into a simple uniform dose distribution with an equivalent biological effect. Several power-law type dose-volume-histogram reduction schemes, particularly Niemierko's generalized equivalent uniform dose model [Med. Phys. 26, 1000 (1999)], have been proposed to achieve this goal. In this study, we carefully examine the mathematical outcome of these schemes. We demonstrate that (1) for tumors, with each tumor cell independently responding to local radiation dose, a closed-form analytical solution for tumor survival fraction and TCP can be obtained; (2) for serial structured normal tissues, an exponential power-law form relating survival to functional sub-unit (FSU) radiation is required, and a closed-form analytical solution for the related NTCP is provided; (3) in the case of a parallel structured normal tissue, when NTCP is determined solely by the number of the surviving FSUs, a mathematical solution is available only when there is a non-zero threshold dose and/or a finite critical dose defining the radiotherapy response. Some discussion is offered for the partial irradiation effect on normal tissues in this category; (4) for normal tissues with alternative architectures, where the radiation response of FSU is inhomogeneous, there is no exact global mathematical solution for SF or NTCP within the available schemes. Finally, numerical fits of our models to some experimental data are also presented.

Future Issues in Highly Conformal Radiotherapy for Head and Neck Cancer

Improving the conformity of the radiation dose to targets in the head and neck promises reduced toxicity and, in some cases, potentially improved local-regional tumor control. Intensity-modulated radiotherapy (IMRT) is a method that allows highly conformal delivery of radiotherapy. In recent years, its use has spread rapidly in both academic and community radiation oncology facilities. The use of IMRT has raised multiple issues related to target definition, optimal treatment delivery methods, and the need to account for anatomic changes occurring during therapy. Some of these issues are reviewed in this article.

On relating the generalized equivalent uniform dose formalism to the linear-quadratic model

Two main approaches are commonly used in the literature for computing the equivalent uniform dose (EUD) in radiotherapy. The first approach is based on the cell-survival curve as defined in the linear-quadratic model. The second approach assumes that EUD can be computed as the generalized mean of the dose distribution with an appropriate fitting parameter. We have analyzed the connection between these two formalisms by deriving explicit formulas for the EUD which are applicable to normal distributions. From these formulas we have established an explicit connection between the two formalisms. We found that the EUD parameter has strong dependence on the parameters that characterize the distribution, namely the mean dose and the standard deviation around the mean. By computing the corresponding parameters for clinical dose distributions, which in general do not follow the normal distribution, we have shown that our results are also applicable to actual dose distributions. Our analysis suggests that caution should be used in using generalized EUD approach for reporting and analyzing dose distributions.