Multileaf Collimator Apertures Research Articles

Feasibility of a Single-Fraction Stereotactic Dose of 30 Gy to Solitary Lung Lesions on Halcyon.

Purpose We sought to explore the feasibility of using the current co-planar Halcyon ring delivery system (RDS) with a novel multileaf collimator (MLC) aperture shape controller in delivering a single high dose of 30 Gy to solitary lung lesions via stereotactic body radiotherapy (SBRT). Materials and methods Thirteen non-small-cell lung cancer (NSCLC) patients previously treated with a single dose of 30 Gy to lung lesions via SBRT on the TrueBeam (6MV-FFF) using non-coplanar volumetric modulated arc therapy (VMAT) arcs were anonymized and replanned onto the Halcyon RDS (6MV-FFF) following RTOG-0915 single-fraction criteria. The Halcyon plans utilized a novel dynamic conformal arc (DCA)-based MLC-fitting approach before VMAT optimization with a user-defined aperture shape controller option. The clinical TrueBeam and Halcyon plans were compared via their protocol compliance, target conformity, gradient index, and dose to organs-at-risk (OAR). Treatment delivery efficacy and accuracy were assessed through end-to-end quality assurance (QA) tests on Halcyon and independent dose verification via in-house Monte Carlo (MC) second-check validation. Results All Halcyon lung SBRT plans met RTOG-0915 protocol's requirements for target coverage, conformity, and gradient indices, and maximum dose 2 cm away from the target (D2cm) while being statistically insignificant (p > 0.05) when compared to clinical TrueBeam plans. Additionally, Halcyon provided a similar dose to OAR except for the ribs, where Halcyon demonstrated a lower maximum dose (15.22 Gy vs 17.01 Gy, p < 0.001). However, Halcyon plans required a higher total monitor unit (8892 MU vs 7413 MU, p < 0.001), resulting in a higher beam modulation factor (2.96 MU/cGy vs 2.47 MU/cGy, p < 0.001) and an increase in beam-on time by a factor of 2.1 (11.11 min vs 5.3 min, p < 0.005). End-to-end QA measurements demonstrate that Halcyon plans were clinically acceptable with an average gamma passing rate of 99.8% for 2%/2mm criteria and independent MC 2nd checks within ±2.86%. Conclusion Our end-to-end testing and validation study demonstrates that by utilizing a DCA-based MLC aperture shape controller before VMAT optimization, Halcyon can be used for delivering a single dose of lung SBRT treatment. However, future improvements of Halcyon RDS are recommended to allow higher output rates, rotational couch corrections, and an integrated intrafraction motion management system that will further enhance Halcyon's capability for site-specific single dosage of SBRT.

Experimental comparison of linear regression and LSTM motion prediction models for MLC-tracking on an MRI-linac.

Magnetic resonance imaging (MRI)-guided radiotherapy with multileaf collimator (MLC)-tracking is a promising technique for intra-fractional motion management, achieving high dose conformality without prolonging treatment times. To improve beam-target alignment, the geometric error due to system latency should be reduced by using temporal prediction. To experimentally compare linear regression (LR) and long-short-term memory (LSTM) motion prediction models for MLC-tracking on an MRI-linac using multiple patient-derived traces with different complexities. Experiments were performed on a prototype 1.0T MRI-linac capable of MLC-tracking. A motion phantom was programmed to move a target in superior-inferior (SI) direction according to eight lung cancer patient respiratory motion traces. Target centroid positions were localized from sagittal 2D cine MRIs acquired at 4Hz using a template matching algorithm. The centroid positions were input to one of four motion prediction models. We used (1) a LSTM network which had been optimized in a previous study on patient data from another cohort (offline LSTM). We also used (2) the same LSTM model as a starting point for continuous re-optimization of its weights during the experiment based on recent motion (offline+online LSTM). Furthermore, we implemented (3) a continuously updated LR model, which was solely based on recent motion (online LR). Finally, we used (4) the last available target centroid without any changes as a baseline (no-predictor). The predictions of the models were used to shift the MLC aperture in real-time. An electronic portal imaging device (EPID) was used to visualize the target and MLC aperture during the experiments. Based on the EPID frames, the root-mean-square error (RMSE) between the target and the MLC aperture positions was used to assess the performance of the different motion predictors. Each combination of motion trace and prediction model was repeated twice to test stability, for a total of 64 experiments. The end-to-end latency of the system was measured to be (389 ± 15)ms and was successfully mitigated by both LR and LSTM models. The offline+online LSTM was found to outperform the other models for all investigated motion traces. It obtained a median RMSE over all traces of (2.8 ± 1.3)mm, compared to the (3.2 ± 1.9)mm of the offline LSTM, the (3.3 ± 1.4)mm of the online LR and the (4.4 ± 2.4)mm when using the no-predictor. According to statistical tests, differences were significant (p-value <0.05) among all models in a pair-wise comparison, but for the offline LSTM and online LR pair. The offline+online LSTM was found to be more reproducible than the offline LSTM and the online LR with a maximum deviation in RMSE between two measurements of 10%. This study represents the first experimental comparison of different prediction models for MRI-guided MLC-tracking using several patient-derived respiratory motion traces. We have shown that among the investigated models, continuously re-optimized LSTM networks are the most promising to account for the end-to-end system latency in MRI-guided radiotherapy withMLC-tracking.

Dosimetrical assessment of jaw tracking technique in volumetric modulated arc therapy for a sample of patients with lateralised targets

Abstract Introduction: In modulated radiotherapy treatments with the jaw tracking technique (JTT), the collimator jaws can dynamically follow the multileaf collimator apertures and reduce radiation leakage. This reduction protects normal tissue from unwanted doses. Previous research has highlighted the importance of defining which patients will benefit most from JTT. Besides, some authors have expressed their concerns about possible increases in monitor units (MUs). Treatments of patients with peripheral targets and isocentre located in the patient’s midline are of particular interest. The current work assessed the effect of JTT on these cases. Methods: JTT plans for thirty-two patients were compared to plans with the static jaws technique. The volumes of normal tissue receiving 5 Gy (V5), 10 Gy (V10) and 20 Gy (V20), mean dose (Dmean), target coverage parameters D95, D2% and Paddick’s conformity index (PCI) were compared. MUs were also registered for comparisons. The decrease in the jaws opening with JTT was correlated to the decrease in dose values in normal tissue. Results: Small decreases were observed in D95 and in D2% values, without statistical significance. A 5% average decrease in PCI values was noticed as well as significant decreases in V5, V10 and Dmean values, 9% on average. A 3% decrease in V20 was also observed. The number of MUs decreased by 2%. A significant correlation was found between the reduction of the secondary collimation opening areas and the dose delivered to normal tissue. Conclusions: JTT technique improved normal tissue protection in volumetric modulated arc therapy treatments for the patients included in the present study.

Small-field dosimetry with detector-specific output correction factor for single-isocenter stereotactic radiotherapy of single and multiple brain metastases.

Recently, the International Atomic Energy Agency and the American Association of Physicists in Medicine reported correction factors (CFs) for detector-response variation considering the uncertainty in detector readings in small-field dosimetry. In this study, the effect of CFs on small-field dosimetry measurements was evaluated for single-isocenter stereotactic radiotherapy for brain metastases. The output factors (OPFs) were measured with and without CFs in a water-equivalent sphere phantom using TrueBeam with a flattening-filter-free energy of 10 MV. Five detectors were used in a perpendicular orientation: CC01, 3D pinpoint ionization chambers, unshielded SFD detector, shielded EDGE detector, and microDiamond detector. First, the square-field sizes were set to 5-100mm using a multi-leaf collimator (MLC) field. The OPFs were evaluated in the presence and absence of CFs. Second, single-isocenter stereotactic irradiation was performed on 22 brain metastases in 15 patients following dynamic conformal arc (DCA) treatment. The equivalent field size was calculated using the MLC aperture for each planning target volume. For the OPFs, the mean deviations from the median of the doses measured with detectors other than the CC01 for square-field sizes larger than 10mm were within ± 4.3% of the median without CFs, and ± 3.3% with CFs. For DCA plans, the deviations without and with CFs were -2.3 ± 1.9% and -4.8 ± 2.4% for CC01, -1.1 ± 3.0% and 1.0 ± 1.6% for 3D pinpoint, 8.8 ± 3.0% and 2.9 ± 2.8% for SFD, -3.1 ± 3.0% and -13.5 ± 4.0% for EDGE, and 8.9 ± 2.1% and 0.8 ± 1.9% for microDiamond. This feasibility study confirmed that the deviation of the detectors can be reduced using an appropriate detector with CFs.

Dosimetric comparison and validation of Eclipse Anisotropic Analytical Algorithm (AAA) and AcurosXB (AXB) algorithms in RapidArc-based radiosurgery plans of patients with solitary brain metastasis.

Stereotactic radiosurgery (SRS) is increasingly being used to manage solitary or multiple brain metastasis. This study aims to compare and validate Anisotropic Analytical Algorithm (AAA) and AcurosXB (AXB) algorithms of Eclipse Treatment Planning System (TPS) in RapidArc-based SRS plans of patients with solitary brain metastasis. Twenty patients with solitary brain metastasis who have been already treated with RapidArc SRS plans calculated using AAA plans were selected for this study. These plans were recalculated using AXB algorithm keeping the same arc orientations, multi-leaf collimator apertures, and monitor units. The two algorithms were compared for target coverage parameters, isodose volumes, plan quality metrics, dose to organs at risk and integral dose. The dose calculated by the TPS using AAA and AXB algorithms was validated against measured dose for all patient plans using an in-house developed cylindrical phantom. An Exradin A14SL ionization chamber was positioned at the center of this phantom to measure the in-field dose. NanoDot Optically Stimulated Luminescent Dosimeters (OSLDs) (Landauer Inc.) were placed at distances 3.0 cm, 4.0 cm, 5.0 cm, and 6.0 cm respectively from the center of the phantom to measure the non-target dose. In addition, the planar dose distribution was measured using amorphous silicon aS1000 Electronic Portal Imaging Device. The measured 2D dose distribution was compared against AAA and AXB estimated 2D distribution using gamma analysis. All results were tested for significance using the paired t-test at 5% level of significance. Significant differences between the AAA and AXB plans were found only for a few parameters analyzed in this study. In the experimental verification using cylindrical phantom, the difference between the AAA calculated dose and the measured dose was found to be highly significant (p < 0.001). However, the difference between the AXB calculated dose and the measured dose was not significant (p = 0.197). The difference between AAA/AXB calculated and measured at non-target locations was statistically insignificant at all four non-target locations and the dose calculated by both AAA and AXB algorithms shows a strong positive correlation with the measured dose. The results of the gamma analysis show that the AXB calculated planar dose is in better agreement with measurements compared to the AAA. Even though the results of the dosimetric comparison show that the differences are mostly not significant, the measurements show that there are differences between the two algorithms within the target volume. The AXB algorithm may be therefore more accurate in the dose calculation of VMAT plans for the treatment of small intracranial targets. For non-target locations either algorithm can be used for the estimation of dose accounting for their limitations in non-target dose estimations.

Plan Complexity and Delivery Accuracy of Knowledge-based Volumetric Modulated Arc Therapy Plans with Single Optimization for Oropharyngeal Cancer.

We investigated the plan complexity of volumetric modulated arc therapy (VMAT) with knowledge-based plan (KBP) for oropharyngeal cancer (OPC) with a single optimization and whether it could be used clinically. KBP model was configured using 55 consecutive OPC and nasopharyngeal cancer plans. Plan complexity as a characteristic of multileaf collimator (MLC) motion and γ pass rate (2%/2 mm criterion) were compared between clinical manual plan (CMP) and KBP for other 10 plans. Plan complexity metrics that had significant differences (p<0.05) (CMP vs. KBP), were mean lateral displacement of MLC from central axis (15.82 mm vs. 18.90 mm), proportions of MLC aperture sizes of ≤5 mm (0.14 vs. 0.11), ≤10 mm (0.24 vs. 0.19), and ≤20 mm (0.41 vs. 0.34), and monitor units (578.68 vs. 505.04). The γ pass rate was 91.3% vs. 93.3%. Single optimized KBP for OPC had simple plan complexity features and comparable delivery accuracy to CMP, and could be clinically applied.

Dose-based optimisation for multi-leaf collimator tracking during radiation therapy

Motion in the patient anatomy causes a reduction in dose delivered to the target, while increasing dose to healthy tissue. Multi-leaf collimator (MLC) tracking has been clinically implemented to adapt dose delivery to account for intrafraction motion. Current methods shift the planned MLC aperture in the direction of motion, then optimise the new aperture based on the difference in fluence. The drawback of these methods is that 3D dose, a function of patient anatomy and MLC aperture sequence, is not properly accounted for. To overcome the drawback of current fluence-based methods, we have developed and investigated real-time adaptive MLC tracking based on dose optimisation. A novel MLC tracking algorithm, dose optimisation, has been developed which accounts for the moving patient anatomy by optimising the MLC based on the dose delivered during treatment, simulated using a simplified dose calculation algorithm. The MLC tracking with dose optimisation method was applied in silico to a prostate cancer VMAT treatment dataset with observed intrafraction motion. Its performance was compared to MLC tracking with fluence optimisation and, as a baseline, without MLC tracking. To quantitatively assess performance, we computed the dose error and 3D γ failure rate (2 mm/2%) for each fraction and method. Dose optimisation achieved a γ failure rate of (4.7 ± 1.2)% (mean and standard deviation) over all fractions, which was significantly lower than fluence optimisation (7.5 ± 2.9)% (Wilcoxon sign-rank test p < 0.01). Without MLC tracking, a γ failure rate of (15.3 ± 12.9)% was achieved. By considering the accumulation of dose in the moving anatomy during treatment, dose optimisation is able to optimise the aperture to actively target regions of underdose while avoiding overdose.

Constrained optimization towards marker-based tumor tracking in VMAT

This study proposes that incorporating marker-based visibility constraints into the optimization of volumetric modulated arc therapy (VMAT) will generate treatment plans which not only ensure a higher chance of successfully applying real-time tumor tracking techniques, but also simultaneously satisfy dosimetric objectives. This was applied clinically and investigated for multiple disease sites (10 prostate, 5 liver, and 5 lung) using a radiotherapy optimization software (MonArc), where these new constraints were added to conventional dosimetric constraints. For all the investigated sites, three fiducial markers were located inside or around the planning target volume (PTV), and VMAT plans were created for each patient. We modified MonArc to analyze the multi-leaf collimator (MLC) beam’s-eye-view at all control points in the gantry arc, while including marker-based visibility constraints of type ‘hard’ (i.e. requiring 100% visibility of all markers, HC) and ‘soft’ (i.e. penalizes visibility for one marker [SCI] or two markers [SCII] only) in the optimization process. Dose distributions resulting from the constrained plans (HC, SCI, and SCII) were compared to the non-constrained plan (NC—plans optimized without visibility constraints) using several quantitative dose metrics including the conformity index, homogeneity index, doses to PTV and to organs-at-risk (OAR). Generally, the NC plan produced the best PTV dose conformity and the least OAR doses for the entire patient datasets, followed by the SC and then HC plans, with all the optimization approaches typically achieving acceptable dose metrics. Across the three disease sites, visibility of all three markers in MLC apertures increased from 32% to 100% of available control points as visibility constraints strengthened. Although dose metrics showed some deterioration for constrained plans (−6% for SCI up to −15% for HC using the PTV average index), the required dosimetric objectives were still satisfied in at least 90% of patients. In conclusion, we demonstrated that marker and tumour visibility constraints can be incorporated with dosimetric objectives to produce treatment plans satisfying both objectives, which should ensure greater success when applying real-time tracking for VMAT delivery.

Adapting to the motion of multiple independent targets using multileaf collimator tracking for locally advanced prostate cancer: Proof of principle simulation study.

For patients with locally advanced cancer, multiple targets are treated simultaneously with radiotherapy. Differential motion between targets can compromise the treatment accuracy, yet there are currently no methods able to adapt to independent target motion. This study developed a multileaf collimator (MLC) tracking algorithm for differential motion adaptation and evaluated it in simulated treatments of locally advanced prostate cancer. A multi-target MLC tracking algorithm was developed that consisted of three steps: (a) dividing the MLC aperture into two possibly overlapping sections assigned to the prostate and lymph nodes, (b) calculating the ideally shaped MLC aperture as a union of the individually translated sections, and (c) fitting the MLC positions to the ideal aperture shape within the physical constraints of the MLC leaves. The multi-target tracking method was evaluated and compared with two existing motion management methods: single-target tracking and no tracking. Treatment simulations of six locally advanced prostate cancer patients with three prostate motion traces were performed for all three motion adaptation methods. The geometric error for each motion adaptation method was calculated using the area of overexposure and underexposure of each field. The dosimetric error was estimated by calculating the dose delivered to the prostate, lymph nodes, bladder, rectum, and small bowel using a motion-encoded dose reconstruction method. Multi-target MLC tracking showed an average improvement in geometric error of 84% compared to single-target tracking, and 83% compared to no tracking. Multi-target tracking maintained dose coverage to the prostate clinical target volume (CTV) D98% and planning target volume (PTV) D95% to within 4.8% and 3.9% of the planned values, compared to 1.4% and 0.7% with single-target tracking, and 20.4% and 31.8% with no tracking. With multi-target tracking, the node CTV D95%, PTV D90%, and gross tumor volume (GTV) D95% were within 0.3%, 0.6%, and 0.3% of the planned values, compared to 9.1%, 11.2%, and 21.1% for single-target tracking, and 0.8%, 2.0%, and 3.2% with no tracking. The small bowel V57% was maintained within 0.2% to the plan using multi-target tracking, compared to 8% and 3.5% for single-target tracking and no tracking, respectively. Meanwhile, the bladder and rectum V50% increased by up to 13.6% and 5.2%, respectively, using multi-target tracking, compared to 2.7% and 1.9% for single-target tracking, and 11.2% and 11.5% for no tracking. A multi-target tracking algorithm was developed and tracked the prostate and lymph nodes independently during simulated treatments. As the algorithm optimizes for target coverage, tracking both targets simultaneously may increase the dose delivered to the organs at risk.

Verification of the Machine Delivery Parameters of Treatment Plan via Deep Learning

To develop a generative adversarial network (GAN)-based deep learning approach to estimate the multileaf collimator (MLC) aperture and corresponding monitor units (MUs) from a given three-dimensional (3D) dose distribution. We developed a treatment plan verification framework by implementing a modified pix2pix network to learn a mapping between CT, segment 3D dose and MUs/MLC shapes. The proposed design of adversarial network, which integrates a residual block into pix2pix framework, jointly trains a “U-Net”-like architecture as generator and a convolutional “PatchGAN” classifier as discriminator. 199 patients, including nasopharyngeal, lung and rectum, treated with intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) techniques were utilized to train the network. The resliced volumetric dose of each segment and CT image datasets were labeled by the corresponding MUs/MLC maps. Additional 47 patients were used to test the prediction accuracy of the proposed deep learning model. The Dice similarity coefficient (DSC) was calculated to evaluate the similarity between the MLC aperture shapes obtained from the treatment planning system (TPS) and the deep learning prediction. The average and standard deviation of the bias between the TPS generated MUs and predicted MUs were calculated to evaluate the MU prediction accuracy. Additionally, the differences between TPS and deep learning-predicted MLC leaf positions were compared. The model performance was first evaluated by five simple fields, including four square fields and one irregular field. The DSC is found to be 0.99, 0.99, 0.99, 0.98 and 0.96, respectively. And the MUs prediction agree with the original plans to within 5%. The average and standard deviation of DSC was 0.94 ± 0.043 for 47 testing patients. The average deviation of predicted MUs from the planned MUs normalized to each beam or arc was within 2% for all the testing patients. The average deviation of the predicted MLC leaf positions was around one pixel for all the testing patients. A novel pix2pix deep learning network was developed to predict MUs/MLC shapes for treatment plan verification. It is the first attempt in using deep learning method to predict fundamental machine delivery parameters and it may provide radiation oncology community a useful tool for improving the efficiency and accuracy of patient specific QA and plan second check process.

Verification of the machine delivery parameters of a treatment plan via deep learning

We developed a generative adversarial network (GAN)-based deep learning approach to estimate the multileaf collimator (MLC) aperture and corresponding monitor units (MUs) from a given 3D dose distribution. The proposed design of the adversarial network, which integrates a residual block into pix2pix framework, jointly trains a ‘U-Net’-like architecture as the generator and a convolutional ‘PatchGAN’ classifier as the discriminator. 199 patients, including nasopharyngeal, lung and rectum, treated with intensity-modulated radiotherapy and volumetric-modulated arc therapy techniques were utilized to train the network. An additional 47 patients were used to test the prediction accuracy of the proposed deep learning model. The Dice similarity coefficient (DSC) was calculated to evaluate the similarity between the MLC aperture shapes obtained from the treatment planning system (TPS) and the deep learning prediction. The average and standard deviation of the bias between the TPS-generated MUs and predicted MUs was calculated to evaluate the MU prediction accuracy. In addition, the differences between TPS and deep learning-predicted MLC leaf positions were compared. The average and standard deviation of DSC was 0.94 ± 0.043 for 47 testing patients. The average deviation of predicted MUs from the planned MUs normalized to each beam or arc was within 2% for all the testing patients. The average deviation of the predicted MLC leaf positions was around one pixel for all the testing patients. Our results demonstrated the feasibility and reliability of the proposed approach. The proposed technique has strong potential to improve the efficiency and accuracy of the patient plan quality assurance process.

Standardized flattening filter free volumetric modulated arc therapy plans based on anteroposterior width for total body irradiation.

In this work, the feasibility of using flattening filter free (FFF) beams in volumetric modulated arc therapy (VMAT) total body irradiation (TBI) treatment planning to decrease protracted beam‐on times for these treatments was investigated. In addition, a methodology was developed to generate standardized VMAT TBI treatment plans based on patient physical dimensions to eliminate plan optimization time. A planning study cohort of 47 TBI patients previously treated with optimized VMAT ARC 6 MV beams was retrospectively examined. These patients were sorted into six categories depending on height and anteroposterior (AP) width at the umbilicus. Using Varian Eclipse, clinical 40 cm × 10 cm open field arcs were substituted with 6 MV FFF. Mid‐plane lateral dose profiles in conjunction with relative arc output factors (RAOF) yielded how far a given multileaf collimator (MLC) leaf must move in order to achieve a mid‐plane 100% isodose for a specific control point. Linear interpolation gave the dynamic MLC aperture for the entire arc for each patient AP width category, which was subsequently applied through Python scripting. All FFF VMAT TBI plans were then evaluated by two radiation oncologists and deemed clinically acceptable. The FFF and clinical VMAT TBI plans had similar Body–5 mm D98% distributions, but overall the FFF plans had statistically significantly increased or broader Body–5 mm D2% and mean lung dose distributions. These differences are not considered clinically significant. Median beam‐on times for the FFF and clinical VMAT TBI plans were 11.07 and 18.06 min, respectively, and planning time for the FFF VMAT TBI plans was reduced by 34.1 min. In conclusion, use of FFF beams in VMAT TBI treatment planning resulted in dose homogeneity similar to our current VMAT TBI technique. Clinical dosimetric criteria were achieved for a majority of patients while planning and calculated beam‐on times were reduced, offering the possibility of improved patient experience.

Impact of Aperture Shape Controller on Volumetric Modulated Arc Therapy Treatment Planning for Nasopharyngeal Cancer

The aperture shape controller (ASC) decreases the complexity of the multi-leaf collimator (MLC) aperture for volumetric modulated arc therapy (VMAT). The purpose of this study was to evaluate the effect of ASC settings on the VMAT plan quality. First, VMAT plans were created (ASC=off) for three test patterns of The American Association of Physicists in Medicine (AAPM) Task Group 119 (TG-119) and 20 cases of nasopharyngeal cancer. Next, for these VMAT plans, only the ASC settings were changed from very low (complexity reduction: low) to very high (complexity reduction: high) in five steps, and VMAT plans were created respectively. To evaluate the created VMAT plans per each ASC settings, we analyzed the modulation complexity score (MCSV) and dosimetric parameters for the planning target volume (PTV) and organ at risk (OAR). In three test patterns, there were no major dosimetric differences between the VMAT plans. In nasopharyngeal cancer, the mean MCSV were 0.413, 0.325, 0.320, 0.307, 0.303, and 0.272 for very high, high, moderate, low, very low, off settings, respectively. Therefore, the most complex MLC aperture was off, followed by very low, low, moderate, high, and very high. In terms of dosimetric parameters, the VMAT plans created using the very high setting showed an increase of D2% in the PTV and worse OAR sparing than that using other ASC settings. On the other hand, the dosimetric results for the very low to moderate setting obtained similar results to those for the off setting, respectively. The ASC was able to decrease the complexity of the MLC aperture according to the setting level. From very low to moderate settings, a plan equivalent to the off setting could be created in terms of dose parameters.

Investigating the use of aperture shape controller in VMAT treatment deliveries

Background: Aperture shape controller (ASC) is a recently introduced leaf sequencer that controls the complexity of multileaf collimator apertures in the Photon Optimizer algorithm of the Eclipse treatment planning system. The aim of this study is to determine if the ASC can reduce plan complexity and improve verification results, without compromising plan quality. Methods: Thirteen plans grouped into cohorts of head and neck/brain, breast/chest and pelvis were reoptimised using the same optimization as the non-ASC setting for low, moderate and high ASC settings. These plans were analyzed using plan quality indices such as the conformity index and homogeneity index in addition to dose-volume histogram based analysis on PTVs and organ at risks. Complexity assessments were performed using metrics such as average leaf pair opening, modulation complexity scores, relative monitor units (MU) and treatment time. Monitor unit per gantry angle variations were also analyzed. A third-party algorithm was also used to assess 3D dose distributions produced using the new leaf sequencer tool. Deliverability for the final multileaf collimator distribution was quantified using portal dose image prediction based gamma analysis. Results: Plan conformality assessments showed comparable results and no significant plan degradation for plans reoptimised using ASC. Reduction in overall MU distributions were seen in some cases using higher ASC however, no overall trends were observed. In general, treatment deliverability, assessed using gamma analysis did not improve drastically however MU per degree distribution in 1 case improved when reoptimised using ASC. Treatment MUs generally reduced when ASC settings were used whilst in 1 case an increase in the treatment time factor > 1.8 was observed. The third-party algorithm assessment showed an underestimation of dose calculations for all cohorts used in this study when a higher ASC setting is used. Conclusions: The impact of using ASC in treatment plans was characterised in this study. Although plan complexity marginally improved when using higher ASC settings, no consensus could be reached based on metrics analyzed in this study. A reduction in MU distribution was observed with increasing ASC settings in most cases. This study recommends that ASC to be used as an additional tool only to test its suitability to reduce plan complexity.

Intra-arc binary collimation algorithm for the optimization of stereotactic radiotherapy treatment of multiple metastases with multiple prescriptions.

To design and implement a novel treatment planning algorithm based on a modification of dynamic conformal arc (DCA) therapy for the treatment of multiple cranial metastases with variable prescription doses. A workflow was developed in which separate dose matrices were calculated for each target at each control point (i.e., the multileaf collimator (MLC) was fit conformally to that single target). A cost function was used to quantify the relative contributions of each dose matrix in the plan to the overall plan objectives. Simulated annealing was used to allow for the inclusion or exclusion of individual dose matrices at each control point. The exclusion of individual targets at a given control point is termed intra-arc binary collimation (iABC) in this work and is accomplished by closing the MLCs over the target for a duration specified by simulated annealing optimization. Dynamic collimator motions were employed to minimize the variation between the idealized dose matrices (i.e., perfectly collimated targets) and actual dose matrices (i.e., MLC apertures that include quantities of nontarget tissue due to the relative orientations of targets in the field). An additional simulated annealing optimization was performed to weight the relative contributions of dose at each control point [referred to as the monitor unit distribution (MUD)] to improve compliance with plan objectives. The algorithm was tested on seven previously treated multiple metastases patients and plans were compared to the clinically treated VMAT plans. Treatment plans generated with iABC used an average of 2716 (34%) fewer MU in the total plan than VMAT (P = 0.01). All normal tissue metrics for all plans and all patients were clinically acceptable. There were no statistically significant differences in any normal tissue dose metrics. Normalized prescription target coverage accuracy for all targets was 3% better on average for VMAT plans when compared to iABC (P = 0.07), and 14% better on average for iABC when compared to optimized DCA (P = 0.03). A novel method of aperture and dose distribution design has been developed to significantly increase the MU efficiency of single isocenter treatment of multiple metastases with variable prescription doses when compared to VMAT, and which improves target coverage accuracy significantly when compared to optimized DCA. By applying a DCA approach to subsets of targets across control points, a hybrid method of treatment delivery has been developed that combines the efficiency of dynamic conformal treatments and the dosimetric flexibility of VMAT.

Mechanical performance of a commercial knowledge-based VMAT planning for prostate cancer

BackgroundThis study clarified the mechanical performance of volumetric modulated arc therapy (VMAT) plans for prostate cancer generated with a commercial knowledge-based treatment planning (KBP) and whether KBP system could be applied clinically without any major problems with mechanical performance.MethodsThirty consecutive prostate cancer patients who underwent VMAT using extant clinical plans were evaluated. The mechanical performance and dosimetric accuracy of the single optimized KBPs, which were trained with other 51 clinical plans, were compared with the clinical plans. The mechanical performance metrics were mean field area (MFA), mean asymmetry distance (MAD), cross-axis score (CAS), closed leaf score (CLS), small aperture score (SAS), leaf travel (LT), modulation complexity score (MCSv), and monitor unit (MU). The γ passing rates were evaluated with ArcCheck and EBT3 film.ResultsThe mean mechanical performance metrics (clinical plan vs. KBP) were as follows: 18.28 cm2 vs. 17.25 cm2 (MFA), 21.08 mm vs. 20.47 mm (MAD), 0.54 vs. 0.55 (CAS), 0.040 vs. 0.051 (CLS), 0.20 vs. 0.23 (SAS5mm), 458.5 mm vs. 418.8 mm (LT), 0.27 vs. 0.27 (MCSv), and 618.2 vs. 622.1 (MU), respectively. Significant differences were observed for CLS and LT. The average γ passing rates (clinical plan vs. KBP) were as follows: 99.0% vs. 99.1% (3%/3 mm) and 92.4% vs. 92.5% (2%/2 mm) with ArcCHeck, and 99.5% vs. 99.4% (3%/3 mm) and 95.2% vs. 95.4% (2%/2 mm) with EBT3 film, respectively.ConclusionsThe KBP used lower multileaf collimator (MLC) travel and more closed or small MLC apertures than the clinical plan. The KBP system of VMAT for the prostate cancer was acceptable for clinical use without any major problems.

Real-time 4D dose reconstruction for tracked dynamic MLC deliveries for lung SBRT.

PurposeThis study provides a proof of concept for real‐time 4D dose reconstruction for lung stereotactic body radiation therapy (SBRT) with multileaf collimator (MLC) tracking and assesses the impact of tumor tracking on the size of target margins.MethodsThe authors have implemented real‐time 4D dose reconstruction by connecting their tracking and delivery software to an Agility MLC at an Elekta Synergy linac and to their in‐house treatment planning software (TPS). Actual MLC apertures and (simulated) target positions are reported to the TPS every 40 ms. The dose is calculated in real‐time from 4DCT data directly after each reported aperture by utilization of precalculated dose‐influence data based on a Monte Carlo algorithm. The dose is accumulated onto the peak‐exhale (reference) phase using energy‐mass transfer mapping. To investigate the impact of a potentially reducible safety margin, the authors have created and delivered treatment plans designed for a conventional internal target volume (ITV) + 5 mm, a midventilation approach, and three tracking scenarios for four lung SBRT patients. For the tracking plans, a moving target volume (MTV) was established by delineating the gross target volume (GTV) on every 4DCT phase. These were rigidly aligned to the reference phase, resulting in a unified maximum GTV to which a 1, 3, or 5 mm isotropic margin was added. All scenarios were planned for 9‐beam step‐and‐shoot IMRT to meet the criteria of RTOG 1021 (3 × 18 Gy). The GTV 3D center‐of‐volume shift varied from 6 to 14 mm.ResultsReal‐time dose reconstruction at 25 Hz could be realized on a single workstation due to the highly efficient implementation of dose calculation and dose accumulation. Decreased PTV margins resulted in inadequate target coverage during untracked deliveries for patients with substantial tumor motion. MLC tracking could ensure the GTV target dose for these patients. Organ‐at‐risk (OAR) doses were consistently reduced by decreased PTV margins. The tracked MTV + 1 mm deliveries resulted in the following OAR dose reductions: lung V 20 up to 3.5%, spinal cord D 2 up to 0.9 Gy/Fx, and proximal airways D 2 up to 1.4 Gy/Fx.ConclusionsThe authors could show that for patient data at clinical resolution and realistic motion conditions, the delivered dose could be reconstructed in 4D for the whole lung volume in real‐time. The dose distributions show that reduced margins yield lower doses to healthy tissue, whilst target dose can be maintained using dynamic MLC tracking.

Optimizing fiducial visibility on periodically acquired megavoltage and kilovoltage image pairs during prostate volumetric modulated arc therapy.

Robust detection of implanted fiducials is essential for monitoring intrafractional motion during hypofractionated treatment. The authors developed a plan optimization strategy to ensure clear visibility of implanted fiducials and facilitate 3D localization during volumetric modulated arc therapy (VMAT). Periodic kilovoltage (kV) images were acquired at 20° gantry intervals and paired with simultaneously acquired 4.4° short arc megavoltage digital tomosynthesis (MV-DTS) to localize three fiducials during VMAT delivery for hypofractionated prostate cancer treatment. Beginning with the original optimized plan, control point segments where fiducials were consistently blocked by multileaf collimator (MLC) within each 4.4° MV-DTS interval were first identified. For each segment, MLC apertures were edited to expose the fiducial that led to the least increase in the cost function. Subsequently, MLC apertures of all control points not involved with fiducial visualization were reoptimized to compensate for plan quality losses and match the original dose-volume histogram. MV dose for each MV-DTS was also kept above 0.4 MU to ensure acceptable image quality. Different imaging (gantry) intervals and visibility margins around fiducials were also evaluated. Fiducials were consistently blocked by the MLC for, on average, 36% of the imaging control points for five hypofractionated prostate VMAT plans but properly exposed after reoptimization. Reoptimization resulted in negligible dosimetric differences compared with original plans and outperformed simple aperture editing: on average, PTV D98 recovered from 87% to 94% of prescription, and PTV dose homogeneity improved from 9% to 7%. Without violating plan objectives and compromising delivery efficiency, the highest imaging frequency and largest margin that can be achieved are a 10° gantry interval, and 15 mm, respectively. VMAT plans can be made to accommodate MV-kV imaging of fiducials. Fiducial visualization rate and workflow efficiency are significantly improved with an automatic modification and reoptimization approach.

Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking.

Real-time multileaf collimator (MLC) tracking is a promising approach to the management of intrafractional tumor motion during thoracic and abdominal radiotherapy. MLC tracking is typically performed in two steps: transforming a planned MLC aperture in response to patient motion and refitting the leaves to the newly generated aperture. One of the challenges of this approach is the inability to faithfully reproduce the desired motion-adapted aperture. This work presents an optimization-based framework with which to solve this leaf-fitting problem in real-time. This optimization framework is designed to facilitate the determination of leaf positions in real-time while accounting for the trade-off between coverage of the PTV and avoidance of organs at risk (OARs). Derived within this framework, an algorithm is presented that can account for general linear transformations of the planned MLC aperture, particularly 3D translations and in-plane rotations. This algorithm, together with algorithms presented in Sawant et al. ["Management of three-dimensional intrafraction motion through real-time DMLC tracking," Med. Phys. 35, 2050-2061 (2008)] and Ruan and Keall [Presented at the 2011 IEEE Power Engineering and Automation Conference (PEAM) (2011) (unpublished)], was applied to apertures derived from eight lung intensity modulated radiotherapy plans subjected to six-degree-of-freedom motion traces acquired from lung cancer patients using the kilovoltage intrafraction monitoring system developed at the University of Sydney. A quality-of-fit metric was defined, and each algorithm was evaluated in terms of quality-of-fit and computation time. This algorithm is shown to perform leaf-fittings of apertures, each with 80 leaf pairs, in 0.226 ms on average as compared to 0.082 and 64.2 ms for the algorithms of Sawant et al., Ruan, and Keall, respectively. The algorithm shows approximately 12% improvement in quality-of-fit over the Sawant et al. approach, while performing comparably to Ruan and Keall. This work improves upon the quality of the Sawant et al. approach, but does so without sacrificing run-time performance. In addition, using this framework allows for complex leaf-fitting strategies that can be used to account for PTV/OAR trade-off during real-time MLC tracking.

Technical Note: Motion-perturbation method applied to dosimetry of dynamic MLC target tracking--A proof-of-concept.

Previous studies show that dose to a moving target can be estimated using 4D measurement-guided dose reconstruction based on a process called virtual motion simulation, or VMS. A potential extension of VMS is to estimate dose during dynamic multileaf collimator (MLC)-tracking treatments. The authors introduce a modified VMS method and quantify its performance as proof-of-concept for tracking applications. Direct measurements with a moving biplanar diode array were used to verify accuracy of the VMS dose estimates. A tracking environment for variably sized circular MLC apertures was simulated by sending preprogrammed control points to the MLC while simultaneously moving the accelerator treatment table. Sensitivity of the method to simulated tracking latency (0-700 ms) was also studied. Potential applicability of VMS to fast changing beam apertures was evaluated by modeling, based on the demonstrated dependence of the cumulative dose on the temporal dose gradient. When physical and virtual latencies were matched, the agreement rates (2% global/2 mm gamma) between the VMS and the biplanar dosimeter were above 96%. When compared to their own reference dose (0 induced latency), the agreement rates for VMS and biplanar array track closely up to 200 ms of induced latency with 10% low-dose cutoff threshold and 300 ms with 50% cutoff. Time-resolved measurements suggest that even in the modulated beams, the error in the cumulative dose introduced by the 200 ms VMS time resolution is not likely to exceed 0.5%. Based on current results and prior benchmarks of VMS accuracy, the authors postulate that this approach should be applicable to any MLC-tracking treatments where leaf speeds do not exceed those of the current Varian accelerators.