Assessing focal spot alignment in clinical linear accelerators: a comprehensive evaluation with triplet phantoms.

A fundamental parameter to evaluate the beam delivery precision and stability on a clinical linear accelerator (linac) is the focal spot position (FSP) measured relative to the collimator axis of the radiation head. The aims of this work were to evaluate comprehensive data on FSP acquired on linacs in clinical use and to establish the ability of alternative phantoms to detect effects on patient plan delivery related to FSP. FSP measurements were conducted using a rigid phantom holding two ball-bearings at two different distances from the radiation source. Images of these ball-bearings were acquired using the electronic portal imaging device (EPID) integrated with each linac. Machine QA was assessed using a radiation head-mounted PTW STARCHECK phantom. Patient plan QA was investigated using the SNC ArcCHECK phantom positioned on the treatment couch, irradiated with VMAT plans across a complete 360° gantry rotation and three X-ray energies. This study covered eight Elekta linacs, including those with 6 MV, 18 MV, and 6 MV flattening-filter-free (FFF) beams. The largest range in the FSP was found for 6 MV FFF. The FSP of one linac, retrofitted with 6 MV FFF, displayed substantial differences in FSP compared to 6 MV FFF beams on other linacs, which all had FSP ranges less than 0.50 mm and 0.25 mm in the lateral and longitudinal directions, respectively. The PTW STARCHECK phantom proved effective in characterising the FSP, while the SNC ArcCHECK measurements could not discern FSP-related features. Minor variations in FSP may be attributed to adjustments in linac parameters, component replacements necessary for beam delivery, and the wear and tear of various linac components, including the magnetron and gun filament. Consideration should be given to the ability of any particular phantom to detect a subsequent impact on the accuracy of patient plan delivery.

Accuracy of Beamscan Software in Determining the Inflection Point from the FFF Beam Profile Using Several Array Detectors.

OBJECTIVE: The goal of this study is to determine the accuracy of the PTW Beamscan program in determining the inflection point from Flattening Filter Free Beam Profile utilizing Multiple Detectors. METHODS: True Beam Linear Accelerator with 6FFF and 10FFF Photon Energies and 10 cm, 15 cm and 20 cm Field Sizes were used for this study. Profile measurements were taken with PTW's 729, 1,500, and 1,600 and the Starcheck system, the Pinpoint 3D with Beamscan system, and Linac's EPID. The first-order derivative was utilized in both the Excel spreadsheet and Beamscan software to analyse raw measured data to locate inflection point and the FWHM was calculated. The accuracy of inflection points and FWHM between the Excel sheet calculation and the software program were investigated. RESULTS: For 10X10 cm2 in the 729 Array, the greatest differences in FWHM were 5.16 mm and 5.04 mm for the X6 FFF and X10 FFF Energies, respectively. The largest difference was 2.26 mm for 1,600 SRS arrays with a 15×15 cm2 field size. The difference in FWHM between Manual and software analysis for 10X10 cm2 and 20X20 cm2 Field Sizes is in decreasing order for detectors from 729, 1,500, 1,600 SRS, Starcheck, Pinpoint 3D, and EPID. In contrast, there is no climbing or declining pattern detected in the difference in Field Width for the 15×15 cm2 Field Size. Similarly, for all detectors except the 1,600 SRS array, the peak of the first-order derivative occurs at the chamber position for a 15X15 cm2 field size. CONCLUSION: The higher resolution of measurement yields more accuracy in inflection point and the FWHM. Irrespective of measurement resolution, the Beamscan software provided the FWHM closer to the respective nominal Field Size. Out of all detectors, results obtained with Excel Starcheck and EPID are good in agreement with values obtained by the software analysis. Thus, it is shown that Beamscan software is so accurate in determining inflection point of a FFF beam profile and used for routine profile analysis.

Small field measurements using electronic portal imaging device.

Purpose/Objective. Small-field measurement poses challenges. Although many high-resolution detectors are commercially available, the EPID for small-field dosimetry remains underexplored. This study aimed to evaluate the performance of EPID for small-field measurements and to derive tailored correction factors for precise small-field dosimetry verification.Material/Methods. Six high-resolution radiation detectors, including W2 and W1 plastic scintillators, Edge-detector, microSilicon, microDiamond and EPID were utilized. The output factors, depth doses and profiles, were measured for various beam energies (6 MV-FF, 6 MV-FFF, 10 MV-FF, and 10 MV-FFF) and field sizes (10 × 10 cm2, 5 × 5 cm2, 4 × 4 cm2, 3 × 3 cm2, 2 × 2 cm2, 1 × 1 cm2, 0.5 × 0.5 cm2) using a Varian Truebeam linear accelerator. During measurements, acrylic plates of appropriate depth were placed on the EPID, while a 3D water tank was used with five-point detectors. EPID measured data were compared with W2 plastic scintillator and measurements from other high-resolution detectors. The analysis included percentage deviations in output factors, differences in percentage for PDD and for the profiles, FWHM, maximum difference in the flat region, penumbra, and 1D gamma were analyzed. The output factor and depth dose ratios were fitted using exponential functions and fractional polynomial fitting in STATA 16.2, with W2 scintillator as reference, and corresponding formulae were obtained. The established correction factors were validated using two Truebeam machines.Results. When comparing EPID and W2-PSD across all field-sizes and energies, the deviation for output factors ranged from 1% to 15%. Depth doses, the percentage difference beyond dmax ranged from 1% to 19%. For profiles, maximum of 4% was observed in the 100%-80% region. The correction factor formulae were validated with two independent EPIDs and closely matched within 3%.Conclusion. EPID can effectively serve as small-field dosimetry verification tool with appropriate correction factors.

Research on the correction method for radiotherapy verification plans based on displaced electronic portal imaging device.

BACKGROUND: It has been observed that under the single isocenter conditions, the potential shifts of the electronic portal imaging devices (EPID) may be introduced when executing portal dosimetry (PD) plans for bilateral breast cancer, pleural mesothelioma, and lymphoma. These shifts are relative to the calibration positions of EPID and result in significant discrepancies in the plan verification results. PURPOSE: To explore methods including correction model and specific correction matrices to revise the data obtained from displaced EPID. METHODS: Two methods, the correction model and the specific correction matrices, were applied to correct the data. Five experiments were designed and conducted to build correction model and to validate the effectiveness of these two methods. Gamma passing rates were calculated and data profiles along X-axis and Y-axis were captured. RESULTS: The gamma passing rates for the EPID-displaced IMRT validation plans after applying correction model, along with the application of specific correction matrices to VMAT and IMRT validation plans, exhibit results that are comparable to the cases with non-displaced EPID. Except for the VMAT plans applied correction model which showed larger discrepancies (0.041 ± 0.028, 0.049 ± 0.030), the other three exhibit minimal differences in discrepancy values. In all profiles, the corrected data from displaced EPID exhibit a high level of agreement with data obtained from non-displaced EPID. Good consistency is observed in actual application of the correction model and the specific correction matrices between gamma passing rates of data corrected and those of non-displaced data. CONCLUSIONS: The proposed methods involving correction model and specific correction matrices can correct the data collected from the displaced EPID, and the gamma passing rates of the corrected data show results that are comparable to some extent with those of non-displaced data. Particularly, the results corrected by specific correction matrices closely resemble the data from non-displaced EPID.

[Research on Position Verification of Multi-Leaf Collimator (MLC) and Dose Verification Based on Electronic Portal Imaging Device].

Objective: A quality control (QC) system based on the electronic portal imaging device (EPID) system was used to realize the Multi-Leaf Collimator (MLC) position verification and dose verification functions on Primus and VenusX accelerators. Methods: The MLC positions were calculated by the maximum gradient method of gray values to evaluate the deviation. The dose of images acquired by EPID were reconstructed using the algorithm combining dose calibration and dose calculation. The dose data obtained by EPID and two-dimensional matrix (MapCheck/PTW) were compared with the dose calculated by Pinnacle/TiGRT TPS for γ passing rate analysis. Results: The position error of VenusX MLC was less than 1 mm. The position error of Primus MLC was significantly reduced after being recalibrated under the instructions of EPID. For the dose reconstructed by EPID, the average γ passing rates of Primus were 98.86% and 91.39% under the criteria of 3%/3 mm, 10% threshold and 2%/2 mm, 10% threshold, respectively. The average γ passing rates of VenusX were 98.49% and 91.11%, respectively. Conclusion: The EPID-based accelerator quality control system can improve the efficiency of accelerator quality control and reduce the workload of physicists.

In vivo EPID-based daily treatment error identification for volumetric-modulated arc therapy in head and neck cancers with a hierarchical convolutional neural network: a feasibility study.

We proposed a deep learning approach to classify various error types in daily VMAT treatment of head and neck cancer patients based on EPID dosimetry, which could provide additional information to support clinical decisions for adaptive planning. 146 arcs from 42 head and neck patients were analyzed. Anatomical changes and setup errors were simulated in 17,820 EPID images of 99 arcs obtained from 30 patients using in-house software for model training, validation, and testing. Subsequently, 141 clinical EPID images from 47 arcs belonging to the remaining 12 patients were utilized for clinical testing. The hierarchical convolutional neural network (HCNN) model was trained to classify error types and magnitudes using EPID dose difference maps. Gamma analysis with 3%/2 mm (dose difference/distance to agreement) criteria was also performed. The F1 score, a combination of precision and recall, was utilized to evaluate the performance of the HCNN model and gamma analysis. The adaptive fractioned doses were calculated to verify the HCNN classification results. For error type identification, the overall F1 score of the HCNN model was 0.99 and 0.91 for primary type and subtype identification, respectively. For error magnitude identification, the overall F1 score in the simulation dataset was 0.96 and 0.70 for the HCNN model and gamma analysis, respectively; while the overall F1 score in the clinical dataset was 0.79 and 0.20 for the HCNN model and gamma analysis, respectively. The HCNN model-based EPID dosimetry can identify changes in patient transmission doses and distinguish the treatment error category, which could potentially provide information for head and neck cancer treatment adaption.

Integrating cine EPID, dynamic delivery, and the off-axis Winston-Lutz test to enhance quality control in multiple brain metastasis stereotactic radiotherapy.

PURPOSE: Stereotactic radiotherapy (SRT) has transformed cancer treatment, especially for brain metastases. Ensuring accurate SRT delivery is crucial, with the Winston-Lutz test being an important quality control tool. Off-axis Winston-Lutz (OAWL) tests are designed for accuracy assessment, but most are limited to fixed angles and hampered by local-field shifts caused by suboptimal Multi-Leaf Collimator (MLC) positioning. This study introduces a new OAWL approach for quality control in multi-brain-metastasis SRT. Utilizing cine Electronic Portal Imaging Device (EPID) images, it can be used with dynamic conformal arc (DCA) therapy. However, dynamic OAWL (DOAWL) is prone to more local-field shifts due to dynamic MLC movements. A two-step DOAWL is proposed: step 1 calculates local-field shifts using dynamic MLC movements in the beam-eye view data from the Treatment Planning System (TPS), while step 2 processes cine EPID images with an OAWL algorithm to isolate true deviations. METHODS: Validation involved an anthropomorphic head phantom with metallic ball-bearings, Varian TrueBeam STx accelerator delivering six coplanar/non-coplanar DCA beams, cine EPID, and ImageJ's OAWL analysis algorithm. RESULTS: Inherent local-field shifts ranged from 0.11 to 0.49 mm; corrected mean/max EPID-measured displacement was 0.34/1.03 mm. Few points exceeded 0.75/1.0-mm thresholds. CONCLUSIONS: This two-step DOAWL test merges cine-EPID acquisitions, DCA, OAWL, and advanced analysis and offers effective quality control for multi-brain-metastasis SRT. Its routine implementation may also improve physicist knowledge of the treatment precision of their machines.

Automation to facilitate optimisation of breast radiotherapy treatments using EPID-basedin vivodosimetry.

Objective. To use automation to facilitate the monitoring of each treatment fraction using an electronic portal imaging device (EPID) basedin vivodosimetry (IVD) system, allowing optimisation of breast radiotherapy delivery for individual patients and cohorts.Approach. A suite of in-house software was developed to reduce the number of manual interactions with the commercial IVD system, dosimetry check. An EPID specific pixel sensitivity map facilitated use of the EPID panel away from the central axis. Point dose difference and the change in standard deviation in dose were identified as useful dose metrics, with standard deviation used in preference to gamma in the presence of a systematic dose offset. Automated IVD was completed for 3261 fractions across 704 patients receiving breast radiotherapy.Main results. Multiple opportunities for treatment optimisation were identified for individual patients and across patient cohorts as a result of successful implementation of automated IVD. 5.1% of analysed fractions were out of tolerance with 27.1% of these considered true positives. True positive results were obtained on any fraction of treatment and if IVD had only been completed on the first fraction, 84.4% of true positive results would have been missed. This was made possible due to the automation that saved over 800 h of manual intervention and stored data in an accessible database.Significance. An improved EPID calibration to allow off-axis measurement maximises the number of patients eligible for IVD (36.8% of patients in this study). We also demonstrate the importance in selecting context-specific assessment metrics and how these can lead to a managable false positive rate. We have shown that the use of fully automated IVD facilitates use on every fraction of treatment. This leads to identification of areas for treatment improvement for both individuals and across a patient cohort, expanding the uses of IVD from simply gross error detection towards treatment optimisation.

A Novel Approach for Position Verification and Dose Calculation through Local MVCT Reconstruction.

Traditional positioning verification using cone-beam computed tomography (CBCT) may incur errors due to potential misalignments between the isocenter of CBCT and the treatment beams in radiotherapy. This study introduces an innovative method for verifying patient positioning in radiotherapy. Initially, the transmission images from an electronic portal imaging device (EPID) are acquired from 10 distinct angles. Utilizing the ART-TV algorithm, a sparse reconstruction of local megavoltage computed tomography (MVCT) is performed. Subsequently, this MVCT is aligned with the planning CT via a three-dimensional mutual information registration technique, pinpointing any patient-positioning discrepancies and facilitating corrective adjustments to the treatment setup. Notably, this approach employs the same radiation source as used in treatment to obtain three-dimensional images, thereby circumventing errors stemming from misalignment between the isocenter of CBCT and the accelerator. The registration process requires only 10 EPID images, and the dose absorbed during this process is included in the total dose calculation. The results show that our method's reconstructed MVCT images fulfill the requirements for registration, and the registration algorithm accurately detects positioning errors, thus allowing for adjustments in the patient's treatment position and precise calculation of the absorbed dose.

Commissioning and dosimetric verification of volumetric modulated arc therapy for multiple modalities using electronic portal imaging device-based 3D dosimetry system: a novel approach.

The purpose of this study was to validate an electronic portal imaging device (EPID) based 3-dimensional (3D) dosimetry system for the commissioning of volumetric modulated arc therapy (VMAT) delivery for flattening filter (FF) and flattening filter free (FFF) modalities based on test suites developed according to American Association of Physicists in Medicine Task Group 119 (AAPM TG 119) and pre-treatment patient specific quality assurance (PSQA).With ionisation chamber, multiple-point measurement in various planes becomes extremely difficult and time-consuming, necessitating repeated exposure of the plan. The average agreement between measured and planned doses for TG plans is recommended to be within 3%, and both the ionisation chamber and PerFRACTION™ measurement were well within this prescribed limit. Both point dose differences with the planned dose and gamma passing rates are comparable with TG reported multi-institution results. From our study, we found that no significant differences were found between FF and FFF beams for measurements using PerFRACTION™ and ion chamber. Overall, PerFRACTION™ produces acceptable results to be used for commissioning and validating VMAT and for performing PSQA. The findings support the feasibility of integrating PerFRACTION™ into routine quality assurance procedures for VMAT delivery. Further multi-institutional studies are recommended to establish global baseline values and enhance the understanding of PerFRACTION™'s capabilities in diverse clinical settings.

Feasibility of Ethos adaptive treatments of lung tumors and associated quality assurance.

MOTIVATION: Online adaptive radiotherapy with Ethos is based on the anatomy determined from daily cone beam computed tomography (CBCT) images. Dose optimization and computation are performed on the density map of a synthetic CT (sCT), a deformable registration of the initial planning CT (pCT) onto the current CBCT. Large density changes as present in the lung region are challenging the system. METHODS: Treatment plans for Ethos were created and delivered for 1, 2, and 3 cm diameter lung lesions in an anthropomorphic phantom, combining different insets in the pCT and during adaptive and non-adaptive treatment sessions. Primary and secondary dose calculations as well as back-projected dose from portal images were evaluated. RESULTS: Density changes due to changed insets were not considered in the sCTs. This resulted in errors in the dose; for example, -15.9% of the mean dose for a plan when changing from a 3 cm inset in the pCT to 1 cm at the time of treatment. Secondary dose calculation is based on the sCT and could therefore not reveal these dose errors. However, dose calculation on the CBCT, either as a recalculation in the treatment planning system or as pre-treatment quality assurance (QA) before the treatment, indicated the differences. EPID in-vivo QA also reported discrepancies between calculated and delivered dose distributions. CONCLUSIONS: An incorrect density distribution in the sCT has an impact on the dose calculation accuracy in the adaptive treatment workflow with the Ethos system. Additional quality checks of the sCT can detect such errors.

MV-based relative electron density estimation (iMREDe) for MR-LINAC dose calculation.

BACKGROUND: MR-LINAC systems have been increasingly utilized for real-time imaging in adaptive treatments worldwide. Challenges in MR representation of air cavities and subsequent estimation of electron density maps impede planning efficiency and may lead to dose calculation uncertainties. PURPOSE: To demonstrate the generation of accurate electron density maps using the primary MV beam with a flat-panel imager. METHODS: The ViewRay MRIdian MR-LINAC system was modeled digitally for Monte Carlo simulations. Iron shimming, the magnetic field, and the proposed flat panel detector were included in the model. The effect of the magnetic field on the detector response was investigated. Acquisition of projections over 360 degrees was simulated for digital phantoms of the Catphan 505 phantom and a patient treated for Head and Neck cancer. Shim patterns on the projections were removed and detector noise linearity was assessed. Electron density maps were generated for the digital patient phantom using the flat-panel detector and compared with actual treatment planning CT generated electron density maps of the same patient. RESULTS: The effect of the magnetic field on the detector point-spread function (PSF) was found to be substantial for field strengths above 50 mT. Shims correction in the projection images using air normalization and in-painting effectively removed reconstruction artifacts without affecting noise linearity. The relative difference between reconstructed electron density maps from the proposed method and electron density maps generated from the treatment planning CT was 11% on average along all slices included in the iMREDe reconstruction. CONCLUSIONS: The proposed iMREDe technique demonstrated the feasibility of generating accurate electron densities for the ViewRay MRIdian MR-LINAC system with a flat-panel imager and the primary MV beam. This work is a step towards reducing the time and effort required for adaptive radiotherapy in the current ViewRay MR-LINAC systems.

The performance of a new type accelerator uRT-linac 506c evaluated by a quality assurance automation system.

PURPOSE: The purpose of this study was to evaluate the performance of our quality assurance (QA) automation system and to evaluate the machine performance of a new type linear accelerator uRT-linac 506c within 6 months using this system. METHODS: This QA automation system consists of a hollow cylindrical phantom with 18 steel balls in the phantom surface and an analysis software to process electronic portal imaging device (EPID) measurement image data and report the results. The performance of the QA automation system was evaluated by the tests of repeatability, archivable precision, detectability of introduced errors, and the impact of set-up errors on QA results. The performance of this linac was evaluated by 31 items using this QA system over 6 months. RESULTS: This QA system was able to automatically deliver QA plan, EPID image acquisition, and automatic analysis. All images acquiring and analysis took approximately 4.6 min per energy. The preset error of 0.1 mm in multi-leaf collimator (MLC) leaf were detected as 0.12 ± 0.01 mm for Bank A and 0.10 ± 0.01 mm in Bank B. The 2 mm setup error was detected as -1.95 ± 0.01 mm, -2.02 ± 0.01 mm, 2.01 ± 0.01 mm for X, Y, Z directions, respectively. And data from the tests of repeatability and detectability of introduced errors showed the standard deviation were all within 0.1 mm and 0.1°. and data of the machine performance were all within the tolerance specified by AAPM TG-142. CONCLUSIONS: The QA automation system has high precision and good performance, and it can improve the QA efficiency. The performance of the new accelerator has also performed very well during the testing period.

Efficient quality assurance for isocentric stability in stereotactic body radiation therapy using machine learning.

This study aims to predict isocentric stability for stereotactic body radiation therapy (SBRT) treatments using machine learning (ML), covers the challenges of manual assessment and computational time for quality assurance (QA), and supports medical physicists to enhance accuracy. The isocentric parameters for collimator (C), gantry (G), and table (T) tests were conducted with the RUBY phantom during QA using TrueBeam linac for SBRT. This analysis combined statistical features from the IsoCheck EPID software. Five ML models, including logistic regression (LR), decision tree (DT), random forest (RF), naive Bayes (NB), and support vector machines (SVM), were used to predict the outcome of the QA procedure. 247 Winston-Lutz (WL) tests were collected from 2020 to 2022. In our study, both DT and RF achieved the highest score on test accuracy (Acc. test) ranging from 93.5% to 99.4%, and area under curve (AUC) values from 90 to 100% on three modes (C, G, and T). The precision, recall, and F1 scores indicate the DT model consistently outperforms other ML models in predicting isocenter stability deviation in QA. The QA assessment using ML models can assist error prediction early to avoid potential harm during SBRT and ensure safe and effective patient treatments.

Deep learning-based tools to distinguish plan-specific from generic deviations in EPID-based in vivo dosimetry.

BACKGROUND: Dose distributions calculated with electronic portal imaging device (EPID)-based in vivo dosimetry (EIVD) differ from planned dose distributions due to generic and plan-specific deviations. Generic deviations are characteristic to a class of plans. Examples include limitations in EIVD dose reconstruction, inaccuracies in treatment planning system (TPS) calculations and systematic machine deviations. Plan-specific deviations have an unpredictable character. Examples include discrepancies between the patient model used for dose calculation and the patient position or anatomy during delivery, random machine deviations, and data transfer, human or software errors. During the inspection work performed with traditional γ-evaluation statistical methods: (i) generic deviations raise alerts that need to be inspected but that rarely lead to action as their root cause is usually understood and (ii) the detection of relevant plan-specific deviations may be hindered by the presence of generic deviations. PURPOSE: To investigate whether deep learning-based tools can help in identifying γ-alerts raised by generic deviations and in improving the detectability of plan-specific deviations. METHODS: A 3D U-Net was trained as an autoencoder to reconstruct underlying patterns of generic deviations in γ-distributions. The network was trained for four treatment disease sites differently affected by generic deviations: volumetric modulated arc therapy (VMAT) lung (no known deviations), VMAT prostate (TPS inaccuracies), VMAT head-and-neck (EIVD limitations) and intensity modulated radiation therapy (IMRT) breast (large EIVD limitations). The network was trained with virtual non-transit γ-distributions: 60 train/10 validation for the VMAT sites and 30 train/10 validation for IMRT breast. It was hypothesized that in vivo γ-distributions obtained in the presence of plan-specific deviations would differ from those seen during training. For each disease site, the sensitivity of γ-analysis and the network to detect (synthetically introduced) patient-related deviations was compared by receiver operator characteristic analysis. The investigated deviations were patient positioning errors, weight gain or loss, and tumor volume changes. The clinical relevance was illustrated qualitatively with 793 in vivo clinical cases (141 lung, 136 head-and-neck, 209 prostate and 307 breast). RESULTS: Error detectability of patient-related deviations was better with the network than with γ-analysis. The average area under the curve values over all sites were 0.86 ± 0.12(1SD) and 0.69 ± 0.25(1SD), respectively. Regarding in vivo clinical results, the percentage of cases differently classified by γ-analysis and the network was 1%, 19%, 18% and 64% for lung, head-and-neck, prostate, and breast, respectively. In head-and-neck and breast cases, 45 γ-only alerts were examined, of which 43 were attributed to EPID dose reconstruction limitations. For prostate, all 15 investigated γ-only alerts were due to known TPS inaccuracies. All 59 investigated network alerts were explained by either patient-related deviations or EPID acquisition incidents. Some patient-related deviations detected by the network were not detected by γ-analysis. CONCLUSIONS: Deep learning-based tools trained to reconstruct underlying patterns of generic deviations in γ-distributions can be used to (i) automatically identify false positives within the set of γ-alerts and (ii) improve the detection of plan-specific deviations, hence minimizing the likelihood of false negatives. The presented method provides clear additional value to the γ-alert management process for large scale EIVD systems.

[Development of a Phantom and Analysis Program for Assessment of Positional Accuracy of Image-guided Radiation Therapy].

PURPOSE: We created a phantom and analysis program for the assessment of IGRT positional accuracy. We verified the accuracy of analysis and the practicality of this evaluation method at several facilities. METHOD: End-to-end test was performed using an in-house phantom, and EPID images were acquired after displacement by an arbitrary amount using a micrometer, with after image registration as the reference. The difference between the center of the target and the irradiated field was calculated using our in-house analysis program and commercial software. The end-to-end test was conducted at three facilities, and the IGRT positional accuracy evaluation was verified. RESULT: The maximum difference between the displacement of the target determined from the EPID image and the arbitrary amount of micrometer displacement was 0.24 mm for the in-house analysis program and 0.30 mm for the commercial software. The maximum difference between the center of the target and the irradiation field on EPID images acquired at the three facilities was 0.97 mm. CONCLUSION: The proposed evaluation method using our in-house phantom and analysis program can be used for the assessment of IGRT positional accuracy.

A phantom based evaluation of the clinical imaging performance of electronic portal imaging devices.

Purpose: In this study an evaluation of the imaging performance of an electronic portal imaging device (EPID) is presented. The evaluation performed employing the QC-3V image quality phantom. Methods: An EPID system of a 6 MV LINAC, was used to obtain images of a QC-3V EPID phantom. The X-ray source to phantom distance was 100 cm and the field size was 15x15 cm2. The irradiation conditions comprised Dose Rates (DR) of 200, 400 and 600 for a 2 MU-100 MU range. The Contrast Transfer Function (CTF), the Noise Power Spectrum (NPS), the Normalized Noise Power Spectrum (NNPS) and the Contrast-to-Noise Ratio (CNR) were studied. In addition, an alternative factor showing a frequency related output signal-to-noise ratio (SNR), the Signal-to-Noise-Frequency Response (SNFR), has been introduced. SNFR is a comprehensive quality index, easily determined in clinical environment. Results: The CTF curves were found comparable to each other. The lowest values were measured at 2 MU and 200 MU/min. Concerning the NPS and NNPS graphs it was found that the values decrease up to approximately 0.3 lp/mm and demonstrate a white noise shape afterwards. SNFR values were found reducing with spatial frequency. Highest CNR were found between the region 7 and 11 of the phantom. Conclusions: The influence of MU and DR on EPID performance were investigated. Image quality was assessed using the QC-3V phantom. The presented results can lead to image quality amelioration and act supportively to current image quality control routine protocols.

Investigation of Intra-fraction Stability and Inter-fraction Consistency of Active Breathing Coordinator (ABC)-Based Deep Inspiration Breath Holds in Left-Sided Breast Cancer.

Background Deep inspiration breath-hold (DIBH) has been established as a standard technique to reduce cardiac dose. The part of the heart exposed to radiation can be significantly decreased using the DIBH technique during tangential left-sided breast cancer (LSBC) irradiation. Aim The objective of this study was to investigate the intra-fraction breath-hold stability and inter-fraction consistency of patient breath-hold against the threshold as a function of air volumes in the setting of active breathing coordinator (ABC)-based DIBH (ABC-DIBH) treatment to LSBC. Methods A total of 34 patients treated with external beam radiation therapy (EBRT) to the left breast using the ABC-DIBH device were included. The frequency of breath-holds per fraction and the entire course of treatment along with the total treatment time was evaluated for all patients. A prescription dose of either 200 cGy (conventional) or 267 cGy (hypofractionation) was administered during 649 fractions, resulting in a total of 4,601 breath-hold measurements being evaluated. The amplitude of deviation in terms of air volumes between the baseline threshold and the patient-specific measurement (during each breath-hold) per fraction was used to define the DIBH stability. Likewise, the consistency of the breathing amplitudes was used to define the compliance of patient breath-holds throughout the entire treatment period. Positional accuracy was evaluated using orthogonal (portal) images. Results The average number of breath-holds measured over the entire course of treatment for each patient was 144 inspirations (58-351). Similarly, the average number of breath-holds for each fraction during the course of treatment was 11 inspirations (7-21), which included setup imaging and treatment. The total number of breath-holds reduced significantly (p-value < 0.05) with hypofractionation (104 inspirations; range 58-170) as compared to conventional fractionation (145 inspirations; 58-351). The average breath-hold threshold in terms of air volume was 1.41 L (0.6-2.1 L) for all patients. The total treatment time reduced significantly after the third fraction (p-value < 0.05). The average deviation between the measured and baseline threshold breath-holds during the course of treatment was 0.5 L/sec (0.12-1.32 L/sec). The consistency of the breathing amplitudes were maintained within ±0.05 L during the entire treatment for all patients. The average translational shifts measured during setup were 0.28 cm ± 0.3 cm, 0.38 cm ± 0.4 cm, and 0.21 cm ± 0.3 cm in the lateral, longitudinal, and vertical directions, respectively. Conclusion The study has demonstrated the variations in intra-fraction breath-hold stability and inter-fraction breath-hold consistency in terms of air volumes for patients who were treated for LSBC. The frequency of breath-holds was observed to be higher with increased total treatment time for the first few fractions and reduced over the course of treatment.

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.

Investigation of uncertainty in internal target volume definition for lung stereotactic body radiotherapy.

This study evaluated the validity of internal target volumes (ITVs) defined by three- (3DCT) and four-dimensional computed tomography (4DCT), and subsequently compared them with actual movements during treatment. Five patients with upper lobe lung tumors were treated with stereotactic body radiotherapy (SBRT) at 48 Gy in four fractions. Planning 3DCT images were acquired with peak-exhale and peak-inhale breath-holds, and 4DCT images were acquired in the cine mode under free breathing. Cine images were acquired using an electronic portal imaging device during irradiation. Tumor coverage was evaluated based on the manner in which the peak-to-peak breathing amplitude on the planning CT covered the range of tumor motion (± 3 SD) during irradiation in the left-right, anteroposterior, and cranio-caudal (CC) directions. The mean tumor coverage of the 4DCT-based ITV was better than that of the 3DCT-based ITV in the CC direction. The internal margin should be considered when setting the irradiation field for 4DCT. The proposed 4DCT-based ITV can be used as an efficient approach in free-breathing SBRT for upper-lobe tumors of the lung because its coverage is superior to that of 3DCT.