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Purpose: We sought to develop machine learning models to predict the results of patient‐specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), which were represented by several dose‐evaluation metrics—including the gamma passing rates (GPRs)—and criteria based on the radiomic features of 3D dose distribution in a phantom. Methods: A total of 4,250 radiomic features of 3D dose distribution in a cylindrical dummy phantom for 140 arcs from 106 clinical VMAT plans were extracted. We obtained the following dose‐evaluation metrics: GPRs with global and local normalization, the dose difference (DD) in 1% and 2% passing rates (DD1% and DD2%) for 10% and 50% dose threshold, and the distance‐to‐agreement in 1‐mm and 2‐mm passing rates (DTA1 mm and DTA2 mm) for 0.5%/mm and 1.0%.mm dose gradient threshold determined by measurement using a diode array in patient‐specific QA. The machine learning regression models for predicting the values of the dose‐evaluation metrics using the radiomic features were developed based on the elastic net (EN) and extra trees (ET) models. The feature selection and tuning of hyperparameters were performed with nested cross‐validation in which four‐fold cross‐validation is used within the inner loop, and the performance of each model was evaluated in terms of the root mean square error (RMSE), the mean absolute error (MAE), and Spearman's rank correlation coefficient. Results: The RMSE and MAE for the developed machine learning models ranged from <1% to nearly <10% depending on the dose‐evaluation metric, the criteria, and dose and dose gradient thresholds used for both machine learning models. It was advantageous to focus on high dose region for predicating global GPR, DDs, and DTAs. For certain metrics and criteria, it was possible to create models applicable for patients' heterogeneity by training only with dose distributions in phantom. Conclusions: The developed machine learning models showed high performance for predicting dose‐evaluation metrics especially for high dose region depending on the metric and criteria. Our results demonstrate that the radiomic features of dose distribution can be considered good indicators of the plan complexity and useful in predicting measured dose evaluation metrics. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to create and evaluate deep learning‐based models to detect and classify errors of multi‐leaf collimator (MLC) modeling parameters in volumetric modulated radiation therapy (VMAT), namely the transmission factor (TF) and the dosimetric leaf gap (DLG). Methods: A total of 33 clinical VMAT plans for prostate and head‐and‐neck cancer were used, assuming a cylindrical and homogeneous phantom, and error plans were created by altering the original value of the TF and the DLG by ± 10, 20, and 30% in the treatment planning system (TPS). The Gaussian filters of σ=0.5$\sigma = 0.5$ and 1.0 were applied to the planar dose maps of the error‐free plan to mimic the measurement dose map, and thus dose difference maps between the error‐free and error plans were obtained. We evaluated 3 deep learning‐based models, created to perform the following detections/classifications: (1) error‐free versus TF error, (2) error‐free versus DLG error, and (3) TF versus DLG error. Models to classify the sign of the errors were also created and evaluated. A gamma analysis was performed for comparison. Results: The detection and classification of TF and DLG error were feasible for σ=0.5$\sigma = 0.5$; however, a considerable reduction of accuracy was observed for σ=1.0$\sigma = 1.0$ depending on the magnitude of error and treatment site. The sign of errors was detectable by the specifically trained models for σ=0.5$\sigma = 0.5$ and 1.0. The gamma analysis could not detect errors. Conclusions: We demonstrated that the deep learning‐based models could feasibly detect and classify TF and DLG errors in VMAT dose distributions, depending on the magnitude of the error, treatment site, and the degree of mimicked measurement doses. [ABSTRACT FROM AUTHOR]

We evaluated the tumor residual volumes considering six degrees-of-freedom (6DoF) patient setup errors in stereotactic radiotherapy (SRT) with multicomponent mathematical model using single-isocenter irradiation for brain metastases. Simulated spherical gross tumor volumes (GTVs) with 1.0 (GTV 1), 2.0 (GTV 2), and 3.0 (GTV 3)-cm diameters were used. The distance between the GTV center and isocenter (d) was set at 0–10 cm. The GTV was simultaneously translated within 0–1.0 mm (T) and rotated within 0°–1.0° (R) in the three axis directions using affine transformation. We optimized the tumor growth model parameters using measurements of non-small cell lung cancer cell lines' (A549 and NCI-H460) growth. We calculated the GTV residual volume at the irradiation's end using the physical dose to the GTV when the GTV size, d, and 6DoF setup error varied. The d-values that satisfy tolerance values (10%, 35%, and 50%) of the GTV residual volume rate based on the pre-irradiation GTV volume were determined. The larger the tolerance value set for both cell lines, the longer the distance to satisfy the tolerance value. In GTV residual volume evaluations based on the multicomponent mathematical model on SRT with single-isocenter irradiation, the smaller the GTV size and the larger the distance and 6DoF setup error, the shorter the distance that satisfies the tolerance value might need to be. [ABSTRACT FROM AUTHOR]

(1) Background: The impacts of metal artifacts (MAs) on the contouring workload for head and neck radiotherapy have not yet been clarified. Therefore, this study evaluated the relationship between the contouring time of the MAs area and MAs on head and neck radiotherapy treatment planning. (2) Methods: We used treatment planning computed tomography (CT) images for head and neck radiotherapy. MAs were classified into three severities by the percentage of CT images containing MAs: mild (<25%), moderate (25–75%), and severe (>75%). We randomly selected nine patients to evaluate the relationship between MAs and the contouring time of the MAs area. (3) Results: The contouring time of MAs showed moderate positive correlations with the MAs volume and the number of CT images containing MAs. Interobserver reliability of the extracted MAs volume and contouring time were excellent and poor, respectively. (4) Conclusions: Our study suggests that the contouring time of MAs areas is related to individual commitment rather than clinical experience. Therefore, the development of software combining metal artifact reduction methods with automatic contouring methods is necessary to reducing interobserver variability and contouring workload. [ABSTRACT FROM AUTHOR]

• Selection criteria for circular cone and MLC for CyberKnife SRS were evaluated. • A mathematical score was adapted to assess the quality of the dose distribution. • MLC is recommended when the tumor radius exceeds 7.6 mm in metastatic brain tumors. • In the benign brain tumors, MLC is recommended when the tumor radius exceeds 17.5 mm. • Collimator selection based on these criteria improves plan quality of CyberKnife SRS. This study aimed to determine the selection criteria for circular collimator (CC)- and multileaf collimator (MLC)-based stereotactic radiosurgery (SRS)/stereotactic radiotherapy (SRT) plans for brain metastases (BM) and benign intracranial disease (BID) in terms of geometric parameters using CyberKnife (CK). Forty-eight and eighty-five patients with BM and BID, respectively, were included. Two plans using CC and MLC were created for each case. Six dosimetric parameters and mathematical scores (MS) were extracted from each plan to assess plan quality. Two geometric parameters in BM—equivalent radius (rGTV) and sphericity index (SI) of the gross tumor volume—and three in BID—rGTV, SI, and the distance between the GTV and organ at risk (dOAR)—were calculated. Their effect on the superiority of CC– or MLC-based plans in terms of dosimetric parameters and MS was evaluated using multiple regression analysis. The rGTV was associated with improved dosimetric parameters of MLC-based plans, especially the GTV conformity in BM and BID cases (β: 0.70 and 0.51) and the OAR sparing in BM cases (β: 0.82), where β represents the regression coefficient. Based on the MS, where the weights for the GTV coverage and OAR sparing were equal, the thresholds at which the MLC-based plans become comparable or superior to the CC-based plans in BM and BID were rGTV > 7.6 and >17.5 mm, respectively. Meanwhile, SI and dOAR were weakly correlated (β ≤ 0.30). In SRS/SRT plans for BM and BID cases using CyberKnife, geometric parameters, especially rGTV, must be considered when selecting CC or MLC. [ABSTRACT FROM AUTHOR]

Purpose: We calculated the dosimetric indices and estimated the tumor control probability (TCP) considering six degree‐of‐freedom (6DoF) patient setup errors in stereotactic radiosurgery (SRS) using a single‐isocenter technique. Methods: We used simulated spherical gross tumor volumes (GTVs) with diameters of 1.0 cm (GTV 1), 2.0 cm (GTV 2), and 3.0 cm (GTV 3), and the distance (d) between the target center and isocenter was set to 0, 5, and 10 cm. We created the dose distribution by convolving the blur component to uniform dose distribution. The prescription dose was 20 Gy and the dose distribution was adjusted so that D95 (%) of each GTV was covered by 100% of the prescribed dose. The GTV was simultaneously rotated within 0°–1.0° (δR) around the x‐, y‐, and z‐axes and then translated within 0–1.0 mm (δT) in the x‐, y‐, and z‐axis directions. D95, conformity index (CI), and conformation number (CN) were evaluated by varying the distance from the isocenter. The TCP was estimated by translating the calculated dose distribution into a biological response. In addition, we derived the x‐y‐z coordinates with the smallest TCP reduction rate that minimize the sum of squares of the residuals as the optimal isocenter coordinates using the relationship between 6DoF setup error, distance from isocenter, and GTV size. Results: D95, CI, and CN were decreased with increasing isocenter distance, decreasing GTV size, and increasing setup error. TCP of GTVs without 6DoF setup error was estimated to be 77.0%. TCP were 25.8% (GTV 1), 35.0% (GTV 2), and 53.0% (GTV 3) with (d, δT,δR) = (10 cm, 1.0 mm, 1.0°). The TCP was 52.3% (GTV 1), 54.9% (GTV 2), and 66.1% (GTV 3) with (d, δT,δR) = (10 cm, 1.0 mm, 1.0°) at the optimal isocenter position. Conclusion: The TCP in SRS for multiple brain metastases with a single‐isocenter technique may decrease with increasing isocenter distance and decreasing GTV size when the 6DoF setup errors are exceeded (1.0 mm, 1.0°). Additionally, it might be possible to better maintain TCP for GTVs with 6DoF setup errors by using the optimal isocenter position. [ABSTRACT FROM AUTHOR]

We aimed to compare the outcomes of high-dose-rate brachytherapy (HDR-BT) boost and external beam radiation therapy (EBRT) alone for high-risk prostate cancer. This was a single-center, retrospective and observational study. Consecutive patients who underwent initial radical treatment by HDR-BT boost or EBRT alone from June 2009 to May 2016 at the Niigata University Medical and Dental Hospital, Japan were included. A total of 96 patients underwent HDR-BT boost, and 61 underwent EBRT alone. The prescription dose of HDR-BT boost was set to 18 Gy twice a day with EBRT 39 Gy/13 fractions. The dose for EBRT alone was mostly 70 Gy/28 fractions. The high-risk group received >6 months of prior androgen deprivation therapy. Overall survival, biochemical-free survival, local control and distant metastasis-free survival rates at 5 years were analyzed. The incidence of urological and gastrointestinal late adverse events of Grade 2 and above was also summarized. In the National Comprehensive Cancer Network (NCCN) high-risk calssification, HDR-BT boost had a significantly higher biochemical-free survival rate at 5 years (98.9% versus 90.7%, P  = 0.04). Urethral strictures were more common in the HDR-BT boost group. We will continuously observe the progress of the study patients and determine the longer term results. [ABSTRACT FROM AUTHOR]

Purpose: We sought to develop machine learning models to detect multileaf collimator (MLC) modeling errors with the use of radiomic features of fluence maps measured in patient‐specific quality assurance (QA) for intensity‐modulated radiation therapy (IMRT) with an electric portal imaging device (EPID). Methods: Fluence maps measured with EPID for 38 beams from 19 clinical IMRT plans were assessed. Plans with various degrees of error in MLC modeling parameters [i.e., MLC transmission factor (TF) and dosimetric leaf gap (DLG)] and plans with an MLC positional error for comparison were created. For a total of 152 error plans for each type of error, we calculated fluence difference maps for each beam by subtracting the calculated maps from the measured maps. A total of 837 radiomic features were extracted from each fluence difference map, and we determined the number of features used for the training dataset in the machine learning models by using random forest regression. Machine learning models using the five typical algorithms [decision tree, k‐nearest neighbor (kNN), support vector machine (SVM), logistic regression, and random forest] for binary classification between the error‐free plan and the plan with the corresponding error for each type of error were developed. We used part of the total dataset to perform fourfold cross‐validation to tune the models, and we used the remaining test dataset to evaluate the performance of the developed models. A gamma analysis was also performed between the measured and calculated fluence maps with the criteria of 3%/2 and 2%/2 mm for all of the types of error. Results: The radiomic features and its optimal number were similar for the models for the TF and the DLG error detection, which was different from the MLC positional error. The highest sensitivity was obtained as 0.913 for the TF error with SVM and logistic regression, 0.978 for the DLG error with kNN and SVM, and 1.000 for the MLC positional error with kNN, SVM, and random forest. The highest specificity was obtained as 1.000 for the TF error with a decision tree, SVM, and logistic regression, 1.000 for the DLG error with a decision tree, logistic regression, and random forest, and 0.909 for the MLC positional error with a decision tree and logistic regression. The gamma analysis showed the poorest performance in which sensitivities were 0.737 for the TF error and the DLG error and 0.882 for the MLC positional error for 3%/2 mm. The addition of another type of error to fluence maps significantly reduced the sensitivity for the TF and the DLG error, whereas no effect was observed for the MLC positional error detection. Conclusions: Compared to the conventional gamma analysis, the radiomics‐based machine learning models showed higher sensitivity and specificity in detecting a single type of the MLC modeling error and the MLC positional error. Although the developed models need further improvement for detecting multiple types of error, radiomics‐based IMRT QA was shown to be a promising approach for detecting the MLC modeling error. [ABSTRACT FROM AUTHOR]

Purpose: The interruption time is the irradiation interruption that occurs at sites and operations such as the gantry, collimator, couch rotation, and patient setup within the field in radiotherapy. However, the radiobiological effect of prolonging the treatment time by the interruption time for tumor cells is little evaluated. We investigated the effect of the interruption time on the radiobiological effectiveness with photon beams based on a modified microdosimetric kinetic (mMK) model. Methods: The dose‐mean lineal energy yD (keV/µm) of 6‐MV photon beams was calculated by the particle and heavy ion transport system (PHITS). We set the absorbed dose to 2 or 8 Gy, and the interruption time (τ) was set to 1, 3, 5, 10, 30, and 60 min. The biological parameters such as α0, β0, and DNA repair constant rate (a + c) values were acquired from a human non‐small‐cell lung cancer cell line (NCI‐H460) for the mMK model. We used two‐field and four‐field irradiation with a constant dose rate (3 Gy/min); the photon beams were paused for interruption time τ. We calculated the relative biological effectiveness (RBE) to evaluate the interruption time's effect compared with no interrupted as a reference. Results: The yD of 6‐MV photon beams was 2.32 (keV/µm), and there was little effect by changing the water depth (standard deviation was 0.01). The RBE with four‐field irradiation for 8 Gy was decreased to 0.997, 0.975, 0.900, and 0.836 τ = 1, 10, 30, 60 min, respectively. In addition, the RBE was affected by the repair constant rate (a + c) value, the greater the decrease in RBE with the longer the interruption time when the (a + c) value was large. Conclusion: The ~10‐min interruption of 6‐MV photon beams did not significantly impact the radiobiological effectiveness, since the RBE decrease was <3%. Nevertheless, the RBE's effect on tumor cells was decreased about 30% by increasing the 60 min interruption time at 8 Gy with four‐field irradiation. It is thus necessary to make the interruption time as short as possible. [ABSTRACT FROM AUTHOR]

In conventional stereotactic radiosurgery (SRS), treatment of multiple brain metastases using multiple isocenters is time‐consuming resulting in long dose delivery times for patients. A single‐isocenter technique has been developed which enables the simultaneous irradiation of multiple targets at one isocenter. This technique requires accurate positioning of the patient to ensure optimal dose coverage. We evaluated the effect of six degrees of freedom (6DoF) setup errors in patient setups on SRS dose distributions for multiple brain metastases using a single‐isocenter technique. We used simulated spherical gross tumor volumes (GTVs) with diameters ranging from 1.0 to 3.0 cm. The distance from the isocenter to the target's center was varied from 0 to 15 cm. We created dose distributions so that each target was entirely covered by 100% of the prescribed dose. The target's position vectors were rotated from 0°–2.0° and translated from 0–1.0 mm with respect to the three axes in space. The reduction in dose coverage for the targets for each setup error was calculated and compared with zero setup error. The calculated margins for the GTV necessary to satisfy the tolerance values for loss of GTV coverage of 3% to 10% were defined as coverage‐based margins. In addition, the maximum isocenter to target distance for different 6DoF setup errors was calculated to satisfy the tolerance values. The dose coverage reduction and coverage‐based margins increased as the target diameter decreased, and the distance and 6DoF setup error increased. An increase in setup error when a single‐isocenter technique is used may increase the risk of missing the tumor; this risk increases with increasing distance from the isocenter and decreasing tumor size. [ABSTRACT FROM AUTHOR]

Objective: To estimate the outcomes of high‐dose‐rate brachytherapy combined with hypofractionated external beam radiotherapy in prostate cancer patients classified as very high risk by the National Comprehensive Cancer Network. Methods: Between June 2009 and September 2015, 66 patients meeting the criteria for very high‐risk disease received high‐dose‐rate brachytherapy (2 fractions of 9 Gy) as a boost of external beam radiotherapy (13 fractions of 3 Gy). Androgen deprivation therapy was administered for approximately 3 years. Biochemical failure was assessed using the Phoenix definition. Results: The median follow‐up period was 53 months from the completion of radiotherapy. The 5‐year biochemical failure‐free, distant metastasis‐free, prostate cancer‐specific and overall survival rates were 88.7, 89.2, 98.5 and 97.0%, respectively. The independent contribution of each component of the very high‐risk criteria was assessed in multivariable models. Primary Gleason pattern 5 was associated with increased risks of biochemical failure (P = 0.017) and distant metastasis (P = 0.049), whereas clinical stage ≥T3b or >4 biopsy cores with Gleason score 8–10 had no significant impact on the two outcomes. Grade 3 genitourinary toxicities were observed in two (3.0%) patients, whereas no grade ≥3 gastrointestinal toxicities occurred. Conclusions: The present study shows that this multimodal approach provides potentially excellent cancer control and acceptable associated morbidity for very high‐risk disease. Patients with primary Gleason pattern 5 are at a higher risk of poor outcomes, indicating the need for more aggressive approaches in these cases. [ABSTRACT FROM AUTHOR]

Purpose: We evaluated the setup accuracy of a three‐degree‐of‐freedom fiducial marker (3DOF‐FM)‐based setup compared to a soft tissue (ST)‐based setup in hypofractionated intensity‐modulated radiotherapy (IMRT) for prostate cancer. Materials and Methods: We analyzed the setup accuracy for 17 consecutive prostate cancer patients with three implanted FMs who underwent hypofractionated IMRT. The 3DOF‐ST‐based setup using cone‐beam computed tomography (CT) was performed after a six DOF‐bony structure (BS)‐based setup using an ExacTrac x‐ray system. The 3DOF‐FM‐based matching using the ExacTrac x‐ray system was done during the BS‐ and ST‐based setups. We determined the mean absolute differences and the correlation between the FM‐ and ST‐based translational shifts relative to the BS‐based setup position. The rotational mean shifts detected by the ExacTrac x‐ray system were also evaluated. Results: The mean differences in the anterior‐posterior (AP), superior‐inferior (SI), and left‐right (LR) dimensions were 0.69, 0.0, and 0.30 mm, respectively. The Pearson correlation coefficients for both shifts were 0.92 for AP, 0.91 for SI, and 0.68 for LR. The percentages of shift agreements within 2 mm were 85% for AP, 93% for SI, and 99% for LR. The absolute values of rotational shifts were 0.1° for AP, 0.3°, and 1.2° for LR. Conclusions: The setup accuracy of the 3DOF‐FM‐based setup has the potential to be interchangeable with a ST‐based setup. Our data are likely to be useful in clinical practice along with the popularization of the hypofractionated IMRT in prostate cancer. [ABSTRACT FROM AUTHOR]

There are no quantitative selection criteria for identifying high-grade glioma (HGG) patients who are suited for volumetric-modulated arc therapy (VMAT). This study aimed to develop selection criteria that can be used for the selection of the optimal treatment modality in HGG. We analyzed 20 patients with HGG treated by 3D conformal radiotherapy (3DCRT). First, VMAT plans were created for each patient retrospectively. For each plan, the normal tissue complication probability (NTCP) for normal brain was calculated. We then divided the patients based on the NTCP s of the 3DCRT plans for normal brain, using the threshold of 5%. We compared the NTCP s of the two plans and the gross tumor volumes (GTV s) of the two groups. For the GTV s, we used receiver operating characteristic curves to identify the cut-off value for predicting NTCP < 5%. We determined the respective correlations between the GTV and the GTV's largest cross-sectional diameter and largest cross-sectional area. In the NTCP ≥ 5% group, the NTCP s for the VMAT plans were significantly lower than those for the 3DCRT plans (P = 0.0011). The NTCP ≥ 5% group's GTV was significantly larger than that of the NTCP < 5% group (P = 0.0016), and the cut-off value of the GTV was 130.5 cm3. The GTV was strongly correlated with the GTV 's largest cross-sectional diameter (R 2 = 0.82) and largest cross-sectional area (R 2 = 0.94), which produced the cut-off values of 7.5 cm and 41 cm2, respectively. It was concluded that VMAT is more appropriate than 3DCRT in cases in which the GTV is ≥130.5 cm3. [ABSTRACT FROM AUTHOR]

We developed a teleradiology system linking a general hospital on Sado Island to tertiary care hospitals in Niigata City. The island is 40 km from Niigata City on the mainland and has only one diagnostic radiologist (for 72,000 islanders). Fibre optic cables between Sado Island and Niigata City were used for transmission. The introduction of the teleradiology system facilitated diagnostic and therapeutic consultation with specialists in Niigata City. The performance of the system was evaluated (on a scale of 0–6, with higher scores indicating better performance) by five diagnostic radiologists, who rated 32 features of the system twice, once in April 2002 and once in September 2003. The performance ratings improved from 1.38 to 2.86. While many of the initial problems with the software had been resolved, many still remained. [ABSTRACT FROM AUTHOR]

Simple Summary: We have shown the efficacy and safety of radiotherapy for the hepatocellular carcinoma as a curative therapy and a part of multidisciplinary therapy which could safely be combined with various therapies. The assessment of local controllability and survival showed the anti-tumor efficacy of the procedure, and the analyses of the serum biochemical factors and hepatic function, including the Child–Pugh score and albumin–bilirubin (ALBI)-grade, demonstrated its safety. While the assessment of a larger number of cases and well-designed randomized trials are essential, the results provided here will contribute to understanding the efficacy of radiotherapy as an additional therapy for the treatment of hepatocellular carcinoma and help physicians make therapeutic decisions. This study investigated the efficacy and safety of radiotherapy as part of multidisciplinary therapy for advanced hepatocellular carcinoma (HCC). Clinical data of 49 HCC patients treated with radiotherapy were assessed retrospectively. The efficacy of radiotherapy was assessed by progression-free survival, disease control rate, and overall survival. Safety was assessed by symptoms and hematological assay, and changes in hepatic reserve function were determined by Child–Pugh score and albumin–bilirubin (ALBI) score. Forty patients underwent curative radiotherapy, and nine patients with portal vein tumor thrombus (PVTT) underwent palliative radiotherapy as part of multidisciplinary therapy. Local disease control for curative therapy was 80.0% and stereotactic body radiotherapy was 86.7% which was greater than that of conventional radiotherapy (60.0%). Patients with PVTT had a median observation period of 651 days and 75% three-year survival when treated with multitherapy, including radiotherapy for palliative intent, transcatheter arterial chemoembolization, and administration of molecular targeted agents. No adverse events higher than grade 3 and no changes in the Child–Pugh score and ALBI score were seen. Radiotherapy is safe and effective for HCC treatment and can be a part of multidisciplinary therapy. [ABSTRACT FROM AUTHOR]