C.F. Behrens

The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques

Pareto optimality is a concept that formalises the trade-off between a given set of mutually contradicting objectives. A solution is said to be Pareto optimal when it is not possible to improve one objective without deteriorating at least one of the other. A set of Pareto optimal solutions constitute the Pareto front. The Pareto concept applies well to the inverse planning process, which involves inherently contradictory objectives, high and uniform target dose on one hand, and sparing of surrounding tissue and nearby organs at risk (OAR) on the other. Due to the specific characteristics of a treatment planning system (TPS), treatment strategy or delivery technique, Pareto fronts for a given case are likely to differ. The aim of this study was to investigate the feasibility of using Pareto fronts as a comparative tool for TPSs, treatment strategies and delivery techniques. In order to sample Pareto fronts, multiple treatment plans with varying target conformity and dose sparing of OAR were created for a number of prostate and head & neck IMRT cases. The DVHs of each plan were evaluated with respect to target coverage and dose to relevant OAR. Pareto fronts were successfully created for all studied cases. The results did indeed follow the definition of the Pareto concept, i.e. dose sparing of the OAR could not be improved without target coverage being impaired or vice versa. Furthermore, various treatment techniques resulted in distinguished and well separated Pareto fronts. Pareto fronts may be used to evaluate a number of parameters within radiotherapy. Examples are TPS optimization algorithms, the variation between accelerators or delivery techniques and the degradation of a plan during the treatment planning process. The issue of designing a model for unbiased comparison of parameters with such large inherent discrepancies, e.g. different TPSs, is problematic and should be carefully considered. fc

Characterizing a pulse-resolved dosimetry system for complex radiotherapy beams using organic scintillators

A fast-readout dosimetry system based on fibre-coupled organic scintillators has been developed for the purpose of conducting point measurements of absorbed dose in radiotherapy beams involving high spatial and temporal dose gradients. The system measures the dose for each linac radiation pulse with millimetre spatial resolution. To demonstrate the applicability of the system in complex radiotherapy fields, output factors and per cent depth dose measurements were performed in solid water for a 6 MV photon beam and compared with Monte Carlo simulated doses for square fields down to 0.6 cm × 0.6 cm size. No significant differences between measurements and simulations were observed. The temporal resolution of the system was demonstrated by measuring dose per pulse, beam start-up transients and the quality factor for 6 MV. The precision of dose per pulse measurements was within 2.7% (1 SD) for a 10 cm × 10 cm field at 10 cm depth. The dose per pulse behaviour compared well with linac target current measurements and accumulated dose measurements, and the system was able to resolve transient dose delivery differences between two Varian linac builds. The system therefore shows promise for reference dosimetry and quality assurance of complex radiotherapy treatments.

A beam-matching concept for medical linear accelerators

The flexibility in radiotherapy can be improved if a patient can be moved between any one of the departments medical linear accelerators without the need to change anything in the patients treatment plan. For this to be possible, the dosimetric characteristics of the various accelerators must be the same, or nearly the same i.e. the accelerators must be beam-matched. During a period of nine months, eight Varian iX accelerators with 6 and 15 MV photon beams and 6–18 MeV electron beams (only four of the eight) were installed at our clinic. All accelerators fulfilled the vendor-defined “fine beam-match” criteria, and a more extensive set of measurements was carried out during commissioning. The measured absorbed dose data for each accelerator were compared with the first accelerator, chosen as reference, and the TPS calculations. Two of the eight accelerators showed a larger discrepancy for the 15 MV beam not revealed by the vendor-defined acceptance criteria, whereas the other six accelerators were satisfactorily matched. The beam-matching acceptance criteria defined by the vendor are not strict enough to guarantee optimal beam-match. Deviations related to dose calculations and to beam-matched accelerators may add up. The safest and most practical way to ensure that all accelerators are within clinical acceptable accuracy is to include TPS calculations in the evaluation. Further, comparisons between measurements and calculations should be done in absolute dose terms.

Pareto front analysis of 6 and 15 MV dynamic IMRT for lung cancer using pencil beam, AAA and Monte Carlo

The pencil beam dose calculation method is frequently used in modern radiation therapy treatment planning regardless of the fact that it is documented inaccurately for cases involving large density variations. The inaccuracies are larger for higher beam energies. As a result, low energy beams are conventionally used for lung treatments. The aim of this study was to analyze the advantages and disadvantages of dynamic IMRT treatment planning for high and low photon energy in order to assess if deviating from the conventional low energy approach could be favorable in some cases. Furthermore, the influence of motion on the dose distribution was investigated. Four non-small cell lung cancer cases were selected for this study. Inverse planning was conducted using Varian Eclipse. A total number of 31 dynamic IMRT plans, distributed amongst the four cases, were created ranging from PTV conformity weighted to normal tissue sparing weighted. All optimized treatment plans were calculated using three different calculation algorithms (PBC, AAA and MC). In order to study the influence of motion, two virtual lung phantoms were created. The idea was to mimic two different situations: one where the GTV is located centrally in the PTV and another where the GTV was close to the edge of the PTV. PBC is in poor agreement with MC and AAA for all cases and treatment plans. AAA overestimates the dose, compared to MC. This effect is more pronounced for 15 than 6 MV. AAA and MC both predict similar perturbations in dose distributions when moving the GTV to the edge of the PTV. PBC, however, predicts results contradicting those of AAA and MC. This study shows that PB-based dose calculation algorithms are clinically insufficient for patient geometries involving large density inhomogeneities. AAA is in much better agreement with MC, but even a small overestimation of the dose level by the algorithm might lead to a large part of the PTV being underdosed. It is advisable to use low energy as a default for tumor sites involving lungs. However, there might be situations where it is favorable to use high energy. In order to deviate from the recommended low energy convention, an accurate dose calculation algorithm (e.g. MC) should be consulted. The study underlines the inaccuracies introduced when calculating dose using a PB-based algorithm in geometries involving large density variations. PBC, in contrast to other algorithms (AAA and MC), predicts a decrease in dose when the density is increased.

Evaluation of setup accuracy for NSCLC patients; studying the impact of different types of cone-beam CT matches based on whole thorax, columna vertebralis, and GTV

Abstract Purpose. The aim of this study is to evaluate the patient setup accuracy by investigating the impact of different types of CBCT matches, performed with 3 (translations only) or 6 (including rotations) degrees-of-freedom (DOF). The purpose is also to calculate and compare CTV to PTV margins based on the various CBCT matches, setups using 2D kV planar imaging or setups using skin markers only (non-IGRT). Material and methods. Setup images from 16 NSCLC patients with weekly CBCT and daily 2D kV planar imaging were analyzed retrospectively. The CBCT matches were based on the columna vertebralis (CV), the whole thorax (WT) and the soft tissue (ST) delineated GTV, where the ST match was chosen as reference. Thus the translational and rotational shifts in three dimensions were assessed. Finally, setup margins were calculated using van Herks margin recipe. Results. For 80% of the investigated 3 DOF/2D kV CV setups, the translational shifts were within [−3, 2] mm for all three directions. Corresponding values for the 6 DOF/non-IGRT CV and the 6 DOF/non-IGRT ST matches were [−5, 8] mm. Furthermore, 80% of all setups were within ± 2° for pitch-, roll- and yaw-rotations, and none exceeded 5°. The calculated margins for non-IGRT, about 10 mm, were reduced to approximately 4 mm, regardless of using IGRT setup by CBCT or 2D kV imaging on CV. However, if using WT CBCT setup, the margin in LNG direction was slightly larger, approximately 6 mm. Conclusion. IGRT for NSCLC is an essential tool for margin reduction, since patient setups based on IGRT leads to approximately half the margin sizes compared to non-IGRT setups. Both CBCT and 2D kV planar imaging yields approximately the same margins for CV/ST matches. The magnitudes of the patient rotations were <5°.

Clinical evaluation of 3D/3D MRI-CBCT automatching on brain tumors for online patient setup verification - A step towards MRI-based treatment planning.

Abstract Background. Magnetic Resonance Imaging (MRI) is often used in modern day radiotherapy (RT) due to superior soft tissue contrast. However, treatment planning based solely on MRI is restricted due to e.g. the limitations of conducting online patient setup verification using MRI as reference. In this study 3D/3D MRI-Cone Beam CT (CBCT) automatching for online patient setup verification was investigated. Material and methods. Initially, a multi-modality phantom was constructed and used for a quantitative comparison of CT-CBCT and MRI-CBCT automatching. Following the phantom experiment three patients undergoing postoperative radiotherapy for malignant brain tumors received a weekly CBCT. In total 18 scans was matched with both CT and MRI as reference. The CBCT scans were acquired using a Clinac iX 2300 linear accelerator (Varian Medical Systems) with an On-Board Imager (OBI). Results. For the phantom experiment CT-CBCT and MRI-CBCT automatching resulted in similar results. A significant difference was observed only in the longitudinal direction where MRI-CBCT resulted in the best match (mean and standard deviations of 1.85±2.68 mm for CT and −0.05±2.55 mm for MRI). For the clinical experiment the absolute difference in couch shift coordinates acquired from MRI-CBCT and CT-CBCT automatching, were ≤2 mm in the vertical direction and ≤3 mm in the longitudinal and lateral directions. For yaw rotation differences up to 3.3 degrees were observed. Mean values and standard deviations were 0.8±0.6 mm, 1.5±1.2 mm and 1.2±1.2 mm for the vertical, longitudinal and lateral directions, respectively and 1.95±1.12 degrees for the rotation (n=17). Conclusion. It is feasible to use MRI as reference when conducting 3D/3D CBCT automatching for online patient setup verification. For both the phantom and clinical experiment MRI-CBCT performed similar to CT-CBCT automatching and significantly better in the longitudinal direction for the phantom experiment.

CTC-ask: a new algorithm for conversion of CT numbers to tissue parameters for Monte Carlo dose calculations applying DICOM RS knowledge

One of the building blocks in Monte Carlo (MC) treatment planning is to convert patient CT data to MC compatible phantoms, consisting of density and media matrices. The resulting dose distribution is highly influenced by the accuracy of the conversion. Two major contributing factors are precise conversion of CT number to density and proper differentiation between air and lung. Existing tools do not address this issue specifically. Moreover, their density conversion may depend on the number of media used. Differentiation between air and lung is an important task in MC treatment planning and misassignment may lead to local dose errors on the order of 10%. A novel algorithm, CTC-ask, is presented in this study. It enables locally confined constraints for the media assignment and is independent of the number of media used for the conversion of CT number to density. MC compatible phantoms were generated for two clinical cases using a CT-conversion scheme implemented in both CTC-ask and the DICOM-RT toolbox. Full MC dose calculation was subsequently conducted and the resulting dose distributions were compared. The DICOM-RT toolbox inaccurately assigned lung in 9.9% and 12.2% of the voxels located outside of the lungs for the two cases studied, respectively. This was completely avoided by CTC-ask. CTC-ask is able to reduce anatomically irrational media assignment. The CTC-ask source code can be made available upon request to the authors.

Introducing multiple treatment plan-based comparison to investigate the performance of gantry angle optimisation (GAO) in IMRT for head and neck cancer

Abstract Background and purpose. The purpose of this study was to evaluate the performance of gantry angle optimisation (GAO) compared to equidistant beam geometry for two inverse treatment planning systems (TPSs) by utilising the information obtained from a range of treatment plans. Material and methods. The comparison was based on treatment plans generated for four different head and neck (H&N) cancer cases using two inverse treatment planning systems (TPSs); Varian Eclipse™ representing dynamic MLC intensity modulated radiotherapy (IMRT) and Oncentra® Masterplan representing segmented MLC-based IMRT. The patient cases were selected on the criterion of representing different degrees of overlap between the planning target volume (PTV) and the investigated organ at risk, the ipsilateral parotid gland. For each case, a number of ‘Pareto optimal’ plans were generated in order to investigate the trade-off between the under-dosage to the PTV (VPTV,D < 95%) or the decrease in dose homogeneity (D5-D95) to the PTV as a function of the mean absorbed dose to the ipsilateral parotid gland (parotid gland). Results. For the Eclipse system, GAO had a clear advantage for the cases with smallest overlap (Cases 1 and 2). The set of data points, representing the underlying trade-offs, generated with and without using GAO were, however, not as clearly separated for the cases with larger overlap (Cases 3 and 4). With the OMP system, the difference was less pronounced for all cases. The Eclipse GAO displays the most favourable trade-off for all H&N cases. Conclusions. We have found differences in the effectiveness of GAO as compared to equidistant beam geometry, in terms of handling conflicting trade-offs for two commercial inverse TPSs. A comparison, based on a range of treatment plans, as developed in this study, is likely to improve the understanding of conflicting trade-offs and might apply to other thorough comparison techniques.

COMPARISON OF IMRT DELIVERY TECHNIQUES AND HELICAL TOMOTHERAPY USING PARETO FRONT EVALUATION

Purpose: The purpose of this work was to explore the possibility to compare treatment-planning- and treatment-delivery systems for intensity modulated radiation therapy (IMRT) using an objective approach. The approach investigated was the Pareto front concept. An additional aim was to adequately compare three different IMRT treatment planning and delivery systemsMaterials and methods: In IMRT treatment planning the goal is to find an optimal compromise between organ at risk (OAR) sparing and target coverage. During the optimization process objectives are chosen for each OAR and for the planning target volume (PTV). For a Pareto optimal plan one objective cannot be improved without worsening another objective. This makes IMRT optimization suitable for Pareto front evaluation. A set of Pareto optimal plans form a Pareto front. By using Pareto front evaluation the influence of individual plans is suppressed and the whole range of plans with the chosen objectives can be evaluated at the same time. Pareto fronts from different treatment planning systems (TPSs) are expected to differ from each other. In this study, different head and neck cases were used. Several plans with varying importance concerning the sparing of a specific OAR were created for each case using different TPSs. The importance of the PTV coverage was held constant for all plans. The TPSs used in the study were Oncentra Masterplan (OMP) (Nucletron B.V.), Eclipse (Varian Medical Systems) and TomoTherapy (Tomotherapy inc.) planning system. A Pareto front was obtained for each TPS by plotting the average OAR dose as a function of underdosed volume of the PTV. The underdosed volume was defined as the relative volume that receives less than 95% of the prescribed dose. Each plan fulfilled the dose restrictions for OARs according to the clinical protocol used apart from the OAR chosen for the trade-off.Results: The TomoTherapy Pareto front is situated below both the OMP front and the Eclipse front indicating that for the same target coverage, the sparing of the parotid is always favourable for this technology. For low priority OAR sparing, however, the Eclipse and the TomoTherapy fronts exhibit almost equal target coverage. As the importance of the OAR increases the target coverage decreases faster for the Eclipse front compared to the TomoTherapy front and is approaching the same coverage as OMP.Conclusion: The results clearly indicate that the approach of using Pareto fronts for different systems is a feasible way to compare different methods and technologies for advanced radiotherapy. For the particular cases studied, TomoTherapy seems to be superior to OMP and Eclipse regarding target coverage and sparing of the parotid gland.

PO-0769: Flattening filter free beam dosimetry with organic scintillators, ionization chambers and diamonds

due to their water equivalency (i.e. they cannot be differentiated from tissue), but accurate localization is necessary for comparison of measured dose to dose calculated on CT images. Materials and Methods: We constructed two mock PSDs with CT-radioopaque metal wire used in place of scintillating fibers. Each mock detector was constructed to the specifications of in-vivo PSDs being used at our institution and consisted of a 7 mm graphite spacer, 2 mm of radio-opaque wire coupled to a clear plastic optical fiber contained in black polyethylene jacketing. 2 mm spherical ceramic fiducials were attached at the end of the detector and to either side of the detector 1 cm distal to the wire as surrogates for calculating the location of the ‘sensitive volume’. The detectors were attached to an endorectal balloon which was subsequently inserted into an anthropomorphic prostate phantom and inflated. A CT scan (2.5 mm slice thickness, the same used when imaging in-vivo detectors in patients) of the phantom was then acquired, and the resulting images imported into the Pinnacle treatment planning system. A script then determined the location of the active volume by calculating a line between the center of the proximal fiducial and a point halfway between the two distal fiducials (i.e. the center of the optical fiber) and contouring 1 mm diameter circles around the line on slices containing the portion of the line between 8 mm and 10 mm. The locations of the resulting contours were compared to the location of the metal wire. This process was repeated ten times – removing and deflating the balloon, detaching the detectors, and then re-setting up the experiment completely each time. Results: The average deviation in the axial plane between the center of the contours and the center of the metal wire was 0.1 mm in the anterior direction (Figure 1). The root-mean-square deviation was 0.4 mm. All contours were within 0.8 mm of the actual location. 13 out of 20 measurements were localized to the correct axial slice, and the other 7 were one slice off. Axial discrepancies were considered more important than SI discrepancies because the dose gradient of patient treatment plans lies primarily along the AP direction. The direction and magnitude of the deviation from actual location for all 20 measurements are shown in Figure 1.