Leaf Offsets Research Articles

Predicted Inferior Outcomes for Lung SBRT With Treatment Planning Systems That Fail Independent Phantom-Based Audits

More than 15% of radiotherapy clinics fail external audits with anthropomorphic phantoms conducted by Imaging and Radiation Oncology Core-Houston (IROC-H) while passing other industry-standard quality assurance (QA) tests. We seek to evaluate the predicted impact of such failed plans on outcomes for patients treated with stereotactic body radiation therapy (SBRT) for lung tumors. We conducted a retrospective study of 55 patients treated with SBRT for lung tumors with prescription BED10 ≥100Gy using a treatment planning system (TPS) that passed IROC-H phantom audits. Sample linac beam models with introduced errors were commissioned by varying the multi-leaf collimator leaf tip offset parameter (i.e., 'dosimetric leaf gap') over the range +/-1.0 mm relative to the validated model. These models mimic TPS that pass internal QA measures but fail IROC-H tests. Patient plans were recalculated on sample beam models. Predicted tumor control probability (TCP) and normal tissue complication probability (NTCP) were calculated based on published dose-response models. A leaf tip offset value of -1.0 mm decreased the fraction of plans receiving a PTV BED10 ≥100 Gy from 95% to 27%. This translated to a significant decrease in 2-yr TCP of 4.8% (95% CI: 2.0-5.5%) with a decrease in TCP up to 21%. Conversely, leaf tip offset of +1.0 mm resulted in 36% of patients exceeding previously met OAR constraints, including two instances of spinal cord and brachial plexus overdoses and a small increase in chest wall NTCP by 0.7%, (95% CI 0.5%-0.8%). Simulated treatment plans with modest MLC leaf offsets result in lung SBRT plans that significantly under-dose tumor or exceed OAR constraints. These dosimetric endpoints translate to significant detriments in TCP. These simulated plans mimic planning systems that pass internal QA measures but fail independent phantom-based tests, underscoring the need for enhanced quality assurance including external audits of TPS.

Impact of systematic MLC positional uncertainties on the quality of single‐isocenter multi‐target VMAT‐SRS treatment plans

PurposeTo study the impact of systematic MLC leaf positional uncertainties (stemming from mechanical inaccuracies or sub‐optimal MLC modeling) on the quality of intracranial single‐isocenter multi‐target VMAT‐SRS treatment plans. An estimation of appropriate tolerance levels is attempted.MethodsFive patients, with three to four metastases and at least one target lying in close proximity to organs‐at‐risk (OARs) were included in this study. A single‐isocenter multi‐arc VMAT plan per patient was prepared, which served as the reference for dosimetric impact evaluation. A range of leaf offsets was introduced (±0.03 mm up to ±0.30 mm defined at the MLC plane) to both leaf banks, by varying the leaf offset MLC modeling parameter in Monaco for all the prepared plans, in order to simulate projected leaf offsets of ±0.09 mm up to ±0.94 mm at the isocenter plane, respectively. For all offsets simulated and cases studied, dose distributions were re‐calculated and compared with the corresponding reference ones. An experimental dosimetric procedure using the SRS mapCHECK diode array was also performed to support the simulation study results and investigate its suitability to detect small systematic leaf positional errors.ResultsProjected leaf offsets of ±0.09 mm were well‐tolerated with respect to both target dosimetry and OAR‐sparing. A linear relationship was found between D 95% percentage change and projected leaf offset (slope: 12%/mm). Impact of projected offset on target dosimetry was strongly associated with target volume. In two cases, plans that could be considered potentially clinically unacceptable (i.e., clinical dose constraint violation) were obtained even for projected offsets as small as 0.19 mm. The performed experimental dosimetry check can detect potential small systematic leaf errors.ConclusionsPlan quality indices and dose–volume metrics are very sensitive to systematic sub‐millimeter leaf positional inaccuracies, projected at the isocenter plane. Acceptable and tolerance levels in systematic MLC uncertainties need to be tailored to VMAT‐SRS spatial and dosimetric accuracy requirements.

SU‐G‐TeP4‐03: A Multileaf Collimator Calibration and Quality Assurance Technique Using An Electronic Portal Imaging Device

Purpose:To develop an accurate and quick multileaf collimator (MLC) calibration and quality assurance technique using an electronic portal imaging device (EPID)Methods:The MLC models used include the MLCi and Agility (Elekta Ltd). This technique consists of two 22(L)x10(W) cm2 fields with 00 and 1800 collimator angles centered to an offset EPID. The MLC opening is estimated by calculating the profile at the image's center in the image's horizontal direction. Scans in the image's vertical direction were calculated every 20 pixels in the inner 70% of estimated MLC opening. The profiles’ edges were fitted with linear equations to determine the image's rotation angle. Then, crossline profiles were scanned at the center of each leaf taking into account the leaf's width at isocenter and the rotation angle. The profiles’ edges determine the location of the leaves’ edges and these were subtracted from the reference leaf's position in order to determine the relative leaf offsets. The edge location of all profiles was determined by using the parameterized gradient of the penumbra region. The technique was tested against an established diode array‐based method, and for different MLC systems, patterns, gantry angles, days, energies, beam modalities and MLC openings.Results:The differences between the proposed and established methods were 0.26±0.19mm. The leaf offsets’ deviation was <0.3mm (5 months period). For pattern fields, the differences between predetermined and calculated offsets were 0.18±0.18mm. The leaf offset deviation of measurements with different energies and MLC openings were <0.1mm and <0.3mm, respectively. The differences between offsets of FF and FFF beams were 0.01±0.02mm (<0.07mm). The differences between the offsets at different gantry angles were 0.08±0.15mm.Conclusion:The proposed method proved to be accurate and efficient in calculating the relative leaf offsets. Parameterized field edge is essential to obtain accurate result by eliminating the noise from EPID.

Utilizing knowledge from prior plans in the evaluation of quality assurance

Increased interest regarding sensitivity of pre-treatment intensity modulated radiotherapy and volumetric modulated arc radiotherapy (VMAT) quality assurance (QA) to delivery errors has led to the development of dose-volume histogram (DVH) based analysis. This paradigm shift necessitates a change in the acceptance criteria and action tolerance for QA. Here we present a knowledge based technique to objectively quantify degradations in DVH for prostate radiotherapy.Using machine learning, organ-at-risk (OAR) DVHs from a population of 198 prior patients’ plans were adapted to a test patient’s anatomy to establish patient-specific DVH ranges. This technique was applied to single arc prostate VMAT plans to evaluate various simulated delivery errors: systematic single leaf offsets, systematic leaf bank offsets, random normally distributed leaf fluctuations, systematic lag in gantry angle of the mutli-leaf collimators (MLCs), fluctuations in dose rate, and delivery of each VMAT arc with a constant rather than variable dose rate.Quantitative Analyses of Normal Tissue Effects in the Clinic suggests V75Gy dose limits of 15% for the rectum and 25% for the bladder, however the knowledge based constraints were more stringent: 8.48 ± 2.65% for the rectum and 4.90 ± 1.98% for the bladder. 19 ± 10 mm single leaf and 1.9 ± 0.7 mm single bank offsets resulted in rectum DVHs worse than 97.7% (2σ) of clinically accepted plans. PTV degradations fell outside of the acceptable range for 0.6 ± 0.3 mm leaf offsets, 0.11 ± 0.06 mm bank offsets, 0.6 ± 1.3 mm of random noise, and 1.0 ± 0.7° of gantry-MLC lag.Utilizing a training set comprised of prior treatment plans, machine learning is used to predict a range of achievable DVHs for the test patient’s anatomy. Consequently, degradations leading to statistical outliers may be identified. A knowledge based QA evaluation enables customized QA criteria per treatment site, institution and/or physician and can often be more sensitive to errors than criteria based on organ complication rates.

SU‐GG‐T‐190: Effects of the MLC Leaf Offset on IMRT Dose Distribution

Purpose: The purpose of this study is to investigate the dosimetric‐effective leaf offset of the multi‐leaf‐collimators (MLC) and its effects on accurate dose delivery and reliable patient‐specific quality assurance (QA) for intensity‐modulated radiation therapy (IMRT). Methods: The effective MLC leaf offsets were determined by simulating the picket‐fence film measurement with variable leaf offsets and comparing with the measured dose profiles. The IMRT dose distributions were calculated using intensity maps built from the actual deliverable IMRT leaf sequences with and without considering the MLC leaf offset. The mean dose of the treatment target and voxel doses in the high dose regions were compared and evaluated for 7 IMRT plans generated for Varian 21EX and Siemens Primus linear accelerators. Results: By comparing the calculated picket‐fence dose profiles with film measurements, leaf offsets of 1mm and −0.3mm were determined for the Varian 21EX and Siemens Primus machines, respectively. The mean target dose was increased by up to 7.8% and the standard deviation of the voxel dose discrepancy was about 5% for Varian IMRT plans when the MLC leaf offset was applied in the dose calculation. These effects will be reduced to half if only 0.5mm leaf offset is considered in the dose calculation. The effects on Siemens IMRT plans were smaller due to the smaller leaf offset. The mean dose was reduced by up to 2.3% and the standard deviation of the voxel dose discrepancy was about 0.5%. Conclusions: It can be concluded that the MLC leaf offset can affect the mean dose significantly and cause uncertainties in individual voxel doses. The dose uncertainties caused by MLC leaf offset are one of the major uncertainty sources for measurement‐based IMRT QA because it is usually not fully considered in the treatment planning system.

SU‐GG‐T‐300: Method for In‐House Leaf‐Dependent MLC Offset Correction

Purpose: Manufacturer recommended rounded leaf offsets for the Philips Pinnacle treatment planning system are inaccurate for leaves away from the central axis, and for varying energies. The need for an in‐house MLC rounded leaf offset correction is established, as well as a method for determining the offsets for individual MLC leaves. Materials and Methods: A standard picket‐fence test is developed with 2 cm separations across a 25×25 field. Dose distributions are calculated for the test, with 20th leaf offset values for the X = 0.0 position ranging from −2.0 to +2.0 mm from the nominal leaf position, using the manufacturer recommended offset curve for leaves 1–40. Dose profiles are collected along the cross‐plane of the 20th leaf. The picket‐fence test plan is delivered to a film, in phantom at 90cm SSD and 10 cm depth, for 6 and 10 MV energies. Dose profiles are measured through the central axis and superimposed on the calculated profiles produced by the TPS. The profiles are compared for agreement. Results: It was found that the measured dose profiles do not match manufacturer recommended offsets for leaves away from the central axis. If the calibrated leaf (20th) is matched to the tabular data, there is deviation in the picket‐fence test at distances >5.0 cm from the central axis, resulting is dose discrepancies. Manufacturer‐recommended offsets were also observed to be inaccurate for the 10 MV beam, exhibiting an energy‐dependence of the required offset values. Conclusions: It is found that manufacturer recommended rounded leaf offsets are inaccurate and in‐house measurements are required to determine appropriate offsets for groups of leaves near and away from the beam's central axis. It was also found that there is an energy dependence for these offsets. A method for making in‐house corrections is established by using measured and calculated dose distributions.

Poster - Wed Eve-49: Patient Specific IMRT QC Tolerance Criteria and the Detection of Systematic Errors in MLC Leaf Position

Patient specific IMRT QC remains standard practice in most clinics. We have evaluated the feasibility of detecting systematic errors in MLC leaf position with IMRT QC based on diode and aSi area detectors. 12 head and neck (HN γ with 3% AD, 3mm DTA; 5% AD, 3mm DTA and 3% RD, 3mm DTA. This sequence applied to both H&N and prostate fields although the H&N fields, being more highly modulated, exhibited greater sensitivity to systematic MLC leaf offsets. The EPID study, which was software limited to the γ criterion, showed higher sensitivity with [2% AD/2mm DTA] γ criteria. Due to the distribution of passing rates in a population of IMRT fields we conclude that patient specific QC alone is not sufficient to identify potentially clinically significant systematic MLC offsets and must be supplemented with regular QC of the MLC.

Comprehensive fluence model for absolute portal dose image prediction

Amorphous silicon (a-Si) electronic portal imaging devices (EPIDs) continue to be investigated as treatment verification tools, with a particular focus on intensity modulated radiation therapy (IMRT). This verification could be accomplished through a comparison of measured portal images to predicted portal dose images. A general fluence determination tailored to portal dose image prediction would be a great asset in order to model the complex modulation of IMRT. A proposed physics-based parameter fluence model was commissioned by matching predicted EPID images to corresponding measured EPID images of multileaf collimator (MLC) defined fields. The two-source fluence model was composed of a focal Gaussian and an extrafocal Gaussian-like source. Specific aspects of the MLC and secondary collimators were also modeled (e.g., jaw and MLC transmission factors, MLC rounded leaf tips, tongue and groove effect, interleaf leakage, and leaf offsets). Several unique aspects of the model were developed based on the results of detailed Monte Carlo simulations of the linear accelerator including (1) use of a non-Gaussian extrafocal fluence source function, (2) separate energy spectra used for focal and extrafocal fluence, and (3) different off-axis energy spectra softening used for focal and extrafocal fluences. The predicted energy fluence was then convolved with Monte Carlo generated, EPID-specific dose kernels to convert incident fluence to dose delivered to the EPID. Measured EPID data were obtained with an a-Si EPID for various MLC-defined fields (from 1 x 1 to 20 x 20 cm2) over a range of source-to-detector distances. These measured profiles were used to determine the fluence model parameters in a process analogous to the commissioning of a treatment planning system. The resulting model was tested on 20 clinical IMRT plans, including ten prostate and ten oropharyngeal cases. The model predicted the open-field profiles within 2%, 2 mm, while a mean of 96.6% of pixels over all IMRT fields was in agreement with the 2%, 3 mm criteria. This model demonstrates accuracy commensurate to existing methods for IMRT pretreatment verification with portal dose image prediction of complex clinical examples (< 2%, 3 mm).

SU‐GG‐T‐263: IMRT Beamlet Match‐Line Dose Heterogeneities Associated with Varian 120 MLCs

Purpose: To measure the dosimetric consequences of a range of MLC leaf offsets, examining effects of leaf tip transmission and “scallop edge” overshine from rounded Varian MLC leaves. In particular, this investigation focuses on how these effects influence the dose heterogeneity of the match‐line between abutted beamlet fields that are often present in step‐and‐shoot IMRT. Method and Materials: Offset values from 0.0 to 1.0 mm were evaluated. For each offset, two abutted 2×2cm2 MLC‐shaped fields were delivered sequentially using 6 MV photons from a Varian Platinum EX accelerator with a 120 leaf MLC. Four different techniques—Kodak EDR‐2 film, GAFChromic EBT film, CC01 Wellhofer ion chamber (1 mm radius), and 1 mm3 LiF TLD chips—were used to measure delivered dose at depths of 5 to 15 cm. Film data was taken at 100 SAD. TLD and ion chamber data were collected at 400 cm SSD to increase their effective resolution. Results: Increasing the offset from 0.0 to 0.5 mm decreased the average overdose from 30 to 10% in the abutment region. For offsets greater than 0.5 mm, dose at the center of the match line decreased, but dose inhomogeneities became more pronounced due to effects of overshine, scatter, and leaf tip penumbra. At larger offsets, both over‐ and underdoses of 5 to 10% were present in the abutment region. Conclusion: The measured dose distributions suggest that an optimum offset provides, at best, a balance of over‐ and underdosing in abutment regions. Our data show that the choice of offset significantly changes the dose distribution in a region approximately 6 mm wide at the match line. The width of this high‐gradient area is sufficient to influence clinical IMRT doses delivered.

TU‐D‐M100F‐03: Tracing the Sources of Absolute Dose Errors in IMRT Plan Verifications

Purpose: Several years since the advent of IMRT, most institutions still perform experimental plan verifications with film and ion‐chamber. In the past year of measurements of Pinnacle3 IMRT plans in our clinic, most isocenter dose measurements were verified to be within 3%, but the 10% that were off by 4–7% were repeated or required MU adjustments. In this work, we trace the main sources of discrepancies by measurement and simulation. Methods: We used an independent dose calculation engine (MCKS) that performs kernel‐based superposition using Monte Carlo sampling of photons, interaction points, and corresponding monoenergetic kernels. The photon source for the simulations is a single phasespace plane scored just above the collimator and generated by an EGS/BEAMnrc code. Even though MCKS models the detailed MLC design (curved ends, tongue‐and‐groove, inter‐leaf gap, and leaf offsets) the MLC material density is fine‐tuned with the measurement of “uniform” intensity map delivered as sequence of narrow strips, which amplifies the leakage dose several fold. Results &amp; Conclusion: Using the code and measurement, we found that a major source of error in IMRT plans from Pinnacle3 is the handling of MLC leakage. For example, if a 1.8% MLC transmission is used, then delivering a 10×10 field with ten 10×1 strips produces a dose overestimation by 12% on the central axis. This reduces to 8% if a 1.5% value is used. In typical IMRT plans, the leakage error is less dramatic, but can frequently exceed the 3% acceptance criterion. Also, no single transmission value is suitable for all possible IMRT fields because MLC scatter varies with field size and shape. Some errors also result from the use of lumped empirical square field output factors to complex IMRT segments without regard to the energy or direction of head scatter photons.

SU-EE-A2-04: Comparison of a MLC Calibration Method Using a Diode Array and Electronic Portal Imaging Device

Purpose: Current methods of MLC calibration and quality assurance include the use of graph paper, scanning water tanks, ion chambers, film and EPIDs; these methods can be both laborious and/or non-quantitative. We propose a convenient and quantitative method for calibrating and performing routine quality assurance for MLCs. Method and Materials: The Profiler 2 (Sun Nuclear Corp., Melbourne, FL), a two dimensional diode array, was visually aligned to the backup jaw and irradiated with an Elekta linac. The backup jaw served as a radiation reference line and was used to determine the positional diode offsets. The MLC was stepped over the Profiler 2 and the 50% position for each diode was determined. Leaf offsets were calculated by offsetting each diodes 50% position by the 50% position of the diode corresponding to leaf pair 20 and subtracting the corresponding positional diode offset. This method was repeated with an EPID for comparison purposes. Results: Linear dose changes of approximately 15%/mm and 13.5%/mm were observed in the penumbras of the backup jaw and MLC, respectively. Leaf positions measured by the EPID and Profiler 2 differed on average by ± 0.12 mm per leaf. Leaf reproducibility of 0.36 mm or better was observed and minimal reproducibility changes were seen with the backup jaw. Conclusion: This work demonstrates the potential of the Profiler 2 as a tool for calibrating and performing quantitative QA for MLC leaf positioning. The Profiler 2 methods are fast, taking an average of 20 minutes to perform and accurately represent leaf positions and reproducibility. Conflict of Interest: This work was supported in part by SBIR Contract No. HHSN261200522014C, ADB Contract No. N43-CM-52214, the University of Florida and Sun Nuclear Corporation.

SU‐FF‐T‐198: Efficient and Automated MLC QA at Variable Gantry Angles for IMRT QA

Purpose: The success of an IMRT program depends upon the accuracy of the Multi‐leaf Collimator's (MLC). The usual QA and calibration of MLC's are carried out at a gantry angle of 0°. We have developed a tool, which efficiently and accurately, measures the MLC offsets from desired position at different gantry angles. Materials/Methods: Data was acquired on a Siemens Oncor linear accelerator, which was equipped with an EPID for a period of 6 weeks. The geometric corrections are applied to the images at the imaging workstation. The EPID was exposed to 5 strips of width equal to 2cm. Data was obtained at various gantry angles. The data was compared with the template and later evaluated with software developed in Matlab 7.1. We compared the results from two edge detection algorithms, ‘Sobel’ and ‘Canny’. Data was obtained to verify the accuracy of the auto initialization process. Results: Time require to obtain and analyze MLC strip data at gantry angles of 0°, 90°, 180°, 270° was 12 minutes. It was observed that the overall effect gantry angle on error distribution is not significant, i.e. it's within ± 2mm. Effect of leaf position on error distribution, Pre and post AI, and weekly drifts were evaluated. It was observed that the percentage of leaves with a cumulative error less than 1mm at gantry angle of 0 and 180 was 80 %, while that for gantry angle of 90 and 270 was 72%. Conclusion: The tool helps the physicist and service engineer regarding the frequency and magnitude of AI/Calibration required. Currently the service engineer enters the leaf offsets manually to correct the encoder, which is stored in an EPROM. We plan to enter the offsets directly from software presented here to the EPROM via the controller card.

An experimental investigation into the radiation field offset of a dynamic multileaf collimator

In this study we investigate the characteristics of a rounded leaf end multileaf collimator (MLC) that is used for delivering intensity-modulated radiotherapy (IMRT) with a Varian linear accelerator. The rounded leaf end MLC design results in an offset between the radiation field edge (the physical leaf position) and the light field (the geometric leaf position). We call this the radiation field offset (RFO). The leaf position is calibrated to the leaf tip at the mid-leaf plane. There is an additional offset between the geometric leaf position and the projected leaf tip position that varies as a function of distance from the collimator central axis due to the MLC geometry. We call this the leaf position offset (LPO). There is a lack of consistency in the interpretation and implementation of the RFO and the LPO in the literature. We investigated the RFO and the LPO on Varian's 600 C/D and 21 EX linear accelerators. We used a combination of film and ion chamber measurements of static, segmental MLC (SMLC) and dynamic MLC (DMLC) fields to quantify the leaf offsets across the range of leaf positions. We were able to improve the dosimetry at large off-axis positions with minor adjustments to the vendor's LPO file. The RFO was determined to within 0.1 mm accuracy at the collimator central axis. The measured RFO value depends on whether the method is based on the radiation field edge position or on an integral dose measurement. The integral dose method results in an RFO that is approximately 0.2 mm greater than the radiation field edge method. The difference is due to the MLC penumbra shape. We propose a methodology for measuring and implementing MLC leaf offsets that is suitable for both SMLC and DMLC IMRT. In addition, we propose some definitions that more clearly describe the MLC leaf position for accurate IMRT dosimetry.