MLC Leaf Research Articles

The Potential Ability of Plan Complexity Metrics on the Dose Calculation and Plans Delivery in Intensity Modulated Radiotherapy.

The excessive modulation of treatment plan during radiotherapy (RT) increases the complexity. Evaluation of the multidimensional relationship between program complexity metrics, computation-based patient-specific quality assurance (PSQA), and conventional measurement-based PSQA could assist in enhancing the robustness of treatment planning, guide the allocation of clinical QA resources, and ultimately lessen QA workload. The fifty-five metrics affecting RT planning and delivery accuracy were calculated by a house-built program to describe the complexity of 404 dynamic IMRT plans, with sensitivity to the small field, aperture position, MLC edge, low MUs, MLC leaf motion, leaf speed/acceleration, etc. The calculation-based PSQA was performed using Monte Carlo (MC) method and Collapsed Cone Convolution (CCC) algorithm, implemented in SciMoCa and Mobius 3D, respectively. The measurement-based PSQA was performed using 3D diode arrays with different geometries covering "O", "+" and " × " shapes which exist in ArcCheck, Delta4 phantom+ (Delta4) and Delta4PT phantom (Delta4PT), respectively. Gamma passing rates (GPRs) were recorded to measure the results of each QA system. This multidimensional relationship was evaluated using correlation analysis and principal component linear regression (PCR) analysis. A total of 4448 GPRs for various QA systems corresponding to two Linacs were counted. The modulation index for speed (MIs) and modulation index for acceleration (MIa) were consistently located at the high points of the radarplots of the Spearman correlation coefficient |rs| between metrics and GPRs of the four QA systems, just except Delta4. Besides, the rs between SciMoCa and ArcCheck were 0.275-0.531 (P ≤ 0.001), SciMoCa and Delta4 were 0.32-0.418 (P ≤ 0.001), and Mobius 3Dand Delta4PT were 0.124-0.226 (P ≤ 0.05). The PCR model's coefficients determination (R2) for SciMoCa were 0.461-0.756 (P ≤ 0.001), ArcCheck were 0.243-0.440 (P ≤ 0.001), Delta4 were 0.268-0.402 (P ≤ 0.001), Mobius 3D were 0.299-0.407 (P ≤ 0.001), and Delta4PT were 0.087-0.141 (P ≤ 0.05). This study is the first overall assessment of the impact of various complexity metrics on the accuracy of TPS calculation and Linac delivery. Of the metrics studied, MIs and MIa metrics have a standout impact on the ability of the TPS calculation and delivery system, extra attention should be paid during the planning process. It is inappropriate to utilize calculation-based QA to predict the results of measurement-based QA since there is a poor correlation between the two. Furthermore, calculation-based QA outperforms measurement-based QA in identifying highly complex plans, which can further guide clinical QA process optimization and save limited clinical resources.

End-to-End Verification and Dosimetric Comparative Study of Brainlab Monte Carlo and Eclipse Acuros XB Photon Dose Calculation Algorithm for VMAT SRS Planning

We commissioned the Brainlab Monte Carlo Dose Calculation Algorithm for VMAT SRS planning and verified it by measurements and comparisons with two other algorithms: Pencil beam and Eclipse Acuros. The end-to-end verification and dosimetric comparative study results are reported in this abstract. Brainlab Elements Cranial SRS (v3.0) provides single lesion planning using VMAT optimization, thus allowing dose modulation with MLC leaf positioning, dose rate, and gantry speed. We commissioned and performed quality assurance for the available dose calculation algorithms, including Pencil Beam (PB) algorithm with only reference beam data (RBM PB) and PB with full beam data (Elements PB), and Monte Carlo (MC) algorithm XVMC. Calculation between the two were compared to each other and to Acuros XB dose calculation algorithm by Varian. Open field MLC, static cone, dynamic MLC, and conical cone plans were calculated with each algorithm. IBA CC01 ionization chamber was used for each measurement, and small field correction factors as determined in TRT-483 were applied. End-to-end tests were performed using an anthropomorphic stereotactic end-to-end verification (STEEV) phantom from CIRS and a phantom/diode array, StereoPHAN/SRSMapCHECK from SunNuclear. Each phantom was CT scanned with 0.5 mm slice thickness. Four clinical plans were optimized in Brainlab Elements Treatment Planning System (TPS). Each plan was calculated with the following algorithms: Elements PB, RBM PB, MC, and Acuros XB with 1 mm dose grid size. The delivered dose was measured with a SunNuclear SRSMapCHECK diode array detector. The calculated dose was compared with the measured dose by Gamma analysis with DTA 1%/1mm, 2%/1mm, and 3%/1mm. The results of point dose measurements for field size larger than 1 × 1 cm2 among measured dose, dose calculated by pencil beam algorithms, and dose calculated by Monte Carlo algorithm were in excellent agreement (1.45% ± 0.7%). For the small rectangular field sizes (0.4 × 1, 0.2 × 1 cm2), Monte Carlo calculation showed superior accuracy and robustness to pencil beam algorithm when compared with measured dose, with percent dose difference 13% and -2.2%, respectively. Monte Carlo calculation have higher gamma results compared with pencil beam algorithm due more accurate calculations with heterogenous materials. Acuros XB showed comparable accuracy with MC in terms of gamma passing rate. The SRS MapCHECK measurement agrees dosimetrically with the plans calculated by Pencil Beam algorithm and the Monte Carlo algorithm XVMC by Brainlab, as well as the Acuros XB dose calculation algorithm by Varian. Point dose calculation for small field dosimetry and gamma analysis using SRS MapCHECK both showed that Monte Carlo algorithm is more robust and is superior in regions of heterogenous materials. Therefore, we recommend that Monte Carlo algorithm for dose calculation be used in clinical SRS and SRT cases.

Universal evaluation of MLC models in treatment planning systems based on a common set of dynamic tests

PurposeTo demonstrate the feasibility of characterising MLCs and MLC models implemented in TPSs using a common set of dynamic beams. Materials and methodsA set of tests containing synchronous (SG) and asynchronous sweeping gaps (aSG) was distributed among twenty-five participating centres. Doses were measured with a Farmer-type ion chamber and computed in TPSs, which provided a dosimetric characterisation of the leaf tip, tongue-and-groove, and MLC transmission of each MLC, as well as an assessment of the MLC model in each TPS. Five MLC types and four TPSs were evaluated, covering the most frequent combinations used in radiotherapy departments. ResultsMeasured differences within each MLC type were minimal, while large differences were found between MLC models implemented in clinical TPSs. This resulted in some concerning discrepancies, especially for the HD120 and Agility MLCs, for which differences between measured and calculated doses for some MLC-TPS combinations exceeded 10%. These large differences were particularly evident for small gap sizes (5 and 10 mm), as well as for larger gaps in the presence of tongue-and-groove effects. A much better agreement was found for the Millennium120 and Halcyon MLCs, differences being within ± 5% and ± 2.5%, respectively. ConclusionsThe feasibility of using a common set of tests to assess MLC models in TPSs was demonstrated. Measurements within MLC types were very similar, but TPS dose calculations showed large variations. Standardisation of the MLC configuration in TPSs is necessary. The proposed procedure can be readily applied in radiotherapy departments and can be a valuable tool in IMRT and credentialing audits.

A method for selecting reference beam model of VMAT plans with three 6MV beam-matched linear accelerators during radiation oncology

Our objective was to provide a method for selecting reference beam model and evaluating the dosimetric accuracy of volumetric modulated arc therapy (VMAT) plans delivered on three Elekta beam-matched linacs during radiation oncology. Beam data was measured on three beam-matched linacs including Synergy1, Synergy2 and VersaHD. For eighteen lung and esophagus cases, fifty-four plans were generated using VMAT technique with three linac beam models respectively for point dose measurement and three-dimensional dose measurement. Each VMAT plan was executed sequentially on three linacs respectively. Measurement results were compared with treatment planning system (TPS) calculation results for all VMAT plans. Among three beam-matched linacs, discrepancy in beam output factor, percentage depth dose at 5 cm, 10 cm, 20 cm depth and MLC leaf offset are all within 1% except 20 × 20 cm2 and 30 × 30 cm2 field sizes, and discrepancy in beam profile is all within 2%. With comparison between measurement result and TPS calculation result, the absolute dose deviations are within the range of ± 3%, and the gamma passing rates are all over 95% for all VMAT plans, which are within the tolerance of clinical acceptability. Compared with all plans delivered on Synegy1 and VersaHD, the point dose discrepancy between measured results and TPS calculated results for plans delivered on Synergy2 is smallest, and the gamma passing rate between measured results and TPS calculated results for plans delivered on Synergy2 is highest. The beam-matched linacs demonstrate good agreement between measurement result and TPS calculation result for VMAT plans. The method can be used for selecting reference beam model for VMAT plans.

Technical note: Feasibility of gating for dynamic trajectory radiotherapy - Mechanical accuracy and dosimetric performance.

Dynamic trajectory radiotherapy (DTRT) extends state-of-the-art volumetric modulated arc therapy (VMAT) by dynamic table and collimator rotations during beam-on. The effects of intrafraction motion during DTRT delivery are unknown, especially regarding the possible interplay between patient and machine motion with additional dynamic axes. To experimentally assess the technical feasibility and quantify the mechanical and dosimetric accuracy of respiratory gating during DTRT delivery. A DTRT and VMAT plan are created for a clinically motivated lung cancer case and delivered to a dosimetric motion phantom (MP) placed on the table of a TrueBeam system using Developer Mode. The MP reproduces four different 3D motion traces. Gating is triggered using an external marker block, placed on the MP. Mechanical accuracy and delivery time of the VMAT and DTRT deliveries with and without gating are extracted from the logfiles. Dosimetric performance is assessed by means of gamma evaluation (3% global/2 mm, 10% threshold). The DTRT and VMAT plans are successfully delivered with and without gating for all motion traces. Mechanical accuracy is similar for all experiments with deviations<0.14° (gantry angle),<0.15° (table angle),<0.09° (collimator angle) and<0.08 mm (MLC leaf positions). For DTRT (VMAT), delivery times are 1.6-2.3 (1.6- 2.5) times longer with than without gating for all motion traces except one, where DTRT (VMAT) delivery is 5.0 (3.6) times longer due to a substantial uncorrected baseline drift affecting only DTRT delivery. Gamma passing rates with (without) gating for DTRT/VMAT were ≥96.7%/98.5% (≤88.3%/84.8%). For one VMAT arc without gating it was 99.6%. Gating is successfully applied during DTRT delivery on a TrueBeam system for the first time. Mechanical accuracy is similar for VMAT and DTRT deliveries with and without gating. Gating substantially improved dosimetric performance for DTRT and VMAT.

PO-2055 Impact of MLC leaf width on plan quality for single-isocenter multi-target conformal-arc SRS

PO-2055 Impact of MLC leaf width on plan quality for single-isocenter multi-target conformal-arc SRS

Impact of electronic portal image quality on Elekta AQUA® collimator isocenter.

The collimator radiation isocenter position determined in AQUA® v3.0 [Elekta AB, Stockholm, Sweden] software test "MLC Leaf and Jaw Position" was independently validated using an in-house MATLAB [Natick, MA: The MathWorks Inc.] script. The AQUA test determines radiation isocenter using the mean field center of nine 4 cm × 4 cm electronic portal imager (EPID) exposures at equidistant collimator angles. Impact of EPID image quality on AQUA reported isocenter for thirteen Elekta linear accelerators with Agility MLC heads were evaluated. Of the thirteen, three had visually and quantitatively identifiable artifacts. For the ten good EPID's there was a systematic 0.25 mm offset of the MATLAB calculated mean field center relative to AQUA in the X-axis and Y-axis. This corresponds to one image pixel and was found to be due to differences in software co-ordinate convention. After subtracting this offset there was no significant difference in AQUA and MATLAB calculated isocenter. For the three machines with poor image quality there was a demonstrated variation in AQUA calculated field center and therefore radiation isocenter relative to MATLAB. Restricting the region of interest (ROI) in AQUA software to only the irradiated section of the EPID brought AQUA and MATLAB result for these three machines into agreement.

Deep learning-based prediction of deliverable adaptive plans for MR-guided adaptive radiotherapy: A feasibility study.

Fast and automated plan generation is desirable in radiation therapy (RT), in particular, for MR-guided online adaptive RT (MRgOART) or real-time (intrafractional) adaptive RT (MRgRART), to reduce replanning time. The purpose of this study is to investigate the feasibility of using deep learning to quickly predict deliverable adaptive plans based on a target dose distribution for MRgOART/MRgRART. A conditional generative adversarial network (cGAN) was trained to predict the MLC leaf sequence corresponding to a target dose distribution based on reference plan created prior to MRgOART using a 1.5T MR-Linac. The training dataset included 50 ground truth dose distributions and corresponding beam parameters (aperture shapes and weights) created during MRgOART for 10 pancreatic cancer patients (each with five fractions). The model input was the dose distribution from each individual beam and the output was the predicted corresponding field segments with specific shape and weight. Patient-based leave-one-out-cross-validation was employed and for each model trained, four (44 training beams) out of five fractionated plans of the left-out patient were set aside for testing purposes. We deliberately kept a single fractionated plan in the training dataset so that the model could learn to replan the patient based on a prior plan. The model performance was evaluated by calculating the gamma passing rate of the ground truth dose vs. the dose from the predicted adaptive plan and calculating max and mean dose metrics. The average gamma passing rate (95%, 3mm/3%) among 10 test cases was 88%. In general, we observed 95% of the prescription dose to PTV achieved with an average 7.6% increase of max and mean dose, respectively, to OARs for predicted replans. Complete adaptive plans were predicted in ≤20 s using a GTX 1660TI GPU. We have proposed and demonstrated a deep learning method to generate adaptive plans automatically and rapidly for MRgOART. With further developments using large datasets and the inclusion of patient contours, the method may be implemented to accelerate MRgOART process or even to facilitate MRgRART.

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.

What is the optimal input information for deep learning-based pre-treatment error identification in radiotherapy?

Deep learning (DL) provides high sensitivity for detecting and identifying errors in pre-treatment radiotherapy quality assurance (QA). This work's objective was to systematically evaluate the impact of different dose comparison and image preprocessing methods on DL model performance for error identification in pre-treatment QA. For 53 volumetric modulated arc therapy (VMAT) and 69 stereotactic body radiotherapy (SBRT) treatment plans of lung cancer patients, mechanical errors were simulated (MLC leaf positions, monitor unit scaling, collimator rotation). Two classification levels were assessed: error type (Level 1) and error magnitude (Level 2). Portal dose images with and without errors were compared using standard (gamma analysis), simple (absolute/relative dose difference, ratio) and alternative (distance-to-agreement, structural similarity index, gradient) dose comparison methods. For preprocessing, different normalization methods (min/max and mean/standard deviation) and image resolutions (32×32, 64×64 and 128×128) were evaluated. All possible combinations of classification level, dose comparison, normalization method and image size resulted in 144 input datasets for DL networks for error identification. Average accuracy was highest for simple dose comparison methods (Level 1: 97.7%, Level 2: 78.1%) while alternative methods scored lowest (Level 1: 91.6%, Level 2: 71.2%). Mean/stdev normalization particularly improved Level 2 classification. Higher image resolution improved error identification, although for SBRT lower image resolution was also sufficient. The choice of dose comparison method has the largest impact on error identification for pre-treatment QA using DL, compared to image preprocessing. Model performance can improve by using simple dose comparison methods, mean/stdev normalization and high image resolution.

Strip detector array (SDA) for beam monitoring in radiotherapy: reconstruction of MLC parameters from multiple projections of flux

Objective. In this paper we propose and investigate a new detector with multiple strip detector arrays (SDA) for monitoring MLC shaped x-ray beams for radiotherapy treatment. Approach. Each SDA measures 1D dose profiles equivalent to dose projections. The goal of such a detector is to determine individual MLC leaf positions as well as the Monitor Units (MU) per MLC segment during radiotherapy. In the present work we investigate an optimal SDA detector configuration and reconstruction algorithm. We determine the accuracy of SDA for different treatment sites (spine, pelvis, retroperitoneum, prostate, brain SRT, SRS, lung and head and neck). We perform a simulation study accounting for different type of MLC leaf positional errors: random MLC leaf, systematic for the whole leaf bank and systematic for an individual leaf. In a similar fashion, we also account for errors in Monitor Units per segment. Main results. We demonstrate that for a broad range of IMRT treatment plans a robust reconstruction of errors is achievable with only 3 projections (3 sets of SDA oriented at at 0°, 45° and 135°). The SDA is capable of capturing both systematic errors in leaf banks and individual leaves as well as random errors sufficient for practical clinical purposes. Significance. These features of the SDA detector makes it suitable for real-time Quality Control of MLC collimated linac output.

First experimental demonstration of VMAT combined with MLC tracking for single and multi fraction lung SBRT on an MR-linac

Background and purposeVMAT is not currently available on MR-linacs but could maximize plan conformality. To mitigate respiration without compromising delivery efficiency, MRI-guided MLC tumour tracking was recently developed for the 1.5 T Unity MR-linac (Elekta AB, Stockholm, Sweden) in combination with IMRT. Here, we provide a first experimental demonstration of VMAT + MLC tracking for several lung SBRT indications. Materials and methodsWe created central patient and phantom VMAT plans (8×7.5 Gy, 2 arcs) and we created peripheral phantom plans (3×18 & 1×34 Gy, 4 arcs). A motion phantom mimicked subject-recorded respiratory motion (A‾=11 mm, f‾=0.33 Hz, drift‾=0.3 mm/min). This was monitored using 2D-cine MRI at 4 Hz to continuously realign the beam with the target. VMAT + MLC tracking performance was evaluated using 2D film dosimetry and a novel motion-encoded and time-resolved pseudo-3D dosimetry approach. ResultsWe found an MLC leaf and jaw end-to-end latency of 328.05(±3.78) ms and 317.33(±4.64) ms, which was mitigated by a predictor. The VMAT plans required maximum MLC speeds of 12.1 cm/s and MLC tracking superimposed an additional 1.48 cm/s. A local 2%/1 mm gamma analysis with a static measurement as reference, revealed pass-rates of 28–46% without MLC tracking and 88–100% with MLC tracking for the 2D film analysis. Similarly, the pseudo-3D gamma passing-rates increased from 22–77% to 92–100%. The dose area histograms showed that MLC tracking increased the GTV D98% by 5–20% and the PTV D95% by 7–24%, giving similar target coverage as their respective static reference. ConclusionMRI-guided VMAT + MLC tracking is technically feasible on the MR-linac and results in highly conformal dose distribution.

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.

PO-1644 Comparison of machine and deep learning models in predicting Elekta MLC leaf positions for VMAT

PO-1644 Comparison of machine and deep learning models in predicting Elekta MLC leaf positions for VMAT

Remote sensing array (RSA) for linac beam monitoring

The purpose of the present work is to evaluate the feasibility of a novel real-time beam monitoring device for medical linacs which remotely senses charge carriers produced in air by the beam without intersecting and attenuating the beamline. The primary goal is to elaborate a theoretical concept of a possible detector geometry and underlying physical model that allows for determination of clinically relevant beam data in real time, namely MLC leaf positions and dose rate. The detector consists of two opposing electrode arrays arranged in two possible orientations around the beamline. Detection of charge carriers is governed by electromagnetic principles described by Shockley–Ramo theorem. Ions produced by ionization of the air column upstream of patient move laterally in an external electric field. According to the method of images, mirror charges and mirror currents are formed in the strip electrodes. Determination of MU rate and MLC positions using the measured signal requires solution of an inverse problem. In the present work we adopted a Least-Square approach and characterized detector response and sensitivity to detection of beam properties for different electrode geometries and MLC shapes. Results were dependent on MLC field shape and the leaf position within the active volume. The accuracy of determination of leaf positions were in the sub-mm range (up to 0.25–1 mm). Additionally, detector sensitivity was quantified by simulating ions/pulse delivered with a radiation transport deterministic computation in 1D in CEPXS/ONEDANT. For a 6 MV linac pulse, signal amplitude per pulse was estimated to be in the lower pA to fA range. We computationally demonstrated feasibility of the remote sensing detector capable of measuring beam parameters such as MLC leaf positions and dose range for each pulse. Future work should focus on optimizing the electrode geometry to increase sensitivity and better reconstruction algorithms to provide more accurate solutions of the inverse problem.

Dosimetric Outcomes for Multiple Intracranial Targets Treated Simultaneously With LINAC-Based Stereotactic Radiosurgery as Dictated by Beam Energy, MLC Leaf Width, and Prescribed Isodose Level

LINAC-based stereotactic radiosurgery (SRS) is often used for treating intracranial tumors. This study aims to evaluate methods for planning multiple brain tumors treated simultaneously with a single isocenter, with dosimetric outcomes as dictated by beam energy, multileaf collimator (MLC) leaf width, and prescribed Isodose Level (IDL).Multiple hypothetical target lesions of varying sizes were contoured on brain MRI images of an index patient to be treated simultaneously in one treatment. The PTVs were constructed to be within 4 respective categories (< 0.5, 0.5-1.0, 1.0-4.0, 4.0-10.0 cc), in inverse proportion to prescription dose range of 16-22.5 Gy. For each lesion, SRS plans were analyzed independently between (1) two photon beam energies (6X-FFF with 1400 MU/min vs. 10X-FFF with 2400 MU/min), (2) two MLC leaf widths (0.5 cm vs. 0.25 cm), and (3) two prescribed IDL (80% vs 90%). Normal tissue sparing was evaluated with the amount of brain volume receiving > 12 Gy (V12) and the dose Gradient Index (GI) - defined as the ratio between volume receiving > 50% of prescribed dose (V50%) and PTV volume. Tumor dose inhomogeneity was analyzed with maximum dose (Dmax) deposited, while conformity was assessed via Conformity Index (CI). Treatment beam-on time to cover all four tumors was also compared. The independent variables of beam energy, MLC leaf width, and prescribed IDL were each held constant when the variable in question was analyzed, with mean relative differences of the dosimetry determined for all 4 lesions of respective volumes.The 4 PTV volumes contoured were 0.24, 0.57, 1.45 and 4.50 cc. Compared to 10X-FFF, the 6X-FFF plans have lower CI by 2.35% ± 2.56%, lower GI by 11.90% ± 2.91%, lower V12 by 15.14% ± 3.84%, and longer beam-on time by 72.69% ± 2.15%. The Dmax was lower by 1.50 ± 0.94%. Compared to 0.5cm MLC leaf-width, the 0.25cm plans have lower CI by 5.60% ± 2.19%, lower GI by 13.53% ± 5.20%, lower V12 by 20.00% ± 4.51%, and longer beam-on time by 1.65% ± 1.49%. The Dmax was lower by 1.50% ± 0.94%. Compared to the 90% prescribed IDL, the 80% plans have lower CI by 4.30% ± 2.72%, lower GI by 22.36% ± 4.57%, lower V12 by 33.81% ± 2.38%, and longer beam-on time by 12.61% ± 1.69%. The Dmax was higher by 12.95% ± 1.57%.This study showed that lower beam energy plans, thinner MLC leaf size, and lower prescribed IDL may provide better brain sparing but incur longer beam-on times. While we have previously shown similar findings for individual tumors treated asynchronously with respective isocenters, this study illustrates the utility in treating multiple intracranial targets at once. This may prove useful for LINAC-based SRS practitioners seeking to customize treatment strategy based on how these variables affect tumor coverage, normal tissue sparing, or treatment duration.B.K. Lee: Employee; Amgen. J. Zhang: Independent Contractor; Veterans Affairs Hospital. W. Inouye: None. W.W. Lien: None.

Portal dosimetry of small unflattened beams

We developed and validated a dedicated small field back–projection portal dosimetry model for pretreatment and in vivo verification of stereotactic plans entailing small unflattened photon beams. For this purpose an aSi–EPID was commissioned as a small field dosimeter. Small field output factors for 6 MV FFF beams were measured using the PTW microDiamond detector and the Agility 160–leaf MLC from Elekta. The back-projection algorithm developed in our department was modified to better model the small field physics. The feasibility of small field portal dosimetry was validated via absolute point dose differences w.r.t. small static beams, and 5 hypofractionated stereotactic VMAT clinical plans measured with the OCTAVIUS 1000 SRS array dosimeter and computed with the treatment planning system Pinnacle v16.2. Dose reconstructions using the currently clinically applied back–projection model were also computed for comparison. We found that the latter yields underdosage of about −8% for square beams with cross section near 10 mm x 10 mm and about −6% for VMAT treatments with PTV volumes smaller than about 2cm3. With the methods described in this work such errors can be reduced to less than the ±3.0% recommendations for clinical use. Our results indicate that aSi–EPIDs can be used as accurate small field radiation dosimeters, offering advantages over point dose detectors, the correct positioning and orientation of which is challenging for routine clinical QA.

Delta4 Discover transmission detector: A comprehensive characterization for in-vivo VMAT monitoring.

To investigate the dosimetric behaviour, influence on photon beam fluence and error detection capability of Delta4 Discover transmission detector. The transmission detector (TRD) was characterized on a TrueBeam linear accelerator with 6 MV beams. Linearity, reproducibility and dose rate dependence were investigated. The effect on photon beam fluence was evaluated in terms of beam profiles, percentage depth dose, transmission factor and surface dose for different open field sizes. The transmission factor of the 10x10 cm2 field was entered in the TPS's configuration and its correct use in the dose calculation was verified recalculating 17 clinical IMRT/VMAT plans. Surface dose was measured for 20 IMRT fields. The capability to detect different delivery errors was investigated evaluating dose gamma index, MLC gamma index and leaf position of 15 manually modified VMAT plans. TRD showed a linear dependence on MU. No dose rate dependence was observed. Short-term and long-term reproducibility were within 0.1% and 0.5%. The presence of the TRD did not significantly affect PDDs and profiles. The transmission factor of the 10x10 cm2 field size was 0.985 and 0.983, for FF and FFF beams respectively. The 17 recalculated plans met our clinical gamma-index passing rate, confirming the correct use of the transmission factor by the TPS. The surface dose differences for the open fields increase for shorter SSDs and greater field size. Differences in surface dose for the IMRT beams were less than 2%. Output variation ≥2%, collimator angle variations within 0.3°, gantry angle errors of 1°, jaw tracking and leaf position errors were detected. Delta4 Discover shows good linearity and reproducibility, is not dependent on dose rate and does not affect beam quality and dose profiles. It is also capable to detect dosimetric and geometric errors and therefore it is suitable for monitoring VMAT delivery.

Reducing treatment machine downtime with a preventative MLC maintenance procedure.

The persistent use of MLCs through VMAT and IMRT is causing additional wear and tear on these mechanical parts, leading to an increase in MLC interlocks, breakdowns and failures. This study investigates the effect of an MLC clean and service procedure on MLC performance and positional accuracy demonstrated through in-house service logbook reports, Varian MLC backlash test results, daily MLC position QC results and Varian TrueBeam trajectory log file data. A service and clean of each individual MLC leaf was carried out on 3 standard MLC and 2 high definition MLC (HDMLC) Varian TrueBeam linacs. In-house service logbook reports, Varian backlash test results, daily MLC picket fence QC results and beam hold data from patient delivery trajectory log files were analysed for up to 6months pre and 2years post the MLC service/clean to assess the impact on unplanned MLC maintenance work and MLC performance. The median (range) of hardware faults reduced from 12 (1-17) pre clean to 0 (0-1) and 4 (1-11) at 12 and 24months respectively for all linacs with the exception of a HDMLC linac where faults increased from 4 pre-clean to 13 and 20 again at 12 and 24months respectively. The reduction in faults in the alternative 4 linacs was consistent with the reduction in the number of MLCs reaching the 0.3mm and the 0.4mm backlash recommendations in the first 12 and 24months following the service/clean. The increase in faults in the HDMLC linac was also consistent with the increase in MLCs reaching the 0.3mm backlash recommendation in the first 12 and 24months. The median (range) of MLCs reaching a daily picket fence QC position tolerance of 0.25mm reduced from 14 (1-40) pre clean to 0 (0) at both 12 and 24months post-clean. This demonstrates the improvement in MLC performance caused by the MLC service/clean but also reveals factors other than MLC position accuracy influence hardware faults. Additionally, the number of beam hold-offs determined from patient delivery trajectory log files were found to have no correlation with the MLC service/clean. The MLC service/clean improves MLC performance and MLC position accuracy, reducing reactive repair work for engineering and physics staff. The results were maintained for 1year post the MLC service/clean, with a trend back towards pre-clean levels in the subsequent 12-24months. This suggests this preventative maintenance work could be performed at a frequency of>2years. This period of reduced faults and improved performance is significant given the 10year expected lifespan of a linac.

Evaluation of Varian Machine Performance Checks for Early Fault Detection

Varian Machine Performance Check (MPC) is an automated and integrated image-based tool for verification of beam and geometry performance of TrueBeam linacs. The tolerances for MPC are set by Varian. The checks involve placing an Isocal Phantom on the treatment couch and a combination of high resolution kV and MV images are taken at different collimator, gantry and couch angles. The images are analyzed and a pass/fail indication is displayed at the end of the check. Daily Beam, 6 MV, geometry checks, enhanced MLC and couch check have been performed in our clinic since April 15th 2019. The enhanced MLC check from initial baseline was 0.18 mm. This started to move beyond the tolerance of 0.2 mm and was investigated by Varian engineers leading to a decision to move the MLC carriage by 1mm yielding a new baseline of 0.03 mm for the MLC leaf offset. Another test which started to fail was the enhanced couch check. This was initially thought to be related to the couch movement but in fact was related to a flatness and symmetry error within the ion chamber which lead to replacing the ion chamber. This problem would have taken a lot longer to present if daily MPC checks were not performed. Overall MPC has been straight forward to implement. This helped us to safely schedule repairs and allowed for earlier detection of failing components.