Unifying gamma passing rates in patient-specific QA for VMAT lung cancer treatment based on data assimilation.

This study aimed to identify systematic errors in measurement-, calculation-, and prediction-based patient-specific quality assurance (PSQA) methods for volumetric modulated arc therapy (VMAT) on lung cancer and to standardize the gamma passing rate (GPR) by considering systematic errors during data assimilation. This study included 150 patients with lung cancer who underwent VMAT. VMAT plans were generated using a collapsed-cone algorithm. For measurement-based PSQA, ArcCHECK was employed. For calculation-based PSQA, Acuros XB was used to recalculate the plans. In prediction-based PSQA, GPR was forecasted using a previously developed GPR prediction model. The representative GPR value was estimated using the least-squares method from the three PSQA methods for each original plan. The unified GPR was computed by adjusting the original GPR to account for systematic errors. The range of limits of agreement (LoA) were assessed for the original and unified GPRs based on the representative GPR using Bland-Altman plots. For GPR (3%/2 mm), original GPRs were 94.4 ± 3.5%, 98.6 ± 2.2% and 93.3 ± 3.4% for measurement-, calculation-, and prediction-based PSQA methods and the representative GPR was 95.5 ± 2.0%. Unified GPRs were 95.3 ± 2.8%, 95.4 ± 3.5% and 95.4 ± 3.1% for measurement-, calculation-, and prediction-based PSQA methods, respectively. The range of LoA decreased from 12.8% for the original GPR to 9.5% for the unified GPR across all three PSQA methods. The study evaluated unified GPRs that corrected for systematic errors. Proposing unified criteria for PSQA can enhance safety regardless of the methods used.

Applications of artificial intelligence for machine- and patient-specific quality assurance in radiation therapy: current status and future directions.

Machine- and patient-specific quality assurance (QA) is essential to ensure the safety and accuracy of radiotherapy. QA methods have become complex, especially in high-precision radiotherapy such as intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), and various recommendations have been reported by AAPM Task Groups. With the widespread use of IMRT and VMAT, there is an emerging demand for increased operational efficiency. Artificial intelligence (AI) technology is quickly growing in various fields owing to advancements in computers and technology. In the radiotherapy treatment process, AI has led to the development of various techniques for automated segmentation and planning, thereby significantly enhancing treatment efficiency. Many new applications using AI have been reported for machine- and patient-specific QA, such as predicting machine beam data or gamma passing rates for IMRT or VMAT plans. Additionally, these applied technologies are being developed for multicenter studies. In the current review article, AI application techniques in machine- and patient-specific QA have been organized and future directions are discussed. This review presents the learning process and the latest knowledge on machine- and patient-specific QA. Moreover, it contributes to the understanding of the current status and discusses the future directions of machine- and patient-specific QA.

Technical note: A universal worksheet for failure mode and effects analysis-A project of the Japanese College of Medical Physics.

BACKGROUND: Failure mode and effects analysis (FMEA), which is an effective tool for error prevention, has garnered considerable attention in radiotherapy. FMEA can be performed individually, by a group or committee, and online. PURPOSE: To meet the needs of FMEA for various purposes and improve its accessibility, we developed a simple, self-contained, and versatile web-based FMEA risk analysis worksheet. METHODS: We developed an FMEA worksheet using Google products, such as Google Sheets, Google Forms, and Google Apps Script. The main sheet was created in Google Sheets and contained elements necessary for performing FMEA by a single person. Automated tasks were implemented using Apps Script to facilitate multiperson FMEA; these functions were built into buttons located on the main sheet. RESULTS: The usability of the FMEA worksheet was tested in several situations. The worksheet was feasible for individual, multiperson, seminar, meeting, and online purposes. Simultaneous online editing, automated survey form creation, automatic analysis, and the ability to respond to the form from multiple devices, including mobile phones, were particularly useful for online and multiperson FMEA. Automation enabled through Google Apps Script reduced the FMEA workload. CONCLUSIONS: The FMEA worksheet is versatile and has a seamless workflow that promotes collaborative work for safety.

Protocol of a phase II study to evaluate the efficacy and safety of deep-inspiration breath-hold daily online adaptive radiotherapy for centrally located lung tumours (PUDDING study).

BACKGROUND: Centrally located lung tumours present a challenge because of their tendency to exhibit symptoms such as airway obstruction, atelectasis, and bleeding. Surgical resection of these tumours often requires sacrificing the lungs, making definitive radiotherapy the preferred alternative to avoid pneumonectomy. However, the proximity of these tumours to mediastinal organs at risk increases the potential for severe adverse events. To mitigate this risk, we propose a dual-method approach: deep inspiration breath-hold (DIBH) radiotherapy combined with adaptive radiotherapy. The aim of this single-centre, single-arm phase II study is to investigate the efficacy and safety of DIBH daily online adaptive radiotherapy. METHODS: Patients diagnosed with centrally located lung tumours according to the International Association for the Study of Lung Cancer recommendations, are enrolled and subjected to DIBH daily online adaptive radiotherapy. The primary endpoint is the one-year cumulative incidence of grade 3 or more severe adverse events, as classified by the Common Terminology Criteria for Adverse Events (CTCAE v5.0). DISCUSSION: Delivering definitive radiotherapy for centrally located lung tumours presents a dilemma between ensuring optimal dose coverage for the planning target volume and the associated increased risk of adverse events. DIBH provides measurable dosimetric benefits by increasing the normal lung volume and distancing the tumour from critical mediastinal organs at risk, leading to reduced toxicity. DIBH adaptive radiotherapy has been proposed as an adjunct treatment option for abdominal and pelvic cancers. If the application of DIBH adaptive radiotherapy to centrally located lung tumours proves successful, this approach could shape future phase III trials and offer novel perspectives in lung tumour radiotherapy. TRIAL REGISTRATION: Registered at the Japan Registry of Clinical Trials (jRCT; https://jrct.niph.go.jp/ ); registration number: jRCT1052230085 ( https://jrct.niph.go.jp/en-latest-detail/jRCT1052230085 ).

Influence of dose calculation algorithms on the helical diode array using volumetric-modulated arc therapy for small targets.

BACKGROUND: For patient-specific quality assurance (PSQA) for small targets, the dose resolution can change depending on the characteristics of the dose calculation algorithms. PURPOSE: This study aimed to evaluate the influence of the dose calculation algorithms Acuros XB (AXB), anisotropic analytical algorithm (AAA), photon Monte Carlo (pMC), and collapsed cone (CC) on a helical diode array using volumetric-modulated arc therapy (VMAT) for small targets. MATERIALS AND METHODS: ArcCHECK detectors were inserted with a physical depth of 2.9 cm from the surface. To evaluate the influence of the dose calculation algorithms for small targets, rectangular fields of 2×100, 5×100, 10×100, 20×100, 50×100, and 100×100 mm2 were irradiated and measured using ArcCHECK with TrueBeam STx. A total of 20 VMAT plans for small targets, including the clinical sites of 19 brain metastases and one spine, were also evaluated. The gamma passing rates (GPRs) were evaluated for the rectangular fields and the 20 VMAT plans using AXB, AAA, pMC, and CC. RESULTS: For rectangular fields of 2×100 and 5×100 mm2, the GPR at 3%/2 mm of AXB was < 50% because AXB resulted in a coarser dose resolution with narrow beams. For field sizes > 10×100 mm2, the GPR at 3%/2 mm was > 88.1% and comparable for all dose calculation algorithms. For the 20 VMAT plans, the GPRs at 3%/2 mm were 79.1 ± 15.7%, 93.2 ± 5.8%, 94.9 ± 4.1%, and 94.5 ± 4.1% for AXB, AAA, pMC, and CC, respectively. CONCLUSION: The behavior of the dose distribution on the helical diode array differed depending on the dose calculation algorithm for small targets. Measurements using ArcCHECK for VMAT with small targets can have lower GPRs owing to the coarse dose resolution of AXB around the detector area.

Development and multi-institutional evaluation of a new phantom for verifying beam-positioning errors at off-isocenter positions.

PURPOSE: Single-isocenter stereotactic radiotherapy for multiple brain metastases requires highly accurate treatment delivery at off-isocenter positions (off-iso). This study aimed to verify the beam-positioning errors at off-iso using a newly developed phantom tested at multiple institutions. METHODS: The off-iso phantom comprised five stainless-steel balls with a 3-mm diameter placed at the center and at four peripheral positions on a diagonal line. Each ball was placed 3.5 cm apart along each of the three axes. Two patterns of the phantom setup were defined as 0° and 90° phantom rotations to evaluate the beam-positioning error, which is the distance between the center of the ball and the irradiated field on the electronic portal imaging device. Furthermore, the reproducibility of the beam-positioning errors was verified by evaluating their standard deviation (SD) at a single institution, which included five measurements for two treatment machines. The errors were evaluated at multiple institutions using eight treatment machines. RESULTS: The measurement time from setup to image acquisition was approximately 20 min for two patterns. The SD of the beam-positioning errors in the reproducibility tests was 0.41 mm. In the multi-institutional evaluation, the beam-positioning error at the isocenter position was within 1.00 mm of the AAPM-RSS tolerance, with the exception of two linacs. The largest beam-positioning error (1.36 mm) was observed 7.5 cm away from the isocenter in three directions at a gantry angle of 180°. CONCLUSIONS: The developed phantom can be applied as a new tool for establishing beam-positioning errors in single-isocenter stereotactic radiotherapy at off-isocenter positions.

Effect of angular dependence for small-field dosimetry using seven different detectors.

BACKGROUND: Small-field dosimetry is challenging for radiotherapy dosimetry because of the loss of lateral charged equilibrium, partial occlusion of the primary photon source by the collimating devices, perturbation effects caused by the detector materials and their design, and the detector size relative to the radiation field size, which leads to a volume averaging effect. Therefore, a suitable tool for small-field dosimetry requires high spatial resolution, tissue equivalence, angular independence, and energy and dose rate independence to achieve sufficient accuracy. Recently, with the increasing use of combinations of coplanar and non-coplanar beams for small-field dosimetry, there is a need to clarify angular dependence for dosimetry where the detector is oriented at various angles to the incident beam. However, the effect of angular dependence on small-field dosimetry with coplanar and non-coplanar beams has not been fully clarified. PURPOSE: This study clarified the effect of angular dependence on small-field dosimetry with coplanar and non-coplanar beams using various detectors. METHODS: Seven different detectors were used: CC01, RAZOR, RAZOR Nano, Pinpoint 3D, stereotactic field diode (SFD), microSilicon, and microDiamond. All measurements were taken using a TrueBeam STx with 6 MV and 10 MV flattening filter-free (FFF) energies using a water-equivalent spherical phantom with a source-to-axis distance of 100 cm. The detector was inserted in a perpendicular orientation, and the gantry was rotated at 15° increments from the incidence beam angle. A multi-leaf collimator (MLC) with four field sizes of 0.5 × 0.5, 1 × 1, 2 × 2, and 3 × 3 cm2 , and four couch angles from 0°, 30°, 60°, and 90° (coplanar and non-coplanar) were adopted. The angular dependence response (AR) was defined as the ratio of the detector response at a given irradiation gantry angle normalized to the detector response at 0°. The maximum AR differences were calculated between the maximum and minimum AR values for each detector, field size, energy, and couch angle. RESULTS: The maximum AR difference for the coplanar beam was within 3.3% for all conditions, excluding the maximum AR differences in 0.5 × 0.5 cm2 field for CC01 and RAZOR. The maximum AR difference for non-coplanar beams was within 2.5% for fields larger than 1 × 1 cm2 , excluding the maximum AR differences for RAZOR Nano, SFD, and microSilicon. The Pinpoint 3D demonstrated stable AR tendencies compared to other detectors. The maximum difference was within 2.0%, except for the 0.5 × 0.5 cm2 field and couch angle at 90°. The tendencies of AR values for each detector were similar when using different energies. CONCLUSION: This study clarified the inherent angular dependence of seven detectors that were suitable for small-field dosimetry. The Pinpoint 3D chamber had the smallest angular dependence of all detectors for the coplanar and non-coplanar beams. The findings of this study can contribute to the calculation of the AR correction factor, and it may be possible to adapt detectors with a large angular dependence on coplanar and non-coplanar beams. However, note that the gantry sag and detector-specific uncertainties increase as the field size decreases.

Development of independent dose verification plugin using Eclipse scripting API for brachytherapy.

In this study, an independent dose verification plugin (DVP) using the Eclipse Scripting Application Programming Interface (ESAPI) for brachytherapy was developed. The DVP was based on the general 2D formalism reported in AAPM-TG43U1. The coordinate and orientation of each source position were extracted from the translation matrix acquired from the treatment planning system (TPS), and the distance between the source and verification point (r) was calculated. Moreover, the angles subtended by the center-tip and tip-tip of the hypothetical line source with respect to the verification point (θ and ß) were calculated. With r, θ, ß and the active length of the source acquired from the TPS, the geometry function was calculated. As the TPS calculated the radial dose function, g(r), and 2D anisotropy function, F(r,θ), by interpolating and extrapolating the corresponding table stored in the TPS, the DVP calculated g(r) and F(r,θ) independently from equations fitted with the Monte Carlo data. The relative deviation of the fitted g(r) and F(r,θ) for the GammaMed Plus HDR 192Ir source was 0.5% and 0.9%, respectively. The acceptance range of the relative dose difference was set to ±1.03% based on the relative deviation between the fitted functions and Monte Carlo data, and the linear error propagation law. For 64 verification points from sixteen plans, the mean of absolute values of the relative dose difference was 0.19%. The standard deviation (SD) of the relative dose difference was 0.17%. The DVP maximizes efficiency and minimizes human error for the brachytherapy plan check.

Automatic measurement of beam-positioning accuracy at off-isocenter positions.

PURPOSE: This study performed an automatic measurement of the off-axis beam-positioning accuracy at a single isocenter via the TrueBeam Developer mode and evaluated the beam-positioning accuracy considering the effect of couch rotational errors. METHODS: TrueBeam STx and the Winston-Lutz test-dedicated phantom, with a 3 mm diameter steel ball, were used in this study. The phantom was placed on the treatment couch, and the Winston-Lutz test was performed at the isocenter for four gantry angles (0°, 90°, 180°, and 270°) using an electronic portal imaging device. The phantom offset positions were at distances of 0, 25, 50, 75, and 100 mm from the isocenter along the superior-inferior, anterior-posterior, and left-right directions. Seventeen patterns of multileaf collimator-shaped square fields of 10 × 10 mm2 were created at the isocenter and off-axis positions for each gantry angle. The beam-positioning accuracy was evaluated with couch rotation along the yaw-axis (0°, ± 0.5°, and ± 1.0°). RESULTS: The mean beam-positioning errors at the isocenter and off-isocenter distances (from the isocenter to ±100 mm) were 0.46-0.60, 0.44-0.91, and 0.42-1.11 mm for the couch angles of 0°, ±0.5°, and ±1°, respectively. The beam-positioning errors increased as the distance from the isocenter and couch rotation increased. CONCLUSION: These findings suggest that the beam-positioning accuracy at the isocenter and off-isocenter positions can be evaluated quickly and automatically using the TrueBeam Developer mode. The proposed procedure is expected to contribute to an efficient evaluation of the beam-positioning accuracy at off-isocenter positions.

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 5-100 mm 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 10 mm 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.

A case of a pregnant woman with locally advanced cervical esophageal cancer treated with definitive chemoradiotherapy.

The information of definitive radiotherapy for a pregnant woman with malignancy was limited; however, it was reported to be potentially feasible with minimal risks. We performed definitive chemoradiotherapy for a pregnant woman with locally advanced cervical esophageal cancer. Feasibility of radiotherapy and safety of fetus were confirmed by the phantom study estimating fetal dose, and monitoring it in each radiotherapy session. The planned chemoradiotherapy completely eradicated esophageal cancer while preserving her laryngopharyngeal function. A female infant was delivered by cesarian section after planned chemoradiotherapy, and she grew without any apparent disorders 2 years after chemoradiotherapy. Chemoradiotherapy might be one of the treatment options for a pregnant woman with cervical esophageal cancer especially wishing the preservation of laryngopharyngeal function.

Evaluation of internal margins for prostate for step and shoot intensity-modulated radiation therapy and volumetric modulated arc therapy using different margin formulas.

PURPOSE: This feasibility study evaluated the intra-fractional prostate motion using an ultrasound image-guided system during step and shoot intensity-modulated radiation therapy (SS-IMRT) and volumetric modulated arc therapy (VMAT). Moreover, the internal margins (IMs) using different margin formulas were calculated. METHODS: Fourteen consecutive patients with prostate cancer who underwent SS-IMRT (n = 5) or VMAT (n = 9) between March 2019 and April 2020 were considered. The intra-fractional prostate motion was observed in the superior-inferior (SI), anterior-posterior (AP), and left-right (LR) directions. The displacement of the prostate was defined as the displacement from the initial position at the scanning start time, which was evaluated using the mean ± standard deviation (SD). IMs were calculated using the van Herk and restricted maximum likelihood (REML) formulas for SS-IMRT and VMAT. RESULTS: For SS-IMRT, the maximum displacements of the prostate motion were 0.17 ± 0.18, 0.56 ± 0.86, and 0.18 ± 0.59 mm in the SI, AP, and LR directions, respectively. For VMAT, the maximum displacements of the prostate motion were 0.19 ± 0.64, 0.22 ± 0.35, and 0.14 ± 0.37 mm in the SI, AP, and LR directions, respectively. The IMs obtained for SS-IMRT and VMAT were within 2.3 mm and 1.2 mm using the van Herk formula and within 1.2 mm and 0.8 mm using the REML formula. CONCLUSIONS: This feasibility study confirmed that intra-fractional prostate motion was observed with SS-IMRT and VMAT using different margin formulas. The IMs should be determined according to each irradiation technique using the REML margin.

Dosiomic feature comparison between dose-calculation algorithms used for lung stereotactic body radiation therapy.

To evaluate the reproducibility of dose-based radiomic (dosiomic) features between dose-calculation algorithms for lung stereotactic body radiation therapy (SBRT). We analyzed 105 patients with early-stage non-small cell lung cancer who underwent lung SBRT between March 2011 and December 2017. Radiation doses of 48, 60, and 70 Gy were prescribed to the isocenter in 4-8 fractions. Dose calculations were performed using X-ray voxel Monte Carlo (XVMC) on the iPlan radiation treatment planning system (RTPS). Thereafter, the radiation doses were recalculated using the Acuros XB (AXB) and analytical anisotropic algorithm (AAA) on the Eclipse RTPS while maintaining the XVMC-calculated monitor units and beam arrangements. A total of 6808 dosiomic features were extracted without preprocessing (112 shape, 144 first-order, and 600 texture features) or with wavelet filters to eight decompositions (1152 first-order and 4800 texture features). Features with absolute pairwise concordance correlation coefficients-|CCcon|-values exceeding or equaling 0.85 were considered highly reproducible. Subgroup analyses were performed considering the wavelet filters and prescribed doses. The numbers of highly reproducible first-order and texture features were 34.8%, 26.9%, and 31.0% for the XVMC-AXB, XVMC-AAA, and AXB-AAA pairs, respectively. The maximum difference between the mean |CCcon| values was 0.70 and 0.11 for the subgroup analyses of wavelet filters and prescribed dose, respectively. The application of wavelet filter-based dosiomic analyses may be limited when using different types of dose-calculation algorithms for lung SBRT.

Development of a plan complexity mitigation algorithm based on gamma passing rate predictions for volumetric-modulated arc therapy.

BACKGROUND AND PURPOSE: Volumetric-modulated arc therapy (VMAT) is a complex rotational therapy technique in which highly conformal dose distribution can be realized by varying the speed of gantry rotation, multileaf collimator (MLC) shape, and dose rate. However, the complexity of the technique creates a discrepancy between the calculated and measured doses. Thus, to mitigate the plan complexity in VMAT, this study aimed to develop an algorithm and evaluate its usefulness by conducting a feasibility study. MATERIALS AND METHODS: A total of 50 patients who underwent VMAT between September 2015 and December 2020 were arbitrarily selected for this study. Specifically, patients with less than 85% gamma passing rate (GPR) at 5%/1 mm or 3%/2 mm criterion were selected randomly. Using the GPR prediction model, problematic MLC positions that contribute to a decrease in GPR were identified. Those problematic MLC positions were optimized using a limited nonlinear algorithm under mechanical limitations. Additionally, the dose prescription for the target was re-normalized. The VMAT modulated complexity score (MCSv ), averaged aperture area (AA), and monitor unit per gray (MU/Gy) were evaluated as plan complexity parameters. Calculated doses in patient geometry were evaluated for the target and its surrounding region. In addition, an ArcCHECK cylindrical diode array was used to measure the dose, and GPRs at 5%/1 mm and 3%/2 mm criteria were evaluated to analyze the difference between the mitigated and original plans. The difference was calculated using the mean ± standard deviation. RESULTS: The differences between the MCSv , AA, and MU/cGy values for the mitigated and original plans were 0.8 ± 1.7 (×10-2 ), 42.7 ± 57.9, and -5.6 ± 8.5, respectively. Regarding the calculated dose, the dose volume parameters were consistent within 1% for the target and the surrounding region. The differences between the mitigated and original plans were 1.8 ± 2.9% and 1.3 ± 1.8% for GPRs at 5%/1 mm and 3%/2 mm, respectively. CONCLUSIONS: This feasibility study resulted in the development of an algorithm with the potential to mitigate plan complexity and improve the GPR for VMAT under minor leaf position modifications.

A randomized phase III study of short-course radiotherapy combined with Temozolomide in elderly patients with newly diagnosed glioblastoma; Japan clinical oncology group study JCOG1910 (AgedGlio-PIII).

BACKGROUND: The current standard treatment for elderly patients with newly diagnosed glioblastoma is surgery followed by short-course radiotherapy with temozolomide. In recent studies, 40 Gy in 15 fractions vs. 60 Gy in 30 fractions, 34 Gy in 10 fractions vs. 60 Gy in 30 fractions, and 40 Gy in 15 fractions vs. 25 Gy in 5 fractions have been reported as non-inferior. The addition of temozolomide increased the survival benefit of radiotherapy with 40 Gy in 15 fractions. However, the optimal regimen for radiotherapy plus concomitant temozolomide remains unresolved. METHODS: This multi-institutional randomized phase III trial was commenced to confirm the non-inferiority of radiotherapy comprising 25 Gy in 5 fractions with concomitant (150 mg/m2/day, 5 days) and adjuvant temozolomide over 40 Gy in 15 fractions with concomitant (75 mg/m2/day, every day from first to last day of radiation) and adjuvant temozolomide in terms of overall survival (OS) in elderly patients with newly diagnosed glioblastoma. A total of 270 patients will be accrued from 51 Japanese institutions in 4 years and follow-up will last 2 years. Patients 71 years of age or older, or 71-75 years old with resection of less than 90% of the contrast-enhanced region, will be registered and randomly assigned to each group with 1:1 allocation. The primary endpoint is OS, and the secondary endpoints are progression-free survival, frequency of adverse events, proportion of Karnofsky performance status preservation, and proportion of health-related quality of life preservation. The Japan Clinical Oncology Group Protocol Review Committee approved this study protocol in April 2020. Ethics approval was granted by the National Cancer Center Hospital Certified Review Board. Patient enrollment began in August 2020. DISCUSSION: If the primary endpoint is met, short-course radiotherapy comprising 25 Gy in 5 fractions with concomitant and adjuvant temozolomide will be a standard of care for elderly patients with newly diagnosed glioblastoma. TRIAL REGISTRATION: Registry number: jRCTs031200099 . Date of Registration: 27/Aug/2020. Date of First Participant Enrollment: 4/Sep/2020.

Appropriate margin for planning target volume for breast radiotherapy during deep inspiration breath-hold by variance component analysis.

BACKGROUND: This study aimed to quantify errors by using a cine electronic portal imaging device (cine EPID) during deep inspiration breath-hold (DIBH) for left-sided breast cancer and to estimate the planning target volume (PTV) by variance component analysis. METHODS: This study included 25 consecutive left-sided breast cancer patients treated with whole-breast irradiation (WBI) using DIBH. Breath-holding was performed while monitoring abdominal anterior-posterior (AP) motion using the Real-time Position Management (RPM) system. Cine EPID was used to evaluate the chest wall displacements in patients. Cine EPID images of the patients (309,609 frames) were analyzed to detect the edges of the chest wall using a Canny filter. The errors that occurred during DIBH included differences between the chest wall position detected by digitally reconstructed radiographs and that of all cine EPID images. The inter-patient, inter-fraction, and intra-fractional standard deviations (SDs) in the DIBH were calculated, and the PTV margin was estimated by variance component analysis. RESULTS: The median patient age was 55 (35-79) years, and the mean irradiation time was 20.4 ± 1.7 s. The abdominal AP motion was 1.36 ± 0.94 (0.14-5.28) mm. The overall mean of the errors was 0.30 mm (95% confidence interval: - 0.05-0.65). The inter-patient, inter-fraction, and intra-fractional SDs in the DIBH were 0.82 mm, 1.19 mm, and 1.63 mm, respectively, and the PTV margin was calculated as 3.59 mm. CONCLUSIONS: Errors during DIBH for breast radiotherapy were monitored using EPID images and appropriate PTV margins were estimated by variance component analysis.

Multi-institutional dose-segmented dosiomic analysis for predicting radiation pneumonitis after lung stereotactic body radiation therapy.

PURPOSE: To predict radiation pneumonitis (RP) grade 2 or worse after lung stereotactic body radiation therapy (SBRT) using dose-based radiomic (dosiomic) features. METHODS: This multi-institutional study included 247 early-stage nonsmall cell lung cancer patients who underwent SBRT with a prescribed dose of 48-70 Gy at an isocenter between June 2009 and March 2016. Ten dose-volume indices (DVIs) were used, including the mean lung dose, internal target volume size, and percentage of entire lung excluding the internal target volume receiving greater than x Gy (x = 5, 10, 15, 20, 25, 30, 35, and 40). A total of 6,808 dose-segmented dosiomic features, such as shape, first order, and texture features, were extracted from the dose distribution. Patients were randomly partitioned into two groups: model training (70%) and test datasets (30%) over 100 times. Dosiomic features were converted to z-scores (standardized values) with a mean of zero and a standard deviation (SD) of one to put different variables on the same scale. The feature dimension was reduced using the following methods: interfeature correlation based on Spearman's correlation coefficients and feature importance based on a light gradient boosting machine (LightGBM) feature selection function. Three different models were developed using LightGBM as follows: (a) a model with ten DVIs (DVI model), (b) a model with the selected dosiomic features (dosiomic model), and (c) a model with ten DVIs and selected dosiomic features (hybrid model). Suitable hyperparameters were determined by searching the largest average area under the curve (AUC) value in the receiver operating characteristic curve (ROC-AUC) via stratified fivefold cross-validation. Each of the final three models with the closest the ROC-AUC value to the average ROC-AUC value was applied to the test datasets. The classification performance was evaluated by calculating the ROC-AUC, AUC in the precision-recall curve (PR-AUC), accuracy, precision, recall, and f1-score. The entire process was repeated 100 times with randomization, and 100 individual models were developed for each of the three models. Then the mean value and SD for the 100 random iterations were calculated for each performance metric. RESULTS: Thirty-seven (15.0%) patients developed RP after SBRT. The ROC-AUC and PR-AUC values in the DVI, dosiomic, and hybrid models were 0.660 ± 0.054 and 0.272 ± 0.052, 0.837 ± 0.054 and 0.510 ± 0.115, and 0.846 ± 0.049 and 0.531 ± 0.116, respectively. For each performance metric, the dosiomic and hybrid models outperformed the DVI models (P < 0.05). Texture-based dosiomic feature was confirmed as an effective indicator for predicting RP. CONCLUSIONS: Our dose-segmented dosiomic approach improved the prediction of the incidence of RP after SBRT.

Quantification and correction of the scattered X-rays from a megavoltage photon beam to a linac-mounted kilovoltage imaging subsystem.

OBJECTIVE: To quantify and correct megavoltage (MV) scattered X-rays (MV-scatter) on an image acquired using a linac-mounted kilovoltage (kV) imaging subsystem. METHODS AND MATERIALS: A linac-mounted flat-panel detector (FPD) was used to acquire an image containing MV-scatter by activating the FPD only during MV beam irradiation. 6-, 10-, and 15 MV with a flattening-filter (FF; 6X-FF, 10X-FF, 15X-FF), and 6- and 10 MV without an FF (6X-FFF, 10X-FFF) were used. The maps were acquired by changing one of the irradiation parameters while the others remained fixed. The mean pixel values of the MV-scatter were normalized to the 6X-FF reference condition (MV-scatter value). An MV-scatter database was constructed using these values. An MV-scatter correction experiment with one full arc image acquisition and two square field sizes (FSs) was conducted. Measurement- and estimation-based corrections were performed using the database. The image contrast was calculated at each angle. RESULTS: The MV-scatter increased with a larger FS and dose rate. The MV-scatter value factor varied substantially depending on the FPD position or collimator rotation. The median relative error ranges of the contrast for the image without, and with the measurement- and estimation-based correction were -10.9 to -2.9, and -1.5 to 4.8 and -7.4 to 2.6, respectively, for an FS of 10.0 × 10.0 cm2. CONCLUSIONS: The MV-scatter was strongly dependent on the FS, dose rate, and FPD position. The MV-scatter correction improved the image contrast. ADVANCES IN KNOWLEDGE: The MV-scatters on the TrueBeam linac kV imaging subsystem were quantified with various MV beam parameters, and strongly depended on the fieldsize, dose rate, and flat panel detector position. The MV-scatter correction using the constructed database improved the image quality.

Positional repeatability and variation in internal and external markers during volumetric-modulated arc therapy under end-exhalation breath-hold conditions for pancreatic cancer patients.

The purpose of this study was to assess the positional repeatability of internal and external markers among multiple breath-hold (BH) sessions and evaluate the positional variation of these markers within BH sessions for volumetric-modulated arc therapy (VMAT) for pancreatic cancer patients. A total of 13 consecutive pancreatic cancer patients with an internal marker were enrolled. Single full-arc coplanar VMAT was delivered under end-exhalation BH conditions while monitoring the internal marker with kilovoltage (kV) X-ray fluoroscopy. Positional repeatability of the internal and external markers was determined by the difference between the reference and zero position in all BH sessions, and positional variation was defined by the displacement from the reference position in each BH session during megavolt beam delivery. The overall positional repeatability was 0.6 ± 1.5 mm in the X-axis for the centroid of the internal marker (CoIM), -0.1 ± 2.2 mm in the Y-axis for the CoIM, and 0.8 ± 2.2 mm for the external marker. The frequency of an internal marker position appearing > 2 mm from the reference position in the Y-axis, despite the external marker position being ≤2 mm from the reference position, ranged from 0.0 to 39.9% for each patient. Meanwhile, the proportion of sessions with positional variation ≤2 mm was 93.2 and 98.7% for the CoIM and external marker, respectively. External marker motion can be used as a surrogate for pancreatic tumor motion during BH-VMAT delivery; however, margins of ~5 mm were required to ensure positional repeatability.

Improvement of prediction and classification performance for gamma passing rate by using plan complexity and dosiomics features.

PURPOSE: The purpose of this study was to predict and classify the gamma passing rate (GPR) value by using new features (3D dosiomics features and combined with plan and dosiomics features) together with a machine learning technique for volumetric modulated arc therapy (VMAT) treatment plans. METHODS AND MATERIALS: A total of 888 patients who underwent VMAT were enrolled comprising 1255 treatment plans. Further, 24 plan complexity features and 851 dosiomics features were extracted from the treatment plans. The dataset was randomly split into a training/validation (80%) and test (20%) dataset. The three models for prediction and classification using XGBoost were as follows: (i) plan complexity features-based prediction method (plan model); (ii) 3D dosiomics feature-based prediction model (dosiomics model); (iii) a combination of both the previous models (hybrid model). The prediction performance was evaluated by calculating the mean absolute error (MAE) and the correlation coefficient (CC) between the predicted and measured GPRs. The classification performance was evaluated by calculating the area under curve (AUC) and sensitivity. RESULTS: MAE and CC at γ2%/2 mm in the test dataset were 4.6% and 0.58, 4.3% and 0.61, and 4.2% and 0.63 for the plan model, dosiomics model, and hybrid model, respectively. AUC and sensitivity at γ2%/2 mm in test dataset were 0.73 and 0.70, 0.81 and 0.90, and 0.83 and 0.90 for the plan model, dosiomics model, and hybrid model, respectively. CONCLUSIONS: A combination of both plan and dosiomics features with machine learning technique can improve the prediction and classification performance for GPR.