Gamma Analysis Research Articles

Students' Level of Awareness on the Waste Contribution of the Fast Fashion with Their Clothing Consumption Behavior

The accessibility and convenience of purchasing fashion items have increased due to continuous manufacturing and high demand. The fast fashion industry has capitalized on the latest trends by offering cheap, affordable, yet disposable items, contributing to global pollution through solid waste and wastewater. This study aims to assess (a) students' level of awareness regarding the waste contribution of the fast fashion industry, (b) their clothing consumption behavior concerning purchases and utilization, (c) their waste disposal practices, and (d) the relationship between clothing consumption behavior and their level of awareness. The study employs systematic random sampling to determine an appropriate sample size from the student population, resulting in 104 student respondents for the adapted survey. Goodman and Kruskal's Gamma analysis assesses the association between clothing consumption and awareness. The results indicate that the students know about the industry's wastewater and solid waste contribution. However, the study also reveals a negligible to moderate relationship between clothing consumption, including the frequency of purchases and utilization, and their overall awareness. This suggests that despite being highly aware of the environmental issues associated with the fast fashion industry, students continue to support and purchase products from this sector.

Dosimetric impact of CT metal artifact reduction for spinal implants in stereotactic body radiotherapy planning.

Metal artifacts due to spinal implants may affect the accuracy of dose calculation for radiotherapy. However, the dosimetric impact of metal artifact reduction (MAR) for spinal implants in stereotactic body radiotherapy (SBRT) plans has not been well studied. The objective of this study was to evaluate the dosimetric impact of MAR in spinal SBRT planning with three clinically common dose calculation algorithms. Gammex phantom and 10 patients' computed tomography (CT) images were studied to investigate the effects of titanium implants. A commercial orthopedic MAR algorithm was employed to reduce artifacts. Dose calculations for SBRT were conducted on both artifact-corrected and uncorrected images using three commercial algorithms [analytical anisotropic algorithm (AAA), Acuros XB (AXB), and Monte Carlo (MC)]. Dose discrepancies between artifact-corrected and uncorrected cases were appraised using a dose-volume histogram (DVH) and 3-dimensional (3D) gamma analysis with different distance to agreement (DTA) and dose difference criteria. The gamma agreement index (GAI) was denoted as G(∆D, DTA). Statistical analysis of t-test was utilized to evaluate the dose differences of different algorithms. The phantom study demonstrated that titanium metal artifacts can be effectively reduced. The patient cases study showed that dose differences between the artifact-corrected and uncorrected datasets were small evaluated by gamma index and DVH. Gamma analysis found that even the strict criterion local G(1,1) had average values ≥93.9% for the three algorithms. For all DVH metrics, average differences did not exceed 0.7% in planning target volume (PTV) and 2.1% in planning risk volume of spinal cord (PRV-SC). Statistical analysis showed that the observed dose differences of MC method were significantly larger than those of AAA (P<0.01 for D98% of PTV and P<0.001 for D0.1cc of spinal cord) and AXB methods (P<0.001 for D98% and P<0.0001 for D0.1cc). Dosimetric impact of artifacts caused by titanium implants is not significant in spinal SBRT planning, which indicates that dose calculation algorithms might not be very sensitive to CT number variation caused by titanium inserts.

Dose-rate dependence and IMRT QA suitability of EBT3 radiochromic films for pulse reduced dose-rate radiotherapy (PRDR) dosimetry.

Pulsed reduced dose rate (PRDR) is an emerging radiotherapy technique for recurrent diseases. It is pertinent that the linac beam characteristics are evaluated for PRDR dose rates and a suitable dosimeter is employed for IMRT QA. This study sought to investigate the pulse characteristics of a 6 MV photon beam during PRDR irradiations on a commercial linac. The feasibility of using EBT3 radiochromic film for use in IMRT QA was also investigated by comparing its response to a commercial diode array phantom. A plastic scintillator detector was employed to measure the photon pulse characteristics across nominal repetition rates (NRRs) in the 5-600 MU/min range. Film was irradiated with dose rates in the 0.033-4Gy/min range to study the dose rate dependence. Five clinical PRDR treatment plans were selected for IMRT QA with the Delta4 phantom and EBT3 film sheets. The planned and measured dose were compared using gamma analysis with a criterion of 3%/3mm. EBT3 film QA was performed using a cumulative technique and a weighting factor technique. Negligible differences were observed in the pulse width and height data between the investigated NRRs. The pulse width was measured to be 3.15±0.01 and the PRF was calculated to be 3-357Hz for the 5-600 MU/min NRRs. The EBT3 film was found to be dose rate independent within 3%. The gamma pass rates (GPRs) were above 99% and 90% for the Delta4 phantom and the EBT3 film using the cumulative QA method, respectively. GPRs as low as 80% were noted for the weighting factor EBT3 QA method. Altering the NRRs changes the mean dose rate while the instantaneous dose rate remains constant. The EBT3 film was found to be suitable for PRDR dosimetry and IMRT QA with minimal dose rate dependence.

A Monte Carlo model of an agility head for a 6 MV Elekta photon beam

IntroductionWith the advance in radiotherapy delivery, the need for a method allowing for a precise dose calculation increased. Monte Carlo modelling of radiotherapy dosages has become an important methodology for the evaluation of dose and beam performance, especially given recent advances in radiotherapy. In this study, an Elekta equipped with an Agility multileaf collimator will be modelled and validated in order to be used in further studies. MethodologyA 6 MV photon beam for the Elekta Synergy linear accelerator with an Agility head was simulated, adjusted, and confirmed using the BEAMnrc/EGSnrc algorithm. Tuning involved comparing percentage depth dose with measured data using different incident electron energies, as analyzed using the gamma index. The best energy so calculated was then used with different full half width maximums (FWHMs) and different angular divergences in order to tune the lateral profiles. Output factors for different field sizes were validated with measurements. Then, the validated model was checked for different depths. ResultsFor PDD comparison, the best electron energy was found to be 6.6 MeV, where the gamma analysis is 100%. A 0.15 cm circle FWHM was found to have the best FWHM. with an angular diverge of 0.03°. The output factors match measured values, proving that the model can achieve a suitably high accuracy. ConclusionThe validated model can be used in advanced radiotherapy dose calculation such as in VMAT, IMRT, and Stereotactic radiotherapy. The model needs to be validated in future studies for smaller field sizes, surface dose, and out-of-field dosimetry.

A deep learning model to generate synthetic CT for prostate MR-only radiotherapy dose planning: a multicenter study

IntroductionFor radiotherapy based solely on magnetic resonance imaging (MRI), generating synthetic computed tomography scans (sCT) from MRI is essential for dose calculation. The use of deep learning (DL) methods to generate sCT from MRI has shown encouraging results if the MRI images used for training the deep learning network and the MRI images for sCT generation come from the same MRI device. The objective of this study was to create and evaluate a generic DL model capable of generating sCTs from various MRI devices for prostate radiotherapyMaterials and methodsIn total, 90 patients from three centers (30 CT-MR prostate pairs/center) underwent treatment using volumetric modulated arc therapy for prostate cancer (PCa) (60 Gy in 20 fractions). T2 MRI images were acquired in addition to computed tomography (CT) images for treatment planning. The DL model was a 2D supervised conditional generative adversarial network (Pix2Pix). Patient images underwent preprocessing steps, including nonrigid registration. Seven different supervised models were trained, incorporating patients from one, two, or three centers. Each model was trained on 24 CT-MR prostate pairs. A generic model was trained using patients from all three centers. To compare sCT and CT, the mean absolute error in Hounsfield units was calculated for the entire pelvis, prostate, bladder, rectum, and bones. For dose analysis, mean dose differences of D99% for CTV, V95% for PTV, Dmax for rectum and bladder, and 3D gamma analysis (local, 1%/1 mm) were calculated from CT and sCT. Furthermore, Wilcoxon tests were performed to compare the image and dose results obtained with the generic model to those with the other trained models.ResultsConsidering the image results for the entire pelvis, when the data used for the test comes from the same center as the data used for training, the results were not significantly different from the generic model. Absolute dose differences were less than 1 Gy for the CTV D99% for every trained model and center. The gamma analysis results showed nonsignificant differences between the generic and monocentric models.ConclusionThe accuracy of sCT, in terms of image and dose, is equivalent to whether MRI images are generated using the generic model or the monocentric model. The generic model, using only eight MRI-CT pairs per center, offers robust sCT generation, facilitating PCa MRI-only radiotherapy for routine clinical use.

Continuous time-resolved estimated synthetic 4D-CTs for dose reconstruction of lung tumor treatments at a 0.35 T MR-linac

Objective. To experimentally validate a method to create continuous time-resolved estimated synthetic 4D-computed tomography datasets (tresCTs) based on orthogonal cine MRI data for lung cancer treatments at a magnetic resonance imaging (MRI) guided linear accelerator (MR-linac). Approach. A breathing porcine lung phantom was scanned at a CT scanner and 0.35 T MR-linac. Orthogonal cine MRI series (sagittal/coronal orientation) at 7.3 Hz, intersecting tumor-mimicking gelatin nodules, were deformably registered to mid-exhale 3D-CT and 3D-MRI datasets. The time-resolved deformation vector fields were extrapolated to 3D and applied to a reference synthetic 3D-CT image (sCTref), while accounting for breathing phase-dependent lung density variations, to create 82 s long tresCTs at 3.65 Hz. Ten tresCTs were created for ten tracked nodules with different motion patterns in two lungs. For each dataset, a treatment plan was created on the mid-exhale phase of a measured ground truth (GT) respiratory-correlated 4D-CT dataset with the tracked nodule as gross tumor volume (GTV). Each plan was recalculated on the GT 4D-CT, randomly sampled tresCT, and static sCTref images. Dose distributions for corresponding breathing phases were compared in gamma (2%/2 mm) and dose–volume histogram (DVH) parameter analyses. Main results. The mean gamma pass rate between all tresCT and GT 4D-CT dose distributions was 98.6%. The mean absolute relative deviations of the tresCT with respect to GT DVH parameters were 1.9%, 1.0%, and 1.4% for the GTV D 98%, D 50%, and D 2%, respectively, 1.0% for the remaining nodules D 50%, and 1.5% for the lung V 20Gy. The gamma pass rate for the tresCTs was significantly larger (p < 0.01), and the GTV D 50% deviations with respect to the GT were significantly smaller (p < 0.01) than for the sCTref. Significance. The results suggest that tresCTs could be valuable for time-resolved reconstruction and intrafractional accumulation of the dose to the GTV for lung cancer patients treated at MR-linacs in the future.

Unbiased evaluation of predicted gamma passing rate by an event-mixing technique.

Predicting models of the gamma passing rate (GPR) have been studied to substitute the measurement-based gamma analysis. Since these studies used data from different radiotherapy systems comprising TPS, linear accelerator, and detector array, it has been difficult to compare the performances of the predicting models among institutions with different radiotherapy systems. We aimed to develop unbiased scoring methods to evaluate the performance of the models predicting the GPR, by introducing both best and worst limits for the performance of the GPR prediction. Two hundred head-and-neck VMAT plans were used to develop a framework. The GPRs were measured using the ArcCHECK device. The predicted GPR [p] was generated using a deep learning-based model [pDL ]. The predicting model was evaluated using four metrics: standard deviation (SD) [σ], Pearson's correlation coefficient (CC) [r], mean squared error (MSE) [s], and mean absolute error (MAE) [a]. The best limit [ , , , and ] was estimated by measuring the SD of measured GPR [m] by shifting the device along the longitudinal direction to measure different sampling points. Mimicked best and worst p's [pbest and pworst ] were generated from pDL . The worst limit was defined such that m and p have no correlation [CC ∼ 0]. The worst limit [σMix , rMix , sMix , and aMix ] was generated using the event-mixing (EM) technique originally introduced in high-energy physics experiments. The range of σ, r, s, and a was defined to be , , , and . The achievement score (AS) independently based on σ, r, s, and a were calculated for pDL , pbest and pworst . The probability that p fails the gamma analysis (alert frequency; AF) was estimated as a function of values within the [ , σMix ] range for the 3%/2mm data with a 95% criterion. SDs of the best limit were well reproduced by . The EM technique successfully generated the pairs with no correlation. The AS using four metrics showed good agreement. This agreement indicates successful definitions of both best and worst limits, consistent definitions of the AS, and successful generations of mixed events. The AF for the DL-based model with the 3%/2mm tolerance was 31.5% and 63.0% with CL's 99% and 99.9%, respectively. We developed the AS to evaluate the predicting model of the GPR in an unbiased manner by excluding the effects of the precision of the radiotherapy system and the spreading of the GPR. The best and worst limits of the GPR prediction were successfully generated using the measured precision of the GPR and the EM technique, respectively. The AS and are expected to enable objective evaluation of the predicting model and setting exact achievement goal of precision for the predicted GPR.

Evaluation of a novel CBCT conversion method implemented in a treatment planning system

BackgroundTo evaluate a novel CBCT conversion algorithm for dose calculation implemented in a research version of a treatment planning system (TPS).MethodsThe algorithm was implemented in a research version of RayStation (v. 11B-DTK, RaySearch, Stockholm, Sweden). CBCTs acquired for each ten head and neck (HN), gynecology (GYN) and lung cancer (LNG) patients were collected and converted using the new algorithm (CBCTc). A bulk density overriding technique implemented in the same version of the TPS was used for comparison (CBCTb). A deformed CT (dCT) was created by using deformable image registration of the planning CT (pCT) to the CBCT to reduce anatomical changes. All treatment plans were recalculated on the pCT, dCT, CBCTc and the CBCTb. The resulting dose distributions were analyzed using the MICE toolkit (NONPIMedical AB Sweden, Umeå) with local gamma analysis, with 1% dose difference and 1 mm distance to agreement criteria. A Wilcoxon paired rank sum test was applied to test the differences in gamma pass rates (GPRs). A p value smaller than 0.05 considered statistically significant.ResultsThe GPRs for the CBCTb method were systematically lower compared to the CBCTc method. Using the 10% dose threshold and the dCT as reference the median GPRs were for the CBCTc method were 100% and 99.8% for the HN and GYN cases, respectively. Compared to that the GPRs of the CBCTb method were lower with values of 99.8% and 98.0%, for the HN and GYN cases, respectively. The GPRs of the LNG cases were 99.9% and 97.5% for the CBCTc and CBCTb method, respectively. These differences were statistically significant. The main differences between the dose calculated on the CBCTs and the pCTs were found in regions near air/tissue interfaces, which are also subject to anatomical variations.ConclusionThe dose distribution calculated using the new CBCTc method showed excellent agreement with the dose calculated using dCT and pCT and was superior to the CBCTb method. The main reasons for deviations of the calculated dose distribution were caused by anatomical variations between the pCT and the corrected CBCT.

Why we should care about gas pockets in online adaptive MRgRT: a dosimetric evaluation.

Contouring of gas pockets is a time consuming step in the workflow of adaptive radiotherapy. We would like to better understand which gas pockets electronic densitiy should be used and the dosimetric impact on adaptive MRgRT treatment. 21 CT scans of patients undergoing SBRT were retrospectively evaluated. Anatomical structures were contoured: Gross Tumour Volume (GTV), stomach (ST), small bowel (SB), large bowel (LB), gas pockets (GAS) and gas in each organ respectively STG, SBG, LBG. Average HU in GAS was converted in RED, the obtained value has been named as Gastrointestinal Gas RED (GIGED). Differences of average HU in GAS, STG, SBG and LBG were computed. Three treatment plans were calculated editing the GAS volume RED that was overwritten with: air RED (0.0012), water RED (1.000), GIGED, generating respectively APLAN, WPLAN and the GPLAN. 2-D dose distributions were analyzed by gamma analysis. Parameter called active gas volume (AGV) was calculated as the intersection of GAS with the isodose of 5% of prescription dose. Average HU value contained in GAS results to be equal to -620. No significative difference was noted between the average HU of gas in different organ at risk. Value of Gamma Passing Rate (GPR) anticorrelates with the AGV for each plan comparison and the threshold value for GPR to fall below 90% is 41, 60 and 139 cc for WPLANvsAPLAN, GPLANvsAPLAN and WPLANvsGPLAN respectively. GIGED is the right RED for Gastrointestinal Gas. Novel AGV is a useful parameter to evaluate the effect of gas pocket on dose distribution.

A comparison of three-film analysis software for stereotactic radiotherapy patient-specific quality assurance.

The aim of this study was to investigate the suitability of three radiochromic film analysis software for stereotactic radiotherapy patient-specific quality assurance (PSQA): FilmQA Pro v5.0, SNC Patient v6.2, and eFilmQA v5.0. Film calibration was conducted for each software followed by three sets of measurements. The first set assessed calibration accuracy by comparing measured and delivered doses at increments different from those used for calibration. The second set used each software to conduct PSQA through gamma analysis on 10 stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT) patients. The third set utilized SNC Patient and eFilmQA to carry out gamma analysis on a collection of four digital test images, eliminating delivery and scanning uncertainties from impacting the analysis. Key supporting features within each software for conducting gamma analysis were identified. Overall, FilmQA Pro and eFilmQA were deemed comparable and favoured over SNC Patient due to the presence of key features such as triple-channel dosimetry, auto-optimization, and dose scaling. FilmQA Pro has a substantial user base and established reputation. eFilmQA, having been introduced more recently, serves as a viable alternative to FilmQA Pro, having been further refined for stereotactic radiotherapy PSQA. This study investigated the suitability of three film analysis software (FilmQA Pro, eFilmQA, and SNC Patient) for stereotactic radiotherapy PSQA. Results from the investigation indicated that both FilmQA Pro and eFilmQA are comparably suitable and are preferred over SNC Patient. Both FilmQA Pro and eFilmQA are recommended for radiotherapy clinics.

Development of a novel delivery quality assurance system based on simultaneous verification of dose distribution and binary multi-leaf collimator opening in helical tomotherapy

BackgroundIntensity-modulated radiation therapy (IMRT) requires delivery quality assurance (DQA) to ensure treatment accuracy and safety. Irradiation techniques such as helical tomotherapy (HT) have become increasingly complex, rendering conventional verification methods insufficient. This study aims to develop a novel DQA system to simultaneously verify dose distribution and multi-leaf collimator (MLC) opening during HT.MethodsWe developed a prototype detector consisting of a cylindrical plastic scintillator (PS) and a cooled charge-coupled device (CCD) camera. Scintillation light was recorded using a CCD camera. A TomoHDA (Accuray Inc.) was used as the irradiation device. The characteristics of the developed system were evaluated based on the light intensity. The IMRT plan was irradiated onto the PS to record a moving image of the scintillation light. MLC opening and light distribution were obtained from the recorded images. To detect MLC opening, we placed a region of interest (ROI) on the image, corresponding to the leaf position, and analyzed the temporal change in the light intensity within each ROI. Corrections were made for light changes due to differences in the PS shape and irradiation position. The corrected light intensity was converted into the leaf opening time (LOT), and an MLC sinogram was constructed. The reconstructed MLC sinogram was compared with that calculated using the treatment planning system (TPS). Light distribution was obtained by integrating all frames obtained during IMRT irradiation. The light distribution was compared with the dose distribution calculated using the TPS.ResultsThe LOT and the light intensity followed a linear relationship. Owing to MLC movements, the sensitivity and specificity of the reconstructed sinogram exceeded 97%, with an LOT error of − 3.9 ± 7.8%. The light distribution pattern closely resembled that of the dose distribution. The average dose difference and the pass rate of gamma analysis with 3%/3 mm were 1.4 ± 0.2% and 99%, respectively.ConclusionWe developed a DQA system for simultaneous and accurate verification of both dose distribution and MLC opening during HT.

Patient-Specific Quality Assurance in Pencil Beam Scanning by 2-Dimensional Array

PurposeThis study aimed to determine the characteristics of 2D ionization chamber array and the confidence limits of the gamma passing rate in pencil beam scanning proton therapy. Materials and Methods:The Varian ProBeam Compact spot-scanning system and the PTW OCTAVIUS 1500XDR array were used as a proton therapy system and detector, respectively. Our methods consisted of 2 parts: (1) the characteristics of the detector were tested and (2) patient-specific quality assurance was performed and evaluated by gamma analysis using dose-difference and distance-to-agreement criteria of 3% and 2 mm, respectively, with 123 treatment plans in head and neck, breast, chest, abdomen, and pelvic regions. Results:The PTW OCTAVIUS 1500XDR array had good reproducibility, uniformity, linearity, repetition rate, and monitor unit per spot within 0.1%, with accuracy, energy dependence, and measurement depth within 0.5%. The overall uncertainty of the PTW OCTAVIUS 1500XDR array was 2.49%. For field size and range shifter, using gamma analysis, the passing rate was 100%. The overall results of patient-specific quality assurance with the gamma evaluation were 98.9% ± 1.6% in 123 plans and confidence limit was 95.7%. Conclusion:The PTW OTAVIUS 1500XDR offered effective performance in pencil beam scanning proton therapy.

Characterisation and application of three-dimensional silicone-based radiochromic dosimetry in 1.5 T magnetic resonance imaging-guided radiotherapy

The magnetic field in magnetic resonance imaging-guided radiotherapy (MRgRT) systems influences the three-dimensional (3D) dose deposition and hence the delivered dose distributions. The aim of this study was to investigate the dose-rate dependency and dose response of silicone-based radiochromic dosimeters for photon irradiation in the precense of a magnetic field using a 1.5 T MRgRT system. Additionally, the study aimed to provide a proof of the concept of radiotherapy treatment based on a treatment plan calculated on magnetic resonance imaging rather than a computed tomography (CT) scan. The delivered dose was read out in 3D with an optical CT scanner and the dose distribution was verified using gamma analysis. We found an insignificant dose-rate dependency for dose rates ranging from 3.2 to 5.1 Gy/min and a linear dose response up to 20 Gy. A 3D 3%/3mm gamma analysis showed a pass rate of 95.1%. The dosimeter showed clinical potential for 3D dose verification of MRgRT delivery.

Developing a 3D-printing-based method to create anthropomorphic dosimeters for radiotherapy-delivery verification

Anthropomorphic three-dimensional (3D) dosimeters can be useful for verification of radiotherapy delivery. The aim of this study was to develop a 3D-printing-based method for creating anthropomorphic 3D dosimeters. Internal structures were created using water dissolvable 3D prints as negatives. External structures were 3D-printed, and a mould was produced using silicone rubber. Realistic liver and trachea dosimeters with both internal and external anthropomorphism were produced and subsequently irradiated with photons and protons. A 3%/3 mm gamma analysis resulted in 87% and 86% pass rates. The limiting factor to the resolution of the dosimeters was the 3D prints detail.

Comparison and evaluation of different deep learning models of synthetic CT generation from CBCT for nasopharynx cancer adaptive proton therapy.

Cone-beam computed tomography (CBCT) scanning is used for patient setup in image-guided radiotherapy. However, its inaccurate CT numbers limit its applicability in dose calculation and treatment planning. This study compares four deep learning methods for generating synthetic CT (sCT) to determine which method is more appropriate and offers potential for further clinical exploration in adaptive proton therapy for nasopharynx cancer. CBCTs and deformed planning CT (dCT) from 75 patients (60/5/10 for training, validation and testing) were used to compare cycle-consistent Generative Adversarial Network(cycleGAN), Unet, Unet+cycleGAN and conditionalGenerative Adversarial Network (cGAN) for sCT generation. The sCT images generated by each method were evaluated against dCT images using mean absolute error (MAE), structural similarity (SSIM), peak signal-to-noise ratio (PSNR), spatial non-uniformity (SNU) and radial averaging in the frequency domain. In addition, dosimetric accuracy was assessed through gamma analysis, differences in water equivalent thickness (WET), and dose-volume histogram metrics. The cGAN model has demonstrated optimal performance in the four models across various indicators. In terms of image quality under global condition, the average MAE has been reduced to 16.39HU, SSIM has increased to 95.24%, and PSNR has increased to 28.98. Regarding dosimetric accuracy, the gamma passing rate (2%/2mm) has reached 99.02%, and the WET difference is only 1.28mm. The D95 value of CTVs coverage and Dmax value of spinal cord, brainstem show no significant differences between dCT and sCT generated by cGAN model. The cGAN model has been shown to be a more suitable approach for generating sCT using CBCT, considering its characteristics and concepts. The resulting sCT has the potential for application in adaptive proton therapy.

Is it still necessary to perform measured based pre-treatment patient-specific QA for SRS HyperArc treatments?

The Mobius3D system was validated as a modern secondary check dosimetry system. In particular, our objective has been to assess the suitability of the M3D as pre-treatment patient-specific Quality Assurance (QA) tool for Stereotactic Radiosurgery (SRS) HyperArc (HA) treatments. We aimed to determine whether Mobius3D could safely replace the measurements-based patient-specific QA for this type of treatment. 30 SRS HA treatment plans for brain were selected. The dose distributions, calculated by Mobius and our routinely used algorithm (AcurosXB v.15.6), were compared using gamma analysis index and DVH parameters based on the patient's CT dataset. All 30 plans were then delivered across the ionization chamber in a homogeneous phantom and the measured dose was compared with both M3D and TPS calculated one. The plans were delivered and verified in terms of PSQA using the electronic portal imaging device (EPID) with Portal Dosimetry (PD) and myQA SRS (IBA Dosimetry) detector. Plans that achieved a global gamma passing rate (GPR) ≥ 97% based on 2%/2mm criteria, with both Mobius3D and the conventional methods were evaluated acceptable. Finally, we assessed the capability of the M3D system to detect errors related to the position of the Multi-Leaf Collimator (MLC) in comparison to the analyzed measurement-based systems. No relevant differences were observed in the comparison between the dose calculated on the CT-dataset by M3D and the TPS. Observed discrepancies are imputable to different used algorithms, but no discrepancies related to goodness of plans have been found. Average differences between calculated (M3D and TPS) vs measured dose with ionization chamber were 2.5% (from 0.41% to 3.2%) and 1.81% (from 0.66% to 2.65%), for M3D and TPS, respectively. All plans passed with a gamma passing rate>97% using conventional PSQA methods with a gamma criterion of 2% dose difference and 2mm distance-to-agreement. The average gamma passing rate for the M3D system was determined to be 99.4% (from 97.3% to 100%). Results from this study also demonstrated Mobius has better error detectability than conventional measurement-based systems. Our study shows Mobius3D could be a suitable alternative to conventional measured based QA methods for SRS HyperArc treatments.

Isodose surface differences: A novel tool for the comparison of dose distributions.

Comparing dose distributions is a routine task in radiotherapy, mainly in patient-specific quality assurance (PSQA). Currently, the evaluation of the dose distributions is being performed mainly with statistical methods, which could underestimate the clinical importance of the spotted differences, as per the literature. This paper aims to provide proof-of-concept for a novel dose distribution comparison method based on the difference of the isodose surfaces. The new method connects acceptance tolerance to QA limitations (equipment capabilities) and integrates a clinical approach into the analysis procedure. The distance of dose points from the isocenter can be used as a function to define the shape of an isodose surface expressed as a histogram. Isodose surface differences (ISD) are defined as the normalized differences of reference and evaluated surface histograms plotted against their corresponding isodose. Acceptance tolerances originate from actual QA tolerances and are presented clinically intuitively. The ISD method was compared to the gamma index using intentionally erroneous VMAT and IMRT plans. Results revealed that the ISD method is sensitive to all errors induced in the plans. Discrepancies are presented per isodose, enabling the evaluation of the plan in two regions representing PTV and Normal Tissue.ISD manages to flag errors that would remain undetected under the gamma analysis. The ISD method is a meaningful, QA-related, registration-free, and clinically oriented technique of dose distribution evaluation. This method can be used either as a standalone or an auxiliary tool to the well-established evaluation procedures, overcoming significant limitations reported in the literature.

Quality assurance for mixed electron-photon beam radiation therapy using treatment log files and MapCHECK.

Mixed photon-electron beam radiotherapy (MBRT) is a technique that combines the use of both photons and electrons in one single treatment plan to exploit their advantageous and complimentary characteristics. Compared to other photon treatment modalities, it has been shown that the MBRT technique contributes to better target coverage and organ-at-risk (OAR) sparing. However, the use of combined photons and electrons in one delivery makes the technique more complex and a well-established quality assurance (QA) protocol for MBRT isessential. To investigate the feasibility of using MapCHECK and log file-dose reconstruction for MBRT plan verification and to recommend a patient-specific quality assurance (PSQA) protocol forMBRT. MBRT plans were robustly optimized for five soft-tissue sarcoma (STS) patients. Each plan comprised step-and-shoot deliveries of a six MV photon beam and a combination of five electron beam energies at an SAD of 100 cm. The plans were delivered to the MapCHECK device with collapsed gantry angle and the 2D dose distributions at the detector depth were measured. To simulate the expected dose distribution delivered to the MapCHECK, a MapCHECK computational phantom was modeled in EGSnrc based on vendor-supplied blueprint information. The dose to the detectors in the model was scored using the DOSXYZnrc user code. The agreement between the measured and the simulated dose distribution was evaluated using 2D gamma analysis with a gamma criterion of 3%/2 mm and a low dose threshold of 10%. One of the plans was selected and delivered with a rotating gantry angle for trajectory log file collection. To evaluate the potential interlinac and intralinac differences, the plan was delivered repeatedly on three linacs. From the collected log files, delivery parameters were retrieved to recalculate the 3D dose distributions in the patient's anatomy with DOSXYZnrc. The recalculated mean dose to the clinical target volume (CTV) and OARs from all deliveries were computed and compared with the planned dose in terms of percentage difference. To validate the accuracy of log file-based QA, the log file-recalculated dose was also compared with filmmeasurement. The agreement of the total dose distribution between the MapCHECK measurement and simulation showed gamma passing rates of above 97% for all five MBRT plans. In the log file-dose recalculation, the difference between the recalculated and the planned dose to the CTV and OARs was below 1% for all deliveries. No significant inter- or intralinac differences were observed. The log file-dose had a gamma passing rate of 98.6% compared to filmmeasurement. Both the MapCHECK measurements and log file-dose recalculations showed excellent agreement with the expected dose distribution. This study demonstrates the potential of using MapCHECK and log files as MBRT QAtools.

Towards real-time EPID-based 3D in vivo dosimetry for IMRT with Deep Neural Networks: A feasibility study

We investigate the potential of the Deep Dose Estimate (DDE) neural network to predict 3D dose distributions inside patients with Monte Carlo (MC) accuracy, based on transmitted EPID signals and patient CTs. The network was trained using as input patient CTs and first-order dose approximations (FOD). Accurate dose distributions (ADD) simulated with MC were given as training targets. 83 pelvic CTs were used to simulate ADDs and respective EPID signals for subfields of prostate IMRT plans (gantry at 0∘). FODs were produced as backprojections from the EPID signals. 581 ADD-FOD sets were produced and divided into training and test sets. An additional dataset simulated with gantry at 90∘ (lateral set) was used for evaluating the performance of the DDE at different beam directions. The quality of the FODs and DDE-predicted dose distributions (DDEP) with respect to ADDs, from the test and lateral sets, was evaluated with gamma analysis (3%,2 mm). The passing rates between FODs and ADDs were as low as 46%, while for DDEPs the passing rates were above 97% for the test set. Meaningful improvements were also observed for the lateral set. The high passing rates for DDEPs indicate that the DDE is able to convert FODs into ADDs. Moreover, the trained DDE predicts the dose inside a patient CT within 0.6 s/subfield (GPU), in contrast to 14 h needed for MC (CPU-cluster). 3D in vivo dose distributions due to clinical patient irradiation can be obtained within seconds, with MC-like accuracy, potentially paving the way towards real-time EPID-based in vivo dosimetry.

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.